The Association of Provider and Practice Factors With HIV Antiretroviral Therapy Adherence

David J. Meyers, MPH; Megan B. Cole, PhD, MPH; Momotazur Rahman, PhD; Yoojin Lee, MS, MPH; William Rogers, PhD, Roee Gutman, PhD; Ira B. Wilson, MD, MSc, FACP

Disclosures

AIDS. 2019;33(13):2081-2089. 

In This Article

Discussion

The current study has two main findings. First, even after adjustment for patient characteristics, variance in ART adherence explained by providers and practices is substantial. Second, in multilevel models of patient-level ART adherence, higher adherence levels were observed for patients seeing generalists and other specialists compared with infectious diseases specialists, MD/DO providers compared with non-MDs, providers with more patients, and for patients who had been with the same provider for longer.

This is the first analysis that we are aware of that has quantitated the impact of provider and practice-level effects on patient-level ART adherence. Measuring these effects is difficult, because it requires the attribution of patients to providers and providers to practices so as to create valid 'levels' to use in multilevel models. The approach that we developed and implemented for this study can be used to study a variety of provider and practice-level effects across diseases, as long as there is a clinically sensible way to link patients to providers, which in this case was the provision of an ART prescription.

It is widely appreciated that medication adherence is a complex behavior with multiple drivers.[24–27] There is abundant literature on the effectiveness of adherence interventions,[26,28,29] with generally similar conclusions – it is very difficult to improve medication adherence, and most interventions have small to no effects. Given the complexity of medication adherence as a behavior, it is no surprise that our most encompassing model captures only 52.9% of the total variance in the adherence outcome variable after adjustments for observed patients, providers, and practice characteristics. More important for our purposes than the total variance explained, is the way in which this explained variance is partitioned among patients, providers, and practices. Most (87%) of the explained variance is explained by patients' latent traits, but 13% were explained by provider and practice latent characteristics. Thus, the contributions of provider and practice characteristics to patient-level medication adherence can be substantial.

There is no recent evidence that directly compares the quality of care provided by HIV providers with different training backgrounds. Our data show that the patients of generalists and 'other specialists' had better adherence than patients of infectious diseases specialists. As previously noted, data from early in the ART era suggested that generalist HIV providers with sufficient experience (as measured by HIV care volumes) perform as well as infectious disease trained physicians.[6–9] As PLWH age, they accumulate other chronic conditions.[15,30–32] It may be that patients with HIV who have providers that are comfortable providing care for these other conditions as well as their HIV (one-stop shopping) are better able to get coordinated primary care, and that this is reflected in better ART adherence.[33] By analogy, it may be that 'other specialists' who also provide ART are able to provide more comprehensive care than infectious disease trained doctors. Our data cannot directly confirm this hypothesis. It is also possible that Medicaid patients cared for by infectious disease trained providers are sicker or more complex in ways that our data cannot capture; however, our findings are adjusted for chronic diseases and robust to the inclusion of zip code fixed effects.

We also found that providers with MD and DO degrees had patients with slightly better ART adherence (1.6%) than other providers (NP/PA/other). Earlier work showed that nonphysicians who were experienced with HIV and supported by MD-trained providers provide care that is equal to that of physicians,[8] and we do not believe that the findings presented here are important counter to this earlier work. More broadly, workforce shortages of providers with expertise in HIV care, particularly in rural areas, suggest that in some clinical situations, care led by nonphysician providers is appropriate.

We were not surprised by the findings that provider (but not practice) volume of Medicaid PLWH was significantly associated with better ART adherence. The idea that 'practice makes perfect' has a long history in health care,[34,35] and literature shows that experience with HIV is associated with both better performance on processes of care and with better health outcomes.[6,7,36] We also were not surprised to find that longer continuity of care is associated with better ART adherence. There is a large literature, both in health care more broadly, but also in HIV care, testifying to the importance of provider continuity.[37,38]

There are likely characteristics of providers and practices outside of what we can include in our analysis that matter for improving patient care. Structural aspects of care, including the organization of practices, differential follow-up procedures, how providers communicate with patients, providing training, and others, may all have a role in influencing ART adherence. Our findings highlight that providers and practices play an important role in the successes or failures of their patient's attribution. More research is needed to further disentangle which structural characteristics have the greatest effect on ART adherence and how to change them.

The current study has several limitations. First, our design is cross sectional, so our results do not formally have a causal interpretation. There may be unmeasured confounding of the types of patients who go to different providers which we cannot account for in our results. For instance, if more complex patients who have greater adherence challenges require greater specialty care, that could explain some of our findings. Second, our attribution methods may be imperfect, particularly for patients who see many different providers within a year, or if team-based care occurs within practices. Further, the practice identifier may be under-detecting providers that provide care at certain locations. If provider or practice attribution is misclassified, then it may draw the variance partition coefficients closer to the null. Third, ideally we would use better defined measures of adherence, such as persistence and implementation.[39] However, our attribution method assigned a provider to a patient at the level of a calendar year, and because of this we believe that the percentage adherence measure that we used was most appropriate. Fourth, we are limited in the provider and practice characteristics available in our models, and the variables we currently include may not account for other important factors. Fifth, we assume that most of the providers and practices in our study care for patients with multiple types of insurance, which means that we are likely capturing only a fraction (those with Medicaid) of the persons using ART cared for by the providers and practices identified. However, about 40% of national PLWH are enrolled in Medicaid. Finally, our findings may not generalize to non-Medicaid patients or Medicaid Managed Care patients.

In conclusion, this article presents a new method to identify treating providers and medical practices using Medicaid claims data. We supplemented this method with analysis that relies on multilevel models. This methodology should be applicable to other clinical conditions. Substantial variance in ART adherence was attributable to variation among clinicians and practices, which suggests that providers and practices can be important targets for adherence interventions. The finding that the patients of generalists and other specialists have better ART adherence than infectious diseases trained providers highlights the need for better care coordination as PLWH have more comorbid conditions and are taking more medications to treat these conditions. These challenges will only increase as PLWH age.

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