Dual Use of Department of Veterans Affairs and Medicare Benefits on High‐Risk Opioid Prescriptions in Veterans Aged 65 Years and Older: Insights from the VA Musculoskeletal Disorders Cohort

Abstract

Objective To examine the association of dual use of both Veterans Health Administration (VHA) and Medicare benefits with high‐risk opioid prescriptions among Veterans aged 65 years and older with a musculoskeletal disorder diagnosis. Data Sources/Study Setting Data were obtained from the VA Musculoskeletal Disorder (MSD) cohort and national Medicare claims data from 2008 to 2010. Study Design We conducted a retrospective analysis of Veterans enrolled in Medicare to examine the association of dual use with long‐term opioid use (>90 days of prescription opioids/year) and overlapping opioid prescriptions. Multivariable logistic regression was performed adjusting for demographic and clinical characteristics. Data Collection/Extraction Methods We identified 21,111 Veterans enrolled in Medicare who entered the MSD cohort in 2008 and received an opioid prescription in 2010. We linked VHA data with Medicare claims data to identify opioid prescriptions for these Veterans in 2010. Principal Findings As compared to Veterans who used only VHA or Medicare, Veterans with dual use of VHA and Medicare were significantly more likely to be prescribed long‐term opioid therapy (OR = 4.61 (95 percent CI 4.05–5.25) and were also found to have higher median number of opioid prescriptions and higher odds of overlapping opioid prescriptions in 1 year. Patients reporting moderate‐to‐severe pain, non‐white‐race/ethnicity, and higher scoring on the Charlson comorbidity index had significantly higher odds of long‐term opioid prescriptions. Conclusions Among Veterans aged 65 years or older, dual use of both VHA and Medicare was associated with higher odds of long‐term opioid therapy. Our findings suggest there may be benefit to combining VHA and non‐VHA electronic health record data to minimize exposure to high‐risk opioid prescribing.

Variations in Long‐term Opioid Therapy Definitions: A Systematic Review of Observational Studies Using Routinely Collected Data (2000‐2019)

“…One‐quarter of studies did not impose age restrictions (32 studies 23–53 ), while 83 studies included adults only, 11 studies 54–64 focused exclusively on the elderly (aged 65+ years) and two studies 65,66 focused on adolescents and young adults (13‐29 years old). Study populations varied substantially in size, ranging from 121 67 to 48 million people 68 .…”

“…One‐fifth of studies included only opioid‐naïve individuals (29 studies), mostly defined as the absence of opioid use in the 6 24,36,37,52,65,69–73 or 12 months 30,48,61,62,74–83 prior to the index date. Some studies investigated opioid use among patients with various specific health conditions: 43 studies 24,26–28,31,37,43,48,49,51,52,59,62,65,70,74,77–80,82–104 focused on noncancer pain, 14 studies 55,56,64,69,105–114 on musculoskeletal conditions, 13 studies 38–40,57,81,115–122 on injuries or trauma and eight studies 23,32,53,67,75,123–125 on infectious diseases. Seven studies 41,44,45,71,126–128 included patients with both cancer and noncancer pain, and six studies evaluated patients with cancer 60,129,130 or cancer survivors 61,131,132 .…”

Predictors of long-term use of prescription opioids in the community-dwelling population of adults without a cancer diagnosis: a retrospective cohort study

“…Most published studies on determinants of long-term opioid use in the population without cancer have focused on subpopulations, such as patients with traumatic injuries, 13 those who have undergone hip arthroscopy, 14 , 15 those with musculoskeletal disorders 16 , 17 or veterans. 18 – 21 In the current study, conducted in the general community-dwelling adult population without a cancer diagnosis, we aimed to identify risk factors for and predictors of long-term prescription opioid use to inform practice change at the point of care.…”

HSR Commentary: Linking VA and Non‐VA Data to Address Important US Veteran Health Services Research Issues

“…; and Chiu et al. ), and the impact of homelessness on health care use and costs (Nelson et al. , and Trivedi et al.…”

“…The papers in this special issue used a range of non-VA datasets, several presented for the first time in a research application. Medicare data were the most commonly linked data (used in Wang et al 2018;Thorpe et al 2018;Vaughan Sarrazin et al 2018;Trivedi et al 2018;Reddy et al 2018;Nelson et al 2018a, b;Vanneman et al 2018;Liu et al 2018;Chui et al 2018;Hebert et al 2018;Lei et al 2018), because these data have been available to VA researchers within the VA under an agreement with Centers for Medicare and Medicaid Services via the VIReC for more than fifteen years and have well-established documentation and file structures (Hynes et al 2007). Other non-VA datasets used by authors in this special issue included US Renal Data System (USRDS) (Wang et al 2018), state data from California birth records (Shaw et al 2018), and Oregon prescription drug monitoring program (PDMP) data (Carlson et al 2018).…”