detailing the complexity of health IT and patient safety, the limitations in the literature to determine health IT’s impact on patient safety, and how the magnitude of harm is masked. The chapter then analyzes the literature to determine how individual components of health IT have impacted patient safety and how data from health IT can be leveraged to improve safety in different populations. Next, it describes how policy makers can learn from health IT experiences from abroad.

COMPLEXITY OF HEALTH IT AND PATIENT SAFETY

In general, health IT is not a specific product but is composed of components—such as computerized provider order entry (CPOE) systems and clinical decision support (CDS) systems—that are designed, implemented, and used differently by various vendors, health care settings, and users (Hayrinen et al., 2008). These differences can have dramatic effects on care processes including care design, workflow, and—ultimately—the quality and safety of the care delivered. When health IT is designed and implemented in a manner that complements how information is transferred between health professionals and patients, the reliability of patient information—and therefore patient safety—can increase (Dorr et al., 2007; Niazkhani et al., 2009; Shah et al., 2006). However, when health IT unexpectedly alters workflow, it has the potential to hinder clinicians’ abilities to communicate patient information (Niazkhani et al., 2009), and it may result in increased cognitive workload, clinicians ignoring computer- generated information, continued reliance on various traditional modes of communication, creation of unsafe workarounds, and more time spent dealing with health IT than with patient care (Ash et al., 2009). Several important factors regarding how health IT products are designed and implemented can have meaningful effects on the collection, storage, and transfer of information, as well as the utility of the product. Slight variations in these factors can have differing effects on how health IT impacts patient safety. Some of these factors include the following:

•   Decisions about implementation strategies (e.g., “big bang” versus incremental);

•   The degree to which users can configure their IT system and the approaches to such configurations;

•   Clinician training strategies;

•   Frontline use (e.g., the IT integration into and redesign of clinical workflow); and

•   Tools for analyzing and reporting results of care (e.g., quality improvement).



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