Opioid Prescription Clusters Associated With Early or Unplanned Military Separation.

INTRODUCTION: Early/unplanned military separation in Active Component U.S. service members can result in reduced readiness during periods of high-tempo combat and increased demand for health care services within the Military Health System and Veterans Administration. Although current assessment tools leverage prescription data to determine deployment-limiting medication receipt and the need for interventions or waivers, there is a lack of understanding regarding opioid prescription patterns and subsequent early/unplanned military separation after return from deployment. As such, understanding these relationships could support future tool development and strategic resourcing. Therefore, the goal of the present study was to identify unique 12-month opioid prescription patterns and evaluate their relationship with early/unplanned military separation in Active Component service members who returned from deployment. MATERIALS AND METHODS: This retrospective, IRB-approved cohort study included data from 137,654 Active Component Army service members who returned from deployment between 2007 and 2013, received a post-deployment (index) opioid prescription, and had at least 1 year of Active Component service post-opioid initiation. A k-means clustering analysis identified clusters using opioid prescription frequency, median dose, median days supply, and prescription breaks (≥30 days) over the 12-month post-initiation (monitoring) period. A generalized additive model examined whether cluster membership and additional covariates were associated with early/unplanned separation. RESULTS: In addition to the single opioid prescription (38%), the cluster analysis identified five clusters: brief/moderate dose (25%), recurrent breaks (16%), brief/high dose (11%), long/few prescriptions (8%), and high prescription frequency (2%). In the generalized additive model, the probability of early/unplanned military separation was higher for the high prescription frequency cluster (74%), followed by recurrent breaks (45%), long/few prescriptions (37%), brief/moderate dose (30%), and brief/high dose (29%) clusters, relative to the single prescription (21%) cluster. The probability of early/unplanned separation was significantly higher for service members with documented substance use disorders, mental health conditions, or traumatic brain injuries during the monitoring periods. Service members assigned male were more likely to have an early/unplanned separation relative to service members assigned female. Latinx service members and service members whose race was listed as Other were less likely to experience early/unplanned separation relative to white service members. Relative to Junior Officers, Junior Enlisted and Senior Enlisted service members were more likely to experience early/unplanned separation, but Senior Officers were less likely. CONCLUSIONS: Further evaluation to support the integration of longitudinal opioid prescription patterns into existing tools (e.g., a screening tool for deployment-limiting prescriptions) may enable more timely intervention and support service delivery to mitigate the probability and impact of early/unplanned separation.

Military Health System Opioid, Tramadol, and Gabapentinoid Prescription Volumes Before and After a Defense Health Agency Policy Release.

BACKGROUND: Clinical practice guidelines (CPGs) and health system policies to mitigate inappropriate opioid prescribing practices may have an extended impact on low-dose opioid (e.g., tramadol) and non-opioid (e.g., gabapentinoid) pain medication prescribing practices. OBJECTIVE: To evaluate changes in opioid, tramadol, and gabapentinoid prescribing rates from January 2016 to February 2020 within the Military Health System, including the degree to which prescribing rates changed after release of a US Defense Health Agency Procedural Instruction. METHODS: In this observational health services research study, opioid, tramadol, and gabapentin prescription dispense events of US Military Health System beneficiaries enrolled in care at military treatment facilities prior to US Defense Health Agency Procedural Instruction release (January 2016-May 2018) were used to forecast values from the post-intervention period (June 2018-February 2020). RESULTS: The median opioid and tramadol prescribing rates decreased from January 2016 to February 2020, aside from tramadol prescribing in Surgery Clinics, which increased. Gabapentinoid prescribing rate changes were mixed. In Bayesian time series models, the forecasted proportion of patients receiving each of the three medications, regardless of age group or clinic type, did not significantly vary from the actual prescribing rates in the post-intervention period. CONCLUSION: Overall, CPGs and policies targeting opioid prescribing practices may have provided the maximal impetus for providers to re-evaluate their prescribing practices, as the policy did not appear to change the slope in prescribing rates. However, it is unclear whether the policies mitigated the likelihood of plateaus in prescribing rates. Further work is needed to assess the degree to which providers simultaneously altered other non-opioid pain medication prescribing practices, self-management recommendations, and non-pharmacological therapy referrals.

Predictors of continued opioid use 6 months after total joint arthroplasty: a multi-site study.

PURPOSE: Continued opioid use after total knee and hip arthroplasty (TKA/THA) is well-documented and associated with both surgical and patient-reported factors. Research examining the combined effects of a multitude of factors on continued, and even chronic, opioid use in a systematic algorithmic manner is lacking. This study prospectively evaluated the combined effect of patient-related and surgical factors associated with continued opioid use after TKA/THA. METHODS: From 2016 to 2018, 198 participants undergoing TKA or THA were recruited from two tertiary care facilities. Participants completed surveys before surgery and at 2 weeks, 1, 3, and 6 months following surgery. A LASSO approach, followed by an exhaustive covariate selection procedure, was used to build a multivariable mixed-effects logistic regression model estimating the odds ratio of continued postoperative opioid use based on surgical factors and patient-reported factors. RESULTS: Approximately half of the participants underwent either TKA (49%) or THA (51%). Preoperatively, 15% of participants reported taking opioid medication. Opioid use decreased from 68% at 2-week follow-up to 7% by 6 months. In addition, preoperative opioid use (95% CI 1.07-4.37), increased pain (95% CI 1.21-1.62), elevated preoperative Pain Catastrophizing Scale scores (95% CI 1.01-1.04), lower Physical Function scores (95% CI 0.87-0.95), and participants undergoing TKA, compared to THA, (95% CI 0.25-0.67) were found to be significantly associated with continued postoperative opioid use up to 6 months. CONCLUSION: Preoperative opioid use, average pain, reduced physical function, and TKA were significantly associated with continued postoperative opioid use. Findings illustrate the need for preoperative and longitudinal assessment of patient-reported outcomes to mitigate poor postoperative pain outcomes. LEVEL OF EVIDENCE: II.