Health IT vendor concentration and the dynamics of hospital costs: evidence from California hospitals
摘要
Health information technology has been widely adopted by hospitals, yet the financial consequences of adoption remain uncertain and may depend on which vendor supplies the system. Despite a highly concentrated electronic medical record (EMR) market, little evidence exists on whether systems from market-dominant vendors are associated with lower hospital costs. This study examines how vendor market position and the depth of Meaningful Use implementation relate to hospital cost performance.
MethodsWe assembled a 2011–2017 panel of California hospitals that links audited financial data from the Department of Health Care Access and Information, Meaningful Use attestation records, and HIMSS installation histories. We defined advanced EMR adoption as the presence of computerized physician order entry or physician documentation, and classified adopters by whether their advanced-module vendor was among the two largest in the market. Using hospital and year fixed-effects models, an event-study specification, and several robustness checks, we estimated associations with three cost outcomes: inpatient cost per discharge, outpatient cost per visit, and operating expense per discharge.
ResultsAdvanced EMR adoption was not associated with immediate reductions in inpatient cost per discharge at any horizon. Estimated reductions emerged with a lag in outpatient costs and in operating expense, broadly consistent with a multi-year adjustment period. Vendor heterogeneity was also important: operating-expense reductions were more evident among hospitals using non-dominant vendors than among hospitals using the two largest vendors, and attaining Stage 2 Meaningful Use was consistently associated with lower costs. These patterns were robust to defining vendor dominance within hospital referral regions and within advanced functionality, to a single-versus-multiple-vendor specification, and to a heterogeneity-robust difference-in-differences estimator.
ConclusionsBecause the analysis is observational, the estimates are interpreted as associations rather than causal effects. The findings highlight the role of implementation depth and organizational fit, and they caution against treating vendor market concentration as inherently efficiency-enhancing.