Quality Worklife Indicators for Nursing Practice Environments in Ontario

Transcription

1 Quality Worklife Indicators for Nursing Practice Environments in Ontario Determining the Feasibility of Collecting Indicator Data Linda McGillis Hall, RN, PhD Diane Doran, RN, PhD Linda O Brien Pallas, PhD Joan Tranmer, RN, PhD Deborah Tregunno, RN, PhD Ellen Rukholm, RN, PhD Donna Thomson, RN, MBA Leah Pink, RN, MN Jessica Peterson, RN, PhD Student Erin Johnston, RN, MN Student Amy Palma, RN, BScN Funded by The Ontario Ministry of Health & Long-Term Care MARCH 2006

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3 Quality Worklife Indicators for Nursing Practice Environments in Ontario Determining the Feasibility of Collecting Indicator Data Linda McGillis Hall, RN, PhD Associate Professor, Faculty of Nursing & CIHR New Investigator & Co-investigator, Nursing Health Services Research Unit, University of Toronto Diane Doran, RN, PhD, Faculty of Nursing, University of Toronto Linda O Brien Pallas, PhD, Faculty of Nursing, University of Toronto Joan Tranmer, RN, PhD, Queen s University/ Kingston General Hospital Deborah Tregunno, RN, PhD, Faculty of Nursing, York University Ellen Rukholm, RN, PhD, School of Nursing, Laurentian University Donna Thomson, RN, MBA, St. Peter s Hospital Leah Pink, RN, MN, Faculty of Nursing, University of Toronto Jessica Peterson, RN, PhD Candidate, Faculty of Nursing, University of Toronto Erin Johnston, RN, MN Student, Faculty of Nursing, University of Toronto Amy Palma, RN, BScN, Faculty of Nursing, University of Toronto Funded by The Ontario Ministry of Health & Long-Term Care MARCH 2006

4 Acknowledgements We gratefully acknowledge the Ontario Ministry of Health and Long-term Care, Dr. Dorothy Pringle Executive Lead, and Peggy White of the Health Outcomes for Better Information and Care initiative for their support of this research. The findings reported herein are those of the authors. No endorsement by the Ontario Ministry of Health and Long-term Care is intended or should be inferred. We would also like to acknowledge the contribution of David Montgomery for his assistance with the statistical analysis. Finally, we would like to thank the hospital nursing personnel, unit managers, nurse executives, and chief executive officers, of the participating sites who gave their time and energy to support this study. Toronto Ontario Region: University Health Network Toronto General Hospital site Shalom Village (Hamilton) Chelsey Park Mississauga Toronto Salvation Army Grace Spectrum Health Care (Toronto) Southwestern Ontario Region: Huron Perth Healthcare Alliance Stratford General Hospital St. Joseph s Health Centre (London) St. Peter s Health System (Hamilton) ParaMed Home Health Care (London) Eastern Ontario Region: Kingston General Hospital Peter D. Clark Long-Term Care Centre (Nepean) Perley & Rideau Veteran s Health Centre (Ottawa) St. Mary s of the Lake Hospital (Kingston) All-Care Health Services (Kingston) Northern Ontario Region: Manitoulin Health Centre-Little Current and Mindemoya sites Bethammi Nursing Home (Thunder Bay) Pioneer Manor (Sudbury) St. Joseph s Care Group (Thunder Bay) Bayshore Home Health (Thunder Bay) Cover photograph provided by University of Toronto, Public Affairs Quality Worklife Indicators for Nursing Practice Environments in Ontario: Determining the Feasibility of Collecting Indicator Data ISBN Copyright 2006 Correspondence regarding this report can be directed to Linda McGillis Hall, RN, PhD Associate Professor, Faculty of Nursing New Investigator, Canadian Institutes of Health Research Co-investigator, Nursing Health Services Research Unit University of Toronto, Toronto, Ontario CANADA T F [email protected] web:

5 EXECUTIVE SUMMARY The Quality Worklife Indicators in Nursing Practice Environments in Ontario study was a provincewide research project that was designed to assess the feasibility, quality, and utility of collecting data on nursing worklife indicators for acute care, long-term care, complex continuing care, and homecare settings. The study also explored the feasibility of linkage of these data to data collected in similar settings as part of the Health Outcomes for Better Information and Care initiative (formerly the Nursing and Health Outcomes Project). The study was conducted at 20 health care facilities (5 acute care, 7 long-term care, 4 complex continuing care, 4 homecare) across Ontario and included questionnaires, interviews, focus groups, and data from selected administrative databases. Approximately 451 nursing personnel and 53 unit managers participated in the study. Data Quality Reliability and Completion of Nursing Worklife Data Two instruments were used to measure the quality of nurses worklife the Work Quality Index (WQI) and the Nursing Work Index Revised (NWI-R). Both instruments were highly reliable with no reliability differences noted between work groups or health care sectors. The NWI-R had lower alpha reliability scores than the WQI for the majority of subscales across the health care sectors, with homecare attaining the lowest alpha values. Overall, the completion rate was best for the WQI, with registered nurses (RNs) having the highest completion rates, followed by registered practical nurses (RPNs) and unregulated health workers (URWs). Homecare participants had the lowest completion rates for both instruments. Feasibility of Collecting Nursing Worklife Data Receptivity and Burden Nursing personnel and unit managers were receptive to collecting these data. Nursing personnel found the surveys to be straightforward although work environment supports to enable nurses to complete the survey were important considerations. Unit managers identified substantial challenges related to having ready access to the data needed to assess nurses worklife. These managers went to inordinate lengths to obtain the data for this study, a burden that could not be maintained on an ongoing basis. Efforts should be made to ensure unit-based managers have access to nursing worklife data to enable them to make linkages between nurse staffing, the work environment, and clinical outcomes. Utility of Nursing Worklife Data Comprehensiveness and Relevance From the perspective of nursing personnel, the data collected in the nursing surveys was considered to be appropriate. However, the challenges encountered by unit managers in accessing accurate unit-based information on key data elements such as percentage of baccalaureate nurses, years of experience, nurse-to-patient ratios, use of casual staff, number of voluntary resignations, orientation and educational programs, absenteeism, and agency use, highlight the importance of having comprehensive and relevant data available for decision-makers. Currently, access to these data is sporadic and inconsistent, depending on sector and site. Potential Data Repositories A number of existing groups with varied experience in gathering, maintaining, and storing data provided information on important considerations for a large data set designed to link nurse staffing, nurses worklife, and clinical outcomes. No specific group could be identified as the ideal repository, given the complexity of this process. Determining the Feasibility of Collecting Indicator Data 3

6 Data Linkage Challenges were encountered when considering linking this data with other sources, such as Management Information System (MIS) data collected as part of the Ontario Hospital Reporting System (OHRS). The first relates the level of analysis the data are available for, while the second relates to the limited scope of available data in terms of health care sectors. The data available from the OHRS is available only at the aggregate level of functional centre, which can include several patient care units. At the current time, there is no method for clearly breaking out the aggregate functional centre data from the OHRS dataset to the level of the patient care unit to link to the clinical outcomes. As well, these linking data are only available in acute care and some complex continuing care facilities in Ontario. Further expansion to other sectors is needed to enable data linkage. This is a concern that needs to be addressed in the future to enable these data to be useful to health care leaders, decision-makers, policy makers, and researchers. Despite this, data obtained from unit managers provided some important information about the consistency and relevance of several of the nursing worklife indicators examined in this study. Specifically, several of the study variables of interest that had emerged from the original review of the literature were found to be related to the nursing work environment measures across sectors. These include span of control of the unit manager, absenteeism, nurse-to-patient ratios, experience, and education. As well, in long-term care, the percentage of RN staffing was also identified. Summary This study demonstrated that the collection of worklife date is feasible and useful, and the quality of the data collected is good, although there were challenges with data collection in some sectors. There does not seem to be overwhelming evidence to suggest that one instrument is superior to the other for collecting nursing worklife data. Both appear to be fairly reliable and consistent, although some specific sectors (i.e., homecare) and nursing personnel groups (i.e., URWs) experienced difficulties relating to some of the questions. Thus, consideration should be given to adapting the language of these measures to specific health care sectors (i.e., homecare, long-term care) to accurately capture their unique work environments in future work. 4 Quality Worklife Indicators for Nursing Practice Environments in Ontario

7 TABLE OF CONTENTS 9 Chapter One: Overview 10 Introduction 10 Goals 10 Purpose 11 Study Objectives 13 Chapter Two: Methods 14 Research Methodology 14 Design 14 Phase 1 14 Phase 2 15 Phase 3 15 Setting 16 Sample 17 Sample Size 18 Recruitment 18 Study Variables 18 Unit Manager Survey 18 Secondary Data 18 Nursing Worklife Survey 19 1) Nursing Work Index Revised (NWI-R) 19 2) Work Quality Index (WQI) 19 Focus Groups 20 Stakeholder Interviews 20 Data Management 20 Data Preparation 20 Data Entry Error and Missing Data 20 Computing Total Scale Scores 21 Chapter Three: Study Participants 22 Description of the Study Sample 22 Settings 22 Nurse Surveys 22 Nursing Personnel 23 Age of Nursing Personnel Participants 24 Educational Preparation of Nursing Personnel 24 Experience of Nursing Personnel 25 Employment Status of Nurse Participants 26 Unit Manager Surveys 26 Staff Mix 26 Percentage of RNs 27 Absenteeism 27 Employment Status 28 Experience 29 Unit Manager Span of Control 30 Nurse-to-Patient Ratios 30 Summary Determining the Feasibility of Collecting Indicator Data 5

8 TABLE OF CONTENTS 31 Chapter Four: Quality of Nursing Worklife Indicators 32 Introduction 32 Instrument Reliability 32 Overall Sample 32 Nursing Personnel Group Reliability and Completion Rate Comparisons 32 Worklife Scale Reliabilities: RN, RPN, and URW 34 Work Quality Index (WQI) 35 Nursing Work Index Revised (NWI-R) 36 Comparison of Worklife Scales: RN, RPN, and URW 36 Sector Reliability and Completion Rate Comparisons 36 Worklife Scale Reliabilities: Acute Care, Long-term Care, Complex Continuing Care, and Homecare 37 Work Quality Index (WQI) 38 Nursing Work Index Revised (NWI-R) 39 Comparison of Worklife Scales: Acute Care, Long-term Care, Complex Continuing Care, and Homecare 39 Missing Data 40 Summary 41 Chapter Five: Feasibility and Utility of Collecting Nursing Worklife Indicator Data 42 Introduction 42 Assessing the Feasibility and Utility of Nursing Worklife Indicator Data Collection 43 Receptivity and Burden of Nursing Worklife Indicator Data Collection for Nursing Personnel 44 Comprehensiveness and Relevance of Nursing Worklife Indicator Data Collection for Nursing Personnel 46 Receptivity and Burden of Nursing Worklife Indicator Data Collection for Unit Managers 46 Comprehensiveness and Relevance of Nursing Worklife Indicator Data Collection for Unit Managers 50 Summary 51 Chapter Six: Collection and Storage of Nursing Worklife Indicator Data 52 Introduction 52 Feasibility of Collecting and Maintaining Nursing Worklife Indicator Data 52 1) College of Nurses of Ontario (CNO) Perspective 52 Challenges for Collecting Nursing Worklife Indicator Data 54 Facilitators for Collecting Nursing Worklife Indicator Data 54 Frequency of Collecting Nursing Worklife Indicator Data 55 Data Collection Process for Nursing Worklife Indicator Data 55 Data Storage and Accessibility 55 Costs Associated with Data Collection and Storage 56 2) Canadian Coucil on Health Services Accreditation (CCHSA) Perspective 56 Challenges for Collecting Nursing Worklife Indicator Data 56 Facilitators for Collecting Nursing Worklife Indicator Data 57 Frequency of Collection of Nursing Worklife Indicator Data 57 Data Collection Process for Nursing Worklife Indicator Data 58 Data Storage and Accessibility 58 Costs Associated with Data Collection and Storage 6 Quality Worklife Indicators for Nursing Practice Environments in Ontario

9 TABLE OF CONTENTS 58 3) Canadian Institute for Health Information (CIHI) Perspective 59 Challenges for Collecting Nursing Worklife Indicator Data 59 Facilitators for Collecting Nursing Worklife Indicator Data 60 Frequency for Collection of Nursing Worklife Indicator Data 60 Data Collection Process for Nursing Worklife Indicator Data 60 Data Storage and Accessibility 60 Costs Associated with Data Collection and Storage 61 Summary 61 Nurses Perspectives of Nursing Worklife Indicator Data Collection (Focus Groups) 62 Managers Perspectives of Nursing Worklife Indicator Data Collection (Focus Groups) 63 Summary 65 Chapter Seven: Nursing Worklife in Ontario 66 Introduction 66 Mean Scale Scores for Work Quality Index (WQI) by Nursing Personnel Group 69 Mean Scale Scores for Nursing Work Index (NWI-R) by Nursing Personnel Group 70 Summary 70 Work Quality Index 71 Nursing Work Index Revised 71 Mean Scale Scores for Work Quality Index (WQI) by Health Care Sector 74 Mean Scale Scores for Nursing Work Index (NWI-R) by Health Care Sector 77 Conclusions 77 Nursing Personnel Groups 77 Health Care Sectors 79 Chapter Eight: Abstracting and Linking Nursing Worklife Indicator Data 80 Introduction 80 Unit-Manager Data 80 Acute Care 81 Complex Continuing Care 81 Long-term Care 82 Home Care 82 Overall 82 Summary 85 Chapter Nine: Discussion and Conclusions 86 Introduction 86 Quality of Nursing Worklife Indicator Data 86 Reliability of Data Collected 86 Completion Rate 87 Receptivity and Burden of Nursing Worklife Indicator Data Collection 87 Comprehensiveness and Relevance Nursing Worklife Indicator Data 87 Collection, Storage and Management of Nursing Worklife Indicator Data 88 Linking Nursing Worklife Indicator Data to Clinical Outcomes 89 A Snapshot of Nursing Worklife in Ontario 89 Conclusions 90 Appendix A: Semi-structured Interview Participants 91 References Determining the Feasibility of Collecting Indicator Data 7

10 LIST OF TABLES 16 Table 1 Setting Selection by Region of the Province 17 Table 2 Nursing Personnel Sample 17 Table 3 Unit Manager Sample 23 Table 4 Participation Rates of Nursing Personnel by Occupational Title and by Sector 23 Table 5 Age of Nursing Personnel by Sector 24 Table 6 Educational Preparation of Nursing Personnel by Sector 24 Table 7 Experience of Nursing Personnel by Sector 25 Table 8 Employment Status of Nursing Personnel by Sector 25 Table 9 Choice of Employment Status of Nursing Personnel by Sector 25 Table 10 Preferred Change in Employment Status of Nursing Personnel by Sector 26 Table 11 Hours Worked Weekly by Study Nurse Participants by Health Care Sector 26 Table 12 Unit Staffing Model by Sector 27 Table 13 Mean Percentage of RNs on Study Units 27 Table 14 Average Number of Days Absent Annually 27 Table 15 Percentage of Employment by Occupational Status 28 Table 16 Percentage Experience of Nursing Personnel 29 Table 17 Span of Control of Unit Managers on Study Units 29 Table 18 Mean Scope of Responsibility 30 Table 19 Mean Nurse-to-Patient Ratios by Shift 32 Table 20 Reliability of Nursing Worklife Measures 33 Table 21 Reliability of Nursing Worklife Measures by Individual Nursing Personnel Group (RN, RPN, and URW) 36 Table 22 Reliability of Nursing Worklife Measures by Health Care Sectors 40 Table 23 Missing Data for Nursing Worklife Measures by Individual Nursing Personnel Group (RN, RPN, and URW) and by Health Care Sectors 66 Table 24 Mean Score for Worklife Indicators for Nursing Personnel Groups (RN, RPN, URW) and Health Care Sectors 68 Table 25 Work Quality Index Mean Score Differences Between Nursing Personnel Groups (RN, RPN, URW) 70 Table 26 Nursing Work Index Mean Score Differences Between Nursing Personnel Groups (RN, RPN, URW) 72 Table 27 Work Quality Index Mean Score Differences Between Health Care Sectors 75 Table 28 Nursing Work Index Mean Score Differences Between Health Care Sectors 83 Table 29 Correlations for Unit-Level Nursing and Unit Structural Variables 8 Quality Worklife Indicators for Nursing Practice Environments in Ontario

11 one Chapter One: Overview Introduction Goals Purpose Study Objectives 9

12 INTRODUCTION A number of recent U.S. and Canadian studies have demonstrated that linkages exist between nurse staffing models and patient outcomes. Little or no work has been conducted that explores variables in the work environment beyond nurse staffing that may also have an impact on patient outcomes. Evidence exists in the literature that the quality of a patient s health care experience can be influenced by nurses job satisfaction. While it is widely recognized that factors in the nursing work environment and the work organization may have an impact on nurses worklife and job satisfaction, indicators for measuring these specific worklife factors have not been identified and validated. This research addresses the need for a description and evaluation of key quality of nursing worklife indicators that can be linked to patient outcomes. GOALS The goals of this overall research study were: (a) to conduct a critical review and analysis of the literature on input or structural variables in work settings that could be considered indicators of the quality of nurses worklife in health care settings in Ontario, Canada, and (b) to conduct a pilot study to determine the feasibility of collecting data related to these indicators. Phase one of this research involved completion of a critical review and analysis of the literature on variables that could be considered indicators of the quality of nurses worklife in health care settings, which was subsequently published as a book, Quality Work Environments for Nurse and Patient Safety (McGillis Hall, 2005). The indicators that emerged from the literature review included: staff mix proportions for registered nurses; percentages of full-time, part-time, and casual nursing staff; educational background of nursing staff; experience of nursing staff; use of overtime hours; use of agency staff; absenteeism hours; level of autonomy and decisionmaking experienced by nurses; professional development opportunities; span of control of the unit manager; team functioning; organizational climate and culture; job satisfaction; and workload/productivity. Following this determination of key indicators of importance for measuring the nursing work environment, a feasibility study was undertaken to provide sound information related to the availability, feasibility, and utility of measuring many of these nursing worklife variables. Ultimately this research will inform decisions and recommendations regarding the complementary data required to link to the clinical outcome database being developed and implemented by the Ontario Ministry of Health and Long-term Care (MOHLTC) as part of the Health Outcomes for Better Information and Care (HOBIC) initiative (Ministry of Health and Long-term Care, 2005). PURPOSE The primary purpose of this study was to evaluate the feasibility, quality, and utility of instituting data collection for nursing worklife indicators in acute care, long-term care, complex continuing care, and homecare settings in Ontario, Canada. A second purpose was to examine the potential for linkage of these data to the clinical outcomes data collected in similar settings as part of the Health Outcomes for Better Information and Care initiative (formerly the Nursing and Health Outcomes Study). A third purpose was to make recommendations regarding potential sources for where these data can be housed in a database in the future. In order to address the primary purpose and sub-purposes, several study objectives and research questions were identified. 10 Quality Worklife Indicators for Nursing Practice Environments in Ontario

13 STUDY OBJECTIVES The first study objective examines the quality of nursing worklife indicator data collected by nurses and managers in everyday practice settings in acute care, complex continuing care, long-term care, and homecare settings in Ontario, Canada. The specific research questions were: (1) What is the reliability of data collected by nurses and managers? and (2) What is the completion rate of the nursing worklife measures collected by nurses and managers? The second study objective was to examine the feasibility of collecting nursing worklife indicator data in everyday practice settings in acute care, complex continuing care, long-term care, and homecare settings in Ontario, Canada. The specific research questions were: (1) What is the receptivity to nursing worklife indicator data collection by nurses and managers? and (2) What is the burden of collecting nursing worklife indicator data for nurses and managers? The third study objective examines the utility of nursing worklife indicator data for nurses and managers in acute care, complex continuing care, long-term care and homecare settings in Ontario, Canada. The specific research questions were: (1) To what extent are the nursing worklife indicator data comprehensive, as perceived by nurses and managers? and (2) How relevant and useful are the nursing worklife indicator data in assisting nurses and managers in decision-making for the organization? The fourth study objective examines the potential sources for where these data can be housed in a database in the future. The specific research questions were: (1) What is the feasibility of collecting nursing worklife indicator data as part of the data collected by the College of Nurses of Ontario (CNO), the Canadian Institute for Health Information (CIHI), the Canadian Council on Health Services Accreditation (CCHSA)? and (2) What is the feasibility of housing nursing worklife indicator data with the CNO, CIHI, and CCHSA? The fifth study objective examines the feasibility of abstracting and linking nursing worklife indicator data to other datasets (e.g., outcomes). The specific research questions were: (1) What is the feasibility of abstracting nursing worklife indicator data? and (2) What are the issues associated with abstracting and linking nursing worklife indicator data to data from different databases, such as Management Information Systems (MIS), CIHI, and across settings? Determining the Feasibility of Collecting Indicator Data 11

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15 Two Chapter Two: Methods Research Methodology Study Variables Data Management 13

16 RESEARCH METHODOLOGY Design A cross-sectional survey research design was used to address the study objectives including nurse and manager surveys, focus groups and interviews. The survey data collection took place over a 9 month period from August 2004 to May The study was designed to provide in-depth examination of the feasibility of instituting nursing worklife indicator data collection in acute care, complex continuing care, long-term care, and homecare settings in Ontario. The research was conducted in each type of practice setting, ensuring province wide representation, and purposively sampling different types of organizations that typify the range of service providers. Phase One Health care unit managers in a sample of acute care, complex continuing care, long-term care, and homecare settings in Ontario were surveyed to obtain data on 8 nurse structural variables percentage of RNs in staff mix; percentage of full-time, part-time, and casual nursing staff; educational background of nursing staff; experience of nursing staff employed on the study units in the study sites; span of control of the unit manager; and unit absenteeism rates. This survey, an adaptation of one used by the principal investigator in a previous study, has been validated in earlier studies to ensure the relevance of the data items (McGillis Hall et al., 2001). Secondary data related to 5 unit structural variables nursing hours per weighted case/rug weighted patient day; nursing overtime hours; agency staff hours; absenteeism hours; and workload/productivity (i.e., direct patient care) was also sought from the organization s management information system database, the Ontario Hospital Reporting System (OHRS) at one point in time for fiscal year 2004/2005, for the acute care and complex continuing care sites in this study. Data were not sought for the long-term care and home-care sectors as no consistent data were collected and available from these sectors at the time of this study. Phase Two In phase two, nurses working on selected units in a sample of acute care, complex continuing care, long-term care, and homecare settings in Ontario were surveyed to obtain data on 8 nursing worklife variables level of autonomy and decision-making experienced by nursing staff; team functioning and professional work relationships; work environment; role enactment; work worth; organizational support; education; and experience in nursing. For each participating unit, the study research coordinator met with eligible nursing staff, i.e., registered nurses (RNs), registered practical nurses (RPNs), and unregulated workers (URWs), to explain the study and the sampling procedure with the assistance of the unit manager or her designate. The research coordinator individually ascertained their interest in participation. A survey questionnaire package along with a letter of explanation and a pre-stamped return envelope was given to all nurses who consented to participate. As part of the returned survey questionnaire package, nursing staff were asked to indicate their interest in participating in a focus group follow-up meeting to be held at a later point in the study aimed at obtaining their input regarding the utility of the worklife data collection. 14 Quality Worklife Indicators for Nursing Practice Environments in Ontario

17 Phase 3 Following completion of phases one and two, the final qualitative component of this study was carried out. The qualitative component was comprised of separate focus groups with the nurses and their managers, and semi-structured interviews with stakeholders involved with the study. Two focus group interviews were held with representatives from each of the four regions involved in the study to obtain input regarding the feasibility and utility of collecting nursing worklife data. The first focus group included nursing staff from acute care, complex continuing care, long-term care, and homecare settings involved in the study. The second focus group involved unit managers from the same settings. As well, semi-structured interviews were conducted individually with relevant stakeholders (i.e., CNO, CCHSA, CIHI) to determine the feasibility for collection and maintenance of these data in the future. Participants in these interviews were asked to discuss the feasibility of collecting and maintaining these data in their organization, and to identify any barriers and facilitators to nursing worklife indicator data collection from their perspective. The frequency that these data should be collected was also discussed. Setting The settings for this feasibility study were acute care, complex continuing care, long-term care, and homecare organizations in Ontario, Canada. Health care organizations were purposively selected for participation in the study based on their involvement in the complementary study project The Nursing and Health Outcomes Study. In cases where the original sites were not accessible, alternate settings were selected. These settings were selected using a stratified random sampling approach based on a set of criteria developed with input from stakeholders (see Table 1). These included: (1) geographic location from the four MOHLTC regions of the province; (2) availability of two medical and two surgical care units in each setting; (3) representation of teaching, community, and small rural facilities; (4) long-term care settings including a for-profit and not-for-profit home (Metro Homes and Charitable Homes for the Aged), a new home (schedule A) and an established home (schedule C), a facility with case mix index (CMI) >110, a small independent facility, and also one facility that is part of a large corporation; (5) complex continuing care settings could be either freestanding or attached to an acute care site; and (6) homecare settings including at least one close to a teaching hospital and one rurally located. Therefore, this feasibility study was conducted in a total of 20 health care facilities, of which 5 were acute care, 7 were long-term care, 4 were complex continuing care, and 4 were homecare settings across the province. A total of 65 patient care units were included in the study; 16 from acute care, 30 from long-term care, and 15 from complex continuing care settings. Determining the Feasibility of Collecting Indicator Data 15

18 Table 1. Setting Selection by Region of the Province Region 1 Region 2 Region 3 Region 4 Setting Central Southwestern Eastern Northern Total Acute care 4 units/1 site: 4 units/1 site: 6 units/1 site: 2 units/2 sites: 16 units/ University Health Huron Perth Kingston Manitoulin Health 5 sites Network Healthcare General Centre Little Toronto General Alliance Hospital Current and Hospital site Stratford General Mindemoya Hospital site sites Long-term 6 units/2 sites: 10 units/1 site: 9 units/2 sites: 5 units/2 sites: 30 units/ care Shalom Village St. Joseph s Peter D. Clark Bethammi Nursing 7 sites (Hamilton)* + ; HealthCentre Long-term Care Home (Thunder Chelsey Park (London)* +/ Centre (Nepean)*+ ; Bay)*; Pioneer Mississauga** ^ Perley & Rideau Veteran s Health Manor (Sudbury)* + Centre (Ottawa)* + Complex 4 units/1 site: 4 units/1 site: 4 units/1 site: 3 units/1 site: 15 units/ continuing Toronto Salvation St. Peter s St. Mary s of the St. Joseph s 4 sites care Army Grace Health System Lake Hospital Care Group (Hamilton) (Kingston) (Thunder Bay) Community 1 site: 1 site: 1 site: 1 site: 4 sites care access Spectrum Health ParaMed Home All-Care Health Bayshore Home centres Care (Toronto) Health Care Services Health (Thunder (London) (Kingston) Bay) Total 15 units/ 19 units/ 20 units/ 11 units/ 65 units/ 5 sites 4 sites 5 sites 6 sites 20 sites * Not-for-profit ** For-profit + New home (Schedule A) Established home (Schedule C) ^ Case Mix Index >110 Sample The sample for the study included (1) nursing personnel caring for patients/residents admitted to acute care, complex continuing care, long-term care, and homecare settings in Ontario; (2) unit managers from units participating in this study; and (3) potential key stakeholders for future data collection and housing of the database. All full-time, part-time, and casual nursing personnel (i.e., RNs, RPNs, URWs) associated with the study units were recruited to participate in the study. Nurses caring for medical-surgical patients were recruited from acute care hospitals, long-term care, and complex continuing care facilities, as well as nurses working within homecare settings. All unit managers associated with the study units were recruited to participate in the study. Organizations currently involved with the collection of data related to nursing in the province were recruited to participate in the study (i.e., CNO, CIHI, CCHSA). 16 Quality Worklife Indicators for Nursing Practice Environments in Ontario

19 Sample Size Sample size determination was based on the data analytic needs. Data analysis to address the questions for feasibility, data quality, and utility were conducted separately for each sector. A minimum of 10 subjects for each variable were included in the analysis for construct validity. Based on this consideration, the desired sample size was 450 nurses, which included a 30% increase for subject refusal and attrition. Table 2 demonstrates that the sample requirements were met for the study overall, with approximately 30% of responses coming from acute care, 29% from long-term care, 23% from complex continuing care, and 18% from homecare nursing staff. Some challenges were encountered achieving the sample within specific sectors and regions (i.e., complex continuing care in the southwest region; long-term care in central and southwest regions; acute care in the north). Reasons for this included heavy workload on the units, which made attending the data collection meetings difficult for some nurses. As well, facility and unit size resulted in lower nursing staff numbers than anticipated. Finally, in some facilities (i.e., long-term care), the numbers of registered nursing staff working at one time were very low. Given these issues, oversampling was undertaken in the other regions of the province to ensure the overall sampling requirements were met (i.e., complex continuing care in eastern region; long-term and acute care in the eastern region). As a result, approximately 40% of the sample came from the eastern region of the province, while 25% came from central Ontario, 18% from the north, and 17% from southwestern Ontario. Table 2. Nursing Personnel Sample Region 1 Region 2 Region 3 Region 4 Minimum Central Southwestern Eastern Northern Total sample (attained/ (attained/ (attained/ (attained/ (attained/ Setting sample/%) sample/%) sample/%) sample/%) sample/%) Acute care 31/30 38/30 53/30 16/30 138/120 (30) Long-term care 15/30 17/30 73/30 27/30 132/120 (29) Complex continuing care 19/30 7/30 47/30 29/30 102/120 (23) Homecare 48/23 16/22 8/23 7/22 79/90 (18) Total 113/113 (25) 78/112 (17) 181/113 (40) 79/112 (18) 451/450 (100) Table 3 demonstrates that all 53 unit managers on the study units participated in the study, for a 100% response rate. Table 3. Unit Manager Sample Region 1 Region 2 Region 3 Region 4 Minimum Central Southwestern Eastern Northern Total sample (attained/ (attained/ (attained/ (attained/ (attained/ Setting sample/%) sample/%) sample/%) sample/%) sample/%) Acute care 4/4 4/4 6/6 2/2 16/16 (30) Long-term care 6/6 2/2 5/5 5/5 18/18 (34) Complex continuing care 4/4 4/4 4/4 3/3 15/15 (28) Homecare 1/1 1/1 1/1 1/1 4/4 (8) Total 15/15 (28) 11/11 (21) 16/16 (30) 11/11 (21) 53/53 (100) Determining the Feasibility of Collecting Indicator Data 17

20 Recruitment Participants in the study were recruited from the settings listed in Table 1. Following ethics approval from the Research Ethics Board of each of the universities affiliated with the 4 university teaching hospitals as well as each of the 20 individual study sites, the study coordinator contacted the managers of each unit involved in the study. At this time the unit managers were recruited to complete the study questionnaire. The study coordinator also arranged to meet with nursing staff (i.e., RNs, RPNs, and URWs) with the help of the unit managers to complete a nursing worklife questionnaire. The ethics review process proved to be quite lengthy for this study, due to the number of university and individual research ethics boards that required study approval and the length of the individual ethics review processes. Approximately 7 months elapsed from the time of the first ethics submission until final approval at the last study site. STUDY VARIABLES Unit Manager Survey Unit managers provided information through a questionnaire about the nurse structural variables percentage of registered nurses in staff mix; percentage of full-time, part-time, and casual nursing staff; educational background of nursing staff; experience of nursing staff employed on the study units in the study sites; span of control of the unit manager; and unit absenteeism rates. Secondary Data Data on the unit structural variables (nursing hours per weighted case/rug weighted patient day; nursing overtime hours; agency staff hours; absenteeism hours; and workload/productivity (i.e., direct patient care) was obtained from the organization s management information system database, the Ontario Hospital Reporting System (OHRS) at one point in time for fiscal year 2004/2005, for the acute care and complex continuing care sites in this study. Nursing Worklife Survey Nursing staff (i.e., RNs, RPNs, and URWs) provided information through a questionnaire about the nursing worklife variables level of autonomy and decision-making experienced by nursing staff; team functioning and professional work relationships; work environment; role enactment; work worth; organizational support; education; and experience in nursing. Instruments with demonstrated reliability and validity were used to collect data on these nursing worklife indicators. The nurses perceptions of the quality of their work environment were measured with two scales; the Nursing Work Index-Revised and the Work Quality Index. The two instruments were used for the following reasons: (1) they captured aspects of the nursing work environment identified as important constructs to measure in the critical appraisal of the literature conducted prior to the development of this study (e.g., autonomy and decision-making, team functioning, organizational climate and culture, job satisfaction); and (2) each has been identified as having acceptable evidence of their psychometric properties. Thus, using both measures in this study enabled a comprehensive assessment of environmental factors affecting nurses work, and enhanced the validity of measurement. 18 Quality Worklife Indicators for Nursing Practice Environments in Ontario

21 1) Nursing Work Index-Revised A measure of nurses reports of the presence or absence of a series of organizational factors: autonomy, control over the work environment, and relationships with physicians. The traits of a hospital or a unit within a hospital were obtained using the Nursing Work Index-Revised (NWI-R; Aiken & Patrician, 2000). This scale contains 57 Likert-like items with four response categories: strongly agree, somewhat agree, somewhat disagree, and strongly disagree. The scale items are coded such that a 1 is equal to strongly agree and a 4 is equal to strongly disagree. Multiple nurses responses on a single item are summed to create a measure of an organizational trait. The organizational trait is an average of that particular item of the NWI-R across a unit or a hospital (Aiken & Patrician). Cronbach s alpha was reported as.96 for the overall scale by the instrument developers. When the data were aggregated to the unit level, Cronbach s alpha for each of the subscales were reported as.80 for autonomy,.91 for control,.84 for relationships with physicians, and.84 for organizational support (Aiken & Patrician). Content, construct, and criterion-related validity were also demonstrated (Aiken & Patrician). 2) Work Quality Index A measure of nurses satisfaction with the quality of their work and their work environment using 6 subscales for job properties: professional work environment, autonomy, work worth, professional relationships, role enactment, and benefits was obtained using the Work Quality Index (WQI; Whitley & Putzier, 1994). This scale contains 38 Likert-like items with seven response categories ranging from not satisfied to satisfied. The scale items are coded such that a 1 is equal to not satisfied and a 7 is equal to satisfied. A high score on this scale indicates a higher degree of job satisfaction. Cronbach s alpha was reported by the instrument developers as.94 for the overall scale,.87 for the work environment scale,.84 for the autonomy scale,.79 for the work worth scale,.80 for the relationships scale,.72 for the role enactment scale, and.79 for the benefits scale. Construct validity was also demonstrated (Whitley & Putzier). Focus Groups Nursing staff and managers who indicated a willingness to participate in focus groups were randomly selected and invited to a focus group meeting. In order to assess the feasibility of collecting nursing data in practice settings, information was obtained in focus groups on the amount of time it takes for a nurse and manager to complete the worklife indicators survey. in Focus group participants were asked to identify the time involved in survey completion, and to identify any barriers and facilitators to nursing worklife indicator data collection. In addition, information was collected from nurses on their perceived ease of collecting the nursing worklife indicator data, ease of interpreting the nursing worklife indicator data, and perceptions of the frequency with which it should be collected. Nurses were asked to comment on their receptivity to incorporating a standardized approach to nursing worklife indicators assessment. Another aspect of feasibility is whether it is possible to collect the nursing worklife indicator data in a timely manner. Data was collected on the time required for data collection to be completed, completeness of data collection, and reasons for failure to complete data collection. Work environment factors may contribute to the receptivity of nurses towards the completion of the data collection. Data was collected from nurses and managers on their perception of the work environment factors that influence nurses receptivity to the data collection. Unit managers were also invited to participate in a focus group concerning their perceptions of the value and/or utility of nursing worklife indicator assessments for management decision-making. Determining the Feasibility of Collecting Indicator Data 19

22 Stakeholder Interviews The stakeholders from the CNO, CCHSA, and CIHI were invited to participate in semi-structured interviews to determine the feasibility for collection and maintenance of these data in the future. DATA MANAGEMENT Data Preparation Prior to conducting statistical analyses on the data set, several preliminary steps were taken. The purpose of these preliminary steps was to ensure accuracy of the data obtained from nurses and unit managers from the 20 participating health care organizations across Ontario, Canada. Specifically, issues related to missing data, coding, and measurement error were addressed. The preliminary steps are presented in sequential order. Data Entry Error and Missing Data Data entry error and missing data occurred for several reasons, such as unclear responses (e.g., circling two response options for the same item). Since data entry errors and missing data can adversely affect the accuracy of the data set, each item in every survey was reviewed three times to increase the validity of the study conclusions. Decision rules were established related to data entry error and missing data by the principal investigator. As well, unit managers were contacted by telephone to clarify any unclear responses on the unit manager surveys. Missing data (i.e., cases with incomplete data or responses) can be problematic in multivariate analyses, particularly when different subgroups of cases have incomplete data on different subsets of variables. This causes the number of cases available for analysis to be reduced, which decreases the statistical power to detect significant effects or correlations; which, in turn, potentially leads to type II error (Ward & Clark, 1991). Computing Total Scale Scores Total scale and subscale scores were computed to quantify the variables of interest. The total scores were calculated based on the scores of the individual items comprising each scale or subscale, as recommended by the tool developer. The subscales represented the different domains of the concept being measured. The formulae for computing the total scores were those provided by the instrument developers, and usually consisted of taking either the sum or the mean of the items. 20 Quality Worklife Indicators for Nursing Practice Environments in Ontario

23 THree Chapter Three: Study Participants Description of the Study Sample Nurse Surveys Unit Manager Surveys Summary 21

24 DESCRIPTION OF THE STUDY SAMPLE Settings The sample consisted of registered nurses (RNs), registered practical nurses (RPNs), unregulated health workers (URWs), and unit managers employed in a sample of acute care, complex continuing care, long-term care, and homecare organizations in Ontario, Canada. Five acute care settings were involved in the study, comprising 16 medical and surgical units in total (see Table 1). In long-term care, seven facilities were included in this study, comprising 30 resident care units. The long-term care facilities included two larger settings that ranged from 216 to 394 beds between them, and four smaller nursing homes that ranged in bed size from 110 to 124. Four complex continuing care settings were included in this study, involving 15 patient care units. Finally, four homecare settings were involved in the study. These settings were representative of all regions of the province with 5 sites comprised of 15 units coming from central Ontario, 4 sites comprised of 19 units from southwestern Ontario, 5 sites comprised of 20 units from eastern Ontario, and 6 sites consisting of 11 units from northern Ontario. Thus, the sample can be considered geographically representative of health care settings in Ontario, as well as representative of the different sectors of interest to this study (i.e., acute care, complex continuing care, long-term care, and homecare). NURSE SURVEYS Nursing Personnel A total of 451 nursing staff questionnaires were completed and returned in the study (see Table 4). The sampling requirements for the study were met and the sample was representative of all sites in the study. Approximately 57% of respondents were RNs, 31% were RPNs, and 10% URWs. Close to half of the RN respondents (n=117) were employed in acute care, while fewer came from homecare, complex continuing care, and long-term care. In contrast, the majority of RPNs were employed in complex continuing care, followed by long-term care, homecare, and the fewest in the acute care sector. The majority of unregulated workers in this study were employed in long-term care settings, while few came from homecare, complex continuing care, or acute care. The employment profiles reported by RNs in the sample are comparable to profiles of RNs working in both Canada and Ontario. In 2004, over 60% of RNs reported working in hospitals including rehabilitation and convalescent centres and approximately 13% of RNs worked in community health (CIHI, 2005a). Additionally, 7.9% of RNs in Ontario and 10.5% of RNs in Canada worked in nursing homes or long-term care facilities (CIHI, 2005a). The places of employment reflected by the RPNs in the sample are less similar to provincial and national profiles, which reported that the majority of RPNs (referred to as Licensed Practical Nurses [LPN] in the database) work in hospitals, followed by long-term care and community health (CIHI, 2005b). This may be partly explained by the fact that the national and provincial databases include convalescent facilities with acute care hospitals. Comparisons of unregulated workers are not possible due to lack of data (CIHI 2005a, 2005b). 22 Quality Worklife Indicators for Nursing Practice Environments in Ontario

25 Table 4. Participation Rates of Nursing Personnel by Occupational Title and by Sector Complex Acute care Long-term care continuing care Homecare Overall care N (%) N (%) N (%) N (%) N (%) RN 117 (84.8) 42 (31.8) 44 (43.1) 55 (69.6) 258 (57.2) RPN 17 (12.3) 47 (35.6) 54 (52.9) 22 (27.8) 140 (31.0) URW 3 (2.2) 42 (31.8) 2 (2.0) 0 (0) 47 (10.4) No response 1 (0.7) 1 (0.8) 2 (2.0) 2 (2.5) 6 (1.3) Total 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0) Age of Nursing Personnel Participants Demographic data included general biographical data and data pertaining to educational preparation and work arrangements. Overall 420 (93%) participants were female and 24 (5%) were male. As Table 5 demonstrates, the age range of study participants varied by health care sector. For example, in acute care, the age range in this study was fairly balanced. Similarly, the age of nurses was fairly consistent in homecare settings, with the exception of new nurses. In contrast, fewer young nurses were employed in long-term care and complex continuing care settings, where the majority of nurse participants were over the age of 40. The information available in the national database separates RNs from RPNs in the reports of ages and therefore are not directly comparable to the study sample which combines RNs, RPNs and URWs. In Ontario, the largest percentages of both RNs and RPNs in all health care sectors are found in the over 50 years of age category. This is most evident in nursing homes or long-term care settings, where almost 50% of RNs and 32.5% of RPNs are over 50 years of age (CIHI, 2005c). Provincially, in all sectors, nurses under the age of 30 make up the smallest percentage of the workforce (CIHI, 2005c). Table 5. Age of Nursing Personnel by Sector Complex Acute care Long-term care continuing care Homecare Overall care N (%) N (%) N (%) N (%) N (%) years 30 (21.7) 11 (8.3) 7 (6.9) 11 (13.9) 59 (13.1) years 32 (23.2) 29 (22.0) 19 (18.6) 19 (24.0) 99 (22.0) years 40 (29.0) 35 (26.5) 42 (41.2) 17 (21.5) 134 (29.7) > 50 years 30 (21.7) 41 (31.1) 23 (22.5) 19 (24.0) 113 (25.1) No response 6 (4.3) 16 (12.1) 11 (10.8) 13 (16.5) 46 (10.2) Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0) Determining the Feasibility of Collecting Indicator Data 23

26 Educational Preparation of Nursing Personnel Table 6 demonstrates that on average the majority of RN, RPN and URW participants (n = 285, 63%) in this study were prepared at the level of diploma education, 91 (20%) had hospital-based certificates, while 65 (14%) were baccalaureate prepared, and 2 (0.4%) held a Masters degree. In comparison, in 2004, the data indicating highest education in nursing of RNs in Canada showed that almost 68% of the RN workforce had a diploma education, 29.8 % had a baccalaureate degree, and another 2.3% were Masters or Doctorate prepared (CIHI, 2005a). In Ontario, almost 80% of RNs were diploma-prepared, while 22.8% of the RN workforce held a baccalaureate degree and 2.2% had a Masters or Doctorate degree (CIHI, 2005a). Over 92% of RPNs in each province in Canada were diploma prepared (CIHI, 2005b). Table 6. Educational Preparation of Nursing Personnel by Sector Complex Acute care Long-term care continuing care Homecare Overall care Education N (%) N (%) N (%) N (%) N (%) Diploma 102 (73.9) 71 (53.8) 63 (61.8) 49 (62.0) 285 (63.2) Hospital-based certificate 9 (6.5) 44 (33.3) 26 (25.5) 12 (15.2) 91 (20.2) Baccalaureate 27 (19.6) 13 (9.8) 10 (9.8) 15 (19.0) 65 (14.4) Masters 0 (0) 1 (0.8) 1 (1.0) 0 2 (0.4) No response 0 (0) 3 (2.3) 2 (2.0) 3 (3.8) 8 (1.8) Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0) Experience of Nursing Personnel Table 7 indicates that 19% of the RN, RPN and URW study respondents (n = 85) have less than 5 years of experience. The range of experience is more evenly distributed for each 5 year interval from 5 to 34 years. Few participants in this study had over 35 years of experience. Acute care settings employed the greatest number of new, less experienced nurses. Table 7. Experience of Nursing Personnel by Sector Complex Acute care Long-term care continuing care Homecare Overall care Years N (%) N (%) N (%) N (%) N (%) < 5 years 36 (26.0) 19 (14.4) 13 (12.7) 17 (21.5) 85 (18.9) 5-9 years 14 (10.1) 24 (18.2) 10 (9.8) 10 (12.6) 58 (12.9) years 15 (10.9) 16 (12.1) 11 (10.8) 9 (11.4) 51 (11.3) years 17 (12.3) 20 (15.1) 16 (15.7) 9 (11.4) 62 (13.7) years 16 (11.6) 15 (11.4) 25 (24.5) 9 (11.4) 65 (14.4) years 18 (13.0) 18 (13.6) 13 (12.7) 8 (10.1) 57 (12.6) years 17 (12.3) 12 (9.1) 9 (8.8) 8 (10.1) 46 (10.2) years 3 (2.2) 2 (1.5) 2 (2.0) 5 (6.3) 12 (2.7) years 1 (0.7) 1 (0.8) 0 (0) 1 (1.3) 3 (0.7) years 0 (0) 0 (0) 0 (0) 1 (1.3) 1 (0.2) No response 1 (0.7) 5 (3.8) 3 (2.9) 2 (2.5) 11 (2.4) Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0) 24 Quality Worklife Indicators for Nursing Practice Environments in Ontario

27 Employment Status of Nurse Participants Table 8 indicates that the majority of nurses participating in this study (n = 275, 61%) were employed full-time, while less than one-third (n = 133, 30%) were employed part-time, and 6% (n = 28) held casual positions. Some nurses indicated that they worked a combination of these alternatives (3%), (n = 12). These patterns of employment remained consistent across all sectors. In comparison, the employment status of the sample is reflective of the averages found in Ontario, in which 50.4% of regulated nursing workers in 2004 were employed full-time, 28.9% were employed part-time, and 7.6% were employed casually (CIHI, 2005a). This is slightly different than the national averages, which showed that 48.8% of all regulated nursing personnel worked full-time, 32.2% part-time, and 10.8% casual (CIHI, 2005a). Table 8. Employment Status of Nursing Personnel by Sector Complex Acute care Long-term care continuing care Homecare Overall care Employment status N (%) N (%) N (%) N (%) N (%) Full-time 91 (65.9) 83 (62.9) 62 (60.8) 39 (49.4) 275 (61.0) Part-time 42 (30.4) 35 (26.5) 33 (32.4) 23 (29.1) 133 (29.5) Casual 2 (1.4) 10 (7.6) 4 (3.9) 12 (15.2) 28 (6.2) Other combinations 3 (2.2) 3 (2.3) 2 (2.0) 4 (5.1) 12 (2.7) No response 0 (0) 1 (0.8) 1 (1.0) 1 (1.3) 3 (0.6) Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0) The majority of respondents (n = 383, 85%) indicated that their employment status had been chosen by them (see Table 9). These response patterns remained consistent across all sectors. Table 9. Choice of Employment Status of Nursing Personnel by Sector Complex Acute care Long-term care continuing care Homecare Overall care Work status N (%) N (%) N (%) N (%) N (%) My choice 118 (85.5) 116 (87.9) 85 (83.3) 64 (81.0) 383 (84.9) Not my choice 19 (13.8) 13 (9.8) 16 (15.7) 13 (16.5) 61 (13.5) No response 1 (0.7) 3 (2.3) 1 (1.0) 2 (2.5) 7 (1.6) Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0) Participants were asked what types of changes they would like to have made to their employment status. Over half (n = 248, 55%) identified that they wanted their work hours to remain unchanged, while one-quarter (n=107, 24%) indicated that they wanted to work more, and 87 (19%) indicated that they wanted to work less (see Table 10). Table 10. Preferred Change in Employment Status of Nursing Personnel by Sector Complex Work status Acute care Long-term care continuing care Homecare Overall care preference N (%) N (%) N (%) N (%) N (%) Same 83 (60.1) 75 (56.8) 49 (48.0) 41 (51.9) 248 (55.0) More hours 21 (15.2) 28 (21.2) 29 (28.4) 29 (36.7) 107 (23.7) Less hours 34 (24.6) 26 (19.7) 20 (19.6) 7 (8.9) 87 (19.3) No response 0 (0) 3 (2.3) 4 (3.9) 2 (2.5) 9 (2.0) Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0) Determining the Feasibility of Collecting Indicator Data 25

28 Table 11 shows that two-thirds of the participants (n=300, 67%) indicated that they worked up to 40 hours a week. Over one-quarter (n=119, 27%) identified that they worked over 40 hours per week. Table 11. Hours Worked Weekly by Study Nurse Participants by Health Care Sector Complex Acute care Long-term care continuing care Homecare Overall care Hours N (%) N (%) N (%) N (%) N (%) < 40 hrs/wk 86 (62.3) 96 (72.7) 73 (71.5) 45 (57.0) 300 (66.5) > 40 hrs/wk 45 (32.6) 23 (17.4) 23 (22.5) 28 (35.4) 119 (26.4) No response 7 (5.1) 13 (9.8) 6 (5.9) 6 (7.6) 32 (7.1) Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0) UNIT MANAGER SURVEYS Staff Mix Nurse staffing models varied by sector in this study (see Table 12). The majority of all-rn staffing models were evidenced in acute care settings (21%), while fewer were seen in complex continuing care (8%), homecare (5%), and long-term care (1%). A regulated professional nursing staff mix model comprised of RNs and RPNs was most prevalent in complex continuing care settings in this study (71%) and homecare (48%), with fewer (33%) in acute care, and long-term care (7%). Nurse staffing models comprised of RNs, RPNs, and URWs were most visible in longterm care settings (83%), followed by homecare (41%), complex continuing care (13%), and acute care (13%). RN/URW models are most often seen in acute care (33%), with fewer evident in homecare (6%), long-term care (6%), and complex continuing care (1%). Finally, RPN/URW models are not common, but when they do occur, they are seen in complex continuing care (6%) and long-term care settings (3%). Table 12. Unit Staffing Model by Sector Complex Acute care Long-term care continuing care Homecare Overall care N (%) N (%) N (%) N (%) N (%) RN only 34 (21.4) 2 (1.4) 8 (7.9) 5 (4.9) 49 (9.7) RNs & RPNs 53 (33.3) 10 (6.9) 72 (71.3) 50 (48.5) 185 (36.5) RNs, RPNs, & URWs 20 (12.6) 119 (82.6) 13 (12.9) 42 (40.8) 194 (38.3) RNs & URWs 52 (32.7) 8 (5.6) 1 (1.0) 6 (5.8) 67 (13.2) RPNs & URWs 0 (0.0) 4 (2.8) 6 (5.9) 0 (0.0) 10 (2.0) Missing 0 (0.0) 1 (0.7) 1 (1.0) 0 (0.0) 2 (0.4) Totals 159 (100.0) 144 (100.0) 101 (100.0) 103 (100.0) 507 (100.0) Percentage of RNs The average number of RNs on the study units also varied as identified in Table 13. Acute care study units had a mean percentage of RNs of 75%, followed by complex continuing care study units with 41%, and long-term care units with 25%. Although homecare settings do not provide unit-based care, they have a mean percentage of 70% RNs in their settings. 26 Quality Worklife Indicators for Nursing Practice Environments in Ontario

29 Table 13. Mean Percentage of RNs on Study Units Complex Acute care Long-term care continuing care Homecare Overall care x (SD) x (SD) x (SD) x (SD) x (SD) RNs 74.9 (20.02) 24.6 (29.57) 41.2 (5.52) 70.0 (8.16) 48.4 (29.42) Absenteeism Average rates of absenteeism were highest in long-term care and complex continuing care in this study (see Table 14). Unregulated workers had the highest absenteeism with their average number of days absent in long-term care (x =61), followed by acute care (x =20), and complex continuing care (x =5). For RNs, the highest average number of days absent occurred in long-term care (x =22), followed by complex continuing care (x =9), acute care (x =8), and homecare (x =4). These patterns were similar for RPNs with the highest average number of days absent being in long-term care (x =27), followed by complex continuing care (x =11), acute care (x =7), and homecare (x =4). Table 14. Average Number of Days Absent Annually Complex Acute care Long-term care continuing care Homecare Overall care Employee Group x (SD) x (SD) x (SD) x (SD) x (SD) RN 8.4 (2.99) 22.3 (28.48) 8.5 (5.77) 3.7 (2.54) 11.5 (15.13) RPN 6.6 (3.11) 27.0 (42.92) 10.6 (5.47) 3.7 (2.54) 15.1 (25.75) URW 19.7 (26.27) 60.6 (100.05) 4.9 (1.90) N/A 42.4 (81.87) Employment Status Overall, unit managers in this study indicated that 43% of RNs were employed full-time, while 33% were employed part-time, and 25% in casual positions (see Table 15). In contrast, 38% of RPNs were employed full-time, with close to 35% part-time, and 27% in casual positions. Finally, 39% of URWs worked full-time, 27% part-time, and 34% casually. Table 15. Percentage of Employment by Occupational Status Complex Acute care Long-term care continuing care Homecare Overall care Status N (%) N (%) N (%) N (%) N (%) RN Full-time (56.8) 50.5 (38.8) 98.0 (34.0) 10.0 (6.1) (42.8) Part-time (31.5) 49.5 (38.1) (51.7) 0.0 (0.0) (32.7) Casual 76.0 (11.7) 30.0 (23.1) 41.0 (14.2) (93.9) (24.5) Total (100.0) (100.0) (100.0) (100.0) (100.0) RPN Full-time 29.0 (39.7) 79.0 (39.9) (44.0) 2.0 (2.5) (37.8) Part-time 31.0 (42.5) 66.0 (33.3) (42.3) 0.0 (0.0) (35.1) Casual 13.0 (17.8) 53.0 (26.8) 49.0 (13.7) 77.0 (97.5) (27.2) Total 73.0 (100.0) (100.0) (100.0) 79.0 (100.0) (100.0) URW Full-time 52.0 (68.0) (40.5) 9.0 (33.3) 0.0 (0.0) (39.2) Part-time 23.5 (30.7) (28.9) 7.0 (25.9) 0.0 (0.0) (26.6) Casual 1.0 (1.3) (30.6) 11.0 (40.7) 78.0 (100.0) (34.2) Total 76.5 (100.0) (100.0) 27.0 (100.0) 78.0 (100.0) (100.0) + single site Determining the Feasibility of Collecting Indicator Data 27

30 Differences in employment status were noted by sector, where 57% of acute care RN staff members were employed full-time, while 39% of long-term care RNs, 34% of complex continuing care RNs, and only 6% of homecare RNs were employed full-time. In contrast, the complex continuing care sector employed the highest percentage of full-time RPNs (44%), while 40% of both acute care and long-term care RPNs, and less than 3% of homecare RPNs were employed full-time. Finally, the acute care sector employed the highest percentage of full-time URWs (68%), while 40% of long-term care URWs and 33% of complex continuing care URWs were employed full-time. No URWs working in the homecare sector were employed full-time. For part-time staff members, complex continuing care employed the highest percentage of parttime RNs (52%), while 38% of long-term care RNs and 32% of acute care RNs were employed parttime. In both the acute care and complex continuing care sectors, 42% of RPNs were employed part-time, while 33% of RPNs in the long-term care sector were employed part-time. Similar findings were seen for the percentage of URWs employed part-time in the acute care, long-term care, and complex continuing care sectors; where 31%, 29%, and 26% of URWs in each respective sector were employed part-time. None of the sites in the study sample of homecare sites employed nursing staff part-time. For casual employment, 94% of homecare RNs were employed casually, while 23% of long-term care RNs, 14% of complex continuing care RNs, and 12% of acute care RNs were employed casually. Similarly, within the homecare sector, 98% of RPNs were employed casually, while 27% of long-term care RPNs, 18% of acute care RPNs, and 14% of complex continuing care RPNs worked as casual employees. Finally, 100% of URWs working in the homecare sector were employed casually, while 41% of complex continuing care URWs, 31% of long-term care URWs, and less than 2% of acute care URWs were employed as casual staff. Experience Table 16 demonstrates that the majority of nurses in this study had over 10 years of experience. Some differences were noted by sector, with complex continuing care settings having the highest percentage of nurses with greater than 10 years of experience (n = 303, 64%), acute care with 42% (n = 264), long-term care with 50% (n = 139), and homecare with 20% (n = 40). In contrast, acute care settings in this study had the highest percentage of nurses with less than 2 years of experience. Table 16. Percentage Experience of Nursing Personnel Complex Acute care Long-term care continuing care Homecare Overall care Years N (%) N (%) N (%) N (%) N (%) < 1 year 45 (7.2) 20 (7.1) 23 (4.9) 5 (2.5) 93 (5.9) 1-2 years 70 (11.2) 29 (10.4) 22 (4.6) 28 (13.9) 149 (9.4) 2-5 years 116 (18.6) 39 (13.9) 44 (9.3) 44 (21.8) 243 (15.4) 5-10 years 130 (20.8) 53 (18.9) 81 (17.1) 85 (42.1) 349 (22.1) > 10 years 264 (42.2) 139 (49.6) 303 (64.1) 40 (19.8) 746 (47.2) Totals 625 (100.0) 280 (100.0) 473 (100.0) 202 (100.0) 1580 (100.0) 28 Quality Worklife Indicators for Nursing Practice Environments in Ontario

31 Unit Manager Span of Control The span of control of unit managers in this study also varied (see Table 17). For the most part, acute care unit managers had between 40 and 59 staff reporting to them, while complex continuing care unit managers had between 30 and 59. The number of staff reporting to unit managers in long-term care settings in this study varied more than any of the sectors in this study. Table 17. Span of Control of Unit Managers on Study Units Complex Acute care Long-term care continuing care Homecare Overall care Staff N (%) N (%) N (%) N (%) N (%) < 10 staff 0 (0.0) 2 (11.1) 0 (0.0) 1 (25.0) 3 (5.7) (0.0) 3 (16.7) 0 (0.0) 0 (0.0) 3 (5.7) (6.3) 0 (0.0) 0 (0.0) 1 (25.0) 2 (3.8) (0.0) 1 (5.6) 4 (26.7) 0 (0.0) 5 (9.4) (25.0) 2 (11.1) 4 (26.7) 0 (0.0) 10 (18.9) (56.2) 1 (5.6) 5 (33.3) 0 (0.0) 15 (28.3) (6.3) 0 (0.0) 0 (0.0) 0 (0.0) 1 (1.9) (0.0) 2 (11.1) 0 (0.0) 1 (25.0) 3 (5.7) (0.0) 2 (11.1) 0 (0.0) 0 (0.0) 2 (3.8) (0.0) 0 (0.0) 1 (6.7) 0 (0.0) 1 (1.9) > (6.3) 2 (11.1) 1 (6.7) 1 (25.0) 5 (9.4) Missing 0 (0.0) 3 (16.7) 0 (0.0) 0 (0.0) 3 (5.7) Totals 16 (100.0) 18 (100.0) 15 (100.0) 4 (100.0) 53 (100.0) With the exception of homecare, the majority of managers (n = 40, 76%) in this study were managing multiple units, regardless of sector (see Table 18). Table 18. Mean Scope of Responsibility Complex Acute care Long-term care continuing care Homecare Overall care Scope (Units) N (%) N (%) N (%) N (%) N (%) Managing One 1 (6.3) 5 (27.8) 5 (33.3) 2 (50.0) 13 (24.5) Managing Multiple 15 (93.8) 13 (72.2) 10 (66.7) 2 (50.0) 40 (75.5) 16 (100.0) 18 (100.0) 15 (100.0) 4 (100.0) 53 (100.0) Determining the Feasibility of Collecting Indicator Data 29

32 Nurse-to-Patient Ratios Nurse-to-patient ratios varied by shift and sector in this study (see Table 19). On acute care study units, the nurse-to-patient ratio was 1:5 on days and evenings, and 1:7 on night shifts. Complex continuing care study units had a nurse-to-patient ratio of 1:4 on day shifts, 1:7 on evenings, and 1:13 on nights. In long-term care, these ratios were higher, averaging 1:17 on days, 1:22 on evenings and 1:46 on night shifts. Homecare settings had a standard ratio of 1:8. Table 19. Mean Nurse-to-Patient Ratios by Shift Complex Acute care Long-term care continuing care Homecare Overall care Shift x (SD) x (SD) x (SD) x (SD) x (SD) Days 1 : 5.1 (0.72) 1 : 16.6 (14.91) 1 : 4.3 (0.90) 1 : (0.00) 1 : 9.1 (10.51) Evenings 1 : 5.4 (0.83) 1 : 21.8 (27.22) 1 : 6.8 (1.61) 1 : (0.00) 1 : 11.7 (17.62) Nights 1 : 6.9 (1.44) 1 : 46.1 (48.59) 1 : 12.7 (3.58) N/A 1 : 23.1 (34.06) +Note only one site, therefore no SD SUMMARY Nurse-to-patient ratios varied by shift and sector in this study (see Table 19). On acute care study units, the nurse-to-patient ratio was 1:5 on days and evenings, and 1:7 on night shifts. Complex continuing care study units had a nurse-to-patient ratio of 1:4 on day shifts, 1:7 on evenings, and 1:13 on nights. In long-term care, these ratios were higher, averaging 1:17 on days, 1:22 on evenings and 1:46 on night shifts. Homecare settings had a standard ratio of 1:8. 30 Quality Worklife Indicators for Nursing Practice Environments in Ontario

33 Four Chapter Four: Quality of Nursing Worklife Indicators Introduction Instrument Reliability Nursing Personnel Group Reliability and Completion Rate Comparisons Sector Reliability and Completion Rate Comparisons Missing Data Summary 31

34 INTRODUCTION The first study objective examines the quality of nursing worklife indicator data collected by nurses and managers in everyday practice settings in acute care, complex continuing care, long-term care and homecare settings in Ontario, Canada. The specific research questions were: (1) What is the reliability of data collected by nurses and managers? and (2) What is the completion rate of the nursing worklife measures collected by nurses and managers? The results of these questions are presented overall, as well as according to nursing personnel groups (i.e., RNs, RPNs, and URWs) and health care sectors examined in this study (i.e., acute care, long-term care, complex continuing care, and homecare). INSTRUMENT RELIABILITY Overall Sample The Cronbach s alpha measure for scale reliability was very high for both the Work Quality Index (WQI; α =.95) and the Nursing Work Index-Revised (NWI-R; α =.95) implying that there was high inter-item correlation in the questions being asked in these surveys (see Table 20 below). Completion of the questions by study respondents was slightly better with the WQI instrument (n = 310) as compared to the NWI-R instrument (n = 297) when completing all possible questions. Table 20. Reliability of Nursing Worklife Measures N µ SD α Work Quality Index (WQI) Nursing Work Index-R (NWI-R) NURSING PERSONNEL GROUP RELIABILITY AND COMPLETION RATE COMPARISONS Worklife Scale Reliabilities: RN, RPN and URW There were no appreciable differences between RNs, RPNs, or URWs with respect to either the WQI Cronbach s alpha scores (α =.95,.95,.96) or the NWI-R Cronbach s alpha scores (α =.95,.96,.93) for the overall scales (see Table 21). Thus, the reliability of both instruments is relatively consistent across the different nursing work groups that participated in this study. 32 Quality Worklife Indicators for Nursing Practice Environments in Ontario

35 Table 21. Reliability of Nursing Worklife Measures by Individual Nursing Personnel Group (RN, RPN, and URW) RN only RPN only URW only All staff N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α WQI Professional work environment Autonomy of practice Work worth to self and others Professional relationships Professional role enactment Benefits Overall scale NWI-R Autonomy Control over practice setting Nurse-physician relationship Organizational support Overall scale Determining the Feasibility of Collecting Indicator Data 33

36 Work Quality Index (WQI) An assessment of the WQI instrument by study participants revealed that the Cronbach alpha s were relatively consistent across each of the six subscales professional work environment, autonomy of practice, work worth to self and others, professional relationships, professional role enactment, and benefits (see Table 21). The alpha range was from.71 to.91 with the subscales containing the greater number of items having the largest alpha score. For example, the 8-item Professional Work Environment subscale achieved the highest alpha scores in general, while the 4-item Work Worth to Self and Others subscale scored the lowest alpha ratings. Completion of the subscale questions was lowest for the Work Worth to Self and Others subscale for the RN group. There were only 230 RNs that fully completed that section, as compared to 236 to 250 for the other subscales. This subscale explores the nurses contribution to the hospital, profession, the overall sense of achievement they get from work, and whether or not the work associated with their position provides the opportunity for them to use a full range of skills. It is possible that some RNs were unable to answer these questions because they generally receive inadequate feedback about their contributions to patient care. As well, nurses may have chosen not to answer questions rather than to provide negative answers. A general lack of recognition of the work of nurses within the institution, media, and within the general public often leads nurses to undervalue their own contribution. Increased patient loads and higher patient acuity make work environments stressful, leaving nurses with insufficient time to do the job the way they intended, and there may also be a disconnect between how much autonomy nurses actually have and how much they should have or want to have. For RPNs, completion of the subscale questions was lowest for the Professional Relationships subscale. There were 114 RPNs that fully completed that section, as compared to 116 to 130 for the other subscales. The professional relationships subscale examines support received from physicians and peers for nursing care decisions, support for work from nurses on other shifts, whether good work relations exist with physicians, peers, and supervisors, and whether adequate praise for work well done is received from hospital physicians and peers. It is possible that the nature of the work of RPNs involves less exposure to disciplines outside of nursing. RPNs may work closely with an RN, but may have difficulty answering questions about their relationships with other categories of health care providers. Some RPNs may feel their skills are underutilized or they may not be satisfied with their level of involvement in decision-making and formulating plans of care in the interdisciplinary team and may therefore have chosen not to respond to these questions rather than give an answer that reflects these feelings. Similarly, completion of the subscale questions was lowest for the Professional Relationships subscale for the URW group. There were 25 URWs that fully completed that section, as compared to 31 to 37 for the other subscales. Reasons for low completion on this subsection may have been similar to RPNs. While the level of involvement with health care professionals may be even more limited for URWs than RPNs, this may be mediated by a lower expectation of involvement since these workers are not a part of a regulated health care profession. 34 Quality Worklife Indicators for Nursing Practice Environments in Ontario

37 Nursing Work Index Revised (NWI-R) For the NWI-R instrument, the Cronbach s alphas were relatively consistent across all four subscales autonomy, control over practice, nurse-physician relationship, and organizational support. They appeared to be less specific than the WQI subscale ratings, in general, ranging from.54 to.80. The subscales with the greater number of items had the largest alphas. For example, the 5-item Autonomy subscale scored the lowest alpha ratings, whereas, the 10-item Organizational Support subscale scored the highest, in general. Completion of the subscale questions was lowest for the Control over the Practice Setting subscale for the RN group. There were only 237 registered nurses that fully completed that section, as compared to 242 to 253 for the other subscales. This subscale examines support services in place to allow nurses to spend time with patients, adequacy of time and opportunity to discuss patient care problems with other nurses, adequacy of nurse staffing to provide quality patient care and get work done, effectiveness of nurse manager as a manager and leader, opportunity to work on a highly specialized unit, and patient assignments that foster continuity of care. Control over their practice setting may be impacted by a shortage of nursing staff, increased patient loads, and higher patient acuity. All of these factors may create a challenge for RNs as they try to respond to this scale. Substantial evidence exists on the Canadian nursing work environment that suggests that RNs are interested in having greater control over their practice settings (Advisory Committee on Health Human Resources, 2000; 2002). The low completion rates may indicate that RNs have chosen not to answer the question rather than provide negative answers. For RPNs, completion of the subscale questions was lowest for the Organizational Support subscale. There were 128 RPNs that fully completed that section, as compared to 130 to 133 for the other subscales. This subscale explores support services in place to allow nurses to spend time with patients, whether physicians and nurses have good working relationships, nursing s control over its own practice, adequacy of time and opportunity to discuss patient care problems with other nurses, adequacy of nurse staffing to provide quality patient care and get work done, effectiveness of the nurse manager as a manager and leader, freedom to make important patient care and work decisions, not being placed in a position of having to do things that are against their nursing judgment, teamwork between nurses and doctors, and patient assignments that foster continuity of care. The items on this subscale may not adequately represent RPN practice. It is possible that those who work in organizations where there are few targeted supports in place for RPNs may have difficulty completing this subscale. Similarly, completion of the subscale questions was lowest for the Organizational Support subscale for the URW group. There were 29 URWs that fully completed that section, as compared to 32 to 39 for the other subscales. Again, reasons for low completion on this subsection may have been similar to RPNs. URWs are employed as unregulated support workers. There are few components of this subscale that would be applicable to this group of employees, which might explain the lower rate of completion. Determining the Feasibility of Collecting Indicator Data 35

38 Comparison of Worklife Scales: RN, RPN, and URW In general, the completion was slightly better for the NWI-R subscales (n = 415, 405, 422, and 402) than the WQI subscales (n = 390, 417, 380, 384, 418, and 400). However, if you look at completeness of records for the overall scales, the WQI seemed to fare better (n = 310) than the NWI-R (n = 297) instrument. For RNs, 195 study participants completed every question of the WQI scale, while 183 participants completed every question of the NWI-R scale. The number of RPNs who completed every scale question was 91 for the WQI and 88 for the NWI-R. Finally, the number of URWs who completed every scale question was very similar for both the WQI (n = 22) and the NWI-R (n = 23). These findings are not surprising as the instruments were both originally developed for use with RN populations. It is plausible that the instruments may be tapping facets of nursing practice that are not central to the RPN or URW role, or perhaps are of less interest to nursing personnel in those roles. SECTOR RELIABILITY AND COMPLETION RATE COMPARISONS Worklife Scale Reliabilities: Acute Care, Long-term Care, Complex Continuing Care, and Homecare There were no appreciable differences between acute care, long-term care, complex continuing care, and homecare with respect to either the WQI Cronbach s alpha scores (α =.94,.96,.96,.93) or the NWI-R Cronbach s alpha scores (α =.92,.96,.96,.95) for the overall scales (see Table 22). Thus, the reliability of both instruments is relatively consistent across the different health care sectors that participated in this study. Table 22. Reliability of Nursing Worklife Measures by Health Care Sectors Long-term Complex Acute care care continuing care Homecare Overall care N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α WQI Professional work environment Autonomy of practice Work worth to self and others Professional relationships Professional role enactment Quality Worklife Indicators for Nursing Practice Environments in Ontario

39 Continued Long-term Complex Acute care care continuing care Homecare Overall care N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α Benefits Overall scale NWI-R Autonomy Control over practice Nurse-physician relationship Organizational support Overall scale Work Quality Index (WQI) An assessment of completion of the WQI instrument by different sectors revealed that the Cronbach alpha s were relatively consistent across each of the six subscales professional work environment, autonomy of practice, work worth to self and others, professional relationships, professional role enactment, and benefits (see Table 22). The alpha range was from.77 to.87. Homecare had the smallest number of completed instruments (n = 34) and the lowest alpha (α =.93), while acute care had the highest number of completed instruments (n = 115). The largest alpha (α =.96) was recorded in complex continuing care. Completion of the subscale questions was lowest for the Work Worth to Self and Others subscale for the homecare group. There were only 53 RNs that fully completed that section, as compared to 57 to 73 for the other subscales. This subscale explores the nurses contribution to the Determining the Feasibility of Collecting Indicator Data 37

40 hospital, the profession, the overall sense of achievement they get from work, and whether or not the work associated with their position provides the opportunity for them to use a full range of skills. For complex continuing care, completion of the subscale questions was also lowest for the Work Worth to Self and Others subscale. There were 91 complex continuing care respondents that fully completed that section and the Professional Relationships subscale, as compared to 93 to 95 for the other subscales. For long-term care, completion of the subscale questions was lowest for the Professional Relationships subscale. There were 100 respondents that fully completed that section, as compared to 105 to 120 for the other subscales. The professional relationships subscale examines support received from physicians and peers for nursing care decisions, support for work from nurses on other shifts, whether good work relations exist with physicians, peers, and supervisors, and whether adequate praise for work well done is received from hospital physicians and peers. For acute care, completion of the subscale questions was lowest for the Benefits subscale. There were 126 respondents that fully completed that section, as compared to 130 to 135 for the other subscales. The benefits subscale examines opportunities for professional growth, salary and other financial benefits, funding adequacy for health care premiums, work hour patterns, vacation, sick leave, and inservice opportunities. Nursing Work Index Revised (NWI-R) Similarly, the overall Cronbach s alpha reliability measure for the NWI-R instrument varied from.92 to.96 for the different health care sectors. Again, homecare had the smallest number of completed instruments (n = 42), while acute care had the largest number of completed instruments (n = 108) along with the lowest alpha (α =.92). With the NWI-R scale, long-term care (α =.96) recorded the highest alpha. For the NWI-R instrument the Cronbach s alphas were relatively consistent across all four subscales autonomy, control over practice, nurse physician relationship, and organizational support. They appeared to be much lower than the WQI subscale ratings, in general, the range being from.71 to.78. The subscales with a greater number of items had the largest alphas. For example, the 10-item Organizational Support subscale scored the highest, in general. Completion of the subscale questions was lowest for the Control over the Practice Setting subscale for the homecare group. There were only 61 registered nurses that fully completed that section, as compared to 66 to 74 for the other subscales. This subscale examines support services in place to allow nurses to spend time with patients, adequacy of time and opportunity to discuss patient care problems with other nurses, adequacy of nurse staffing to provide quality patient care and get work done, effectiveness of nurse manager as a manager and leader, opportunity to work on a highly specialized unit, and patient assignments that foster continuity of care. For complex continuing care and long-term care, completion of the subscale questions was lowest for the Organizational Support subscale. There were 95 and 108 respondents respectively that fully completed that section, as compared to 98 to 118 for the other subscales. This subscale explores support services in place to allow nurses to spend time with patients, whether 38 Quality Worklife Indicators for Nursing Practice Environments in Ontario

41 physicians and nurses have good working relationships, nursing s control over its own practice, adequacy of time and opportunity to discuss patient care problems with other nurses, adequacy of nurse staffing to provide quality patient care and get work done, effectiveness of nurse manager as a manager and leader, freedom to make important patient care and work decisions, not being placed in a position of having to do things that are against their nursing judgment, teamwork between nurses and doctors, and patient assignments that foster continuity of care. Completion of the subscale questions was lowest for the Autonomy subscale for the acute care sector. There were 130 respondents that fully completed that section, as compared to 132 to 136 for the other subscales. Comparison of Worklife Scales: Acute Care, Long-term Care, Complex Continuing Care, and Homecare As noted earlier, the completion was slightly better for the NWI-R subscales than the WQI subscales. When examined by sector, for acute care participants, 115 study participants completed every question of the WQI scale, while 108 participants completed every question of the NWI-R scale. The number of long-term care participants who completed every scale question was 81 for the WQI and 77 for the NWI-R. For complex continuing care, 79 participants completed every WQI scale question, while 70 completed the NWI-R. Finally, for home care, the number of participants who completed every scale question was much lower overall, for the WQI (n = 34) and the NWI-R (n = 42). These findings are not surprising as the instruments were both originally developed for use with acute-care or hospital settings, and may not be representative of home care practice. MISSING DATA Overall, for all of the nursing worklife data, every hospital sector and nursing personnel group included, there are no significant differences between the percent of missing values for the WQI questions and the percent of missing values for the NWI-R (see Table 23). Homecare had the highest percentage of missing data on both instruments, followed by long-term care, complex continuing care, and acute care. This corresponds to the findings reported in the focus groups, where homecare and long-term care nursing personnel suggested the instruments were reflective of acute care nursing work environments. For one particular sector and one particular staff group, there were some significant differences between the instruments, with the WQI questions having a few more missing values than the NWI-R questions. Specifically, in the long-term care sector, the WQI questions had an average of 7.79% missing values, whereas the NWI-R questions had an average of 6.17% missing values. These means are judged to be statistically significantly different (t = 1.809; 84 df; p<.10), indicating that in long-term care missing data was significantly greater than that of other sectors. As well, for the URW group of staff, WQI questions had an average of 16.07% missing values, whereas the NWI-R questions had an average of 11.50% missing values. These means are also statistically significantly different (t = 3.115; 78 df; p<.05), indicating that URWs had a higher proportion of missing data than other care providers in this study. Determining the Feasibility of Collecting Indicator Data 39

42 Table 23. Missing Data for Nursing Worklife Measures by Individual Nursing Personnel Group (RN, RPN, and URW) and by Health Care Sectors Overall Acute Long-term Complex Home RN RPN URW nurses care care care care only only only N=451 N=138 N=132 N=102 N=79 N=259 N=140 N=47 Mean Mean Mean Mean Mean Mean Mean Mean (SD) (SD) (SD) (SD) (SD) (SD) (SD) (SD) WQI Average 4.98% 1.60% 7.79% 3.12% 8.56% 3.17% 4.61% 16.07% percent missing (3.03) (1.56) (4.20) (2.45) (9.91) (2.46) (3.86) (7.15) NWI-R Average 4.58% 1.48% 6.17% 3.04% 9.55% 3.96% 3.40% 11.50% percent missing (3.36) (1.61) (4.43) (1.88) (12.6) (3.77) (3.35) (6.79) t-test Average * ** percent missing 86 df 83 df 84 df 67 df 92 df 95 df 73 df 78 df * p < 0.10 ** p < 0.05 SUMMARY These results imply that overall, there were no substantial differences between the WQI and NWI-R scale reliabilities. However, the NWI-R instrument tended to have lower alpha scores than the WQI instrument for the majority of the subscales, within all health care sectors. As well, within the NWI-R subscales, the homecare sector appears to have lower alpha values than the other sectors, for three out of four NWI-R subscales. The completion rate for the scales showed some differences with the WQI subscales achieving a better completion rate by respondents in this study. While there does not seem to be overwhelming evidence to suggest that one instrument is superior to the other, this study suggests that the WQI may be a more stable measure of nursing work environments. Both appear to be fairly reliable and consistent, although some specific sectors (i.e., long-term care) and nursing personnel groups (i.e., URWs) experienced difficulties relating to some of the questions. Thus, consideration should be given to adapting the language of these measures to specific health care sectors (i.e., long-term care, homecare) to accurately capture their unique work environments. 40 Quality Worklife Indicators for Nursing Practice Environments in Ontario

43 FIve Chapter Five: Feasibility and Utility of Collecting Nursing Worklife Indicator Data Introduction Assessing the Feasibility and Utility of Nursing Worklife Indicator Data Collection Summary 41

44 INTRODUCTION The second study objective was to examine the feasibility of collecting nursing worklife indicator data in everyday practice settings in acute care, complex continuing care, long-term care, and homecare settings in Ontario, Canada. The specific research questions were: (1) What is the receptivity to nursing worklife indicator data collection by nurses and managers? and (2) What is the burden of collecting nursing worklife indicator data for nurses and managers? The third study objective examines the utility of nursing worklife indicator data for nurses and managers in acute care, complex continuing care, long-term care and homecare settings in Ontario, Canada. The specific research questions were: (1) To what extent are the nursing worklife indicator data comprehensive, as perceived by nurses and managers? and (2) How relevant and useful are the nursing worklife indicator data in assisting nurses and managers in decision-making for the organization? ASSESSING THE FEASIBILITY AND UTILITY OF NURSING WORKLIFE INDICATOR DATA COLLECTION Focus groups were held with nursing personnel and unit managers to explore the feasibility and utility issues related to nursing worklife data collection. Nursing staff participants worked in either a surgical or a medical unit in an acute care, long-term care, complex continuing care, or homecare setting. Most of the participants were registered nurses, although there were RPNs and URWs as well. All participants were actively involved in the discussion and validated the points raised. Focus group interviews were conducted with 14 nursing staff (i.e., RN, RPN and URW) and 10 manager representatives from each of the four regions in Ontario where the study was being conducted. Nursing staff participants consisted of one person from Region 1 (Central Ontario), six from Region 2 (Southwestern Ontario), three from Region 3 (Eastern Ontario), and four from Region 4 (Northern Ontario). Managers included two from Region 1 (Central Ontario), one from Region 2 (Southwestern Ontario), five from Region 3 (Eastern Ontario), and two from Region 4 (Northern Ontario). In order to assess the feasibility of collecting nursing data in practice settings, information was obtained in focus groups on the amount of time it takes for a nurse and manager to complete the worklife indicator survey. Participants in focus groups were asked to identify the time involved in survey completion, and to identify any barriers and facilitators to nursing worklife indicator data collection. In addition, data was collected from nurses on their perceived ease of collecting the nursing worklife indicator data, ease of interpreting the nursing worklife indicator data, and perceptions of the frequency that it should be collected. Nurses were consulted on their receptivity to incorporating a standardized approach to nursing worklife indicators assessment. Another aspect of feasibility is whether it is possible to collect the nursing worklife indicator data in a timely manner. Information was gathered about the time required for data collection to be completed, completeness of data collection, and reasons for failure to complete the survey. Data was collected from nurses and managers on their perceptions of the factors in the work environment that influence nurses receptivity to completing the survey. 42 Quality Worklife Indicators for Nursing Practice Environments in Ontario

45 Receptivity and Burden of Nursing Worklife Data Collection for Nursing Personnel The nurse surveys contained two instruments that measure aspects of the nursing work environment, the Nursing Work Index Revised and the Work Quality Index, as well as a number of demographic questions. Nursing personnel in this study identified that it took between 15 to 30 minutes to complete the nursing worklife indicators survey, and identified that it was relatively straightforward. Nurses receptivity towards nursing worklife data collection and assessments of the burden associated with it can be characterized by exploring their perceptions of the barriers and facilitators to the process of this data collection. Most of these relate to the organization of nursing work and the work environment. While a few nurses denied any barriers to this data collection existed, a number of impediments were identified by others that related to time available to complete the worklife indicators survey. Getting away from the unit and then returning later to a mess of things that went wrong was a problem for one nurse. In addition to returning to the unit to face a number of problems, nurses also had to cope with colleagues who were frustrated that they had to cover for them when they were gone. Trying to make do with fewer nurses was identified as a challenge. Another nurse felt that the timing of the survey was an obstacle to participation. In this case, the data collection took place at a point in the day when the workload was heavy. Some nurses ended up staying late to complete the survey while others completed the survey on their own personal time. While some expressed aggravation at taking their own time to complete the survey, others talked about the importance of participating despite the additional time required. I did it at the end of shift and I was very, very frustrated....it causes resentment when it s imposed upon my time to say you re to do this but you ll do it on your own time. I specifically had to arrange my day so that I could take time to come and do it. And I just believe that it s important so it was something that I wanted to do. You really do have to create time if you want to do these things. I guess I looked at it from the standpoint that yes, I did it on my coffee break but I wanted to get my opinion in so I didn t mind, I specifically had to arrange my day so that I could take time to come and do it. And I just believe that it s important so it was something that I wanted to do. There was some concern among nurses that management would catch wind of the data they reported in the survey. I was kind of rallying my colleagues to fill it in. They were a little bit intimidated to think that this might be something that might reflect on them badly should they sit down and take the time to do it. I found people when they filled it out they were asking each other back and forth, you know, is it okay to put this type deal because they didn t want to be reprimanded for it. Determining the Feasibility of Collecting Indicator Data 43

46 Participants identified a number of factors that facilitated their participation. Several people talked about being given a room where they could sit, along with a treat to have while they filled out the surveys (i.e., cookies). cookies helped because we were able to sit down, have a snack. If I m not mistaken, it was the only break I had that day which was nice. Support from managers to participate was also identified as a facilitator. We had a nice experience. Our nurse manager mentioned it at a staff meeting and then supplied a nice quiet room for us to go to and had cookies so it was a good experience. We were very well prepared and our manager actually pulled us pulled us from the floor and said don t worry. Our manager was very supportive because a group of us were isolated up in a room and said here s a half an hour to fill out this survey. She was very supportive and encouraged us to do that. We had a nice experience. Our nurse manager mentioned it at a staff meeting and then supplied a nice quiet room for us to go to and had cookies so it was a good experience. A couple of nurses talked about how having the data collector explain confidentiality facilitated their willingness to participate. [The data collector] who did come to our facility did stress that this was completely anonymous. They were very good at reassuring us that this was anonymous and was research and not punitive based. Despite the need to use personal time, one nurse suggested it helped that the survey was dropped off in the morning and picked up later, giving her time to ponder her responses over coffee and lunch breaks. The opportunity to debrief facilitated participation for some of the nurses. I really found I actually enjoyed doing the survey because I think as nurses we don t often have the opportunity to sit down and meet with each other and talk. It was really nice just to sit down for even half an hour with my peers and just say, you know, maybe this place isn t such a bad place to work and I really enjoyed it. Comprehensiveness and Relevance of Nursing Worklife Indicator Data Collection for Nursing Personnel Most nursing staff participants reported that the survey was comprehensive, detailed, and really did get to the heart of the matter. However, there were some difficulties identified by homecare nurses who were completing the survey, compared to nurses working in long-term care, complex continuing care, and acute care sectors. One nurse explained, There were a lot of questions that didn t apply to them [homecare nurses] and they weren t sure what to answer. 44 Quality Worklife Indicators for Nursing Practice Environments in Ontario

47 Participants further highlighted the unique environment in which homecare nurses work. They discussed a variety of services they provide to patients that normally fall outside of nursing (e.g., social work, occupational therapy, and physiotherapy). There are definitely things that the homecare nurses face that you wouldn t necessarily face in a facility. One nurse pointed out that the survey refers to interactions and relationships with other staff on the unit, such as physicians. These questions do not capture the quality of the work of homecare nurses (e.g., isolation) because they are tailored to the acute care rather than the community setting. In response to these problems, one nurse suggested that a future survey elicit feedback specifically from homecare nurses. One participant referred to trick questions, where items on the surveys were unclear or difficult to understand. Participants were asked about a number of specific areas of the survey that had been identified in preliminary data analysis as not being consistently answered. Some nurses had difficulty with questions that referred to a Chief Nursing Officer, Clinical Nurse Specialist, or support staff because there were no such positions in their organizations. While there may have been at one point in time, the question was not applicable to the organization s current status at the time of data collection. when I put not applicable it s because really they don t exist and you should have an explanation as to why it s not applicable. There were a lot of questions that didn t apply to them [homecare nurses] and they weren t sure what to answer. There was also some confusion over the question on the survey pertaining to nursing care delivery models. Focus group participants indicated that the model used in practice can often be ambiguous. years ago they converted us from team nursing to total patient care and yet in fact the ways things went it started out that way but we ve gone back to team nursing because you cannot do total patient care anymore because things are so hectic and stressed and rushed so you absolutely depend on the team. One nurse referred to the model of care as a method of survival. Another nurse denied that there was any official model of care delivery, rather it s just what we need to do to get the work done. When nurse participants in the focus group talked about preceptorship there was a sense that additional clarity for survey questions around preceptorship would be helpful. preceptor program, does that mean an orientation program for new staff? what is the definition of that preceptorship? Determining the Feasibility of Collecting Indicator Data 45

48 Another question on the survey asked about opportunities to participate in hospital committees. One participant said that there were no formal committees in their organizations, therefore the question did not apply to them. Others had a problem answering this question because, while committees exist within their organizations, there were either no openings for new members or the nurses had no time to spare. Nurses also talked about the beneficial aspects of the survey in terms of how they view this process as giving them a voice. I think we want a voice and what I m hearing is that we don t have one. However, the motive and outcome of the research was questioned by a nurse who contemplated whether their opinions were really valued or if interest in their feedback was just, lip service. Another nurse wondered, who s really doing anything about this because over the years you receive so many of these surveys and you fill them out with good intentions but we still go to work and we re still shortstaffed and nobody listens to us. Receptivity and Burden of Nursing Worklife Indicator Data Collection for Unit Managers Unit managers were asked to provide information on the unit-related information in a survey that related to the percentage of RNs in staff mix; percentage of full-time, part-time, and casual nursing staff; educational background of nursing staff; experience of nursing staff employed on the study units in the study sites; span of control of the unit manager; and unit absenteeism rates. Managers identified that it took them between 45 minutes to 2 hours to complete. Survey completion took longer for those managers responsible for multiple nursing units. Similar to the nursing staff, unit managers also found the institutional-focus of the survey a barrier for those in a homecare setting. One manager commented that the survey did not seem applicable to all health care sectors, and expected that the community sector would have filled out a different survey. Comprehensiveness and Relevance of Nursing Worklife Indicator Data Collection for Unit Managers A few participants suggested that there was a need to look at advanced practice nurses (APN) and how they were utilized on the unit, although there was concern that it might be difficult to capture an APNs mandate on a survey. depending on whether they have a regional mandate versus just an organizational mandate makes a difference to their availability on the patient care areas. With respect to the usefulness of the information, managers felt that knowledge of the percentage of baccalaureate nurses, use of casual staff, and breakdown of full- and part-time staff was useful. Gathering those kinds of data made the managers more aware of their numbers. I think knowing how many degree nurses I have was important. And it also made me look at my ratio because I ve always strived for 70% full-time and 30% parttime so in that sense it made me re-look at my complement, my ratio. 46 Quality Worklife Indicators for Nursing Practice Environments in Ontario

49 Managers found some survey questions difficult to complete because the requested information was not readily available. Some problematic areas included the percentage of baccalaureate nurses, years of experience, nurse to patient ratios, use of casual staff, and the number of voluntary resignations. I had to go to Human Resources and to our nursing staffing office to help with the years of experience. To determine the casual staff over a year in each category is I don t know I d collect it all. We don t keep it. We don t keep that kind of data in categories and by unit. Unit managers discussed some of the problems they faced in completing the survey. Several participants described having to gather information from different computer programs to fill out the survey. one of the biggest challenges for myself in doing the questionnaire was having to go from one program electronically to another to access some of the information. And it also made me look at my ratio because I ve always strived for 70% full-time and 30% part-time so in that sense it made me re-look at my complement, my ratio. Other participants had to physically search for the needed information in different departments. As one manager noted, I think some of us had to physically run from one building to the other to Human Resources and to Finance to find some of the data that we needed. Overall, questions about part-time and casual employment numbers as well as voluntary resignations, and number of beds was a source of difficulties for several participants. I also found that the last page, there was a lot of answers I had I couldn t get. In general, the survey was less challenging to fill out for those with smaller units and was more problematic for larger units with more staff. It depends on how many staff you do have because it means HR has to look up the file on each of those people. My unit s small with 20 registered staff so the information was right there. I didn t have the same challenges that the larger units had. There were four areas with inconsistent answers that needed clarification, which included data pertaining to the length of orientation programs and educational programs offered, absenteeism data, and information on the use of agency staff. When asked to clarify their responses around orientation programs, most respondents stated that orientation was provided in their facilities, and the length of orientation was based on need. if the staff nurse comes and say that they need more we will give more orientation. We really do try to individualize it to meet the needs. Determining the Feasibility of Collecting Indicator Data 47

50 Most agreed that new graduates received more orientation than experienced nurses. we give a week for an RN but if they require more we give more and for new grads we ve done a mentorship program for about a month. Also new grads are given more orientation. Managers were also asked about keeping track of educational programs for nurses as well as funding for education. Most units kept track of mandatory education classes attended, such as WHMIS and Advanced Cardiac Life Support courses. It s tracked through our staff education department and it s tracked on-line which courses they ve attended because they have mandatory WHMIS, all that are mandatory. We have a binder on the unit that the nurses sort of keep track on their own unless it s something that s mandatory education and then the clinical educator keeps track of that but we haven t gotten to the on-line part yet. If there s a course that let s say, for example, 10 nurses wanted to go [to] then we might draw names out of a hat. With respect to educational funding, there was a mix of responses with some managers commenting that course and conference registration fees were paid for, and others stating that registration fees were not paid for. Registration fees are given. We pay for the course cost. we were getting reimbursement from RNAO, submitting like a group of nurses registration fees for the year type thing but we re not doing that this year, they re not doing that. One manager commented that time off was given for courses, however, several participants referred to a lack of paid education days. We ll accommodate their time off. but we don t have paid education days per se. We don t have education paid education in the budget. but they don t get paid for their day of work so To determine who had access to educational opportunities, one unit manager stated, If there s a course that let s say, for example, 10 nurses wanted to go [to] then we might draw names out of a hat. 48 Quality Worklife Indicators for Nursing Practice Environments in Ontario

51 Many commented that educational funding is limited as the educational budget for the unit is divided per nurse. Managers spoke of having to divide funds allotted for education among nurses. Programs have a certain amount of money budgeted, however, it s watered down significantly per nurse. The education line budget is held with the Director and the Director has more than one program or one area so it s hard to even know what we have available but I know it s not a lot and it s probably getting less. Managers were also asked to clarify their responses about the absenteeism. Several participants stated absenteeism data was easily available and many kept track of nurse absenteeism with attendance management programs. We re very aware because of our new attendance management program that s been implemented. It s available on the staffing program and it ll break down stats-leave of absence, sick time, WSIB, whatever. And we ve also implemented an attendance management program so the managers are very well aware of absenteeism. We have an attendance management program in [facility name] as well and that s how we re keeping track of, you know, the frequent offenders. it does have an attendance awareness program on-line, which is tracked to the information that our Occupational Health Services department provides us quarterly information so we follow up. Unit managers participating in the focus groups also clarified their responses around use and tracking of agency staff. Some hospitals did not use agency nurses, while others had an inhospital resource pool or used casual nurses for staffing. [Name of organization] does not use agency nurses. [Name of organization] has no agencies like that. internally we have a resource pool and that s how we manage our staffing vacancies. Some units did use agency staff and agency use was tracked and accessible for managers. One manager commented that when benefits for full-time staff were considered, the cost for agency staff was roughly the same as for regular staff. [Name of organization] does use agency nurses and we can track that on our financial reports. When you factor in the benefits that the full-time staff get, 14%, or what part-time staff would get the dollar figure is approximately the same as with agency replacement. Determining the Feasibility of Collecting Indicator Data 49

52 SUMMARY The focus groups examined nursing personnel and unit managers perceptions of the data collection process and provided a better understanding of the feasibility of gathering these data. Specifically, focus groups provided information about the experience of completing the surveys, comprehensiveness, feasibility, utility, and barriers and facilitators to participation. As well, areas identified as problematic during preliminary analysis were explored in more detail. Nurses and managers reported that while the surveys were mostly comprehensive, they were institutionally-focused and therefore, at times, not applicable to the homecare setting. In addition, one manager suggested that the manager survey look more specifically at the presence and utilization of APNs. Several barriers and facilitators for completing the nurse surveys were identified, a number of which were related to problems with physically leaving the unit. A heavy workload, leaving colleagues to cover their patients, fewer nurses left on the unit, and having to stay late were among the challenges discussed. The institutional focus of both the nurse and unit manager surveys was identified as a barrier. There was also intimidation around management having access to nurses responses. Conversely, one of the facilitators identified by nurses was having a data collector who thoroughly explained how confidentiality would be protected. Support from managers, time and space to complete the survey, and providing refreshments were also identified as facilitators. A number of problematic sections of the surveys were identified and explored during the focus groups. In the nursing surveys, questions referring to nursing administrative and support staff were not always answered because they did not exist in some organizations at the time of data collection. Similarly, questions around opportunity for committee involvement may not have been answered because there were either no committees in the facility, or there were no openings on committees. Finally, the question that referred to model of care delivery was not always answered because the model in practice was unclear in some settings. Problematic sections in the unit manager surveys were also explored. For the most part this related to their lack of access to key data on their units such as percentage of baccalaureate nurses, years of experience, nurse to patient ratios, use of casual staff, and number of voluntary resignations. There were also some areas with inconsistencies requiring clarification, including orientation and educational programs, absenteeism, and agency use. Concern with government access to worklife data was raised in the manager focus group, specifically related to disparity between two sources of the same data: reports to the government and the survey data. 50 Quality Worklife Indicators for Nursing Practice Environments in Ontario

53 SIx Chapter Six: Collection and Storage of Nursing Worklife Indicator Data Introduction Feasibility of Collecting and Maintaining Nursing Worklife Indicator Data Summary Nurses Perspectives of Nursing Worklife Indicator Data Collection (Focus Groups) Managers Perspectives of Nursing Worklife Indicator Data Collection (Focus Groups) Summary 51

54 INTRODUCTION The fourth study objective examines the potential sources for where these data can be housed in a database in the future. The specific research questions were: (1) What is the feasibility of collecting nursing worklife indicator data as part of the data collected by the College of Nurses of Ontario (CNO), the Canadian Institute for Health Information (CIHI), and the Canadian Council on Health Services Accreditation (CCHSA), and (2) What is the feasibility of housing nursing worklife indicator data with the CNO, CIHI, and CCHSA. These interviews were held between July 19, 2005 and July 26, Representatives from the CNO, CCHSA, and CIHI were interviewed separately to determine their positions on the feasibility of their involvement in collecting, maintaining, and storing nursing worklife data. These interviews were led by the Principal Investigator and were taped and transcribed to allow for analysis and integration of responses. As well, information obtained from nurses and managers during the focus groups that relates to these study objectives are also presented. FEASIBILITY OF COLLECTING AND MAINTAINING NURSING WORKLIFE INDICATOR DATA (1) College of Nurses of Ontario (CNO) Perspective The CNO is the governing body for the 140,000 RNs and RPNs in Ontario, Canada. The CNO regulates nursing to protect the public interest and sets requirements to enter the profession, establishes and enforces standards of nursing practice, and assures the quality of practice of the profession and the continuing competence of nurses (CNO, 2005). The CNO is in the process of reviewing all of the data currently collected on their annual membership renewal form, and at the moment CNO is not considering collecting data on nursing worklife in Ontario. There are a number of reasons for the current review of their data. First, it is reviewed regularly, with the impetus of enhancing the accuracy of the data that is collected as there is heavy reliance externally on CNO data. It is self-report data and thus the CNO encounters obvious problems with individual nurses not completing the form, which leads to gaps in the data, particularly around employment status. Second, the review is examining why and how CNO can make the tool more user-friendly, while retaining the compulsory elements needed from a regulatory perspective. Challenges for Collecting Nursing Worklife Indicator Data A number of challenges for the CNO to collect nursing worklife data were identified. When considering the CNO strategic plan, which in part discusses bridging the practice realities for nurses, you could make an argument for how it fits with the idea of collecting data on nursing worklife in Ontario. On the other hand, the CNO s current requirement for data and the approach taken is to try to enhance the trust that individual nurses have in the regulator s role. The CNO has been actively working at meeting health human resource data planning needs in Ontario. Moving into collecting data on nursing worklife would be an entirely new agenda for them to consider. The CNO would have to strategically think about how or if they could meet another data collection need. One of the challenges to be considered would be how CNO could merge these two perspectives nursing health human resources and worklife data collection. CNO 52 Quality Worklife Indicators for Nursing Practice Environments in Ontario

55 would need to give serious consideration to whether or not it is appropriate for them to collect data on nursing worklife. Of particular importance is the mandate of the college, as well as nurses perception of the role of the college. A determination of whether the data being collected related to nursing worklife were mandatory would be required. The focus of current CNO data collection as part of the renewal form is mandatory data, not voluntary reporting of select items. If these new data elements were not compulsory, it could lead to confusion for nurses completing the form. The rationale for collecting these data needs to be clearly articulated. Nurses want to know what is going to happen as a result of these data being collected and how quickly they are going to see the difference. Otherwise, they will question the point of collecting these data. As well, this is a very costly exercise, not just financially, but in the goodwill and the general interest that nurses have in ensuring quality care. If the effort, time, and resources of nurses are being put towards mandatory collection of these data, we need to ensure that it really has an impact on quality of care. On the contrary, if these data were compulsory, a number of new challenges would emerge. First, a by-law change would be required. The CNO would have to look at their legislation and determine whether regulatory bodies have the authority to make this information mandatory. It is likely that both a regulation change as well as a by-law change would be required, as the information currently collected by CNO is specified in the by-law. It will be important to consider the length of time and the process that is required for legislative and by-law changes. If the MOHLTC is convinced that there is a role within regulatory colleges to collect worklife data, it should be explored sooner rather than later, because the Health Professions Regulatory Advisory Council s (HPRAC) consultation regarding potential changes to the Regulated Health Profession s Act is going on at this time. The report to the Minister is due by the end of March, It is timely to be looking at expanding it while the legislation is opened. The minister s current plan is to bring legislation forward in the fall of If a legislative change is to happen after that time, it will take substantially longer, perhaps 2009 at the earliest. The terminology used on the CNO renewal form can also pose challenges. The CNO would have to create definitions to ensure that everyone completing the forms understands what is meant when they use a term. That will require substantial education for nurses prior to beginning to collect the data, as well as re-formatting of the existing renewal form. It is also important to consider the implicit assumptions that underpin data collection by the CNO. It is possible that a skewed response would occur if the regulator is collecting information about nurses worklife. Nurses may underrate the quality of their work environment when reporting to the regulatory body. For example, a nurse may know that their obligation as a member of a self-regulated profession is to meet the standards of practice. For whatever reason, they may find themselves having difficulty meeting the standards of practice. The environment might be a factor, but the individual nurse is then deciding how much of a factor the environment is. From a more philosophical perspective, it is quite likely that people would challenge nursing worklife data being collected by the CNO, even if a legislated change were made for it to become the regulator s role, particularly if there is any intention of linking these data to the individual Determining the Feasibility of Collecting Indicator Data 53

56 nurse and patient outcomes. A substantial barrier is the link to a unique identifier the link to individual nurses. This raises questions about what the data are going to be used for. For the CNO, this concern could compromise their quality assurance program. The CNO would need to look at the impact this would have on the College s mandate in relation to ongoing competence. If it were to move forward, it would be a huge initiative that would require a great deal of planning, consultation, and external stakeholder support. The CNO could envision it as a possibility down the road far more easily if it were aggregate data for settings, rather than data linked to individual nurses. Facilitators for Collecting Nursing Worklife Indicator Data The most obvious reason for the CNO to collect data on nursing worklife is that a mechanism already exists for them to obtain information from Ontario s nurses on an annual basis. Advantages can be seen in linking this data collection with registration and annual renewal. The primary advantage is that registration is mandatory annually, and if the regulator collects these data, it reinforces the importance of completing the data forms for nurses. If the intent is not to have mandatory data collection for the nursing worklife data, then it probably does not make sense to have the CNO collect these data. This does not mean that the college might not have a role in collecting the data, but maybe it would be at a different time of the year. As well, the CNO strategic plan serves as a facilitator with strategies aimed at bridging nurses practice realities and supports for nurses and employers in providing quality care in practice settings. This linkage would be evident to the CNO College Council. This leads to some reasons why CNO may be interested in having access to these data, even if the data were available at an aggregate level. Whether the nursing worklife data are collected by CNO or another body, CNO might have an interest in looking at the relationships between nursing worklife data and data it collects through its regulatory processes, such as kinds of calls they get to their practice line in relation to care in a particular sector, the incidence and type of complaints from the public, and reports of termination of nurses. If the nursing worklife data were collected and reported at a higher level of analysis than the individual nurse, it would be easier to achieve compliance with data collection. Collecting nonaggregate data begs the question of what is the real purpose of linking the data to the individual nurse. The obvious conclusion for a CNO member would be that it will be used to challenge nurses individual competencies. It therefore seems like the logical place to start would be at the organization- or unit-level, to get nurses to accurately report in a manner that they feel that they will not be incriminating themselves. If collection of worklife data were mandatory for all regulated health professions, that would be a facilitator. As well, support and buy-in by unions would also be a facilitator. Frequency of Collection of Nursing Worklife Data The CNO representatives felt that the collection of data on nurses worklife should definitely not be conducted any more frequently than annually. Based on their expertise, the CNO suggested that it would be hard to go to nurses and ask them to report on this more frequently than once a year. While decision-makers may wish to have data on nurses worklife more frequently, it is not practical. It takes considerable time to collect these data, review what is being collected, ensure 54 Quality Worklife Indicators for Nursing Practice Environments in Ontario

57 that the data being collected are the right data, and ensuring that good quality data are being collected in an accurate manner. Data Collection Process for Nursing Worklife Indicator Data One of the concerns that have been identified by the advisory committee to the Hospital Report Research Collaborative (HRRC) is the number of different data collection activities that are going on within the province related to worklife. Institutions are saturated with these activities, and that means that individuals are saturated too. The more data collection that we can link, the better. Also, people would be able to see a logical connection among the data that they are providing. The HRRC collect their data annually, so it would make sense to have some of these new initiatives linked. Perhaps the nursing worklife indicator data could be collected through that process. Data Storage and Accessibility A number of locations for data storage and access were identified by the CNO respondents. Possible locations included the Canadian Institute for Health Information (CIHI), the Ontario Ministry of Health and Long-term Care (MOHLTC), the HRRC, and the CNO if legislated. CIHI was identified as an option, particularly if the data being collected involved more than just nursing and were national, rather than just provincial data. Another option is the information management infrastructure within the MOHLTC the Health Results Team for Information Management. The HRRC collaborative was previously identified as they collect annual hospitallevel data from hospitals across Ontario. Finally, the CNO could be contemplated given all of the considerations outlined in this interview. The CNO stressed the importance of standardization of the data collection process for these data. The CNO suggested that there should be means and ways of having the data accessible to researchers and decision-makers. Such systems are currently in place at the CNO and they are exploring new ones to enhance accessibility. There are safeguards that need to be in place to ensure privacy, a clear understanding of why the information is being obtained, what it is going to be used for, and who it is released to. Currently the college publishes annual membership statistics reports that are posted on the website. The CNO also handles complex research requests regarding information not available through the report. This involves a separate request that is submitted and processed. When data are released, it is aggregate data that cannot link back to the individual nurse. Costs Associated with Data Collection and Storage A number of costs are associated with the collection of data of this nature. Many of these are difficult to estimate. If these data were to be collected by CNO, it may be layered on to the existing renewal forms, or it may need to be done separately. The current renewal process is a smooth, but complicated process. There would be an additional cost involved in collecting and processing the data because it is quite a lengthy process of reviewing and cleaning the annual renewal form. Costs associated with collecting nursing worklife data could be based somewhat on the annual renewal process costs, as well as this parallel process required to collect the new worklife data. It would be that cost plus the extra burden in the first few years for data cleaning, set up of the database, and testing. As well, it may be necessary to house the data offsite because of space challenges, thus leading to additional costs. Determining the Feasibility of Collecting Indicator Data 55

58 (2) Canadian Council on Health Services Accreditation (CCHSA) Perspective The mission of the CCHSA is to drive quality in health services through accreditation. To achieve its mission, CCHSA provides health services organizations with an accreditation program based on national standards and knowledge exchange. CCHSA has a demonstrated interest and proven experience in data collection related to work life indicators. In March 2004, CCHSA convened a national meeting to share information and knowledge regarding recent work in the area of work life indicators in Canada. A significant number of meeting participants represented professional nursing bodies from across Canada. In 2004, CCHSA and the Ontario Hospital Association (OHA) formed a partnership to collaborate on a worklife indicators research project. The objective was to develop and test a pulse-type survey tool that would enable health service organizations to monitor key work life indicators. Challenges for Collecting Nursing Worklife Indicator Data CCHSA representatives have noted that a number of different data collection initiatives targeting the health care workplace and worklife issues are currently underway, both nationally and provincially. If a review of the data/information that is being collected from each of the tools was conducted, collaboration on data collection may be possible. For example, CCHSA could identify the information that it requires for their accreditation process. Then, once the tools required to measure nursing worklife were identified, they may complement the accreditation process, and CCHSA could explore whether there is a way to either synchronize or tie together the data collection tools. As a national organization, it is important to CCHSA that any tool developed and resulting data collected are applied nationally so that all health care organizations benefit. Consequently if work in this area is Ontario-based, it is important for CCHSA to be able to apply it on a broader scale so that all can benefit. While data collection on nursing work life is profession-specific and provides vital information, worklife quality is a concern of leaders in health care organizations across all employment and professional groups. CCHSA has noted that it is important to pursue a measurement tool that provides a worklife pulse relevant to multiple professions and employees. Facilitators for Collecting Nursing Worklife Indicator Data CCHSA would be interested in nursing worklife data, regardless of which organization collects the data. As the accreditation program evolves, CCHSA will be collecting and monitoring organizational data on a continual basis, to provide surveyors with information about the environment in which they will survey. This will identify specific areas upon which the surveyors might focus. CCHSA is therefore looking at a number of priority areas and associated data elements that would help to scope out and identify these survey target areas. The identification of elements that need to be measured in the nursing work environment would be important information that CCHSA would benefit from. Based on CCHSA s leadership position in accreditation, the Council may be well-positioned to collect nursing work environment-related data. CCHSA s involvement would facilitate recognition of the importance that the nursing work environment must be attended to, and that it is an essential component of measuring quality within health care organizations. CCHSA recently completed a pilot test of the worklife Pulse survey, in conjunction with the Ontario Hospital Association. The Pulse survey includes measures related to the work 56 Quality Worklife Indicators for Nursing Practice Environments in Ontario

59 environment (e.g., communication, supervision, job control); individual outcomes (e.g., perceived job stress, self-rated overall health, job satisfaction); and organizational outcomes (e.g., absenteeism, presenteeism, organizational satisfaction). CCHSA is currently investigating whether to incorporate this tool into the accreditation program. The Pulse survey would then be available to any of its client organizations. In addition to providing the organizations leadership with important information, as mentioned above, these data elements would also help CCHSA identify target areas within organizations upon which the surveyors might focus. Frequency of Collection of Nursing Worklife Indicator Data From CCHSA s perspective, it is important to collect data in a timely manner to support the accreditation process. As a result, the timing of data collection as well as data utilization are important issues for CCHSA to consider. Ideally, the timing for data collection should correspond to and support the accreditation timeline and the critical issues (priority focus areas) that face the organization. In addition, ultimately, the data must be accessible in a timely way and meet the accreditation process requirements. By way of example, CCHSA discussed the worklife Pulse tool and the frequency of data collection. The Pulse survey is a simple tool that can be administered by an organization at almost any time. At the direction of the organization s leadership, staff could complete the online survey from a computer within the organization or externally. To optimize its value, the Pulse survey should be completed relatively frequently a minimum of twice a year. This minimum takes into consideration the rapid changes in the health care environment, and the related issues and stressors faced by care and service providers. As improvement initiatives are implemented, the online survey can provide a pulse as to the results or impact. Are initiatives and strategies which have been implemented, having the desired impact on worklife? The tool can therefore provide relatively rapid insight into key worklife indicators being monitored and inform decision-making. The simplicity of data collection may also be an important factor to consider when attempting to identify an appropriate measurement instrument related to nursing worklife. The CCHSA-OHA Pulse tool includes 20 measures that would inform planning and action within health care organizations. The Pulse survey should be considered as complementary to a more comprehensive employee survey. At indicated, the Pulse survey would be administered at regular intervals, complementing a more intensive employee survey currently used annually or biannually by health care organizations. The complementary model approach may also enable organizations to add a limited number of specific measures (questions) to the Pulse tool in order to gather data on a particular issue or concern that the organization is facing at that time. Data Collection Process for Nursing Worklife Indicator Data As discussed above, CCHSA is supportive of an online data collection process for a worklife survey. Nurses would be able to complete the survey from their homes or work. While access to computers and computer knowledge can both be challenging issues, strategies can be implemented to manage them successfully. CCHSA s experience is that a Pulse survey team/champion within each organization is required to facilitate and coordinate the online survey process. It is important to communicate the objectives of the survey clearly and consistently, and to take action based on survey results. Determining the Feasibility of Collecting Indicator Data 57

60 Data Storage and Accessibility Collecting the nursing worklife data and maintaining it in a database is something that CCHSA would consider. Factors such as the size of the survey, and the scope of the data collection anticipated for the future would be important considerations. The current survey data that CCHSA collects, not including the worklife Pulse data, is accessible to members in aggregate form. CCHSA also produces a national health accreditation report which is released on an annual basis. This aggregate report is widely distributed across the country, and available on the CCHSA website. Individual client organizations can also access their own organization-specific confidential data. Given the significant database built on survey data, CCHSA has the potential to compare sectors across the country and produce provincial roll-up reports, as long as individual organization data confidentiality is maintained. Similarly, CCHSA has processes and systems in place to share data with researchers and decision-makers while protecting client confidentiality. CCHSA suggests that a national organization is best suited to manage the worklife data collection and storage. This would ensure consistency in data collection and storage, and would support integrity of the overall objective. CCHSA has no concern if these data were to be collected and housed by another national organization, provided that CCHSA has timely access to the data for accreditation-related purposes. Data collection and storage by provincial regulatory colleges would likely lead to data inconsistencies between the provinces, as well as challenges when trying to aggregate the data nationally. Costs Associated with Data Collection and Storage If CCHSA were to lead the data collection and storage processes, the associated costs would have to be identified and long-term funding obtained. Sustainable funding would be required to support long-term data collection and analysis so that worklife trends and patterns can be identified and addressed across the country. The costs of collecting, analyzing, maintaining, and storing data are important questions for any national organization considering this challenging and exciting endeavor. (3) Canadian Institute for Health Information (CIHI) Perspective CIHI is an independent, pan-canadian, not-for-profit organization working to improve the health of Canadians and the health care system by providing quality, reliable and timely health information (CIHI, 2005d). CIHI develops and maintains a number of health databases and registries related to health care, including health care services, health human resources, and health spending. This includes identifying national health indicators and conducting special studies and analyses on key areas of interest. CIHI has led the development of a standardized database on nursing health human resources in Canada, and publishes nursing workforce reports annually based on these data. Most recently, CIHI has partnered with Statistics Canada and Health Canada in undertaking a National Survey of the Work and Health of Nurses. The survey is being administered by Statistics Canada to a sample of registered nurses (RNs), licensed practical nurses (LPNs), and registered psychiatric nurses from across Canada and will help to identify relationships between selected health outcomes, the work environment, and worklife experiences. Specific topic areas include: work history, job satisfaction, hours of work, absences from work, perception of the quality of care, respect and support, general health, chronic conditions and work limitations, and work stress. 58 Quality Worklife Indicators for Nursing Practice Environments in Ontario

61 The one-time survey will produce a comprehensive national data set that will provide information on the health and working conditions of nurses across Canada (CIHI, 2005d). Challenges for Collecting Nursing Worklife Indicator Data CIHI typically does not do primary data collection, although because of their level of existing involvement in nursing data collection in Canada, CIHI may consider the possibility of collecting this nursing worklife data. CIHI s role would likely be that of the data warehouse, therefore somebody else would need to collect the data and file it in an electronic format that is consistent with CIHI standards. At CIHI there is a transfer of ownership or partnership that needs to be established for the maintenance of data. Typically, there would be an agreement between the owner and CIHI to create a partnership that would establish the frequency of data collection, that privacy is being respected, and how the data can be used and accessed. The time involved with this process may be considered a challenge for data collection. Data being collected also have to fit within the CIHI mandate, and the use and relevancy for CIHI to house and maintain this type of database must be considered. Currently the mandate of CIHI may be broad enough to reflect data collection on nursing worklife indicators, but this request would need to be considered by the Board of Directors and the Chief Executive Officer to determine if CIHI can play a role with these data. It is important to consider how these data can be considered an important component of health information in Canada to fit with CIHI s mandate. CIHI is a nationally based institute, but they do not reject data collection because it takes place in a single province. CIHI would normally be interested in promoting it if other provinces wanted to use the tool and provide the data back to CIHI for the development of larger reports. Facilitators for Collecting Nursing Worklife Indicator Data The key facilitator for CIHI is that it has longstanding experience in collecting data related to nursing human resources in Canada. Currently CIHI is also collaborating on data being collected by Statistics Canada on the National Survey of the Work and Health of Nurses. The areas covered in that survey are similar to those identified as key worklife indicators for nursing. Thus, CIHI is uniquely positioned both experientially and as a data institute to manage these data and has the system in place and the technology for such data collection. It would be necessary to adapt their technology according to the fields and the number of records that would need to be maintained. CIHI also has a data quality framework that is applied to all data. They have experience with developing data quality processes for large datasets to ensure the accuracy of the information. Essentially, when CIHI receives a file, it would go through some edit checks electronically as well as an edit check visually. Often there is a need to go back to the owner or the sender with a few questions, and then once the process is done and the data is considered clean, it goes into the database where it could be queried for analytical output. After that, the data goes through CIHI s data quality framework where every piece of information is documented (e.g., number of surveys sent out, response rates, changes to survey, number of questions removed or added, etc.). This data framework guides CIHI s interpretation of the data in any reports generated from it. Determining the Feasibility of Collecting Indicator Data 59

62 Frequency for Collection of Nursing Worklife Indicator Data One of the key factors to consider with data collection of this nature is who the target audience is. For decision-makers, planners, or health care professionals, they tend to want to see the results of the data collection and have time to develop strategies around the findings. In some cases it can take up to three years for an institution to respond. Therefore by repeating the survey too quickly, you would not see the results expected from the application of a new policy, new guidelines, or new procedure as a result of the previous findings. It can take four to five years to see a change. Decision-makers always indicate the need to generate a response to the data and to give that change time to occur. Some policies can be applied quickly, while others take time. In contrast, if you are looking for trends only, data collection could be conducted yearly. Caution should be taken with annual trends data to ensure that they are not used in a negative or punitive manner towards the institution. Annual data collection could be used more for monitoring of worklife. This can be particularly useful at times of changes in government funding or new policy directions that are out of the control of the institution. In these cases the yearly data collection could give some good information timely information. You could get the reaction to a SARS event, for example, things that the employer cannot control. CIHI works with a lot of stakeholders, and one of the challenges they hear is that if the tool is changed too frequently, you lose comparability. Comparability is a key element to be considered in order to see trends and enable accurate comparisons. Data Collection Process for Nursing Worklife Indicator Data From CIHI s perspective individual-level data collection is always better. With gathering individual-level nursing worklife data at the place of employment there may be a sense that the administration will have ownership of the data. If data collection were to be conducted by the MOHLTC, responses may be reflective of government policies (i.e., cutbacks to funding), rather than the issue being addressed in the survey. The regulatory bodies or Colleges may be most feasible as they already have the mechanisms and processes for surveying nurses annually. Data Storage and Accessibility CIHI, as the premier health information data warehouse in Canada, have systems and processes in place for data storage and access. These systems include mechanisms to ensure data consistency and accuracy, as well as processes for accessing data by researchers and decisionmakers. This process includes preparing a statement of the project purpose or research question, determining the data holdings from which data are needed, reviewing the relevant data quality and privacy information, developing a list of the scope of data and data elements required to achieve the study purpose including a rationale for each variable requested, prior to having initial discussion with the CIHI data contact person, and completion of a data request and confidentiality form. CIHI provides cost estimates for these data requests. Costs Associated with Data Collection and Storage CIHI costs related to data management would include an initial cost for the system, and then smaller costs associated with maintenance of the system on an ongoing basis. As well, human resources costs for data maintenance would need to be determined. 60 Quality Worklife Indicators for Nursing Practice Environments in Ontario

63 SUMMARY All three of the stakeholder groups provide some considerations for who could be a potential source to house the nursing worklife data in the future. Each has specific challenges that bear deliberation. It is plausible that data collection and storage will need to be considered separately. For example, while CIHI may be seen as a repository for storage and maintenance of these data, they are not in the habit of conducting primary data collection. In contrast, the CNO has a mechanism in place to survey nurses annually, yet to do so would require a change in their mandate. Finally, CCHSA has identified an existing short Pulse tool that they are currently testing, and suggest it could serve as a marker for when a more focused nursing worklife survey is needed. As well, CCHSA may able to accommodate this nursing worklife survey as part of their accreditation process. Nurses Perspectives of Nursing Worklife Indicator Data Collection (Focus Groups) When asked about preferred methods of data collection, nurses in the focus groups discussed a variety of options, weighing the pros and cons of completing the survey along with their nursing registration, on-line, at home, and at work. Several nurses preferred the idea of having the data collected along with annual renewal of their College of Nursing registration. If you re already in the frame of mind of having to fill out a survey and what s another couple of pages when you re already sitting down and dedicating that block of time to doing something. It was also suggested that the response rate would be higher if the data was collected along with CNO registration. However, there was a concern expressed regarding anonymity. if you want to reach more nurses and have everybody have a chance to do it then send it with the registration as long as they can send it back in a separate envelope and be anonymous. If you re already in the frame of mind of having to fill out a survey and what s another couple of pages when you re already sitting down and dedicating that block of time to doing something. There were also nurses who disagreed with the notion of collecting the data along with the CNO registration. One nurse suggested that it would cause problems for nurses who tended to procrastinate with renewing registration. An alternative to collecting data with renewal of registration was an on-line survey. Other focus group participants resisted on-line data collection. I dislike the computer. I don t get on-line often enough because my kids are always on-line. One nurse suggested that they be given the choice between completing the survey on-line or with registration. Determining the Feasibility of Collecting Indicator Data 61

64 Another debate centred on whether it was best to complete the survey at home or at work. While some completed their nursing worklife study survey at home out of necessity (e.g., sick leave), others chose to complete it at home because they found it more relaxing. Nurses talked about how completing it at work made them feel rushed. Some questioned the accuracy of either approach to data collection. One nurse was concerned that they may not have paid as much attention to the survey at work as they might have if they had done it at home. I really felt that if we had the opportunity to take it home some of my answers would have been maybe a bit different because I would have had more time to consider the right response. Another indicated that it was possible that by completing the survey at home, there would be a failure to capture the emotions aroused in the work environment. if you do it at work you re getting an honest opinion at the time of the irritations, of the things you like, things you don t like. If you come home you sort of cool off and you think well maybe it wasn t this bad but then you go back the next day and it was that bad. I get impatient with having to provide the same information, I would rather update information. Focus group participants were asked how often they thought the nursing worklife indicator data should be collected. The vast majority thought that in order to fully capture changes in the workplace, the data should be collected approximately every six months. because in our society now everything is changing so fast. You can go into work one week, be off three weeks, go back and they ve decided to change something already. And I mean there s just so much change going on in our world and with our patients. my answers I would have sent in last fall would be totally different from how I would answer the questionnaire today. depending on which provincial party s in or if there s a change of rules that comes down the pipeline, you know, you can be stressed at one time of year and then things resolve and you re less stressed at another time of year and things happen frequently. There s a little bit more volatility in the workplace because of the changing government and budgets and the downfall from, you know, top down kind of perspective but I think definitely needing it at least twice a year because of that change and we need to reflect that. Managers Perspectives of Nursing Worklife Indicator Data Collection (Focus Groups) Managers were also asked about their preferred method of collecting nursing worklife data. Many were happy to submit the data on-line and most preferred to be able to update changes instead of re-entering data from the start. If this was somehow on-line and I could just go in and amend the data when something changed. I get impatient with having to provide the same information, I would rather update information. then if we could do it and then send it back and just make any changes that would be one option. 62 Quality Worklife Indicators for Nursing Practice Environments in Ontario

65 Others would prefer that the survey be sent out electronically or that a central website be created where the information would be located, only requiring periodic updates. Some managers wanted an integrated way of collecting nursing worklife data, but there were no specific suggestions on how to achieve this. it sounds good to have an integrated way of doing it. Participants discussed access to the nursing worklife data, and some expressed concern over the MOHLTC having access to the information, especially if there were inconsistencies between the data submitted from the nursing worklife survey and information from other reports and sources. I guess we would have to make sure that the numbers that we were submitting to this were consistent with what the hospital was submitting to the Ministry numbers coming in from two different sources don t always match up for very, very innocent reasons that kind of thing I found in my experience is a bit of an alert to the Ministry where there doesn t really need to be one. We have to report that to the Ministry anyway so it s not like they re unaware of what our numbers are. It might perhaps be overly emphasizing a point that some of us would rather not be overly emphasized. it sounds good to have an integrated way of doing it. Others were concerned about submitting data that could be misinterpreted if information was collected at a time when the unit was in the process of reorganization or change. They [the Ministry] wouldn t have any idea of the changes that were going on within an organization that could impact our responses from one six month period or annually. in how this information was going to be used in the sense that if you were in an environment that was evolving or changing, programs, units, or increasing the number of staff based on the opening of beds, that would make a different flavour to answer those questions on an annual or every six month basis for some and so it could be misleading in some way SUMMARY In terms of frequency, focus group participants recommended that nursing data should be collected every six months to keep up with the dynamic health care environment. Nurses discussed different methods of data collection, such as collecting data along with annual College of Nursing registration and on-line. There was a suggestion that nurses be given a choice between the two methods of data collection as there was some resistance to both. Managers also expressed a preference for a system in which data could be entered one time only, and then updated. Determining the Feasibility of Collecting Indicator Data 63

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67 seven Chapter Seven: Nursing Worklife in Ontario Introduction Mean Scale Scores for Work Quality Index (WQI) by Nursing Personnel Group Summary Mean Scale Scores for Work Quality Index (WQI) by Health Care Sector Mean Scale Scores for Nursing Work Index (NWI-R) by Health Care Sector Conclusions 65

68 INTRODUCTION Further analysis of the nursing worklife survey data was conducted to obtain an assessment of nursing worklife in Ontario. First, the mean scores for each of the scales and subscales were assessed. Next, differences in the mean scores for each of the nursing personnel groups and health care sectors were explored. MEAN SCALE SCORES FOR WORK QUALITY INDEX (WQI) BY NURSING PERSONNEL GROUP The WQI has seven response options ranging from not satisfied to satisfied. Overall, the mean score for all of the nursing staff grouped together was indicating that study participants were neither satisfied nor dissatisfied with the quality of their work environment (see Table 24). Table 24. Mean Score for Worklife Indicators for Nursing Personnel Groups (RN, RPN, URW) and Health Care Sectors Long- RN RPN URW All Acute term Complex Home Overall only only only staff care care care care care WQI Professional work environment Autonomy of practice Work worth to self and others Professional relationships Professional role enactment Benefits Overall scale NWI-R Autonomy Control over practice setting Nurse-physician relationship Organizational support Overall scale Quality Worklife Indicators for Nursing Practice Environments in Ontario

69 Further analysis of the responses for each of the nursing personnel groups was conducted by exploring the mean scores on the WQI overall. Table 26 demonstrates that registered nurses had a significantly higher overall mean WQI score (x = 4.392) than did the unregulated workers (x = 4.008) [t = 1.989, 26 df, p <.05 one tailed] in this study. Mean scores for registered practical nurses (x = 4.237) were not significantly different from either the RNs or the URWs. Some variation in the mean scores could be seen for the individual subscales (see Table 25). The overall mean scores were highest for the work worth to self and others (x = 4.996) and autonomy of practice (x = 4.967) subscales, and lowest for the professional work environment (x = 3.745) and benefits (x = 3.901) subscales. RNs scored highest on all but one of the subscales with the exception of work worth to self and others. In turn, RPNs scored higher than URWs on all of the subscales with the exception of work worth to self and others and benefits. Some of these differences in mean scores were found to be significant (see Table 26). Specifically, RNs had a significantly higher mean score for the professional work environment (x = 3.819) than URWs (x = 3.520) [t =2.164, 37 df, p <.05 two tailed]. In contrast, RPN mean scores were not significantly different from either the RNs or the URWs for the professional work environment subscale. RNs also had a significantly higher mean score for autonomy of practice (x = 5.155) than did the URWs in this study (x = 4.243) [t =15.30, 44 df, p <.05 two tailed] (see Table 26). As well RNs had a significantly higher mean score for autonomy of practice (x = 5.155) than did the RPNs (x = 4.243) [t = 9.16, 222 df, p <.05 two tailed]. Similarly, RPNs had a significantly higher mean score for autonomy of practice (x = 4.830) than did the URWs (x = 4.243) [t =9.126, 59 df, p <.05 two tailed]. In contrast, URWs had a significantly higher mean score for work worth to self and others (x = 5.073) than did RPNs (x = 4.922) [t =2.011, 52 df, p <.05 two tailed] (see Table 26). Also, RNs had a significantly higher mean score for work worth to self and others (x = 5.030) than did RPNs (x = 4.922) [t = 2.396, 233 df, p-value <.05 two tailed. Mean scores for RNs and URWs were not significantly different for the work worth to self and others subscale. RNs also had a significantly higher mean score for professional relationships (x = 4.735) than did URWs (x = 3.845) [t = 4.776, 27 df, p <.05 two tailed] (see Table 26). As well, RPNs had a significantly higher mean score for professional relationships (x = 4.565) than did URWs (x = 3.845) [t = 3.672, 33 df, p-value <.05 two tailed]. Mean scores for RNs and RPNs were not significantly different for the professional relationships subscale. RNs also had a significantly higher mean score for professional role enactment (x = 4.434) than URWs (x = 3.933) [t = 2.54, 44 df, p <.05 two tailed] (see Table 26). As well, RPNs had a significantly higher mean score for professional role enactment (x = 4.355) than URWs (x = 3.933) [t = 2.105, 47 df, p-value <.06 two tailed]. Mean scores for RNs and RPNs were not significantly different for the professional role enactment subscale. RNs had significantly higher mean scores for benefits (x = 3.988) than RPNs (x = 3.758) [t = 4.29, 270 df, p <.05 two tailed] (see Table 25). Mean scores between RPNs and URWs as well as RNs and URWs were not significantly different for the benefits subscale. Determining the Feasibility of Collecting Indicator Data 67

70 Table 25. Work Quality Index Mean Score Differences Between Nursing Personnel Groups (RN, RPN, and URW) WQI x SD N Professional work environment RN URW t = 2.164*, df = 1,37 Autonomy of practice RN URW t = 15.30*, df = 1,44 RN RPN t = 9.16*, df = 1,222 RPN URW t = 9.126*, df = 1,59 Work worth to self and others RN RPN t = 2.396*, df = 1,233 URW RPN t = 2.011*, df = 1,52 Professional relationships RN URW t = 4.776*, df = 1,27 RPN URW t = 3.672*, df = 1,33 Professional role enactment RN URW t = 2.54*, df = 1,44 RPN URW t = 2.105*, df = 1,47 Benefits RN RPN t = 4.29*, df = 1,270 Overall RN *P <0.05 URW t = 1.989*, df = 1,27 68 Quality Worklife Indicators for Nursing Practice Environments in Ontario

71 Mean Scale Scores for the Nursing Work Index (NWI-R) by Nursing Personnel Group The NWI-R has four response options ranging from strongly agree to strongly disagree. Table 25 demonstrates that overall, the mean score for all of the nursing staff grouped together was indicating that study participants reported some presence of the key work environment factors in their work settings (i.e., autonomy, control over practice setting, nursephysician relationships and organizational support). Further analysis of the responses for each of the nursing personnel groups was conducted by exploring the mean scores on the NWI-R overall. No significant differences were found between the overall mean scores for RNs (x = 2.314), RPNs (x = 2.251) and URWs (x = 2.304; see Table 25). RNs had a significantly lower mean score on the autonomy subscale (x = 2.192) than URWs (x = 2.385) [t = , 55 df, p <.05 two tailed] (see Table 27). RNs also had a significantly lower mean score on the autonomy subscale (x = 2.192) than RPNs (x = 2.270) [t = 4.567, 186 df, p <.05 two tailed]. As well, RPNs had a significantly lower mean score for autonomy (x = 2.270) than did the URWs (x = 2.385) [t = 5149, 117 df, p <.05 two tailed]. There were no significant differences in mean scores for the control over practice subscale between the three nursing personnel groups in this study. RNs had a significantly higher mean score on the nurse-physician relationship subscale (x = 2.153) than RPNs (x = 2.110) [t = 4.035, 352 df, p <.05 two tailed] (see Table 27). RNs also had a significantly higher mean score on the nurse-physician relationship subscale (x = 2.153) than did the URWs (x = 2.021) [t = 5.429, 44 df, p <.05 two tailed]. Finally, RPNs had a significantly higher mean score on the nurse-physician relationship subscale (x = 2.110) than URWs (x = 2.021) [t = 3.893, 34 df, p <.05 two tailed]. RNs had a significantly higher mean score for organizational support (x = 2.287) than RPNs (x = 2.240) [t = 1.961, 334 df, p <.05 two tailed] (see Table 26). Mean scores between RNs and URWs and between RPNs and URWs were not significantly different for the organizational support subscale. Determining the Feasibility of Collecting Indicator Data 69

72 Table 26. Nursing Work Index Mean Score Differences Between Nursing Personnel Groups (RN, RPN, and URW) NWI-R x SD N Autonomy RN URW t = *, df = 1,55 RN RPN t = 4.567*, df = 1,186 RPN URW t = 5.149*, df = 1,117 Nurse-physician relationship RN RPN t = 4.035*, df = 1,352 RN URW t = 5.429*, df = 1,44 RPN URW t = 3.893*, df = 1,34 Organizational support RN *P <0.05 RPN t = 1.961*, df = 1,334 SUMMARY Work Quality Index RNs in this study had significantly higher overall perceptions of the quality of their work and work environment than URWs. Specifically, RNs held higher perceptions of the professional work environment, autonomy of practice, professional relationships and professional role enactment than URWs. As well, RNs had higher perceptions of autonomy of practice, work worth to self and others, and benefits than RPNs in this study. RPNs in this study had higher perceptions of autonomy of practice, professional relationships, and professional role enactment than URWs. In contrast, URWs held a higher perception of their work worth to self and others than RPNs in this study. 70 Quality Worklife Indicators for Nursing Practice Environments in Ontario

73 Nursing Work Index-Revised No substantial differences between the nursing personnel groups were noted overall for the NWI-R. RNs had lower scale scores for autonomy, which indicates that they have higher perceptions of autonomy than URWs or RPNs. As well, RNs had higher perceptions of the nurse-physician role than either RPNs or URWs, and higher perceptions of organizational support than RPNs. RPNs had lower scale scores for autonomy than URWs, indicating that they have higher levels of autonomy. As well, RPNs identified higher perceptions of the nurse-physician relationship than URWs. MEAN SCALE SCORES FOR WORK QUALITY INDEX (WQI) BY HEALTH CARE SECTOR Table 27 demonstrates that homecare nurses had a significantly higher overall mean WQI score (x = 4.809) than acute care nurses (4.163) [t = 3.258, 47 df, p <.05] and complex continuing care nurses (x = 4.215) [t = 2.925, 51 df, p <.05]. As well, long-term care nurses had a significantly higher overall mean WQI score (x = 4.440) than acute care nurses (x = 4.163) [t = 2.568, 194 df, p-value <.05]. Homecare nurses had significantly higher mean scores on the professional work environment subscale (x = 4.261) than acute care nurses in this study (x = 3.475) [t = 5.557, 73 df, p <.05] as well as complex continuing care nurses (x = 3.511) [t = 4.961, 92 df, p <.05] (see Table 28). Long-term care nurses had significantly higher mean scores on the professional work environment subscale (x = 4.013) than complex continuing care nurses (x = 3.511) [t = 5.773, 173 df, p <.05] and acute care nurses (x = 3.475) [t = 7.838, 229 df, p <.05]. Homecare nurses had significantly higher mean scores on the autonomy of practice subscale (x = 5.713) than acute care nurses in this study (x = 4.921) [t = , 115 df, p <.05], as well as complex continuing care nurses (4.748) [t = , 162 df, p <.05), and long-term care nursing staff (x = 4.758) [t = , 145 df, p <.05]. In contrast, acute care nurses had significantly higher mean scores on the autonomy of practice subscale (x = 4.921) than complex continuing care nurses (x = 4.748) [t = 3.919, 144 df, p <.05] and long-term care nursing staff (x = 4.758) [t = 5.548, 264 df, p <.05]. Long-term care nurses had significantly higher mean scores on work worth to self and others (x = 5.002) than complex continuing care nursing staff (x = 4.92) [t = 2.249, 193 df, p <.05]. Determining the Feasibility of Collecting Indicator Data 71

74 Table 27. Work Quality Index Mean Score Differences Between Health Care Sectors WQI x SD N Professional work environment Home Acute t = 5.557*, df = 1,73 Home Complex t = 4.961*, df = 1,92 Long-term Complex t = 5.773*, df = 1,173 Long-term Acute t = 7.838*, df = 1,229 Autonomy of practice Home Acute t = *, df = 1,115 Home Complex t = *, df = 1,162 Home Long-term t = *, df = 1,145 Acute Complex t = 3.919*, df = 1,144 Acute Long-term t = 5.548*, df = 1,264 Work worth to self and others Long-term Complex t = 2.249*, df = 1,193 Professional relationships Home Acute t = 6.389*, df = 1,130 Home Complex t = 4.111*, df = 1,139 Home Long-term t = 4.449*, df = 1, Quality Worklife Indicators for Nursing Practice Environments in Ontario

75 Continued WQI x SD N Professional role enactment Home Acute t = 9.349*, df = 1,208 Home Complex t = *, df = 1,163 Home Long-term t = *, df = 1,187 Benefits Complex Home t = 2.400* df = 1,127 Long-term Home t = 4.003*, df = 1,149 Long-term Complex t = 2.114*, df = 1,203 Complex Acute t = 3.147*, df = 1,173 Long-term Acute t = 5.174*, df = 1,175 Overall Home Acute t = 3.258*, df = 1,47 Home Complex t = 2.925*, df = 1,51 Long-term Acute t = 2.568*, df = 1,194 *P <0.05 Homecare nurses had significantly higher mean scores on the professional relationships subscale (x = 5.081) than acute care nurses in this study (x = 4.480) [t = 6.389, 130 df, p <.05] as well as complex continuing care nurses (x = 4.588) [t = 4.111, 139 df, p <.05], and long-term care nurses (x = 4.599) [t = 4.449, 120 df, p <.05]. Determining the Feasibility of Collecting Indicator Data 73

76 Homecare nurses had significantly higher mean scores on the professional role enactment subscale (x = 5.499) than acute care nurses in this study (x = 4.173) [t = 9.349, 208 df, p <.05] as well as complex continuing care nurses (x = 4.027) [t = 10.63, 163 df, p <.05], and long-term care nurses (x = 4.158) [t = 10.26, 187 df, p <.05]. Complex continuing care nurses had significantly higher mean scores on the benefits subscale (x = 3.961) than homecare nurses (x = 3.732) [t = 2.400, 127 df, p <.05] and acute care nurses (x = 3.756) [t = 3.147, 173 df, p <.05]. As well, long-term care nurses had significantly higher mean scores on the benefits scale (x = 4.139) than homecare nurses (x = 3.732) [t = 4.003, 149 df, p <.05], complex continuing care nurses (x = 3.961) [t = 2.114, 203 df, p <.05], and acute care nursing staff (x = 3.756) [t = 5.174, 175 df, p <.05]. MEAN SCALE SCORES FOR NURSING WORK INDEX (NWI-R) BY HEALTH CARE SECTOR Table 28 demonstrates that homecare nurses had a significantly lower overall mean NWI-R score (x = 1.89) than acute care nurses (x = 2.44) [t = , 94 df, p <.05], complex continuing care nurses (x = 2.34) [t = 7.621, 103 df, p <.05] and long-term care nurses (x = 2.28) [t = 6.869, 99 df, p-value <.05]. As well, long-term care nurses had a significantly lower overall mean NWI-R score(x = 2.28) than acute care nurses (x = 2.43) [t = 3.057, 170 df, p <.05]. For the specific subscales, home care nurses also had significantly lower mean scores on the autonomy subscale (x = 1.85) than acute care nurses (x = 2.37) [t = , 202 df, p <.05], complex continuing care nurses (x = 2.33) [t = , 151 df, p <.05], and long-term care nurses (x = 2.257) [t = , 187 df, p <.05] (see Table 28). As well, long-term care nurses had significantly lower mean scores on the autonomy subscale (x = 2.25) than complex continuing care nurses (x = 2.33) [t = 3.327, 174 df, p <.05] and acute care nurses (x = 2.37) [t = 6.063, 244 df, p <.05]. Home care nurses also had significantly lower mean scores on the control over practice subscale (x = 1.92) than acute care nurses (x = 2.52) [t = , 136 df, p <.05], complex continuing care nurses (x = 2.57) [t = , 111 df, p <.05], and long-term care nurses (x = 2.437) [t = 9.971, 155 df, p <.05] (see Table 29). As well, long-term care nurses had significantly lower mean scores on the control over practice subscale (x = 2.44) than complex continuing care nurses (x = 2.57) [t = 3.067, 196 df, p <.05]. Home care nurses also had significantly lower mean scores on the nurse-physician relationship subscale (x = 2.05) than acute care nurses (x = 2.26) [t = , 170 df, p <.05], complex continuing care nurses (x = 2.22) [t = , 117 df, p <.05], and significantly higher than long-term care nurses (x = 1.96) [t = 8.001, 168 df, p <.05] (see Table 29). As well, complex continuing care nurses had significantly higher mean scores on the nurse-physician relationship subscale (x = 2.04) than long-term care nurses (x = 1.96) [t = , 161 df, p <.05]. Finally, acute care nurses had significantly higher mean scores on the nurse-physician relationship subscale (x = 2.26) than long-term care nurses (x = 1.96) [t = , 231 df, p <.05]. 74 Quality Worklife Indicators for Nursing Practice Environments in Ontario

77 Home care nurses also had significantly lower mean scores on the organizational support subscale (x = 1.96) than acute care nurses (x = 2.41) [t = , 151 df, p <.05], complex continuing care nurses (x = 2.36) [t = , 145 df, p <.05], and long-term care nurses (x = 2.24) [t = 6.707, 172 df, p <.05] (see Table 29). As well, complex continuing care nurses had significantly higher mean scores on the organizational support subscale (x = 2.36) than long-term care nurses (x = 2.24) [t = 2.985, 194 df, p <.05]. Finally, acute care nurses had significantly higher mean scores on the organizational support subscale (x = 2.41) than long-term care nurses (x = 2.24) [t = 4.340, 204 df, p <.05]. Table 28. Nursing Work Index Mean Score Differences Between Health Care Sectors NWI-R x SD N Autonomy Home Acute t = *, df = 1,202 Home Complex t = *, df = 1,151 Home Long-term t = *, df = 1,187 Long-term Complex t = 3.327*, df = 174 Long-term Acute t = 6.063*, df = 1,244 Control over practice Home Acute t = *, df = 1,136 Home Complex t = *, df = 1,111 Home Long-term t = 9.971*, df = 1,155 Long-term Complex t = 3.067*, df = 1,196 Determining the Feasibility of Collecting Indicator Data 75

78 Continued NWI-R x SD N Nurse-physician relationship Home Acute t = *, df = 1,170 Home Complex t = *, df = 1,117 Home Long-term t = 8.001*, df = 1,168 Complex Long-term t = *, df = 1,161 Acute Long-term t = *, df = 1,231 Organizational support Home Acute t = *, df = 1,151 Home Complex t = *, df = 1,145 Home Long-term t = 6.707*, df = 1,172 Complex Long-term t = 2.985*, df = 1,194 Acute Long-term t = 4.340*, df = 1,204 Overall Home Acute t = *, df = 1.94 Home Complex t = 7.621*, df = 1,103 Home Long-term t = 6.869*, df = 1,99 Long-term Acute t = 3.057*, df = 1,170 *P < Quality Worklife Indicators for Nursing Practice Environments in Ontario

79 CONCLUSIONS Nursing Personnel Groups From the perspective of individual nursing personnel groups, the WQI appears to tap more dimensions of the nursing work environment that are relevant to different care provider groups than the NWI-R in this study. Overall, the NWI-R appeared to discriminate less between the provider groups in this study. Health Care Sectors From the perspective of the different health care sectors, both instruments appear to discriminate between the sector groups well. Home care nurses had higher perceptions of the work environment overall and on most of the subscales for both instruments. Determining the Feasibility of Collecting Indicator Data 77

80

81 eight Chapter Eight: Abstracting and Linking Nursing Worklife Indicator Data Introduction Unit-Manager Data Summary 79

82 INTRODUCTION The fifth study objective examines the feasibility of abstracting and linking nursing worklife indicator data to other datasets (e.g., outcomes). The specific research questions were: (1) What is the feasibility of abstracting nursing worklife indicator data? and (2) What are the issues associated with abstracting and linking nursing worklife indicator data to data from different databases, such as Management Information Systems (MIS), Canadian Institute for Health Information (CIHI), and across settings? Data were collected using two mechanisms to test these linkages. First, unit managers for each of the study units were asked to provide unit-level data on the nurse structural variables percentage of registered nurses in staff mix; percentage of full-time, part-time, and casual nursing staff; educational background of nursing staff; experience of nursing staff employed on the study units in the study sites; span of control of the unit manager; unit absenteeism rates; nursing overtime hours; and agency staff hours. These data elements were used in a unit-level analysis of the data. As well, secondary data on the secondary data structural variables nursing hours per weighted case/rug weighted patient day; nursing overtime hours; agency staff hours; absenteeism hours; and workload/productivity (i.e., direct patient care) was also sought from the organization s management information system database, the Ontario Hospital Reporting System (OHRS) at one point in time for fiscal year 2004/2005, for the acute care and complex continuing care sites in this study. However, data provided for this secondary analysis were not available at the level of the patient care unit rather they are provided only at the aggregate level of functional centre, which is comprised of a grouping of units in a program. Thus, the data analysis using secondary analysis could not be conducted, as the units of measurement were not consistent. The results presented for the linkage are based on primary data obtained from unit managers. Unit-Manager Data The unit manager data were analyzed to determine if relationships existed between any of the unit-level nursing structural variables and the overall WQI and NWI-R scores for each of the health care sectors in this study. Acute Care A statistically significant positive relationship was found between overall NWI-R scores and span of control (rho =.25, p =.00*) in acute care (see Table 29). This indicates that the higher the span of control of the unit manager, the higher unit staff nurses responses on the overall NWI-R. Higher scores on the NWI-R indicate that nurses are not satisfied with the level or presence of specific factors in their work environment including autonomy, control over the work environment, relationships with physicians and organizational supports. As well, a statistically significant positive relationship was noted between the overall NWI-R and RN absenteeism rates (rho =.51, p =.08**), suggesting that the higher RN absenteeism, the greater dissatisfaction with the quality of the nursing work environment. Finally, a statistically significant positive relationship was found between the nurse-to-patient ratio on the day (rho =.48, p =.06**) and night shifts (rho =.47, p =.07**) and overall NWI-R scores, suggesting that nurses on units where the nurse-to-patient ratio was highest on these shifts, reported higher dissatisfaction with the quality of the work environment. 80 Quality Worklife Indicators for Nursing Practice Environments in Ontario

83 Similarly, a statistically significant relationship was noted between overall WQI scores and span of control (rho = -.19, p =.03*) in acute care. This suggests that the lower the span control of the unit manager the higher the level of satisfaction reported by unit nurses with the quality of their work and work environment. High scores on the WQI indicate greater satisfaction with the professional work environment, autonomy, work worth, professional relationships, role enactment and benefits. Complex Continuing Care A statistically significant positive relationship was noted between the overall NWI-R scores and overall nursing experience (rho=.25, p=.01*) and experience in the present role (rho =.25, p =.01*), suggesting that nurses with more years of experience indicated greater dissatisfaction with the quality of the nursing work environment. As well, a statistically significant positive relationship was noted between the overall NWI-R scores and RPN absenteeism rates (rho=.49, p=.09**), suggesting that the higher RPN absenteeism, the greater unit nurses dissatisfaction with the quality of the nursing work environment. Finally, a statistically significant positive relationship was found between the nurse-to-patient ratio on the day (rho=.46, p=.10**) and evening shift (rho =.49, p =.08**) and overall NWI-R scores, suggesting that nurses reported higher dissatisfaction with the quality of the work environment on units with higher nurse-to-patient ratios. A statistically significant positive relationship was noted between the overall WQI scores and nursing education (rho =.25, p =.01*), indicating that the higher the level of education of nurses on the unit, the higher the level of satisfaction reported with the quality of their work and work environment. As well, a statistically significant negative relationship was noted between the overall WQI scores and overall nursing experience (rho = -.24, p =.02*) and experience in the present role (rho = -.26, p =.01*), suggesting that less experienced nurses reported the highest level of satisfaction with the quality of the nursing work environment. Finally, a statistically significant negative relationship was noted between the nurse-to-patient ratio on the day (rho = -.48, p =.08**) and night shifts (rho = -.59, p =.03*) suggesting that the higher the nurse-topatient ratio on these shifts, the lower nurses satisfaction with the work and work environment. Long-term Care A statistically significant positive relationship was found between overall NWI-R scores and span of control (rho =.22, p =.01*) in long-term care, indicating that the higher the span of control of the unit manager, the greater the dissatisfaction with the quality of the nursing work environment. A statistically significant positive relationship was noted between the overall WQI scores and the percentage of RNs employed on the unit (rho =.55, p =.03*), indicating that the higher the percentage of RNs on the unit, the higher the level of satisfaction reported by unit nurses with the quality of their work and work environment. As well, a statistically significant positive relationship was noted between the overall WQI scores and nursing education (rho =.18, p =.04*), indicating that the higher the level of education of nurses on the unit, the higher the level of satisfaction reported with the quality of their work and work environment. A statistically significant negative relationship was noted between the overall WQI scores and experience in the present role (rho = -.15, p =.10*), suggesting that less experienced nurses reported the highest level of satisfaction with the quality of the nursing work environment. Determining the Feasibility of Collecting Indicator Data 81

84 Home Care A statistically significant positive relationship was noted between the overall NWI-R scores and nursing education (rho =.28, p =.02*) suggesting that home care nurses with the highest level of education indicated greater dissatisfaction with the quality of the nursing work environment. Overall A statistically significant positive relationship was noted between the overall NWI-R scores and nurses experience in the present role (rho =.17, p =.00*), suggesting that nurses with the largest amount of experience indicated greater dissatisfaction with the quality of the nursing work environment. A statistically significant positive relationship was found between overall NWI-R scores and span of control (rho =.26, p =.00*), indicating that the higher the span of control of the unit manager the greater overall nurses dissatisfaction with the quality of the nursing work environment. Finally, a statistically significant positive relationship was noted between the overall NWI-R scores and the number of hours nurses worked per week (rho =.09, p =.06**), suggesting that the more nurses work each week the greater their dissatisfaction with the quality of their work and work environment. A statistically significant positive relationship was noted between the overall WQI scores and nursing education (rho =.14, p =.01*) indicating that the higher the level of education of nurses on the study units, the higher the level of satisfaction reported with the quality of their work and work environment. A statistically significant negative relationship was noted between the overall WQI scores and experience in the present role (rho = -.13, p =.01*), suggesting that overall in this study, less experienced nurses reported the highest level of satisfaction with the quality of the nursing work environment. SUMMARY The results from the unit-level analysis are fairly consistent across both of the nursing work environment instruments. Several of the study variables of interest that had emerged from the original review of the literature were found to be related to the nursing work environment measures across sectors. These include span of control of the unit manager, absenteeism, nurseto-patient ratios, experience, and education. As well, in long-term care, the percentage of RN staffing was also identified. 82 Quality Worklife Indicators for Nursing Practice Environments in Ontario

85 Table 29: Correlations for Unit-Level Nursing and Unit Structural Variables Complex Acute care continuing care Home care Long-term care Overall care NWI-R WQI NWI-R WQI NWI-R WQI NWI-R WQI NWI-R WQI rho(p) rho(p) rho(p) rho(p) rho(p) rho(p) rho(p) rho(p) rho(p) rho(p) Nurse Structural Variables Percent Registered Nurse -.31(.24) -.21(.44) -.21(.46).44(.12) -.22(.78).89(.11) -.34(.20).55(.03)* -.02(.92).23(.12) Percent Full Time -.05(.86) -.38(.21) -.20(.56) -.15(.67) -.19(.81).50(.50) -.25(.41) -.07(.82) -.10(.54) -08(.61) Percent Part Time -.12(.71).43(.14) -.35(.29).45(.17) -.19(.81).49(.51) -.27(.37) -.47(.11) -.14(.39) -.08(.62) Percent Casual.13(.67) -.43(.15).48(.13) -.26(.44).19(.81) -.50(.50).33(.28).37(.22).14(.38).10(.55) Education.01(.96).05(.57) -.16(.11).25(.01)*.28(.02)* -.10(.38).07(.45).18(.04)*.05(.28).14(.01)* Experience Years employed in nursing -.01(.87).08(.38).25(.01)* -.24(.02)*.08(.47) -.03(.83).08(.36).05(.62).08(.11) -.01(.79) Years employed in present role.02(.84).07(.42).25(.01)* -.26(.01)*.05(.70) -.04(.75).05(.55) -.15(.10).17(.00)* -.13(.01)* Span of Control.25(.00)* -.19(.03)*.09(.40).09(.37) -.01(.96).05(.68).22(.01)* -.07(.47).26(.00)* -.08(.10) Absenteeism RN.51(.08).24(.43).44(.14) -.23(.45) (.27).06(.88) -.12(.49).13(.45) RPN.01(.99) -.53(.47).49(.09) -.30(.32) (.93) -.07(.87) -.04(.85) -.11(.57) URW.79(.42) -.46(.70).50(.67).08(.95) (.54).13(.75) -.20(.47).12(.67) Unit Structural Variables Nursing hours worked per week.07(.42).07(.42).15(.16) -.07(.53) -.12(.33).00(.99).08(.40) -.05(.57).09(.06) -.02(.62) OT -.06(.68).12(.42).20(.36) -.20(.37).22(.26) -.32(.10) -.28(.18).24(.28) -.04(.67) -.01(.93) Agency RN (.84) -.09(.87) (.62).32(.45) -.01(.97).01(.96) RPN (.35).59(.21) (.30) -.23(.58) -.27(.35).00(1.00) URW (.84) -.35(.77) (.42) -.09(.82).05(.87).03(.92) Workload/productivity: Nurse-Patient Ratio: Day.48(.06).29(.28).46(.10).-48(.08) (.65).27(.30).04(.77).21(.15) Evening.08(.77).17(.53).49(.08).43(.13) (.53) -.22(.40).10(.50) -.04(.77) Night.47(.07).42(.11).45(.11) -.59(.03)* (.66).06(.82) -.17(.26).12(.42) Determining the Feasibility of Collecting Indicator Data 83

86

87 nine Chapter Nine: Discussion and Conclusions Introduction Quality of Nursing Worklife Indicator Data A Snapshot of Nursing Worklife in Ontario Conclusions 85

88 INTRODUCTION The primary purpose of this study was to evaluate the feasibility, quality, and utility of instituting data collection for nursing worklife indicators in acute care, long-term care, complex continuing care, and homecare settings in Ontario, Canada. A second purpose was to examine the potential for linkage of these data to the clinical outcomes data collected in similar settings as part of the Health Outcomes for Better Information and Care initiative (formerly the Nursing and Health Outcomes Study). A third purpose was to make recommendations regarding potential sources for where these data can be housed in a database in the future. The study was conducted in a total of 65 patient care units in 20 health care facilities, of which 5 were acute care, 7 were long-term care, 4 were complex continuing care, and 4 were homecare settings across the province. The sample comprised a total of 451 nursing personnel (i.e., RNs, RPNs, and URWs) in these facilities, with approximately 30% of responses coming from acute care, 29% from long-term care, 23% from complex continuing care, and 18% from homecare nursing staff. Approximately 57% of respondents were RNs, 31% were RPNs, and 10% were URWs. All 53 unit managers on the study units participated in the study. QUALITY OF NURSING WORKLIFE INDICATOR DATA Reliability of Data Collected The Cronbach s alpha measure for scale reliability was very high for both the Work Quality Index and the Nursing Work Index-Revised indicating that both instruments are stable, and the questions being asked in these surveys elicit consistent and reliable responses. There were no appreciable differences between the scale reliabilities for RNs, RPNs, or URWs with respect to either the WQI or the NWI-R overall scales. There were also no notable differences between acute care, long-term care, complex continuing care, and homecare with respect to either the WQI or the NWI-R Cronbach s alpha scores. Thus, the reliability of both instruments is relatively consistent across the different nursing work groups and health care sectors that participated in this study. These results imply that overall, there were no substantial differences between the WQI and NWI-R scale reliabilities. However, the NWI-R instrument tended to have lower alpha scores than the WQI instrument for the majority of the subscales, within all health care sectors. As well, within the NWI-R subscales, the homecare sector appears to have lower alpha values than the other sectors, for three out of four NWI-R subscales. Completion Rate In general, the WQI seemed to fare better than the NWI-R instrument in terms of completion rate. RNs appeared to have the most ease of completion, followed by RPNs and URWs. These findings are not surprising as the instruments were both originally developed for use with RN populations. It is plausible that the instruments may be tapping facets of nursing practice that are not central to the RPN or URW role, or perhaps are of less interest to nursing personnel in those roles. When examined by sector, the number of homecare participants who completed every scale question was much lower than the other sectors for both instruments, suggesting that the instruments are best suited for hospital settings, and may not be feasible for homecare practice. This corresponds 86 Quality Worklife Indicators for Nursing Practice Environments in Ontario

89 to the findings reported in the focus groups, where homecare and long-term care nursing personnel suggested the instruments were reflective of acute care nursing work environments. There does not seem to be overwhelming evidence to suggest that one instrument is superior to the other. Both appear to be fairly reliable and consistent, although some specific sectors (i.e., homecare) and nursing personnel groups (i.e., URWs) experienced difficulties relating to some of the questions. Thus, consideration should be given to adapting the language of these measures to specific health care sectors (i.e., long-term care, homecare) to accurately capture their unique work environments. Receptivity and Burden of Nursing Worklife Indicator Data Collection Focus groups were held with nursing personnel (i.e., RN, RPN, and URW) and unit managers to explore the feasibility and utility issues related to nursing worklife data collection from across the different health care sectors. Nursing personnel in this study identified that it took between 15 to 30 minutes to complete the nursing worklife indicators survey, and identified that it was relatively straightforward. Nurses receptivity towards nursing worklife data collection and assessments of the burden associated with it related primarily to whether there were supports in place to permit them to complete the survey in their work environment. While a few nurses denied any barriers to this data collection existed, a number identified that time available to complete the worklife indicators survey was a potential impediment. Participants identified a number of factors that facilitated their participation. Comprehensiveness and Relevance of Nursing Worklife Indicator Data Some challenges were encountered with obtaining accurate and comparable data from the unit managers in this study. For example, managers were asked to provide data on the average number of days annually that they used agency nursing staff as replacement staff. These data were not available by managers from all settings, and the data quality when provided was questionable. Most nursing staff participants reported that the survey was comprehensive, although there were some difficulties identified by homecare nurses who were completing the survey. The relevance of specific items for homecare nursing practice was questioned. As well, some participants identified concern with the relevance of the questions to their practice settings. Managers identified that it took them between 45 minutes to 2 hours to complete the unit manager survey, particularly for those managers responsible for multiple nursing units. One of the concerns identified by managers was the lack of necessary data to complete the questionnaire. Problematic sections in the unit manager surveys were also identified. For the most part this related to their lack of access to key data on their units such as percentage of baccalaureate nurses, years of experience, nurse-to-patient ratios, use of casual staff, and number of voluntary resignations. There were also some areas with inconsistencies requiring clarification, including orientation and educational programs, absenteeism, and agency use. Collection, Storage, and Management of Nursing Worklife Data Representatives from the College of Nurses of Ontario, CCHSA, and CIHI were interviewed to determine the feasibility of their involvement in collecting, maintaining, and storing nursing worklife data. As well, this information was also sought from nurses and managers during the focus groups. All three of the stakeholder groups provided some considerations for who could Determining the Feasibility of Collecting Indicator Data 87

90 be a potential source to house the nursing worklife data in the future. Each has specific challenges that bear consideration. It is plausible that data collection and storage will need to be considered separately. For example, while CIHI may be seen as a repository for storage and maintenance of these data, they are not in the habit of conducting primary data collection. Despite this, they have considerable experience in the management of large administrative datasets, and the systems and processes necessary to determine data reliability and consistency. In contrast, the CNO has a mailing mechanism in place to contact Ontario regulated nursing personnel annually, yet to add on a worklife survey would require a change in their mandate. While there may be a fit with their strategic plan, the CNO would need to consider their role as a regulatory body prior to making this decision. Finally, CCHSA has identified an existing short Pulse tool that they are currently testing, and suggest it could serve as a marker for when a more focused nursing worklife survey is needed. Thus, they have an identified interest and are leading some work in this area across the country. CCHSA may be able to accommodate this nursing worklife survey as part of their accreditation process in the future, although the frequency of administration of this survey would need to be assessed. All three groups have mechanisms in place to provide access to such data in an anonymized ethical manner. Further work is required prior to a decision being made on the location and storage of these data in the future. Linking Nursing Worklife Data to Clinical Outcomes The feasibility of abstracting and linking nursing worklife indicator data to other datasets and the issues associated with this abstraction and linkage were examined in this study. Data for the nursing worklife indicators were obtained at the nursing unit level in this study. Complementary data from study units were obtained from the Management Information System (MIS) as part of the Ontario Hospital Reporting System (OHRS) for the acute care and complex continuing care settings in this study. These are the only sectors where data currently exist that could be used for data linkage. However, the data available from the OHRS is available only at the level of the functional centre, which can include several patient care units in the aggregate data. At the current time, there is no method for clearly breaking out the aggregate functional centre data from the OHRS dataset to the level of the patient care unit, thus this analysis could not be conducted in this study. This is a concern that needs to be addressed in the future to enable these data to be useful to health care leaders, decision-makers, policy makers, and researchers. Similar data elements were also obtained from unit managers in the study in an effort to explore these linkages. As noted earlier, this process was quite burdensome and time-intensive for unit managers, requiring them to seek out data sources that were not readily accessible to them. It is evident that this process is not a viable approach to use in the future. Despite this, the data obtained from unit managers provided some important information about the consistency and relevance of several of the nursing worklife indicators examined in this study. Specifically, several of the study variables of interest that had emerged from the original review of the literature were found to be related to the nursing work environment measures across sectors. These include span of control of the unit manager, absenteeism, nurse-to-patient ratios, experience, and education. As well, in long-term care, the percentage of RN staffing was also linked to higher work environment perceptions. 88 Quality Worklife Indicators for Nursing Practice Environments in Ontario

91 A SNAPSHOT OF NURSING WORKLIFE IN ONTARIO When considering the Work Quality Index, RNs in this study had significantly higher overall perceptions of the quality of their work and work environment than URWs higher perceptions of the professional work environment, autonomy of practice, professional relationships, and professional role enactment; and higher perceptions of autonomy of practice, work worth to self and others, and benefits than RPNs in this study. RPNs in this study had higher perceptions of autonomy of practice, professional relationships, and professional role enactment than URWs. In contrast, URWs held a higher perception of their work worth to self and others than RPNs in this study. No substantial differences between the nursing personnel groups were noted overall for the NWI-R. RNs had lower scale scores for autonomy, which indicates that they have higher perceptions of autonomy than URWs or RPNs. As well, RNs had higher perceptions of the nurse-physician role than either RPNs or URWs, and higher perceptions of organizational support than RPNs. RPNs had lower scale scores for autonomy than URWs, indicating that they have higher levels of autonomy. As well, RPNs identified higher perceptions of the nurse-physician relationship than URWs. CONCLUSIONS From the perspective of individual nursing personnel groups, the WQI appears to tap more dimensions of the nursing work environment that are relevant to different care provider groups than the NWI-R in this study. Overall, the NWI-R appeared to discriminate less between the provider groups in this study. From the perspective of the different health care sectors, both instruments appear to discriminate between the sector groups well. Homecare nurses had higher perceptions of the work environment overall and on most of the subscales of both of the instruments. Determining the Feasibility of Collecting Indicator Data 89

92 Appendix A SEMI-STRUCTURED INTERVIEW PARTICIPANTS SSI # 1 July 19, 2005 College of Nurses of Ontario Anne Coghlan, Executive Director Margaret Poon, Manager, Information Management SSI # 2 July 21, 2005 Francine Anne Roy SSI # 3 July 26, 2005 Wendy Nicklin 90 Quality Worklife Indicators for Nursing Practice Environments in Ontario

93 References Advisory Committee on Health Human Resources. The Nursing Strategy for Canada, Report of the Advisory Committee on Health Human Resources, Retrieved from the WWW on April 14, 2003, ( Advisory Committee on Health Human Resources. Our Health, Our Future Creating Quality Workplaces for Canadian Nurses, Final Report of the Canadian Nursing Advisory Committee, Retrieved from the WWW on April 14, 2003, ( cnac_report/index.html), Aiken, L. H., & Patrician, P. A. (2000). Measuring organizational traits of hospitals: The revised nursing work index. Nursing Research, 49(3), Canadian Council on Health Services Accreditation (CCHSA). (2004). Worklife Indicators Research Project. Ottawa, ON: Health Canada. Canadian Institute for Health Information (CIHI; 2005a). Workforce Trends of Registered Nurses in Canada, Retrieved on October 26, 2005 from Workforce_RN_2004_e.pdf Canadian Institute for Health Information (CIHI; 2005b). Workforce Trends of Licensed Practical Nurses in Canada, Retrieved on October 29, 2005 from products/workforce_lpn_2004_e.pdf Canadian Institute for Health Information (CIHI; 2005c). Workforce Trends of Regulated Nurses in Canada, (CD-ROM ISBN # ). Ottawa, ON: Author. Canadian Institute for Health Information (CIHI). (2005d, August 29). CIHI Taking health information further. Retrieved November 26, 2005, from disppage.jsp?cw_page=profile_e College of Nurses of Ontario. (2005, January 25). CNO s Mission and Vision. Retrieved November 26, 2005, from McGillis Hall, L., Irvine, D., Baker, G.R., Pink, G., Sidani, S., O Brien Pallas, L., & Donner, G. (2001). A Study of the Impact of Nursing Staff Mix Models & Organizational Change Strategies on Patient, System & Caregiver Outcomes. Final report submitted to Canadian Health Services Research Foundation, February, McGillis Hall, L. (2005). Quality Work Environments for Nurse and Patient Safety. Sudbury, MA: Jones and Bartlett Publications. Determining the Feasibility of Collecting Indicator Data 91

94 Ministry of Health and Long-term Care. (n.d.) Nursing Health Outcomes Project: Project background. Retrieved August 4, 2005, from project/nursing/background.html Ward, T. J. & Clark, H. T. (1991). A reexamination of public versus private school achievement: the case for missing data. Journal of Educational Research, 84 (3), Whitley, MP., & Putzier, D. ( 1994) Measuring nurses satisfaction with the quality of their work and work environment. Journal of Nursing Care Quality, 8(3), Quality Worklife Indicators for Nursing Practice Environments in Ontario

95 Faculty of Nursing University of Toronto 155 College Street Toronto, Ontario M5T 1P8