Cost-benefit analysis with return on investment of clinical pharmacists in the Military Health System.

BACKGROUND: The Defense Health Agency comprises more than 700 military medical, dental, and veterinary facilities and provides care to more than 9.6 million beneficiaries. As medication experts, pharmacists identify opportunities to optimize medication therapy, reduce cost, and increase readiness to support the Defense Health Agency's mission. The Tripler Pilot Project and the Army Polypharmacy Program were used to establish a staffing model of 1 clinical pharmacist for every 6,500 enrolled beneficiaries. No large-scale cost-benefit study within the military health care system has been done, which documents the number of clinical interventions and uses established cost-avoidance (CA) data, to determine the cost-benefit and return on investment (ROI) for clinical pharmacists working in the medical treatment facilities. OBJECTIVE: To validate the patient-centered medical home staffing model across the military health care system using the Tripler Pilot Project results to provide a cost-benefit analysis with an ROI. The secondary goal is to describe the interventions, staffing levels, and US Department of Defense-specific requirements impacting the provision of clinical pharmacy. METHODS: A retrospective analysis of 3 years of encounters by clinical pharmacists in which an intervention was documented in the Tri-Service Workflow (TSWF) form as part of the electronic health record was completed. The analysis used 6 steps to assign CA intervention types and to prevent duplication and overestimation of the ROI. The absolute number of clinical pharmacists was determined using workload criteria defined as at least 20 encounters per month for at least 3 months of each calendar year. The number of clinical pharmacist full-time employees (FTEs) was determined by dividing the number of total active months by 12 months. Attrition was calculated comparing the presence of a unique provider identification between calendar years. The ROI range was calculated by dividing the CA by the total cost of clinical pharmacists using the variables' raw and extrapolated CA based on percentage of documentation template usage and the active clinical pharmacist calculation (absolute and FTE-based). RESULTS: Between January 1, 2017, and December 31, 2019, a total of 1,069,846 encounters by clinical pharmacists were documented in the electronic health record. The TSWF Alternative Input Method form was used by pharmacists to document 616,942 encounters. Forty-three percent of TSWF documented encounters had at least 1 CA intervention. The absolute number of clinical pharmacists associated with a documented encounter in any medical treatment facility ranged from 404 in 2017 to 374 in 2018 and the clinical pharmacist FTEs ranged from 324 in 2017 to 314 in 2019. Annual attrition rates for clinical pharmacists ranged from 15% to 20% (58 to 81 clinical pharmacists) annually. The total CA range was $329,166,543-$534,014,494. The ROI range was between $2 and $4 per dollar spent. CONCLUSIONS: This analysis demonstrated that ambulatory care clinical pharmacists in the Military Health System bring value through a positive ROI. Our study also identified a potential shortage of clinical pharmacists within the Air Force and Navy branches impacting medication management. This can have a negative impact on the readiness of service members, one of the leading priorities of the US Department of Defense.

Evaluation of an Opioid Overdose Composite Risk Score Cutoff in Active Duty Military Service Members.

OBJECTIVE: To evaluate the current cutoff score and a recalibrated adaptation of the Veterans Health Administration (VHA) Risk Index for Serious Prescription Opioid-Induced Respiratory Depression or Overdose (RIOSORD) in active duty service members. DESIGN: Retrospective case-control. SETTING: Military Health System. SUBJECTS: Active duty service members dispensed ≥ 1 opioid prescription between January 1, 2018, and December 31, 2019. METHODS: Service members with a documented opioid overdose were matched 1:10 to controls. An active duty-specific (AD) RIOSORD was constructed using the VHA RIOSORD components. Analyses examined the risk stratification and predictive characteristics of two RIOSORD versions (VHA and AD). RESULTS: Cases (n = 95) were matched with 950 controls. Only 6 of the original 17 elements were retained in the AD RIOSORD. Long-acting or extended-release opioid prescriptions, antidepressant prescriptions, hospitalization, and emergency department visits were associated with overdose events. The VHA RIOSORD had fair performance (C-statistic 0.77, 95% CI 0.75, 0.79), while the AD RIOSORD did not demonstrate statistically significant performance improvement (C-statistic 0.78, 95% CI, 0.77, 0.80). The DoD selected cut point (VHA RIOSORD > 32) only identified 22 of 95 ORD outcomes (Sensitivity 0.23), while an AD-specific cut point (AD RIOSORD > 16) correctly identified 53 of 95 adverse events (Sensitivity 0.56). CONCLUSIONS: Results highlight the need to continually recalibrate predictive models and to consider multiple measures of performance. Although both models had similar overall performance with respect to the C-statistic, an AD-specific index threshold improves sensitivity. The calibrated AD RIOSORD does not represent an end-state, but a bridge to a future model developed on a wider range of patient variables, taking into consideration features that capture both care received, and care that was not received.