Transitioning From Medicaid Disability Coverage to Long-Term Medicare Coverage: The Case of People Living With HIV/AIDS in California

Using a cohort study of diabetes and peripheral artery disease to compare logistic regression and machine learning via random forest modeling

BACKGROUND

This study illustrates the use of logistic regression and machine learning methods, specifically random forest models, in health services research by analyzing outcomes for a cohort of patients with concomitant peripheral artery disease and diabetes mellitus.

METHODS

Cohort study using fee-for-service Medicare beneficiaries in 2015 who were newly diagnosed with peripheral artery disease and diabetes mellitus. Exposure variables include whether patients received preventive measures in the 6 months following their index date: HbA1c test, foot exam, or vascular imaging study. Outcomes include any reintervention, lower extremity amputation, and death. We fit both logistic regression models as well as random forest models.

RESULTS

There were 88,898 fee-for-service Medicare beneficiaries diagnosed with peripheral artery disease and diabetes mellitus in our cohort. The rate of preventative treatments in the first six months following diagnosis were 52% (n = 45,971) with foot exams, 43% (n = 38,393) had vascular imaging, and 50% (n = 44,181) had an HbA1c test. The directionality of the influence for all covariates considered matched those results found with the random forest and logistic regression models. The most predictive covariate in each approach differs as determined by the t-statistics from logistic regression and variable importance (VI) in the random forest model. For amputation we see age 85 + (t = 53.17) urban-residing (VI = 83.42), and for death (t = 65.84, VI = 88.76) and reintervention (t = 34.40, VI = 81.22) both models indicate age is most predictive.

CONCLUSIONS

The use of random forest models to analyze data and provide predictions for patients holds great potential in identifying modifiable patient-level and health-system factors and cohorts for increased surveillance and intervention to improve outcomes for patients. Random forests are incredibly high performing models with difficult interpretation most ideally suited for times when accurate prediction is most desirable and can be used in tandem with more common approaches to provide a more thorough analysis of observational data.

The Impact of ACA and Medicaid Expansion on Progress Toward UNAIDS 90-90-90 Goals

PURPOSE OF REVIEW

Passage of the Affordable Care Act (ACA) in 2010 and subsequent Medicaid expansion has influenced access to HIV treatment and care in the USA. This review aims to evaluate whether the implementation of these policies has impacted progress toward UNAIDS 90-90-90 goals.

RECENT FINDINGS

Preliminary evidence has emerged suggesting that the ACA and Medicaid expansion has increased the likelihood of HIV testing and diagnosis, reduced the number of people unaware of HIV infection, and increased the number of people on antiretroviral therapy (ART) who are virally suppressed. While the ACA is associated with some progress toward 90-90-90 goals, more years of data after policy implementation are needed for robust analysis. Methods including difference-in-differences, instrumental variables, and propensity scores are recommended to minimize bias from unmeasured confounders and make causal inference about non-random Medicaid expansion among states.

Access to HIV Medication in the Community Versus a Nursing Home for the Medicare Eligible HIV population

Access to appropriate antiretroviral therapy (ART) is key to people living with HIV/AIDS (PLWH) living a near normal life time, which has resulted in increasing numbers of PLWH requiring nursing home care for age-related reasons. However, one study found that 21% of Medicare eligible PLWH in US nursing homes between 2011 and 2013 were not dispensed ART through the nursing home pharmacy. Cost-sharing assistance programs exist to facilitate access to medications for low-income community dwelling older adults, but these programs do not necessarily extend to people admitted to a nursing home, which may cause interruptions in access to ART for PLWH in this setting. Policies may need to be updated to reduce drug-related financial burden to PLWH and nursing homes in order to maintain continued access to ART in the nursing home setting.