The value of computerized physician order entry and complementary organizational inputs in the production of quality

Presenter: Jeffrey S. McCullough, University of Minnesota

Abstract

Clinical error reduction is among the most pressing issues facing the US healthcare system. The Institute of Medicine estimates that errors cause at least 44,000 deaths annually and impose a direct cost of more than $17 billion. Information technology (IT) holds the potential to improve hospital quality while reducing costs. In particular, computerized physician order entry (CPOE) systems may remedy communication problems while facilitating clinical guideline implementation. CPOE also captures information for both clinical and management purposes. Numerous case studies have documented successful CPOE implementations.

Effective CPOE implementation is not as simple as installing hardware and software; rather, hospitals must make complementary technological and organizational investments. CPOE must interoperate with electronic medical record and medication administration record systems. These technologies must also penetrate the organization, providing access to staff throughout the hospital. Finally, physicians must invest their own time to learn and use health information technology (HIT).

We will measure the effect of HIT on both quality and costs. Our research will build on the existing CPOE literature in three ways. First, we will utilize national patient level data in conjunction with hospitals’ IT adoption decisions for the 1997-2007 time period. These data and a difference-in-differences strategy that exploits CPOEs rapid diffusion during this period will provide more generalizable measures of CPOE value. Second, we will measure the value of hospitals’ complementary technological and organizational investments. Although the importance of these investments has been recognized, their value has not previously been estimated.

We will measure HIT value in two steps. First, we will measure the effect of HIT and its organizational complements on medical errors. Second, we will combine these measures with previous research deriving the financial cost of medical errors (Zhan and Miller, 2005); thus, we will estimate the financial value of CPOE-driven error reductions. We will employ a difference-in-differences identification strategy. We will also employ a set of identification tests based on different patient safety outcomes that should, and should not, be affected by HIT. Overall, this study will provide new insight into how HIT creates both financial and clinical value while enhancing the empirical rigor with which that value is measured.