Development, implementation, and evaluation of a clinical decision support tool to improve naloxone coprescription within Military Health System pharmacies.

PURPOSE: To describe the development, implementation, and evaluation of a pharmacy clinical decision support tool designed to increase naloxone coprescription among people at risk for opioid overdose in a large healthcare system. SUMMARY: The Military Health System Opioid Registry and underlying presentation layer were used to develop a clinical decision support capability to improve naloxone coprescription at the pharmacy point of care. Pharmacy personnel use a patient identification card barcode scanner or manually enter a patient's identification number to quickly visualize information on a patient's risk for opioid overdose and medical history related to pain and, when appropriate, receive a recommendation to coprescribe naloxone. The tool was made available to military treatment facility pharmacy locations. An interactive dashboard was developed to support monitoring, utilization, and impact on naloxone coprescription to patients at risk for opioid overdose. CONCLUSION: Initial implementation of the naloxone tool was slow from a lack of end-user awareness. Efforts to increase utilization were, in part, successful owing to a number of enterprise-wide educational initiatives. In early 2020, the naloxone tool was used in 15% of all opioid prescriptions dispensed at a military pharmacy. Data indicate that the frequency of naloxone coprescription to patients at risk for opioid overdose was significantly higher when the naloxone tool was used than when the tool was not used.

Public Health Surveillance via Template Management in Electronic Health Records: Tri-Service Workflow's Rapid Response to an Infectious Disease Crisis.

OBJECTIVE: To describe the use of template-based screening for risk of infectious disease exposure of patients presenting to primary care medical facilities during the 2014 West African Ebola virus outbreak. METHODS: The Military Health System implemented an Ebola risk-screening tool in primary care settings in order to create early notifications and early responses to potentially infected persons. Three time-sensitive, evidence-based screening questions were developed and posted to Tri-Service Workflow (TSWF) AHLTA templates in conjunction with appropriate training. Data were collected in January 2015, to assess the adoption of the TSWF-based Ebola risk-screening tool. RESULTS: Among encounters documented using TSWF templates, 41% of all encounters showed use of the TSWF-based Ebola risk-screening questions by the fourth day. The screening rate increased over the next 3 weeks, and reached a plateau at approximately 50%. CONCLUSIONS: This report demonstrates the MHS capability to deploy a standardized, globally applicable decision support aid that could be seen the same day by all primary care clinics across the military health direct care system, potentially improving rapid compliance with screening directives.

Abdominal circumference is superior to body mass index in estimating musculoskeletal injury risk.

PURPOSE: The purpose of this study was to compare body mass index (BMI) and abdominal circumference (AC) in discriminating individual musculoskeletal injury risk within a large population. We also sought to determine whether age or sex modulates the interaction between body habitus and injury risk. METHODS: We conducted a retrospective cohort study involving 67,904 US Air Force personnel from 2005 to 2011. Subjects were stratified by age, sex, BMI, adjusted BMI, and AC. New musculoskeletal injuries were recorded relative to body habitus and time elapsed from the start of study. RESULTS: Cox proportional hazards regression revealed increased HR for musculoskeletal injury in those with high-risk AC (males, >39 inches; females, >36 inches) compared with HR in those with low-risk AC (males, ≤35 inches; females, ≤32 inches) in all age categories (18-24 yr: HR = 1.567, 95% confidence interval (CI) = 1.327-1.849; 25-34 yr: HR = 2.089, 95% CI = 1.968-2.218; ≥35 yr: HR = 1.785, 95% CI = 1.651-1.929). HR for obese (BMI, ≥30 kg·m) compared with that for normal individuals (BMI, <25 kg·m) were less elevated. Kaplan-Meier curves showed a dose-response relation in all age groups but most prominently in 25- to 34-yr-old participants. Time to injury was consistently lowest in 18- to 24-yr-old participants. Score chi-square values, indicating comparative strength of each model for injury risk estimation in our cohort, were higher for AC than those for BMI or adjusted BMI within all age groups. CONCLUSIONS: AC is a better predictor of musculoskeletal injury risk than BMI in a large military population. Although absolute injury risk is greatest in 18- to 24-yr-old participants, the effect of obesity on injury risk is greatest in 25- to 34-yr-old participants. There is a dose-response relation between obesity and musculoskeletal injury risk, an effect seen with both BMI and AC.