. "6 Action Agenda for the Pharmaceutical, Medical Device, and Health Information Technology Industries ." Preventing Medication Errors: Quality Chasm Series. Washington, DC: The National Academies Press, 2007.
The following HTML text is provided to enhance online
readability. Many aspects of typography translate only awkwardly to HTML.
Please use the page image
as the authoritative form to ensure accuracy.
Preventing Medication Errors
knowledge-based systems used for laboratory and pharmacy data, patient safety reporting systems, infusion pumps, and applications for computerized provider order entry (CPOE) and electronic prescribing (IOM, 2004). Bar code medication administration systems have been implemented in some institutions. A key feature of pharmacy database systems, infusion pumps, and bar code and decision-support applications is the alert function that warns clinicians of potential medication safety problems. In general, a fully developed set of drug alerts includes drug–dose defaults, drug–dose checking, allergy checking, drug interaction checking, drug–laboratory checking, drug–condition checking, and drug–diet (food) checking. Other rule-based alerts (e.g., a required laboratory test for the use of particular drug) and automated surveillance for ADEs and near misses also are important to improving safety and reducing errors. Yet most providers currently use these technologies as independent, stand-alone systems rather than as integrated components of comprehensive clinical information systems—the overarching goal in building the national health information infrastructure (IOM, 2004). Nurses rely on the medication administration record generated by infusion and bar code systems to administer medications; physicians rely on CPOE and, if linked, pharmacy database systems for prescribing; and pharmacists rely on their databases for preparation and dispensing of prescriptions. As a result, each component of the medication use-system remains compartmentalized, increasing safety risks.
The lack of common drug information standards and integration of pharmacy database, decision-support, infusion, and bar code systems can have particularly devastating effects on patient safety (Patterson et al., 2002; Han et al., 2005; Koppel et al., 2005). For example, Koppel and colleagues (2005) found that medication errors increased as a result of data fragmentation, failures of system integration, and poorly designed human– machine interfaces. Because all of the above systems produce medication administration records, they must be able to communicate with each other to produce a comprehensive view of the patient’s medication regimen. If they operate as stand-alone systems, no one has the full medication administration record, and clinicians have incomplete information.
Recommendation 5: Industry and government should collaborateto establish standards affecting drug-related health informationtechnologies. Specifically:
The NLM should take the lead in developing a common drugnomenclature for use in all clinical information technologysystems, based on standards for the national health informationinfrastructure.