The Effect of Opioid Use and Mental Illness on Chronic Disease Medication Adherence in Superutilizers.

backgroundNonadherence to essential chronic medications has been identified as a potential driver of high health care costs in superutilizers of inpatient services. Few studies, however, have documented the levels of nonadherence and factors associated with nonadherence in this high-cost, vulnerable population.

objectiveTo examine the factors associated with nonadherence to essential chronic medications, with special emphasis on mental illness and use of opioid medications.

methodsThis study was a retrospective panel analysis of 2-year baseline data for Medicare Part D beneficiaries eligible for the SafeMed care transitions program in Memphis, Tennessee, from February 2013 to December 2014. The 2-year baseline data for each patient were divided into four, 6-month patient periods. The study included Medicare superutilizers (defined as patients with ≥ 3 hospitalizations or ≥ 2 hospitalizations with ≥ 2 emergency visits in 6 months) with continuous Part D coverage who had filled at least 1 drug class used to treat hypertension, diabetes mellitus, congestive heart failure, coronary artery disease, or chronic lung disease. The outcome included medication nonadherence assessed using proportion of days covered (PDC), with PDC < 80% defined as nonadherent, and the main exposure variables included mental illness (defined as a diagnosis of depression or anxiety or ≥ 1 anxiolytic or antidepressant fill) and opioid medication fills assessed in each 6-month period. Pooled observations from the four 6-month periods were used for multivariable analyses using the patient periods as the unit of analysis. A random effects model with robust standard errors and a binary distribution were used to examine associations between independent variables (time invariant and time variant factors) and medication nonadherence. The model included lagged effects of time variant factors measured in each period.

resultsOverall nonadherence to essential chronic medications ranged from 39.3% to 58.4%, with the highest for chronic lung disease medications (49.1%-64.4%). Factors associated with nonadherence included ≥ 4 opioid medication fills in the previous 6-month period (adjusted odds ratio [OR] = 1.90, 95% CI = 1.32-2.73); age 22-44 and 45-64 years vs. ≥ 65 years (OR = 3.57, 95% CI = 2.07-6.16, and OR = 2.07, 95% CI = 1.49-2.88); and a higher number of unique prescribers (OR = 1.10, 95% CI = 1.04-1.17). Factors protecting against nonadherence included higher number of unique medications filled (OR = 0.95, 95% CI = 0.92-0.98) and ≥ 1 physician office visit in the previous 6-month period (OR = 0.66, 95% CI = 0.46-0.94).

conclusionsThis study demonstrated that high levels of opioid medication use are significantly associated with essential chronic disease medication nonadherence among superutilizers. Other risk factors for nonadherence were aged < 65 years, low-income status, and a higher number of unique prescribers. Factors protecting against nonadherence were physician office visits and filling higher number of medications. Medication management interventions targeting superutilizers should focus on supporting chronic disease medication adherence. DISCLOSURES: This project was supported by Funding Opportunity Number 1C1CMS331067-01-00 from the Centers for Medicare & Medicaid Services, Center for Medicare and Medicaid Innovation. Support was also provided by the Pharmaceutical Research and Manufacturers of America Foundation. The content of this study is solely the responsibility of the authors. The authors declare no relevant conflicts of interest or financial relationships. Study concept and design were contributed by Surbhi, Bailey, and Graetz. Surbhi and Wan collected the data, and data interpretation was performed primarily by Surbhi, along with Graetz, Bailey, and Gatwood. The manuscript was primarily written by Surbhi, with assistance from Bailey and Graetz, and revised by Bailey, Graetz, Gatwood, and Surbhi. This study was presented as a poster at the Academy Health Annual Research Meeting in Boston, Massachusetts, on June 26-28, 2016.