Cost-Effectiveness of a Peer and Practice Staff Support Intervention | Page 1
Published Online: March 20, 2014
Christopher S. Hollenbeak, PhD; Mark G. Weiner, MD; and Barbara J. Turner, MD, MSED
Innovative models of primary care offer the potential to reduce disparities in health outcomes for vulnerable populations with chronic diseases.1 Cost-effectiveness studies have reported that future healthcare utilization and costs can be reduced by implementing a diabetes patient registry along with clinical meetings.2 Supplementing a registry with education for patients with diabetes about self-management and improving professional quality of care also meets standard guidelines of increasing quality-adjusted life-years (QALYs).3 However, few cost analyses have been conducted of interventions based on Wagner’s chronic care model that focus on reducing coronary heart disease (CHD) risk and improving blood pressure (BP) in those from racial/ethnic minority backgrounds.
We report a cost-effectiveness analysis of a randomized, controlled trial of a 6-month community- and staff-based intervention of behavioral support and education for African Americans with sustained, uncontrolled hypertension based on a practice-based registry. All subjects received educational brochures and usual physician care while intervention subjects received 3 community support phone calls from trained peers from the same practices alternating with personal counseling by trained mid-level staff at 2 practice visits on alternate months. The study outcomes were 6-month changes in systolic blood pressure (SBP) and CHD risk. These results add to evidence of the potential cost-effectiveness from a provider standpoint of adopting features of the chronic care model to empower patients to reduce CHD risk due to poorly controlled risk factors.
Study subjects were recruited from July 2007 through November 2009 in 2 urban academic general internal medicine practices largely serving low-income patients. Subjects were identified from a registry of all 9135 African American patients aged 40 to 75 years receiving longitudinal care (2+ visits in 2 years). We identified those patients with treated but uncontrolled hypertension per the 7th Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7) targets (ie, SBP 130 mm Hg or higher, or diastolic blood pressure [DBP] 80 mm Hg or higher, if chronic kidney disease or diabetes; otherwise, SBP 140 mm Hg or higher, or DBP 90 mm Hg or higher) and at least 1 value 10 mm Hg above goal.4 Of 1057 subjects with uncontrolled hypertension, recent lipid levels, and at least moderate adherence to keeping primary care visits, 810 were randomly selected to ask approval from the provider for the trial; 574 were approved and sent a recruitment letter. Of 440 patients who were contacted, 280 subjects were randomized.
The Healthy Heart trial randomly assigned subjects to 1 telephone-based peer counseling session and office-based visits with trained mid-level providers over 6 time frames, or to a control condition of usual physician care. Practice providers nominated 20 patients to serve as peer coaches from lists of African Americans with well-controlled hypertension aged 50 to 75 years, because they were perceived to be “good communicators.” Of these, 11 completed training and 5 continued to the end of the study while 3 replacements were recruited and trained to assist with peer support. Training involved viewing and discussing illustrated slide shows created by the study team about CHD in the community and risks and barriers to control. Peer coaches were taught elements of motivational interviewing and practiced phone calls before being assigned patients. Peer coaches contacted intervention patients every other month for 6 months (minimum of 3 calls).
For practice-based counseling visits, we trained 3 African American staff members (eg, medical assistants) with the same slide shows used to train peers, and also trained them to use a personalized, computer-based, 4-year CHD risk calculator as a teaching tool. On alternate months from peer calls, patients made two 15- to 30-minute visits with trained practice staff to review personal CHD risk factors. All study subjects received culturally appropriate educational brochures and healthy recipes from the American Heart Association. Participants received $50 in gift certificates for participation ($20 at enrollment and $30 at end point visit). Peer coaches received $20 per completed phone call and followed a mean of 8 patients at once (other costs in Table 1). The protocol and procedures were reviewed and approved by the University of Pennsylvania Institutional Review Board.
Direct intervention costs were estimated from the perspective of the provider/ health system and measured in 2010 US dollars. Because the trial was based on outcomes monitored over 6 months, we did not apply any discounting. Specific resources used for the intervention included cost of training peer coaches, labor cost of peer coach telephone calls, cost of training office-based health educators, cost of clinic visits and laboratory tests, incentives for patients, cost of brochures, and cost of materials such as transportation, postage, and office supplies (Table 1). We also included costs for the overall administration of the trial, but not solely research-related costs. For the brochure control group, resources included the cost of clinic and laboratory visits and the cost of the brochures. Patients in the intervention group incurred all of these costs. Costs that were not relevant to the provider perspective, such as indirect costs for patients, were not considered.
We studied 2 measures of effectiveness for the withintrial stochastic cost-effectiveness analysis: predicted 6-month CHD risk avoided and 6-month improvements in SBP (per mm Hg). The 6-month CHD risk measure was derived from D’Agostino’s risk equations for primary events and secondary events in Framingham data (eg, myocardial infarction, angina), using original (rather than the calibrated) versions of these equations.5 Separate risk equations were used for men and women. Our primary CHD event end point combined predicted 6-month risk of primary and secondary CHD events for patients. All outcomes were based on an intention-to-treat approach. In the long-term costeffectiveness analysis, we studied 2 measures of effectiveness: years of life saved (YLS) and QALYs, both over a 10-year lifetime horizon.
Two cost-effectiveness analyses were performed: a withintrial stochastic cost-effectiveness analysis that focused on cost-effectiveness during the 6-month trial period, and longterm cost-effectiveness based on a Markov model that modeled the longer-term benefits of BP reduction.6,7 For the within-trial stochastic cost-effectiveness analysis, we estimated 2 incremental cost-effectiveness ratios (ICERs): incremental cost per predicted CHD event avoided within 6 months, and incremental cost per mm Hg in SBP reduced. To characterize the uncertainty of the within-trial cost-effectiveness results, we used bootstrapping to estimate a 95% confidence ellipse around the ICER.8,9 The bootstrap method resampled the data 10,000 times with replacement, and computed the ICER for each replicate. From the bootstrap samples, we estimated the probability that one treatment was cost-effective compared with the other for a given willingness to pay (WTP). In addition, we computed the cost-effectiveness acceptability curve (CEAC) and plotted the probability that the behavioral health intervention was cost-effective over a reasonable range of levels of WTP.10
We performed a subgroup analysis for patients who were compliant with the intervention. We defined an effective “dose” as at least 2 peer coach calls and 1 practice visit. We then estimated the ICER for the intervention in this intervention subgroup relative to the control group. All stochastic cost-effectiveness analyses were performed using R statistical software (version 2.10.1, http://www.r-project.org).
Long Term Cost-Effectiveness
To estimate the long-term costs and benefits of BP reduction observed in the trial, data on costs and effectiveness from the clinical trial were entered into a Markov model of CHD risk in order to extrapolate trial results to a 10-year lifetime horizon. The Markov model was designed to study the impact of antihypertensive medications and was adapted to this setting. The model has a 10-year time horizon with yearly cycles. All costs begin in year 2010 US dollars and were discounted at a rate of 3%. Utility values for health states were drawn from Sullivan et al and Currie et al.13,14 As effectiveness measures, the model estimates YLS and QALYs. Additional details of the model are provided in Baker et al.11 Because the trial only lasted 6 months, it was necessary to make assumptions about how the intervention would be provided over the 10-year time horizon of the Markov model. We assumed that yearly reinforcements of the intervention would be required in order to sustain improvements.
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