Medicaid's Impact on Chronic Disease Biomarkers: A Cohort Study of Community Health Center Patients

Abstract

Background: Understanding the impact of health insurance is critical, particularly in the era of Affordable Care Act Medicaid expansion. The electronic health record (EHR) provides new opportunities to quantify health outcomes.

Objective: To assess changes in biomarkers of chronic disease among community health center (CHC) patients who gained Medicaid coverage with the Oregon Medicaid expansion (2008-2011).

Design: Prospective cohort. Patients were followed for 24 months, and rate of mean biomarker change was calculated. Time to a controlled follow-up measurement was compared using Cox regression models.

Setting/patients: Using EHR data from OCHIN (a non-profit network of CHCs) linked to state Medicaid data, we identified three cohorts of patients with uncontrolled chronic conditions (diabetes, hypertension, and hyperlipidemia). Within these cohorts, we included patients who gained Medicaid coverage along with a propensity score-matched comparison group who remained uninsured (diabetes n = 608; hypertension n = 1244; hyperlipidemia n = 546).

Main measures: Hemoglobin A1c (HbA1c) for the diabetes cohort, systolic and diastolic blood pressure (SBP and DBP, respectively) for the hypertension cohort, and low-density lipoprotein (LDL) for the hyperlipidemia cohort.

Key results: All cohorts improved over time. Compared to matched uninsured patients, adults in the diabetes and hypertension cohorts who gained Medicaid coverage were significantly more likely to have a follow-up controlled measurement (hazard ratio [HR] =1.26, p = 0.020; HR = 1.35, p < 0.001, respectively). No significant difference was observed in the hyperlipidemia cohort (HR = 1.09, p = 0.392).

Conclusions: OCHIN patients with uncontrolled chronic conditions experienced objective health improvements over time. In two of three chronic disease cohorts, those who gained Medicaid coverage were more likely to achieve a controlled measurement than those who remained uninsured. These findings demonstrate the effective care provided by CHCs and the importance of health insurance coverage within a usual source of care setting.

Clinical trials registration: NCT02355132 [ https://ichgcp.net/clinical-trials-registry/NCT02355132 ].

Keywords: Medicaid; access to healthcare; biomarkers.

Conflict of interest statement

Prior Presentations

These results were presented at the 43rd North American Primary Care Research Group Annual Meeting, October 24–28, 2015, in Cancun, Mexico.

Conflict of Interest

The authors declare that they do not have a conflict of interest.

Figures

Figure 1

Kaplan-Meier survival curves: time from baseline elevated measurement to a controlled measurement by insurance category among propensity score-matched patients. HR hazard ratio, CI confidence interval. Note: Cox regression modeling was used to estimate HRs, with p values noted on each figure. Models were adjusted for covariates with residual imbalance (SD ≥ 0.10). A robust sandwich variance estimator was used to account for correlation of subjects within propensity score-matched sets and subjects nested in community health centers.

Figure 2

Patient-specific profile plots and average LOWESS curves: biomarkers over time by insurance category among propensity score-matched patients. Note: Black lines denote limits of “controlled” range. LOWESS curves are denoted by solid lines, and represent a locally weighted average of biomarkers over time, stratified by insurance status. Thin dashed lines represent patient-specific profile plots. Due to large sample sizes, the points in the two hypertension cohort graphs represent 100 matched pairs selected at random, whereas the LOWESS curves reflect results from the entire hypertension cohort.