Complementarities in the Impacts of Health Information Technology on Hospital Performance: A Spatial Approach
Ms. Hyeyoung HAH
PhD Candidate in Information Systems
Goizueta Business School
In this job talk, she will address some of the current challenges faced by hospitals in the US – whether they are ready for the new technological innovations driven by electronic health records systems (EHR). As hospitals are increasingly adopting EHR, the integration of EHR into a hospital’s existing HIT infrastructure becomes a non-trivial matter. However, there is limited academic investigation on whether and how EHR can create performance gains in concert with the ex ante HIT infrastructure. In this paper, she present a model of hospital performance that considers complementarities of EHR with administrative and clinical HIT infrastructure, as key antecedents to hospital performance. Drawing from the theory of complementarity, she view the existing HIT infrastructure as enhancing the EHR capabilities across two major functional units, administrative and clinical units. The theoretical model then introduces the two-way complementarities of EHR-administrative HIT infrastructure and EHR-clinical HIT infrastructure as well as three-way complementarities of EHR-administrative HIT-clinical HIT infrastructure. The complementarity model is tested using triangulated archival data from California hospitals during 2002-2010. Regarding a hospital in a location as unit of analysis, she attempt to rule out unobserved spatial interactions that simultaneously affect the adoption of HIT and hospital performance by using spatial error model (SEM). Results show that the two-way complementarities of EHR with administrative HIT and with clinical HIT infrastructure differentially contribute to performance gains of a hospital. While the three-way complementarities influence patient volume of a hospital in the location, the contemporary results reveal that only selective, HIT intensive hospitals can translate the increased patient volume into net patient revenue via the three-way complementarities of HIT. These results are robust to concerns of omitted variable bias and selection bias.