Nurse Care Coordination of Older Patients in an Academic Family Medicine Clinic: 5-Year Outcomes

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1 Nurse Care Coordination of Older Patients in an Academic Family Medicine Clinic: 5-Year Outcomes Robin L. Kruse, PhD, Steven C. Zweig, MD, MSPH, Betty Nikodim, Joseph W. LeMaster, MD, MPH, Jared S. Coberly, BS, and Jack M. Colwill, MD Abstract Objective: To evaluate the impact of a nurse care coordinator in a family medicine clinic. Methods: We identified patients aged 65 years and older who had been seen at least 3 times by a family medicine outpatient team during These patients (intervention group) received care coordination by a nurse partner and were matched 1:2 with patients who had 3 or more outpatient visits with another clinic team during We followed both groups for up to 5 years. Outcomes included number of outpatient, emergency department (ED), and urgent care visits, inpatient stays, and observation stays. We also performed a death certificate search. We examined mortality with survival analysis and compared the 2 groups other outcomes with Poisson and negative binomial regression. Results: There were 130 patients in the intervention group and 249 controls. After adjusting for age and sex, participants in the intervention group had fewer ED visits (0.71/1000 patient-days) than the control group (1.04/1000 patient-days; P = 0.034) and fewer urgent care visits (0.17/1000 patient-days vs. 0.43/1000 patient-days for controls; P < 0.001). There was no difference between groups for other measures, including mortality. Conclusion: Care coordination in a U.S. primary care clinic by a nurse partner reduced emergent and urgent visits without increasing primary care or physician specialty visits. There was no reduction in use of inpatient services or mortality. While the program benefits patients and payors, there is currently no mechanism for supporting it in a fee-for-service system. Two-thirds of U.S. Medicare beneficiaries aged 65 years old and older have multiple chronic illnesses, and those with multiple comorbidities are at especially high risk for death and hospitalization [1,2]. Primary care practice in the United States, however, is organized around the needs of patients with acute illnesses and is not wellsuited to provide care with an emphasis on preventing disease exacerbations and preserving function [3]. The U.S. population aged 65 years and over is expected to double between 2000 and 2030; people over age 65 seek care from generalists at twice the rate of those under age 65, further burdening a health care system that is not adequately structured to provide chronic care [4,5]. Given current visit numbers, primary care visits will increase 29% due to population growth and aging, while the workforce will only increase 4% to 5% [4]. As attention has been drawn to the impact of chronic illness on the elderly, alternatives to traditional medical care delivered primarily by physicians have been proposed. During the 1990s there was great interest in care coordination of elderly patients due to the pressures of managed care and growing numbers of older persons with chronic illness [6]. Programs generally were of 2 types: low-intensity/highvolume programs, where case managers coordinated services for large numbers of individuals with whom they had little personal contact, and high-intensity/low-volume programs, where case managers worked closely with smaller numbers of individuals over time [6]. The needs of frail, older patients are often better met with high-intensity/lowvolume programs due to frequent changes in care settings and providers that require long-term coordination of services and information. Primary care based case management has most often occurred within managed care settings. Case management teams often included social workers and geriatricians [6,7], who might not be available in typical primary care practices. From the University of Missouri School of Medicine (Drs. Kruse, Zweig, LeMaster, Colwill, and Mr. Coberly) and the University of Missouri Hospital and Clinics (Ms. Nikodim), Columbia, MO. Vol. 17, No. 5 May 2010 JCOM 209

2 Nurse care coordination The Department of Family and Community Medicine at the University of Missouri (MU), in collaboration with the MU health care system, started a pilot project by creating a role for a nurse partner within a practice of family medicine faculty and resident physicians. We modeled our experiment on the nurse partner role developed at the Carle Clinic in Urbana, IL, as part of the Community Nursing Organization Demonstration [8]. The nurse role focused on care coordination, including disease monitoring, patient education, coordinating physician and home health referrals, medication review, and patient follow-up. Our interest was to create a system of care that would provide support for those who needed it most older patients with chronic diseases who were at risk for catastrophic illnesses. Using Wagner s model for chronic illness care, we strived to create provider teams that centered on the patient-nurse-physician relationship to meet the complex needs of our patients with chronic illness [3]. This type of care coordination is not typical of U.S. primary care practices. Qualitatively, our patients reported enthusiasm for their nurse partner [9]. We also wanted to know the effect of the nurse partner role on utilization of health care and patient survival. We hypothesized that the nurse partner would increase continuity of care and hopefully decrease hospital admissions and emergency department (ED) visits. We addressed this through 2 research questions: (1) What is the impact of adding a nurse partner to a teaching family medicine practice with regard to utilization of health care (as measured by ED, primary and specialty care visits and hospitalization) by elderly patients of that practice? (2) Does this model of care impact patient mortality? Methods The University of Missouri Health Sciences Review Board approved this study. We used a quasi-experimental design, following patients of 2 similar academic family medicine clinics that serve a cross-section of the population in Columbia, MO. Both clinics had resident and faculty physicians and resided in the same building. There was little overlap in the patients seen at the 2 clinics, but both drew patients from the same community. In early 1999, we queried billing data to identify patients who had 3 or more outpatient visits to 1 family medicine clinic for any reason during The intervention group consisted of 130 patients of this family medicine clinic. Using the same criteria (3 or more outpatient visits during 1988), we selected 249 patients from the other clinic to comprise the control group. The inclusion criteria were meant to identify patients who used the respective clinics as a major source of care and who could potentially benefit from additional support. Patients in the intervention group were followed by a nurse practitioner (nurse partner) who assessed patients health maintenance needs, reviewed medications, saw the patient in the office (often at the same visit as the primary care physician), provided patient education, coordinated referrals to specialty physicians and home health services, and provided both first access care on the telephone for patients with problems and follow-up phone care to check on patients after doctor visits or hospitalizations. The control group received usual medical care with no additional care coordination by a nurse partner. Outcomes We collected information on utilization outcomes from 2 administrative databases for a 5-year period starting 1 July Information included patient demographics; number of hospital stays, observation stays, ED visits, and urgent care outpatient visits; and total days spent in the hospital. Visits to family medicine or general internal medicine physicians were defined as primary care visits; visits to all other specialties were aggregated. Urgent care visits took place in a separate clinic from primary care and specialty visits. In our context, the urgent care clinic handles instances when patients wish to be seen immediately but either their regular provider is not available or not available in the desired time frame. We also searched administrative data for the latest contact with our hospital and clinics to determine when patients were no longer receiving care from our system. We looked for date of death in administrative data and performed a National Death Index search for patients whose vital status was unknown as of 30 June Total days in the study were calculated from 1 July 1999 to either the date of last contact or death. All outcome measures except death were expressed as number of events per 1000 days in the study. Age was calculated as of 1 July Statistical Analysis We used SAS 9.1 for Windows (SAS Institute, Cary, NC) for all statistical analyses. We compared the age distribution and sex of participants in the intervention and control groups using an independent t test and chi-square test, respectively. Because the distribution of days in the study was not normal, we compared the 2 groups using the Wilcoxon rank sum test. We used Kaplan-Meier analysis to produce unadjusted survival curves and compared survival between groups with Cox regression, including age and sex as covariates in the model. For observation stays and urgent care visits, we compared outcome rates between the 2 groups with Poisson regression, using either a Poisson or negative binomial distribution depending on the dispersion (deviance divided by the degrees of freedom). To account for differing length of observation times between patients, we included the natural logarithm of the number of days in the study in the 210 JCOM May 2010 Vol. 17, No. 5

3 model (offset variable). Because age and sex were related to mortality as well as several of the utilization measures, we included them as control variables in these regressions. To determine if time since enrollment affected use of various health services, we also compared outcome rates between the 2 groups by year following enrollment using the same regression techniques. Results There were 130 patients in the intervention group and 249 controls (Table 1). The intervention group had fewer women (53.1%) than the control group (64.7%; P = 0.028). Mean age was slightly higher for the intervention group (76.5) than for the control group (75.0); the difference was of borderline significance (P = 0.053). Three patients from each group died or left the system between January and June of These patients were included in the survival analysis but eliminated from all analyses of health care utilization. There was no difference in the mean number of days in the study between groups (P = 0.91). Just over one-quarter of the participants in both groups died by the end of the observation period: 26.9% in the intervention group and 27.3% in the control group (P = 0.94). A plot of the simple Kaplan-Meier analysis (Figure 1) shows that the 2 survival curves overlap, with neither group showing a survival advantage. After controlling for age and sex in Cox regression, membership in either cohort was not associated with survival (P = 0.56). After controlling for age and sex, there was no difference between groups for mean number of inpatient stays, total inpatient days, number of observation stays, number of outpatient primary care visits, or number of outpatient visits to other specialties (Table 2). The intervention group had 15.1 primary care visits/1000 patient-days during the follow-up period, which equates to 5.5 visits for each patient per year, almost double the visit rate seen in the year prior to study onset. After adjusting for age and sex, participants in the intervention group had fewer ED visits (0.71/1000 patientdays; 95% confidence interval [CI], 0.54/ /1000) than the control group (1.04/1000 patient-days; 95% CI, 0.86/ /1000; P = 0.034), yielding an absolute risk reduction of 0.33 ED visits/1000 patient-days. Urgent care visits were reduced in the intervention group as well. Intervention participants had 0.17 urgent care visits/1000 patientdays (95% CI, 0.12/ /1000) versus 0.43 urgent care visits/1000 patient-days (95% CI, 0.36/ /1000) for control participants (P < 0.001; absolute risk reduction = 0.26 urgent care visits/1000 patient-days). The relative risk reduction for ED visits for the nurse partner intervention was 0.32 (95% CI, ), and the relative risk reduction for urgent care visits was 0.59 (95% CI, ). Only ED and urgent care visits differed between groups Table 1. Patient Characteristics Intervention n = 130 Control n = 249 P Value Mean age ± SD, yr 76.5 (7.5) 75.1 (6.8) Female, n (%) 69 (53.1) 161 (64.7) Mortality, n (%)* 35 (26.9) 68 (27.3) 0.94 Mean days in study ± SD 1459 (548) 1456 (572) 0.91 *Between 1 January 1999 and 1 July Six patients died or left the system prior to 1 July 1999 (3 in each group), leaving 373 patients for analysis of health care utilization. Days between 1 July 1999 and death, leaving the health care system, or 30 June 2004, whichever came first. when comparing them each year of the study (Figure 2). For ED visits, there was no difference between groups at study onset, but the 2 groups steadily diverged, with annual visits decreasing in the intervention group and increasing in the control group. The difference between groups was statistically significant for years 3 through 5 (all P < 0.05). For urgent care visits, the intervention group did not differ in years 1 and 5, but the intervention group made significantly fewer visits during years 2 through 4 (all P < 0.05). Discussion Our nurse partner physician collaboration resulted in lower rates of ED and urgent care visits but not lower rates of hospitalization, fewer hospital days, or fewer subspecialty office visits. Furthermore, there was no difference in mortality rates over 5 years of observation. An earlier report of these data found that hospitalization and ED visits were reduced after 1 year [10]. The current cohorts, however, were more rigorously defined and followed for 5 years, resulting in a different sample and findings. While we were disappointed that the nurse partner program showed no impact on hospitalization or mortality for the 5-year follow-up period, we were pleased to find that the intervention was not associated with increased primary care or specialty visits. Given that our population was not at particularly high risk for hospitalization, it is not surprising that inpatient services were not reduced. Of interest, both the intervention and control groups had more primary care visits per year in the followup period than in the year prior to the study. From interviews with patients, we found that direct phone access to the nurse partner was one of the most valued aspects of the program. Since all residents and faculty physicians are available on only a part-time basis in the family medicine clinics we studied, this may have been especially important in this context [10]. Patients and family members often expressed their appreciation for the Vol. 17, No. 5 May 2010 JCOM 211

4 Nurse care coordination Figure 1. Five-year survival of intervention and control patients. nurse partner [9]. She was viewed as a permanent aspect of the practice, while the physicians, especially the resident physicians, might change. Similarly, implementation of the Evercare program in the United Kingdom resulted in no net savings for the health care system, but case management at the practice level was highly valued for increasing psychosocial support and improving communication with health professionals [11]. Like our study, the GRACE model, a randomized trial that used nurse/social worker/geriatrician teams working in collaboration with primary care physicians to care for lowincome elders, lowered ED use without affecting mortality or hospitalization [7]. Also like our study, GRACE participants were older, established patients of 6 primary care clinics and not selected based on high risk for hospitalization. Several programs have lowered mortality but have had variable effects on utilization. As part of a capitated program, the Carle Clinic put nurses and case assistants in physician offices [8]. Physicians in the intervention group selected patients based on the presence of 1 or more risk factors, such as recent hospitalization, lack of support, or complex care needs; the program resulted in lower mortality with no increase in hospitalizations, hospital length of stay, or Medicare payments [12]. Boult and colleagues [13] conducted a randomized trial of a geriatric evaluation and management program for elders at greater than 40% risk of hospitalization in the next 4 years. The intervention lowered mortality and ED use but did not change hospitalization rates. Recently, Intermountain Health Care enrolled physician-selected, chronically ill seniors in a multidisease management program in which nurse care managers were supported by specialized information technology in primary care clinics [14]. The program reduced mortality, particularly for patients with diabetes, and reduced hospitalizations, but ED visits increased slightly. In 2002, the Centers for Medicare and Medicaid Services selected 15 programs to participate in the Medicare Coordinated Care Demonstration. Participants were Medicare beneficiaries with a chronic condition; each program defined its own target population [15]. Thirteen of 15 trials showed no reduction in hospitalization, and none generated net savings. During this same time, the Evercare approach to case management for frail elderly people was implemented in 9 primary care trusts in the United Kingdom. Patient satisfaction increased, but no association was found between case management and emergency admissions, bed days, or mortality, perhaps due to increased case finding [11,16]. Lim and colleagues [17] randomized older patients following hospital discharge to usual care or post acute care coordination. Care coordination did not reduce 6-month mortality or unplanned readmissions, but was associated with increased quality of life at 1 month and fewer hospital bed-days and lower costs in the ensuing 6 months. Geriatric case management programs that enrolled patients with differing illness severity and utilization patterns have had variable results on patient outcomes. In a recent 212 JCOM May 2010 Vol. 17, No. 5

5 Figure 2. Annual use of emergency department (ED) and urgent care visits by intervention and control patients. Vol. 17, No. 5 May 2010 JCOM 213

6 Nurse care coordination Table 2. Health Care Utilization of Intervention and Control Patients Measure Mean/1000 Patient-Days (95% CI)* Intervention Inpatient stays 1.04 ( ) Total inpatient days 6.65 ( ) Observation stays ( ) Emergency department visits ( ) Urgent care visits ( ) Outpatient visits Primary care 15.1 ( ) Other specialties 16.9 ( ) CI = confidence interval. Control 1.09 ( ) 7.23 ( ) ( ) 1.04 ( ) ( ) 15.8 ( ) 16.4 ( ) P Value < *Utilization is reported as the mean of each measure per 1000 days in the study (95% confidence interval), as determined with Poisson or negative binomial regression after controlling for age and sex. systematic review of case management for frail elders, only 9 articles met the authors selection criteria for methodological quality. Of those, 6 studies examined hospital admission, and only 1 showed a small decrease in hospital admissions. Of the 5 studies that investigated ED visits, 1 intervention showed a decrease, whereas another showed an increase [18]. Differences in patient characteristics and interventions make it difficult to compare studies and determine which approaches work. Generalizability From our previous report, we found that the nurse partner spent about one-fourth of her time with patient and physicians, one-fourth providing teaching and care coordination in the clinic alone with the patient, one-fourth of the time on the phone with patients, and the rest of her time divided between other activities such as documentation and record review. We found physicians, staff, and patients so satisfied with this role that other practices within our network also wanted nurse partners. For elderly patients, support from the nurse partner was overwhelmingly positive and provided them with improved access and comfort as well as reduced anxiety [9]. Physicians perceived that quality of care was improved via phone follow-up after visits, coordination of home and referral services, and calls to patients and family members [10]. We have no objective measure of that improved quality, although our electronic medical record (EMR) now enables patient registries, treatment algorithms for numerous chronic diseases, and population-based outcomes. The nurse partners in our practices now have an even greater role partnering with the patients and physician in improving care. In the United States, outside a managed care environment, there is currently no mechanism to financially support this enhanced care model. There is general agreement that primary care physicians cannot provide high-quality care including preventive, acute, and chronic care services during a 15-minute office visit without additional support [19,20]. Care coordination care across disease episodes requiring complex management that optimizes function and prevents health catastrophes is not reimbursable in the current health care system, making it even less likely to take place when needed. The teamlet model described by Bodenheimer [21] comes closest to what we set up in 1999 and continue today. In the 15 case studies described [22], this model was sometimes seen as financially viable, even in the fee-for-service system. A physician enabled now to see 1 to 2 extra patients daily may be able to support the additional services of a nurse partner. In our practices and others, we believe this model can play an important role transforming practices to become patient-centered medical homes by improving access to care, effectively using the EMR, tracking referrals, and helping to set goals of care for each patient [23]. Strengths and Limitations The study has several weaknesses. Because it was initiated as a pilot program to improve quality of care, the evaluation was not constructed as a randomized controlled trial, which limited our ability to control for the disease severity of our study participants. However, the fact that mortality was virtually identical after 5 years of follow-up suggests that the study groups had comparable disease severity. If more participants had been at higher risk for hospitalization, other benefits of the program may have been found. It is also possible that differences in health care utilization were related to differences between physicians at the 2 clinics or their patient populations. We were quite limited in the variables available to control for this potential confounding. Our intervention involved 1 nurse partner and therefore may not generalize to other settings. We have, however, successfully expanded the intervention to other family medicine clinics and are monitoring similar outcomes in that expanded program. We were unable to measure use of health care services outside University of Missouri Health Care, although we had no a priori reason to expect this to vary between groups. Strengths of this study include its team approach to care coordination, its patient-oriented care, the long period of follow-up, and its relevance to other primary care practices. For the duration of this study, both clinics had first one 214 JCOM May 2010 Vol. 17, No. 5

7 and then another more advanced EMR. Unfortunately, during the course of the study, neither was able to assemble a computerized disease registry based on the EMR, create a reminder system or tickler file, or measure population-based outcomes for patients. Each of these barriers created limits to the types of disease management and care coordination that were possible. These capabilities may have contributed to the lower hospitalization and mortality rates found in the Intermountain Health Care demonstration [14]. Conclusion In our population of older adults, care coordination by a nurse partner resulted in modest reductions in emergency and urgent care visits, with no changes in primary care and specialty visits, hospitalization, or mortality. The reported effect of care coordination on hospitalization, ED visits, and mortality varies widely, suggesting the need for large randomized controlled trials to determine the effects of care coordination on these outcomes as well as which aspects of care coordination are responsible for the effect. Acknowledgment: The authors would like to acknowledge Rebecca Rastkar, RNC, for coordinating this study and helping with follow-up data collection. Corresponding author: Robin L. Kruse, PhD, Dept. of Family & Community Medicine, University of Missouri School of Medicine, Columbia, MO 65212, kruser@health.missouri.edu. Financial disclosures: None. Author contributions: conception and design, SCZ, JWL; analysis and interpretation of data, RLK, SCZ, JWL, JSC; drafting of article, RLK, SCZ; critical revision of the article, RLK, SCZ, BN, JWL, JSC; provision of study materials or patients, SCZ; statistical experience, RLK; administrative or technical support, SCZ, BN, JSC; collection and assembly of data, RLK, SCZ, BN, JSC. References 1. Anderson GF. Medicare and chronic conditions. N Engl J Med 2005;353: Wolff JL, Starfield B, Anderson G. Prevalence, expenditures, and complications of multiple chronic conditions in the elderly. Arch Intern Med 2002;162: Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Eff Clin Pract 1998;1: Colwill JM, Cultice JM, Kruse RL. Will generalist physician supply meet demands of an increasing and aging population? Health Aff (Millwood). 2008;27:w Trends in aging United States and worldwide. MMWR Morb Mortal Wkly Rep 2003;52: Phillips-Harris C. Case management: high-intensity care for frail patients with complex needs. Geriatrics 1998;53: Counsell SR, Callahan CM, Clark DO, et al. Geriatric care management for low-income seniors: a randomized controlled trial. JAMA 2007;298: Schraeder C, Britt T. The Carle Clinic. Nurs Manage 1997;28: Shigaki CL, Moore CM, Wakefield B, et al. Nurse partners in chronic illness care: a qualitative study of patients perceptions. J Nursing Care Quality. In press Rastkar R, Zweig S, Delzell JE Jr, Davis K. Nurse care coordination of ambulatory frail elderly in an academic setting. Case Manager 2002;13: Sheaff R, Boaden R, Sargent P, et al. Impacts of case management for frail elderly people: a qualitative study. J Health Serv Res Policy 2009;14: Schraeder C, Shelton P, Sager M. The effects of a collaborative model of primary care on the mortality and hospital use of community-dwelling older adults. J Gerontol A Biol Sci Med Sci 2001;56:M Boult C, Boult L, Murphy C, et al. A controlled trial of outpatient geriatric evaluation and management. J Am Geriatr Soc 1994;42: Dorr DA, Wilcox AB, Brunker CP, et al. The effect of technologysupported, multidisease care management on the mortality and hospitalization of seniors. J Am Geriatr Soc 2008;56: Peikes D, Chen A, Schore J, Brown R. Effects of care coordination on hospitalization, quality of care, and health care expenditures among Medicare beneficiaries: 15 randomized trials. JAMA 2009;301: Gravelle H, Dusheiko M, Sheaff R, et al. Impact of case management (Evercare) on frail elderly patients: controlled before and after analysis of quantitative outcome data. BMJ 2007;334: Lim WK, Lambert SF, Gray LC. Effectiveness of case management and post-acute services in older people after hospital discharge. Med J Aust 2003;178: Oeseburg B, Wynia K, Middel B, Reijneveld SA. Effects of case management for frail older people or those with chronic illness: a systematic review. Nurs Res 2009;58: McGlynn EA, Asch SM, Adams J, et al. The quality of health care delivered to adults in the United States. N Engl J Med 2003;348: Bodenheimer T. Coordinating care a perilous journey through the health care system. N Engl J Med 2008;358: Bodenheimer T, Laing BY. The teamlet model of primary care. Ann Fam Med 2007;5: Bodenheimer T. Building teams in primary care: 15 case studies. Oakland (CA): California HealthCare Foundation; The patient centered medical home: history, seven core features, evidence and transformational change. Washington (DC): The Robert Graham Center; 2007 [updated November 2007; cited 5 June 2009]. Accessed 5 Apr 2010 at: org/online/etc/medialib/graham/documents/publications/ mongraphs-books/2007/rgcmo-medical-home.par.0001.file. tmp/rgcmo-medical-home.pdf. Copyright 2009 by Turner White Communications Inc., Wayne, PA. All rights reserved. Vol. 17, No. 5 May 2010 JCOM 215