Cost-Effectiveness of a Peer and Practice Staff Support Intervention | Page 3
Published Online: March 20, 2014
Christopher S. Hollenbeak, PhD; Mark G. Weiner, MD; and Barbara J. Turner, MD, MSED
This study finds that a combined community and office staff behavioral health intervention to reduce hypertension and risk of CHD among African American primary care patients with uncontrolled hypertension and other CHD risks is potentially cost-effective at reducing SBP in the short term, and in terms of cost per YLS and QALY in the long term, but not cost-effective for reducing CHD risk in the short term (6 months). There are 2 explanations for the relatively high within-trial ICER to prevent CHD events. First, substantial costs are expended for the initial training of peer coaches and practice team members. With a more mature program, these may be reduced, yielding lower cost-effectiveness ratios. We conducted qualitative interviews with our peer coaches and identified key characteristics that motivated sustained participation and may be used to find a cohort of committed, long-term peer coaches.16 Second, the number of predicted CHD events avoided was low, as would be expected for a short (6-month) time frame. Extrapolating for 4 years, we found that predicted CHD risk would be reduced by 12% (0.73% absolute reduction from 6.1% baseline risk). Of course, additional costs would need to be incurred as well.
Another practical concern in regard to the high ICER for preventing 1 CHD event is that our within-trial analysis takes the provider or healthcare system’s perspective, so the provider must cover the cost of the additional services to prevent this event. At this point in the United States, peer coaches are not routinely covered by payers and behavioral health visits with mid-level staff would not be reimbursed unless payment for care were changed from fee-for-service to another bundled scheme, such as one under the medical home model. Indeed, providers are not rewarded directly for avoiding CHD events. Only in a setting such as a national healthcare system would this expense be clearly beneficial from the provider perspective. On the other hand, pay-forperformance measures in the United States do evaluate BP control for persons with hypertension, so a $47 expense per mm Hg reduction in BP in persons whose control continues to be inadequate despite treatment might presently be attractive to a provider.
Our within-trial cost-effectiveness results regarding the role of lay counselors in CHD risk reduction are much higher than those from other countries. Barton et al studied the costeffectiveness of lay health trainers in a randomized trial conducted in Liverpool, where the intervention involved offering information, advice, and support aimed at changing beliefs and behaviors in order to reduce risk of cardiovascular disease.18 The intervention had an estimated ICER of £14,480 (approximately $22,709 per QALY) over 6 months. However, there was only a 39.5% chance that it would be cost-effective at a WTP threshold of £20,000, and at no WTP threshold was it cost-effective with a probability greater than 50%. A costeffectiveness analysis of an Australian cluster-randomized trial of telephone counseling addressing diet and physician activity in 434 adult participants with type 2 diabetes mellitus or hypertension reported that the cost per QALY gained in 2008 Australian dollars was $29,375.19 Although these studies use different metrics for cost-effectiveness assessment, collectively they paint a much more favorable picture for the use of lay counselors to reduce cardiovascular risk than our withintrial analysis. Extrapolating the trial results using the Markov model suggested that our intervention was cost-effective, even under the conservative assumption that the intervention would have to be repeated every year.
This study targeted a highly vulnerable population— African Americans—who have a greatly increased CHD risk in the United States.21 CHD risk factor screening and counseling interventions that target low-income older persons in the community who are uninsured, such as the WISEWOMAN study, have found that, in the best-case analysis, it costs US $4400 per discounted life-year gained, but a sensitivity analysis revealed substantial uncertainty around this estimate.22 Nonetheless, these data suggest that patients in healthcare delivery settings and persons in the community with poor access to care may benefit from interventions to reduce CHD risks that exact a great toll on minority populations. Of course, the financial resources required for these interventions may not be insignificant.
There are several limitations to this study. CHD risk is based on predicted score, and we did not measure actual events. This is a common limitation of any trial to prevent CHD events, since few events can be expected over the short term. We used a CHD risk measure developed by D’Agostino and colleagues that is less commonly employed but offers the advantage of allowing us to assess risk of either a primary or a secondary CHD event.5 Also, as noted in the results from the clinical end points, the difference in CHD risk was not statistically significant. This is less of a concern for the costeffectiveness analysis since we are able to model the uncertainty in both the outcome and costs. In addition, because we did not directly measure utilities, we could not evaluate QALYs—a standard benchmark for cost-effectiveness—in the short term. This has 2 implications. First, it means that the within-trial results cannot be compared with other costutility analyses. And second, the usual thresholds for declaring an intervention cost-effective in terms of cost per QALY are in the range of $50,000 to $100,000. Since we do not report cost per QALY, decision makers must come to their own conclusions as to whether the intervention is cost-effective in the first 6 months, given the ICER. Finally, as noted earlier, the trial lasted only 6 months. But very few CHD events can be expected over such a short time period. We attempted to address these limitations by extrapolating the trial results using a Markov model. This has the advantage of providing QALYs, but is limited in that the results are modeled and not directly observed as they are in the within-trial analysis. The Markov model was also limited by the fact that its risk equations did not differentiate between primary and secondary CHD events for the 50 patients (20 cases and 30 controls) who had been previously diagnosed with coronary artery disease.
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