The Impact of Accelerating Electronic Prescribing on Hospitals' Productivity Levels: Can Health Information Technology Bend the Curve?

Article excerpt

This paper examines how different strategies for implementing computerized prescriber order entry (CPOE) impact hospitals' productivity. We used the American Hospital Association's Annual Survey to construct hospital-level measures for 1,812 facilities and analyzed the productivity indices against CPOE use rates. The relationship between CPOE use rates and indices for "technical efficiency change" and "total factor productivity" was significant. Hospitals introducing CPOE facility wide in a one-year period (where usage went from zero to more than 50%) experienced declines in both productivity indices. One implication is that hospitals achieving the goals of the "meaningful use" program promoted by the Centers for Medicare and Medicaid Services may do so at the expense of productivity.


Significant parts of the 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act and the 2010 Patient Protection and Affordable Care Act (ACA) are dedicated to increasing the use of health information technology (HIT) as a way of coordinating patient care, improving hospital operating efficiencies, and helping to control costs (Blumenthal 2010). In particular, order entry systems have been promoted as potential innovations for savings because they serve as the starting point for nearly 80% of all hospital activities (McCormack 2011). Collectively, the transforming of clinical processes on a national scale is intended to "bend the curve" of health care inflation downward (Cutler, Davis, and Stremikis 2009).

The timelines and levels for implementing HIT are being measured against a "meaningful use" standard promulgated by the Centers for Medicare and Medicaid Services (CMS). Meaningful use measures revolve around providers' utilization levels of specific applications, the generation of key information during care delivery, and the demonstration of improved clinical outcomes. The meaningful use program, which provides financial incentives to organizations that use HITs at ever increasing levels, is being implemented in multiple stages to allow providers to adapt to the magnitude of changes required. Nevertheless, the deadline for the initial meaningful use program stage occurred in 2011, and hospitals used aggressive implementation strategies to meet the deadline (Ford et al. 2010; Furukawa, Raghu, and Shao 2010).

Despite the reported benefits of computerized prescriber order entry (CPOE), U.S. hospitals have been slow to adopt the systems due to their high installation and operating costs, disruptions to operating procedures, organizational and clinical work practice issues, and uncertainty about governmental requirements related to HIT (Ash and Bates 2005; Callen, Westbrook, and Braithwaite 2006; Ford et al. 2008; Wachter 2006). As of 2010, only 14% of U.S. hospitals had achieved the 10% use rate of CPOE required to receive Stage 1 meaningful use rewards in 2011 (Chaffee 2010; Hess 2010). However, the impact of CPOE systems on hospitals' efficiency and productivity levels is not well understood.

The purpose of this paper is to quantify the impact on hospitals' productivity associated with implementing CPOE technology (in particular, the prescription order entry component). We also measure how accelerating CPOE implementation rates--as is being promoted by the Office of the National Coordinator for Health Information Technology (ONC)--affects productivity. Using data from the American Hospital Association's (AHA's) Annual Survey and CMS, we have calculated "total factor productivity" (TFP) indices for the hospital sector. Productivity is the ratio of outputs created compared to the inputs required to complete a process. In addition to measuring the number of outputs, it is common practice to assess the quality of those outputs as part of the productivity calculation. In the hospital setting, productivity is derived by assessing hospitals' patient care output levels, which are measured as discharges and average length of stay. …


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