Journal of Cardiopulmonary Rehabilitation & Prevention:
Cardiac Rehabilitation Enrollment Among Referred Patients: PATIENT AND ORGANIZATIONAL FACTORS
Turk-Adawi, Karam I. PhD; Oldridge, Neil B. PhD; Tarima, Sergey S. PhD; Stason, William B. MD; Shepard, Donald S. PhD
Brandeis University, Waltham, Massachusetts (Drs Turk-Adawi, Stason, and Shepard); Aurora Cardiovascular Services, Aurora Health Care, Milwaukee, Wisconsin (Dr Oldridge); and Division of Biostatistics, Medical College of Wisconsin, Milwaukee (Dr Tarima).
Correspondence: Karam I. Turk-Adawi, PhD, c/o Donald Shepard, Brandeis University, 415 S St, MS 035, Waltham, MA 02454 (firstname.lastname@example.org).
The authors declare no conflicts of interest.
PURPOSE: Cardiac rehabilitation (CR) is underutilized despite well-documented benefits for patients with coronary heart disease. The purpose of this study was to identify organizational and patient factors associated with CR enrollment.
METHODS: Facilities of the Wisconsin Cardiac Rehabilitation Outcomes Registry (N = 38) were surveyed, and the records of referred patients were analyzed. Generalized estimating equations were used to account for clustering of patients within facilities.
RESULTS: Of the 6874 patients referred to the 38 facilities, 67.6% (n = 4,644) enrolled in CR. Patients receiving coronary artery bypass grafting (adjusted odds ratio [OR], 1.72; 95% CI: 1.36–2.19) and those who possessed health insurance (OR, 3.04; 95% CI: 2.00–4.63) were more likely to enroll. Enrollment was also positively impacted by organizational factors, including promotion of CR program (OR, 2.35; 95% CI: 1.39–4.00), certification by the American Association of Cardiovascular Pulmonary Rehabilitation (OR, 2.63; 95% CI: 1.32–5.35), and a rural location (OR, 3.30; 95% CI: 2.35–4.64). Patients aged ≥65 years (OR, 0.81; 95% CI: 0.74–0.90) and patients with heart failure (OR, 0.40; 95% CI: 0.22–0.72), diabetes (OR, 0.58; 95% CI: 0.37–0.89), myocardial infarction without a cardiac procedure (OR, 0.78; 95% CI: 0.67–0.90), previous coronary artery bypass grafting (OR, 0.72; 95% CI: 0.56–0.92), depression (OR, 0.56; 95% CI: 0.36–0.88), or current smoking (OR, 0.59; 95% CI: 0.44–0.78) were less likely to enroll.
CONCLUSIONS: Predictors of patient enrollment in CR following referral included both organizational and personal factors. Modifiable organizational factors that were associated either positively or negatively with enrollment in CR may help directors of CR programs improve enrollment.
Cardiac rehabilitation (CR) is considered an integral component of the continuum of care for patients with coronary heart disease (CHD).1 Many major meta-analyses have shown participation in CR promotes a healthy lifestyle, reduces risk factors, improves health-related quality of life, and decreases mortality and morbidity.2–9 Despite the documentation of substantial morbidity and mortality benefits, fewer than 30% of eligible patients utilize CR services.10–12 However, there is increasing evidence on improving CR enrollment by implementation of referral strategies.13–17 A recent systematic review by Grace et al13 reported enrollment rates of 44% to 73% in patients referred to CR, using various recently identified, but still underutilized, referral strategies. Higgins et al14 and Mueller et al15 have also reported relatively high enrollment rates of 72% and 53%, respectively, in patients who were referred to CR.
Several studies have examined extensively patient- and provider-related factors11,18,19 contributing to low enrollment rates. However, organization level–related factors have been studied only recently and to a lesser extent than patient- or provider-related factors.20–23 Notably, most studies that investigated organizational factors are qualitative in nature and based on patients' and health care professional perceptions and beliefs,20–23 without demonstration of statistical inferences on the role of these organizational factors in CR enrollment. Therefore, the aim of this study was to examine concurrently the role of patient and CR organizational factors in CR enrollment in a multisite sample of 38 CR facilities and their patients.
Organizational data were provided by 38 of the 69 CR facilities in the Wisconsin Cardiac Rehabilitation Outcomes Registry (WiCORE) Project in 2010, with 6874 patients providing data. Those facilities self-selected to participate in the study; organizational data were completed by CR program mangers or coordinators and collected via a Web-based survey. Patient data were collected by the CR staff at each facility by using the WiCORE Web-based questionnaire. All patients were formally referred to the CR programs by health care professionals and were also personally contacted by the CR program staff to encourage enrollment in the CR program.
The following patient data were included: gender, race, age, educational level, social support, health insurance status, tobacco use (“current” smoker is actively using tobacco products at the time of the assessment or has quit within the past 12 months; “former” smoker has used tobacco products in the past but quit more than 12 months before the assessment; or “never smoked”), American Association of Cardiovascular Pulmonary Rehabilitation (AACVPR) risk category (low, moderate, or high), and history of depression defined as whether the patient has a documented history of clinical depression (yes, no) (Table 1). Other patient factors examined in this study were admitting diagnosis and coronary procedures (yes, no), including acute myocardial infarction (AMI), angina, heart failure, coronary artery bypass grafting (CABG), percutaneous coronary intervention, and valve replacement. For patients with multiple indications, we classified the qualifying indication by using a hierarchy of CABG, percutaneous coronary intervention, AMI, and angina in that order. Patient factors also included comorbid conditions and previous history of CHD (yes, no) (Table 2).
Facility variables consisted of (a) facility characteristics: medical school affiliation, geographical location (urban, rural, defined by the US Census Bureau at http://www.census.gov/geo/www/ua/2010urbanruralclass.html), CR program location (inside hospital, outside hospital), and provision of other rehabilitation services (yes, no): maintenance or phase III and pulmonary rehabilitation; (b) scheduling the initial visit: person who scheduled the initial visit (CR staff, clerical staff, patients) and time lapse to schedule the initial visit after receiving a referral request; (c) CR staff: whether inpatient and outpatient staff have interchangeable roles; (d) CR program resources: adequate space, flexibility in scheduling classes, program promotion, AACVPR certification, offering gender-specific classes, transportation, and parking.
The outcome variable was enrollment in the CR program, defined as attending at least 1 CR session by patients referred to CR.
Summary statistics were used to describe the baseline characteristics and the proportion of patients who enrolled in CR. Bivariate analyses were performed on patient and organization level factors to assess differences in CR enrollment rates. The differences were assessed using P values obtained by generalized estimating equations with the LOGIT link function. A logistic regression model was fitted to identify significant patient and organizational predictors of CR enrollment. This final parsimonious model was chosen with a stepwise forward variable selection technique in which all the patient and organizational factors listed under the “Patient Factors” and “Organizational Factors” sections were entered in the model one by one. If a variable had a P value of <.05, it was kept in the model for the next run in which a new variable was entered for examination. If a variable had a P value ≥.05, it was removed. The process continued until all patient and organizational variables were examined. The variables that were frequently reported in published literature to be associated with enrollment were always kept in the model. These variables included admitting diagnosis, age, sex, and race. The generalized estimating equation procedure was used to account for clustering of patients within CR facilities. The LOGIT link function and the exchangeable working correlation matrix were used in the generalized estimating equation analysis. A P value of <.05 was considered statistically significant. All statistical analyses were performed using SPSS 19.0.24
Our cohort consisted of 6874 patients, of whom, 4644 (67.6%) enrolled and received at least 1 session of outpatient CR. Recipients of CR received a mean ± standard deviation of 21 ± 10 sessions. Results of bivariate analyses on patient factors are given in Tables 1 and 2. Younger age (<65 years), having health insurance, and no history of depression were positively associated with enrollment, whereas “current” smoking was negatively associated with enrollment (Table 1). Table 2 describes enrollment rates by patient diagnosis and comorbidities: CABG was positively associated with enrollment, whereas heart failure diagnosis, having an AMI, a previous CABG, and diabetes disease were negatively associated with enrollment.
Of the 38 CR facilities, 65.8% were located in urban areas and 86.8% were located in hospitals; only 1 facility was medical school affiliated. All facilities provided free parking, and only 1 facility provided transportation service, which was paid for by the patients. As shown in Table 3, enrollment rates were positively and significantly associated with promotion to patients and health care providers, AACVPR certification, and CR facility location.
CR Enrollment Predictors
Results of the logistic regression model that examined for patient and organizational factors role in CR enrollment are presented in Tables 4 and 5. Patient factors associated with CR enrollment are shown in Table 4. Patients who had undergone CABG and patients with health insurance were more likely to enroll than patients who did not have had CABG or those without health insurance, respectively. Conversely, patients aged ≥65 years, patients with heart failure, with diabetes, with an AMI (no cardiac procedure), with a previous history of CABG, and with a history of depression, and current smokers were significantly less likely to enroll compared with patients aged <65 years, patients without heart failure, without diabetes, without an AMI, without a previous history of CABG, and without depression, and patients who never smoked, respectively.
Organizational factors associated with CR enrollment are shown in Table 5. The following factors were positively associated with CR enrollment: a greater frequency of CR promotion to patients and health care providers, having AACVPR certification, and a rural CR facility location.
The present study examined the effects of both organizational and patient factors on CR enrollment in CHD patients. Findings with respect to patient factors and enrollment in CR programs confirm other published reports.11,25,26 To our knowledge, the present study is the first to have quantified the role of organizational factors in CR enrollment. Our findings emphasize the important role of modifiable organizational factors, including CR promotion and AACVPR certification, and suggest that a rural location of CR programs is positively associated with patient enrollment in CR programs.
The overall CR enrollment rate in this cohort of 6874 CHD patients referred to CR by health care professionals was 67.6%, which is similar to the 64% rate in patients referred to CR in a recent study by Weingarten et al.27 There is a growing body of research suggesting that implementation of systematic referral strategies, electronic referral, or standard referral forms at discharge can be used as tools to increase enrollment in CR.13–17 A recent systematic review by Grace et al13 reported enrollment rates between 44% and 73% in patients referred to CR, using various referral strategies: a “systematic” strategy on the basis of use of systematic discharge order sets (45%; 95% CI: 33%-57%), a “liaison” strategy based on discussions with allied health care providers (44%; 95% CI: 35%-53%), “combined systematic and liaison” (66%; 95% CI: 54%-77%), and “other”—letters to patients disseminating patient educational and/or motivational materials (73%; 95% CI: 39%-92%). Higgins et al14 and Mueller et al15 have also reported relatively high enrollment rates of 72% and 53%, respectively, in patients who were referred to CR. The relatively high enrollment rates in the present study and in Grace et al13 may partially be accounted for by the high referral rate to CR and/or focus on referred patients when compared with the enrollment rates in earlier studies where the proportion of patients referred to CR was low.28–31 Conversely, a recent study demonstrated enrollment rates as low as 29% within 1 month and 48% within 6 months of AMI event in patients referred to CR from 19 US sites.32 Mazzini et al,33 in their evaluation of the American Heart Association Get with the Guidelines–based clinical pathway as a referral strategy, found that although the referral rate was increased, only 34% of patients who were referred actually enrolled in CR. This underlines the role of other factors in patient enrollment, such as the strength of physician endorsement.19
Low patient referral rates have been underscored as a major contributing factor to the underutilization of CR in a recent statement by the American Heart Association.34 The statement also discussed methods to facilitate referral and enrollment, such as automatic referral, following up with those referred but not yet enrolled, establishing initial CR appointment at the point of care, and personal visits from CR liaison (personal bedside provision of information and invitation to enroll). In line with these techniques, the relatively high enrollment rate seen in our study is partially related to the following factors: (a) the use of automatic referral: according to our survey, hospitals of 87% of CR facilities used automatic referral, 50% electronic referral, and 37% automatic manual referral, paper-based standard referral forms at discharge; (b) 96.8% of patients in our study were referred to CR by a physician (62.1% by physicians from inpatient settings, 21.6% by cardiologists, 10.7% by cardiac surgeons, and 2.4% by primary physicians), (c) contact patient to schedule the initial visit: patients were contacted by CR staff to schedule the initial visit either before patient discharge, as in 22% of the participating facilities, or after patient discharge, and (d) the contribution of the inpatient CR staff who play an important role in informing patients about CR and securing referral to CR: 62.1% of the source of referral in our data was from inpatient CR team.
In our study, there was no significant difference in enrollment rates by gender, supporting finding of similar enrollment rates in a recent study.27 However, older age, current smokers, history of depression, diabetes, heart failure (not a reimbursable diagnosis), AMI without a cardiac procedure, and prior CABG were all associated with low enrollment, which is consistent with results of previous observations.11,18,27,35–41 Also consistent with previous studies,11,27,41 patients with CABG were more likely to enroll than patients without CABG. Financial issues have been repeatedly reported as barriers to CR enrollment,32,42–45 and, in our study, lack of health insurance was a strong predictor for low CR enrollment.
A lack of knowledge of the benefits of CR and a feeling that rehabilitation is not necessary have been found to be associated with a decreased enrollment,18,46–48 and marketing of the CR program has been highlighted in a recent qualitative study as a means to help improving participation.49 In our study, the frequency of CR promotion to patients and health care providers was positively associated with increased enrollment rates. Our finding of a positive effect of AACVPR certification on enrollment may reflect both the factors required for AACVPR certification and the program likelihood of implementing other recommended standards and guidelines. If this is so, further research is needed to explore how AACVPR certification positively affects patient enrollment in CR programs.
We found that CR facilities located in rural areas were associated with higher enrollment rates than facilities in urban areas, although some studies have demonstrated higher enrollment rates in CR facilities located in urban areas.9,49 There may be several possible explanations as suggested by 6 CR staff (personal communication via e-mail, February 20, 2012) at different rural facilities: (a) a close relationship between health care providers and patients and between CR staff and cardiologists or primary care physicians in a small community; (b) promotion of the program by previously enrolled patients; and (c) physician support through involvement with visits to the CR activity sites.
A limitation of the study includes the nonavailability of baseline clinical data for referred patients but who did not enroll; clinical factors, including blood pressure,32 lipid levels,50 body weight,27,50 and physical activity38 have each been reported to be associated with enrollment. With only 55% of the WiCORE Project participating in our study, self-selection bias cannot be ruled out, potentially limiting the generalizability of our organizational findings; specifically, most of the nonparticipating facilities were small programs, in terms of the number of patients, with limited resources, that is, CR staff to participate in the study.
However, positive trends were observed between enrollment and scheduling the initial visit within 4 days of receiving a referral request, CR rather than clerical staff scheduling the initial visit, CR staff with a distinct role versus CR staff with interchangeable role, as well as gender-specific classes, after-work classes, and adequate space. Therefore, we suggest replicating the study with a larger number of CR facilities to better identify additional potential modifiable organizational factors that may help improve CR enrollment rates.
In summary, the study has implications for organizational factors in increasing enrollment in CR programs adding to the limited literature on the role of organizational factors in CR enrollment. The modifiable organizational factors identified may help directors of the CR programs improve enrollment.
The authors thank the Wisconsin Society for Cardiovascular and Pulmonary Health and Rehabilitation members, particularly the WiCORE administrators and staff who provided the data, specifically, Mark Vitcenda, MS (WiCORE project manager), for providing the data files and consultations, Sandra Zemke, BSN (supervisor of CR programs, Aurora St Luke's Medical Center) for her contribution in the development of the organizational questionnaire, and the many CR staff participating in WiCORE for their efforts in entering patient data and providing invaluable feedback.
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cardiac rehabilitation; enrollment; organizational factors; patient factors
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