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Healthcare spending in the U.S.A. is expected to reach $4 trillion in 2015 – roughly 20% of gross domestic product (GDP) (Borger, Smith, Truffer, Keehan, Sisko, Poisal, et al., 2006; Bourgeois, Prater, & Slinkman, 2009). This has led “many policymakers, industry experts, and medical practitioners [to] contend that the U.S. health care system is in crisis,” (Trimmer, Cellucci, Wiggins, & Woodhouse, 2009, p. 55). Many believe that this crisis can be at least partially addressed by improving integration in the healthcare delivery supply chain – also thought of as clinical integration – using information technology (Ford & Scanlon, 2007; Falan & Han, 2011). Given this, there is a “…call for increased adoption and use of health care information technology (HIT) to address structural inefficiencies and care quality issues plaguing the US health care industry” (GAO, 2005; Trimmer et al., 2009). According to Katsamakas, Janamanchi, Raghupathi, and Gao (2009, p. 19), “HIT has the potential to transform the healthcare industry by increasing productivity, reducing errors and costs, facilitating information sharing and improving the quality of healthcare services” (Brailer, 2005).
Growth in HIT use among hospitals is motivated by the desire for these improved outcomes (Bourgeois et al., 2009; Dobrzykowski, 2011). This growth is primarily led by two HIT applications: picture archiving computer systems (or electronic health records used for results viewing (ERV)) and computerized provider order entry systems (CPOE) (Dorenfest, 2004). These applications (ERV and CPOE) represent a range of functional sophistication (Bourgeois et al., 2009) in that ERV can be defined as basic electronic health record (EHR) use and CPOE can be defined as advanced (or comprehensive) EHR use (Jha, DesRoches, Campbell, Donelan, Rao, Ferris, et al., 2009). Unfortunately, the adoption and use of these EHR technologies has been below expectations (Reardon, 2009), and heterogeneous among hospital providers (McCullough, Casey, Moscovie, & Burlew, 2011). In other words, while all hospitals use EHR to some extent, the levels of sophistication vary substantially (Cohen, 2005).
The heterogeneity in EHR use among hospitals may be contingent on a variety of factors present in a hospital’s environmental or operational context (Helms, Moore, & Ahmadi, 2008; Spil, LeRouge, Trimmer, & Wiggins, 2009). One key contingency in such an operational context might be a hospital’s structural constraints such as location or type (Li, Benton, & Leong, 2002). For example, a high volume teaching hospital treating high acuity patients may be more likely to adopt advanced EHR applications than critical access hospitals which typically face less competition and possess fewer resources (Hough, Chen, & Lin, 2005; Helms et al., 2008). Given the substantial investment afoot for EHR among hospitals, it would be useful to better understand some of the adoption patterns of specific hospital types (Bourgeois et al., 2009). Understanding the extant contingencies may “…help to smooth IT implementation in the future” (Spil et al., 2009, p. 70).