Technology Integration in Service Supply Chains : An Empirical Analysis of Electronic Medical Record Integration by Healthcare Providers

An array of information-intensive and customer-centric technologies is available today that promise significant performance improvements for manufacturing and service supply chains. Managers are overwhelmed by the abundance of such technologies. And, increasingly, managers are finding it challenging to determine what each of the available technologies do, which technologies they should invest in, and how to integrate the technologies so that the promised performance benefits of the technologies can be realized. The extant supply chain management and information system literatures provide limited insights into strategies for technology integration and its implications for performance, especially in the context of service supply chains. This paper, based on the first part of my dissertation research, is an attempt to address this gap in the literature. The context of my dissertation research is service supply chain operations. Specifically, we investigate technology selection and technology integration in the context of healthcare supply chains. We conceptualize technology integration in the healthcare supply chain by way of a classification scheme for clinical information technologies (electronic medical records) comprising of five levels. The levels are ordered with respect to an increasing order of medical record preparedness – i.e., information storage and access capability to coordinate and support superior quality and timely clinical decision making. Drawing on the relevant streams of academic and practitioner literatures, we posit the following proposition that guides the empirical analysis: Healthcare providers that select a higher level of technology integration will outperform the healthcare providers that select a lower level of technology integration. The performance measure we investigate is patient turnover measured as patient-discharges per bed. By way of research design, we model a healthcare provider’s choice of a level of technology integration as a discrete choice model. Given the limitation of traditional regression approaches in accounting for self-selection in decision making, this study adopts an econometric technique corrected for self-selection to examine the level of technology integration selection process and its impact on operational performance. The research design involves the use of a two-step selection model to account for the endogeneity bias. Electronic medical records (EMR) , that entail the capture, storage, retrieval and transmission of patient-specific healthcare-related data and whose successful operation is dependent on the tight integration of various clinical information technologies across the healthcare supply chain, is the technological domain of our research. Based on data from 1011 acute care providers in the US, our results suggest that healthcare providers self-select into different levels of technology integration in the context of their supply chains. While some healthcare providers are better off investing in higher levels of technology integration and benefit from doing so, others are better off not following suit.