Dual Receipt of Prescription Opioids From the Department of Veterans Affairs and Medicare Part D and Prescription Opioid Overdose Death Among Veterans

Abstract

Amid the ongoing opioid crisis in the United States, the health care system of the U.S. Department of Veterans Affairs (VA) has adopted several strategies to reduce opioid overprescribing and related adverse health outcomes (1, 2). Although these efforts by the largest integrated health care system in the country include robust monitoring of opioid prescriptions dispensed within VA, less attention has been directed toward opioids dispensed to VA enrollees through non-VA providers and non-VA insurance. Yet, approximately 80% of VA enrollees have other types of public or private health insurance coverage. More than half (51%) have Medicare, and of these, nearly a third are also enrolled in the Medicare Part D prescription drug benefit (3). The number of veterans using alternative sources of medical and prescription benefits in addition to receiving care at VA facilities is likely to increase given ongoing reforms to bolster access to non-VA care through VA s community care programs (4, 5). Use of both VA and non-VA providers may increase the complexity of medication management by limiting providers ability to monitor and coordinate services because of limited information sharing across health systems (613). Furthermore, use of multiple health systems could undermine the effectiveness of VA s internal efforts to discourage opioid overuse and reduce opioid-related harms (14, 15). Evidence from prior studies indicates that receipt of care from unconnected health systems is associated with excess use and costs (9, 1618) and increased risk for potentially unsafe prescribing of opioids and other medications (11, 12, 19, 20). Among veterans dually enrolled in VA and Part D, receiving opioids from both systems (that is, dual use) is associated with significantly increased risk for high-dose opioid exposure (12) and overlapping opioid and benzodiazepine prescriptions (20), both of which are strongly associated with increased risk for overdose death (2123). Although the association between dual use and unsafe medication use is now well established, no prior study to our knowledge has evaluated the association between dual use and adverse health outcomes of unsafe prescribing, such as overdose death. Veterans are at increased risk for opioid use disorders and have fatal accidental overdoses at nearly twice the rate seen in U.S. adults (24). We aimed to assess the association between dual receipt of opioid prescriptions from VA and Part D and death from prescription opioid overdose among veterans enrolled in both systems. We hypothesized that dual users would be more likely to die of prescription opioid overdose than those receiving opioids through 1 system only. Methods We conducted a nested casecontrol study in a previously defined cohort of more than 3.2 million veterans who filled at least 1 opioid prescription from either VA or Part D between 1 July 2011 and 31 December 2013. We chose a casecontrol approach because death from prescription opioids is a relatively infrequent health outcome at the population level. The nested casecontrol design ensures that case and control patients are derived from the same source population. The VA Pittsburgh Healthcare System Institutional Review Board approved this study. Data Sources We linked national patient-level data from the VA and Centers for Medicare & Medicaid Services in calendar years 2011 to 2013. Data from the Centers for Medicare & Medicaid Services were unredacted and included substance abuse claims. Veteran demographic characteristics came from the VA Corporate Data Warehouse and Medicare beneficiary summary files. We obtained information on outpatient prescription medications from VA Pharmacy Benefits Management Services and Medicare Part D. We determined cause of death using the National Death Index, a comprehensive epidemiologic resource of death certificates from all state vital statistics offices (25). National Death Index data for all veterans are stored in the Joint Department of DefenseVA Suicide Data Repository, and data from 2013 were the most recent available during the study (26). We obtained ZIP code of patient residence from Public Safety Strategies Group data on VA enrollee geocodes, and census region and urban influence code from the Area Health Resources File. Identification of Case and Control Patients We defined case patients as veterans who died of a prescription opioid overdose that was unintentional or of indeterminate intent between 1 January 2012 and 31 December 2013, determined by the presence of underlying cause-of-death code X42, X44, Y12, or Y14 from the International Classification of Diseases, 10th Revision (ICD-10), in combination with code T40.2, T40.3, or T40.4 (Appendix) (27). We excluded suicides and overdose deaths attributed to heroin to focus exclusively on prescription opioids, which are in theory more directly linked to dual prescribing. Case patients were also required in the 6 months before death to be continuously enrolled in both VA and Part D and to fill at least 1 opioid prescription. We excluded case patients whose only opioid either was a formulation for which reliable morphine milligram equivalents (MME) could not be computed (for example, oral liquid) or was intended solely for treatment of substance use disorder (that is, buprenorphinenaloxone or liquid methadone). We also excluded case patients who received hospice services or had missing information on key variables. We defined index date as the date of death. We matched up to 4 living control patients with each case patient on the basis of 9 variables. We initially matched patients on the 5 time-invariant variables (birthdate 5 years, sex, race/ethnicity, region of residence, and rurality of residence). We then assigned the date of death from each case patient as the index date for matched control patients and proceeded to match on 4 time-variant variables (disability as the reason for Medicare enrollment in index year; enrollment in Medicaid and Part D low-income subsidy in prior 6 months; Medicare managed care enrollment in prior 6 months; and a medication-based comorbidity index, the adapted RxRisk-V [28], in prior 6 months). We captured race/ethnicity from VA data supplemented by the Research Triangle Institute race/ethnicity indicator from Medicare (when missing from VA data). We used all medications prescribed through VA and Part D to calculate the RxRisk-V score. This validated measure of comorbidity classifies prescribed medications into 45 disease-related categories and predicts all-cause mortality with good discrimination (28). Because medical comorbid conditions are systematically undercoded in VA compared with Medicare, we chose to adjust for comorbidity using RxRisk-V; this measure is less susceptible to measurement discrepancies across health systems than the Elixhauser index, which ascertains 30 comorbidity indicators from diagnosis codes (2831). We applied all selection criteria equally to case and control patients through a matching process comprising 4 steps, of which the first 3 allowed replacement of control patients and the last did not. First, we matched patients on the time-invariant variables and assigned the date of death from each case patient as the index date for matched control patients. Second, we filtered control patients according to the same inclusion criteria described earlier for case patients, although control patients had to be alive on the case patient s index date. This step ensured that control patients received at least 1 opioid prescription within 6 months before the index date to define the source of these prescriptions. Third, we matched case and control patients on the time-variant covariates. Finally, we randomly sampled up to 4 control patients per case patient without replacement (Figure 1). Figure 1. Selection criteria for case and control patients. MME= morphine milligram equivalent; VA= U.S. Department of Veterans Affairs. * Matching proceeded in 4 steps: The first 3 allowed replacement of control patients, and the final step was without replacement. Therefore, unique control patients could be possible matches for 1 case patient before the last step. First, we matched control patients to case patients on the 5 time-invariant variables (birthdate 5 y, sex, race/ethnicity, region of residence, and rurality of residence), and assigned the date of death from each case patient as the index date for matched control patients (n= 1522446 unique control patients matched to n= 219 case patients). Second, we applied the same exclusion criteria to control patients as described for case patients (n= 271805 unique control patients matched to n= 219 case patients). Third, we matched case and control patients on the 4 time-variant variables (disability as the reason for Medicare enrollment [year of death], enrollment in Medicaid and Part D low-income subsidy [prior 6 mo], Medicare managed care enrollment [prior 6 mo], and medication-based comorbidity index [Rx-Risk, prior 6 mo]; n= 34289 unique control patients were matched to n= 215 case patients, including 10 case patients with <4 control patients). Finally, we randomly sampled up to 4 control patients per case patient without replacement (n= 833), where 205 case patients had 4 control patients each, 7 had 1 control patient, and 3 had 2 control patients. The final number of case patients was 215 after exclusion of 4 who lacked any matches on the 4 time-varying variables. Definition of the Exposure of Interest For all case and control patients, we identified sources of opioid prescriptions (VA only, Part D only, or both VA and Part D) dispensed within 6 months before the index date. Part Donly and VA-only users were veterans who obtained all opioid prescriptions through Part D or VA, respectively. Dual users obtained at least 1 opioid prescription from each source. Definition of Covariates We used data from the VA and Centers for Medicare & Medicaid Services to identify potentia