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Introduction The DoD and VA Infrastructure for Clinical Intelligence (DaVINCI) data-sharing initiative has bridged the gap between DoD and VA data. DaVINCI utilizes the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to map DoD and VA-specific health care codes to a standardized terminology. Although OMOP CDM provides a standardized longitudinal view of health care concepts, it fails in capturing multiple and changing relationships beneficiaries have with DoD and VA as it has a static (vs. yearly) person characteristic table. Furthermore, DoD and VA utilize different policies and terminology to identify their respective beneficiaries, which makes it difficult to track patients longitudinally. The primary purpose of this report is to provide a methodology for categorizing beneficiaries and creating continuous longitudinal patient records to maximize the use of the joint DoD and VA data in DaVINCI. Materials and Methods For calendar year 2000-2020, we combined DoD and VA OMOP CDM and source databases to uniquely categorize beneficiaries into the following hierarchical groups: Active Duty, Guard, and Reserve Service Members (ADSMs); Separatees; Retirees; Veterans; and Deceased. Once the cohorts were identified, we examined calendar year 2020 health care utilization data using the OMOP VISIT_OCCURRENCE, DRUG_EXPOSURE, MEASUREMENT, and PROCEDURE tables. We also used the Defense Enrollment and Eligibility Reporting System source table to derive enrollment periods for DoD beneficiaries. As VA does not have enrollment plans, we utilized the VA’s priority groups (1-5) in the SPATIENT source table to crosswalk the DoD’s enrollment concept to the VA. We then assessed lengths of continuous enrollments in DoD and VA and the impact of appending the longitudinal records together. Results The majority of the ADSMs utilized the DoD system, but about 60,557 (3%) were seen in the VA for varied types of care. The market share of care provided to ADSMs by the VA varied by specialty and location. For Retirees, the split between DoD (1,625,874 [75%]) and VA (895,992 [41%]) health care utilization was more significant. The value added for utilizing DaVINCI in longitudinal studies was the highest for researchers normally limited to DoD data only. For beneficiaries who had 5 years of continuous enrollment, DaVINCI increased the potential study population by over 202% compared to using DoD data alone and by over 14% compared to VA data alone. Among beneficiaries with 20 years of continuous enrollment, DaVINCI increased the potential study population by over 133% compared to DoD data and by nearly 39% compared to VA data. Conclusions DaVINCI has successfully combined DoD and VA data and utilized OMOP CDM to standardize health care concepts. However, to fully maximize the potential of DaVINCI’s DoD and VA OMOP databases, researchers must uniquely categorize the DaVINCI cohort and build longitudinal patient records across DoD and VA. Because of the low other health insurance rates among DoD enrollees and their choice to enroll to a DoD Primary Care Manager, we believe this population to be the least censored in the DoD. Applying a similar concept through VA’s priority groups (1-5) would enable researchers to follow ADSMs as they transition from the military.

Introduction Low back pain (LBP) has accounted for the most medical encounters every year for the past decade among Active Duty Service Members (ADSMs) of the U.S. Armed Forces. The objectives of this retrospective, descriptive study were to classify LBP by clinical category (Axial, Radicular, and Other) and duration (Acute, Subacute, and Chronic) and examine the LBP-related health care utilization, access to care, and private sector costs for ADSMs over a 2-year follow-up period. Materials and Methods The Military Health System Data Repository was queried in fiscal year 2017 for all ADSMs (ages 18-62) with outpatient encounters documented with any of 67 ICD-10 diagnosis codes indicative of LBP. A 1-year clean period before the first (index) outpatient LBP encounter date was used to ensure no recent history of LBP care. Patients were eligible if continuously enrolled and on active duty for 1 year before and 2 years following the index visit. Patients were excluded for non-musculoskeletal causes for LBP, red flags, or acute trauma within 4 weeks of the index visit and/or systemic illness or pregnancy anytime during the clean or follow-up period. Results A total of 52,118 ADSMs met the inclusion criteria, and the cohort was classified by duration of LBP symptoms as Acute [17,916 (34.4%)], Subacute [4,119 (7.9%)], and Chronic [30,083 (57.7%)]. Over 2-year follow-up, 419,983 outpatient visits were recorded, with the majority occurring at MTFs [363,570 (86.6%)]. 13,237 (25.4%) of ADSMs in the total cohort were documented with no other LBP-related visits beyond their index encounter. In contrast, the Chronic cohort comprised the highest number of encounters [371,031 (89.2% of total encounters)], including 86% of imaging studies performed for LBP, and accounted for $9,986,606.17 (94.9%) of total private sector costs over the 2-year follow-up period. Interventional pain procedures ($2,983,767.50) and physical therapy ($2,298,779.07) represented the costliest categories in the private sector for the Chronic cohort, whereas Emergency Department ($283,307.43) and physical therapy ($137,035.54) encounters were the top contributors to private sector costs for the Acute and Subacute cohorts, respectively. Overall reliance on the private sector was highest for specialty care, including 10,721 (75.4%) interventional pain procedures and 306 (66.4%) spine surgeries. Conclusions Uncovering current trends in health care utilization and access to care for ADSMs newly presenting with LBP is vital for timely and accurate diagnosis, as well as early intervention to prevent progression to chronic LBP and to minimize its negative impact on military readiness and quality of life. This retrospective, descriptive study highlights the burden of chronic LBP on health care utilization and costs within the Military Health System, including reliance on the private sector care, amounting to $10,524,332.04 over the study period.