Abstract: Building Prevention-Focused Data Infrastructure: The Army Wellness Center Model (Society for Prevention Research 27th Annual Meeting)

227 Building Prevention-Focused Data Infrastructure: The Army Wellness Center Model

Schedule:
Wednesday, May 29, 2019
Pacific D/L (Hyatt Regency San Francisco)
* noted as presenting author
L. Omar Rivera, PhD, Quantiative Data Advisor, U.S. Army Public Health Center, APG-EA, MD
Patricia A. Erickson, MPH, Program Evaluator, U.S. Army Public Health Center; Oak Ridge Institute for Science and Education, APG-EA, MD
Todd Hoover, MA, Program Manager, U.S. Army Public Health Center, APG-EA, MD
Introduction: It is widely agreed upon that current reactive, treatment-oriented healthcare systems are not sustainable. The Army is engaged in reshaping the military healthcare system to enhance identification and prevention of emerging health threats. In alignment with Community Preventive Services Task Force recommendations, the Army Public Health Center (APHC) implemented a standardized, evidence-informed wellness model designed to identify health risks and empower healthy behavior change among military beneficiaries. The Army Wellness Center (AWC) model is delivered through a worldwide network of community-based facilities on Army installations.

Monitoring and evaluation are central to shaping AWC implementation and assessing AWC effectiveness, and depend on robust processes and systems for program data collection, integration, and reporting. Guided by big data strategy, the APHC is building a data infrastructure to sustain long-term AWC monitoring and evaluation, and link collected data with other Department of Defense (DOD) data sources to better identify and prevent emerging health threats.

Methods: The APHC is working along three lines of effort to build a data infrastructure that supports AWC efforts to identify and address health risks, including: (a) developing, refining, and maintaining a standardized data collection and reporting system for AWC client data, (b) standardizing the communication of AWC client data with clinical providers through the DOD’s existing electronic health record (EHR), and (c) integrating AWC client data with other military health and administrative data.

Results: The APHC has developed a data collection and reporting system that collects data on over 50,000 clients a year and provides information about: health risks to clients; client services to health educators; reporting tools for monitoring client outcomes to local leadership; and program effectiveness for program evaluators to answer questions from leadership. Evaluation results show that AWC clients with at least one follow-up outcome assessment experience improvements in health risk factors over time. The APHC has also implemented guidelines to standardize AWC client data documentation in the DOD’s EHR to facilitate communication about client care between health educators and clinical staff. Finally, the APHC is building links between AWC records and Soldier administrative records to improve identification of Soldiers at risk for musculoskeletal injury, facilitate referral to preventive services, and track changes in injury risk and injury.

Conclusions: Applying big data strategy to prevention, the APHC is building a data infrastructure alongside a primary prevention service delivery model that will help the military healthcare system proactively address health threats.