New York State Nursing Home Quality Pool New York State Department of Health May 2, 2012 1
Overview First meeting in January discussed performance measurement for the Quality Pool Materials were sent to DOH by interested parties DOH has reviewed the material as well as additional research At the January meeting there was consensus to define the Quality Pool as four domains 2
Structure of the Quality Pool Quality Utilize MDS 3.0 Quality measures Two NYS-specific measures Satisfaction CMS Quality Indicator Survey (QIS) Or another survey Compliance QIS surveillance data Timely and accurate submission of cost reports Employee Flu Immunization data Avoidable Hospitalizations Short Stay Long Stay 3
Quality Measures Why Certain Measures were Selected? Focused on measures that assess quality for Long Stay residents Initially, we will utilize existing quality measures from existing data MDS 3.0 Data on staffing from cost reports Data from immunization reports Strived for a balance between process and outcome measures 4
Quality Measures Source Risk Adjusted by NYS 1 Percent of Residents Who Have/Had a Catheter Inserted and Left in Their CMS Bladder 2 Percent of Long Stay Residents with a Urinary Tract Infection CMS a 3 Percent of Long Stay Residents Who Lose Too Much Weight CMS 4 Percent of Residents Whose Need for Help with Daily Activities Has Increased CMS 5 Percent of Low Risk Long Stay Residents Who Lose Control of Their Bowels or CMS Bladder 6 Percent of Residents Who Self-Report Moderate to Severe Pain CMS a 7 Percent of Long Stay Residents Assessed and Given, Appropriately, the CMS Seasonal Influenza Vaccine. 8 Percent of Long Stay Residents Assessed and Given, Appropriately, the CMS Pneumococcal Vaccine. 9 Percent of Residents Experiencing One or More Falls with Major Injury CMS 10 Percent of Residents Who have Depressive Symptoms. CMS 11 Annual Percent Turnover of RN, LPN and CNAs from Annual Cost Reports NYS 5 12 Percent of Employees vaccinated for the Flu Annually reported to Bureau of Immunization NYS
Quality Measure Annualized Percent Turnover Utilize turnover data submitted as part of the annual cost reports Formula from Advancing Excellence Assessing non-contract staff (RN, CNA, LP, lines 1-5) % turnover= total number of terminations during 12 months / average number of staff during 12 months 6
Quality Measures Not Selected This is a Starting Point Process will be refined and reevaluated each year Proposed list crosses different functional and clinical needs Quality measures (N=12) More can be added in the future if appropriate Staffing Ratio measure Appropriate benchmark Attempt to align with national and state measures that have been already tested and reported 7
Issues for Discussion related to Quality Measurement Measurement year? MDS 3.0 data available from October 2010 forward New assessment form Nursing Home ranking by NYS Percentiles Similar to data on the DOH website on nursing home quality Risk Adjustment by NYS Not by CMS Only NYS Nursing Homes data (covariates) included in Risk Adjustment 8
Satisfaction Current Data Available: QIS QIS Stage I provides for initial review of resident, family and staff interviews. Small sample of respondents. QIS responses are yes/no and are not Satisfaction with Care type of questions Examples from Resident interview.. Dignity QP212 Do you feel the staff treats you with respect and dignity? For example, does staff take the time to listen to you and are staff helpful when you request assistance? (The focus of this question is how well staff interacts with the resident.) No Yes Sufficient Staff QP232 Do you feel there is enough staff available to make sure you get the care and assistance you need without having to wait a long time? No Yes 9
Issues for Discussion related to Satisfaction QIS is utilized in NYS by approximately 60% of Nursing homes Lag in onsite survey Survey occurs every 9-15 months Other options/suggestions? Separate survey? A Possible Satisfaction Measure is being proposed by CMS Recommendation: Since QIS is not complete for all nursing homes, we propose to not include satisfaction results in year 1 of the Quality Pool 10
Compliance QIS surveillance data Timely and accurate submissions of annual cost reports Employee Flu immunization reporting If deficiency data shows a level J/K/L deficiency, home is automatically excluded from the Quality Pool 11
Issues for Discussion related to Compliance Lag in onsite survey Survey occurs every 9-15 months QIS is utilized in NYS by approximately 60% of Nursing homes 12
Avoidable Hospitalizations: Background A number of studies have found that a sizeable number of hospitalizations from nursing homes might have been avoided. Hospitalizations of nursing home residents can be disruptive, disorienting, and even dangerous Risks of medication errors and hospital-acquired infections Hospital episodes may be especially difficult for residents with dementia Preventing such hospitalizations whenever possible is viewed as an important quality-improvement objective for nursing homes. Hospitalizations from nursing homes are also expensive One study here in New York found that in 2004 roughly 23% of the 972 million dollars spent on hospitalizations from nursing homes were attributable to conditions that might have been treated in the nursing home without hospitalization. 13
Current Initiatives to Reduce Hospitalization of Nursing Home Residents CMS is sponsoring programs to reduce hospitalizations from nursing homes The Nursing Home Value Based Purchasing (NHVBP) demonstration ties financial incentives to performance level or improvement across four sets of performance measures One of these performance measures is avoidable hospitalizations Arizona, New York, and Wisconsin are participating in this demonstration The Initiatives to Reduce Avoidable Hospitalizations Among Nursing Facility Residents will select eligible organizations to test evidence-based clinical interventions to: Reduce the frequency of avoidable hospital admissions Improve resident health outcomes Improve the process of transitioning between inpatient hospitals and nursing facilities Reduce overall health care spending without restricting access to care or providers 14
Proposed Nursing Home Preventable Hospitalization Quality Indicator We propose to develop a potentially preventable hospitalization quality indicator that is patterned after the methodology developed in the NHVBP demonstration Four major components of this methodology Defining episodes of care in the nursing home Defining the number of potentially preventable hospitalizations during each episode Defining the medical conditions that described the resident s condition during each episode Developing a risk-adjustment methodology that permits comparison between nursing facilities in terms of potentially preventable hospitalizations 15
Episodes of Care A nursing home episode will begin with a nursing home admission and will end when the resident resides in the community for at least 30 days is discharged to another nursing home is deceased We will define two types of episodes: short stay and long stay episodes A short stay resident typically enters a nursing home following a hospital stay and needs skilled nursing care or rehabilitation for a short period before returning to the community Short stay episodes are those where the resident resides in the nursing home for less than 90 days A long stay resident typically requires chronic care for extended periods Long stay episodes are these where the resident resides in the nursing home for at least 90 days 16
Episodes of Care (continued) We will use MDS data to define episodes of care We will use all assessments that took place between October 1, 2009 and September 30, 2010 to define these episodes Some episodes will begin prior to October 1, 2009 and will continue past September 30, 2010 To define short stay and long stay episodes, we will only consider nursing home days within our study period. 17
Potentially Avoidable Hospitalizations (PAHs) For all episodes, the number of hospital admissions for the resident during the episode will be identified. If the episode ended in a discharge, any hospital admissions that took place within 3 days of the discharge will be included Medicaid claims, Medicare claims, and SPARCS data will be used to identify hospital inpatient events and associated conditions A hospitalization will be considered potentially avoidable if any one of the following conditions was present during the hospitalization For short and long term episodes: heart failure, respiratory infection, electrolyte imbalance, sepsis, or urinary tract infection For long term episodes also include anemia 18
Two PAH Measures For short term episodes, the measure will be the number of potentially avoidable hospitalizations per short term episode during the 12 month period. For long term episodes, the measure will be the number of potentially avoidable hospitalizations per 100 long term episode days 19
Medical Conditions We will develop measures that describe the resident and any medical conditions present immediately before or during the episode. We will use these measures in our risk adjustment models These measures will include: Demographic items. For all episodes, we will calculate the resident s age at the beginning of the episode and include and indicator for gender. MDS data will be used for these Comorbidities. For each episode, we will include indicators for the following conditions: Myocardial Infarction Congestive Heart Failure Peripheral Vascular Disease Cerebrovascular Disease Dementia Chronic Pulmonary Disease Rheumatolic Disease Peptic Ulcer Disease Mild Liver Disease Diabetes with and without Complications Paraplegia and Hemiplegia Renal Disease Cancer/Leukemia Moderate or Severe Liver Disease Metastatic Carcinoma AIDs/HIV We will use inpatient and outpatient claims beginning 12 months prior to the start of the episode (and within 3 days of the end of the episode) and MDS data during the episode to determine the presence or absence of each of these conditions. These items will be weighted and a comorbidity index will be calculated 20
Medical Conditions (continued) Additional items based on MDS data during the episode include the presence or absence of Pneumonia Urinary Tract Infection Pressure ulcers Oral feeding tubes Septicemia (long stay episodes only) Parenteral/IV nutrition (long stay episodes only) Indwelling Catheter (long stay episodes only) Antibiotic resistant infection (long stay episodes only) Advanced Directive, DNR (long stay episodes only) Whether or not an inpatient hospitalization took place in the 90 days prior to the start of the episode (long stay episodes only) 21
Resident s Condition: Functional Status We will also use a measure of the resident s functional status based on MDS data during the episode. The functional status measure will assess the resident s independence or need for assistance in the following areas Feeding Transfer Grooming Toileting Bathing Walking Dressing Bowel incontinence Bladder incontinence These items will be weighted and summed to form and index that describes the resident s functional level during the episode. 22
Risk-Adjustment Methodology The medical condition and functional status indicators will be used to calculate the probability of avoidable hospitalizations during the episode. Separate regression models will be fit for short term episodes and long term episodes. The result of these analyses will be that each episode has a predicted probability of a potentially avoidable hospitalization based on the demographic, medical condition, and functional status of the resident before and during the episode. For all episodes within each nursing facility, these predicted probabilities can be summed to estimate the predicted number of potentially avoidable hospitalizations in the facility, given the characteristics of the facility s patients At this point a number of strategies exist to compare each facility s actual performance to their predicted performance No final decisions have been made regarding which of these strategies will be pursued 23
Preventable Hospitalization: Conclusion This approach mirrors the methodology used by CMS to define and assess potentially avoidable hospitalizations in their NHVBP demonstration We selected this methodology because: It focuses on an outcome of care that is widely recognized as important The outcome can be measured using existing data sources The methodology is rigorous and permits extensive risk-adjustment so that nursing home outcomes can be compared We plan to base our standard of performance on New York State data only, not on national data This is a work in progress, and much work remains to be done before outcomes can be described. Any comments and suggestions will be considered as the project progresses 24
Quality Pool Scoring Quality Measures - 60 points Satisfaction - 0 points in year 1 Compliance - 20 points Avoidable Hospitalizations - 20 points 100 points total 25
Scoring Details For each of the 12 quality measures: 5 points for measure in the top quintile 3 points for measure in the 2 nd quintile 1 point for measure in the 3 rd quintile 0 points for measure in the 4 th or bottom quintile Compliance Using information from Scope and Severity grid as well as data submission completeness and accuracy, 20 Compliance points will be awarded Avoidable Hospitalizations 10 points for each of the two measures that are statistically below the statewide average (lower is better) 5 points for each measure at the statewide average 0 points for each measure that are statistically higher that the statewide average 26
Exclusions Facilities that will be excluded from the Quality Pool Non-Medicaid Facilities Special Focus Facilities Continuing Care Retirement Unit (CCRC) Facilities Transitional Care Units If deficiency data shows a level J/K/L deficiency, home is automatically excluded from the Quality Pool Determination of Fraud or abuse 27
Next Steps Comments on Proposal Year 1 Pay for Reporting. Per Diem Rate Reduction for facilities that have not sent in reliable data for: Timely and Accurate Cost report (including staffing information) Employee Flu Immunization data If deficiency data showed a level J/K/L deficiency, home will be automatically excluded from quality pool Year 2 Quality Pool based on Quality Pool Investigate satisfaction options Refine risk adjustment for two quality measures using New York State data only 28