Health information technology and implementation science: partners in progress in the VHA.

BACKGROUND: The Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI) has demonstrated how implementation science can enhance the quality of health care. During this time an increasing number of implementation research projects have developed or utilized health information technology (HIT) innovations to leverage the VA's electronic health record and information systems. OBJECTIVE: To describe the HIT approaches used and to characterize the facilitators and barriers to progress within implementation research projects in the VA QUERI program. PARTICIPANTS: Nine case studies were selected from among 88 projects and represented 8 of 14 HIT categories identified. Each case study included key informants whose roles on the project were principal investigator, implementation science and informatics development. APPROACH: We conducted documentation analysis and semistructured in-person interviews with key informants for each of the 9 case studies. We used qualitative analysis software to identify and thematically code information and interview responses. RESULTS: : Thematic analyses revealed 3 domains or pathways critical to progression through the QUERI steps. These pathways addressed: (1) compliance and collaboration with information technology policies and procedures; (2) operating within organizational policies and building collaborations with end users, clinicians, and administrators; and (3) obtaining and maintaining research resources and approvals. CONCLUSION: Sustained efforts in HIT innovation and in implementation science in the Veterans Health Administration demonstrates the interdependencies of these initiatives and the critical pathways that can contribute to progress. Other health care quality improvement efforts that rely on HIT can learn from the Veterans Health Administration experience.

Use of Medicare and DOD data for improving VA race data quality.

We evaluated the improvement in Department of Veterans Affairs (VA) race data completeness that could be achieved by linking VA data with data from Medicare and the Department of Defense (DOD) and examined agreement in values across the data sources. After linking VA with Medicare and DOD records for a 10% sample of VA patients, we calculated the percentage for which race could be identified in those sources. To evaluate race agreement, we calculated sensitivities, specificities, positive predictive values (PPVs), negative predictive values, and kappa statistics. Adding Medicare (and DOD) data improved race data completeness from 48% to 76%. Among older patients (≥65 years), adding Medicare data improved data completeness to nearly 100%. Among younger patients (<65 years), combining Medicare and DOD data improved completeness to 75%, 18 percentage points beyond that achieved with Medicare data alone. PPVs for white and African-American categories were 98.6 and 94.7, respectively, in Medicare and 97.0 and 96.5, respectively, in DOD data using VA self-reported race as the gold standard. PPVs for the non-African-American minority groups were lower, ranging from 30.5 to 48.2. Kappa statistics reflected these patterns. Supplementing VA with Medicare and DOD data improves VA race data completeness substantially. More study is needed to understand poor rates of agreement between VA and external sources in identifying non-African-American minority individuals.