Reporting trends in a regional medication error data-sharing system
Department of Sociology, Purdue University, West Lafayette, IN 47907-2059, USA.Health Care Management Science (Impact Factor: 1.05). 03/2010; 13(1):74-83. DOI: 10.1007/s10729-009-9111-1
Inter-organizational systems for sharing data about medication errors have emerged as an important strategy for improving patient safety and are expected to encourage not only voluntary error reporting but also learning from errors. Yet, few studies have examined the hypothesized benefits of inter-organizational data sharing. The current study examined the developmental trends in information reported by hospitals participating in a regional reporting system for medication errors. A coalition of hospitals in southwestern Pennsylvania, under the auspices of the Pittsburgh Regional Healthcare Initiative (PRHI), implemented a voluntary system for quarterly sharing of information about medication errors. Over a 12-month period, 25 hospitals shared information about 17,000 medication errors. Using latent growth curve analysis, we examined longitudinal trends in the quarterly number of errors and associated corrective actions reported by each hospital. Controlling for size, teaching status, and JCAHO accreditation score, for the hospitals as a group, error reporting increased at a statistically significant rate over the four quarters. Moreover, despite significant baseline differences among hospitals, error reporting increased at similar rates across hospitals over subsequent quarters. In contrast, the reporting of corrective actions remained unchanged. However, the baseline levels of corrective actions reporting were significantly different across hospitals. Although data sharing systems promote error reporting, it is unclear whether they encourage corrective actions. If data sharing is intended to promote not just error reporting but also root-cause-analysis and process improvement, then the design of the reporting system should emphasize data about these processes as well as errors.
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ABSTRACT: Two major challenges to current voluntary medical incident reporting system (VMIR) are underreporting and low quality reports, which make it difficult for health providers to effective use and learn from mistakes for patient safety improvement. According to prior researches on a variety of voluntary system design and usage in different domains such as aviation, system usability and utility were considered as significant contributing factors that influence the system acceptance. However, the published studies of dealing with these factors to maximize system acceptance and effectiveness in medical incident reporting domain are few and fragmented. In this study, we elaborated the background and problems in target domain of medical incident reporting firstly, and then synthesized practical and academic instance by unobtrusive data analysis and literature review to propose a design framework to the future applications. Finally, a developing computer-based prototype as a partial solution of proposed design was paraphrased to illustrate our initial progress on user-centered design of VMIR. It is expected to increase reporting efficiency and data quality that will promote a learning culture and help remove shame-blame barriers in collecting patient safety events.
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ABSTRACT: Voluntary medical incident reporting systems (VMIR) are an application of information technology to support medical errors reporting for health professionals and thus ultimately improve healthcare quality and patient safety. The overall goal of this paper was to investigate the usage and effective design of VMIR by literature review. We expected to uncover design potentials from prior studies by examining on both incident reports analysis and system design, by which to establish a user-centered design framework that integrates identified factors for advancing VMIR effectiveness and efficiency. All papers regarding voluntary reporting system were identified through systematic electronic database searches. Three eligibility criteria were applied: 1) voluntary programs; 2) information system; 3) medical incident/error reporting. Of 8 eligible articles identified, the main themes are about current systems’ shortcomings on underreporting, report quality, standardized nomenclature/ taxonomy, communication, usability as well as reporting culture and environment. Eventually, all of identified concerns in the study will be addressed in a VMIR system prototyping process to attack the shortcomings aforementioned.Human Interface and the Management of Information. Interacting with Information - Symposium on Human Interface 2011, Held as Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part II; 01/2011
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ABSTRACT: This paper examines the difficulties of learning from event analysis. The central idea is that learning represents a distinct set of team-or unit-level outcomes and processes that is different from valid analysis, effective problem-solving, or individual learning. In other words, event analysis cannot automatically generate group learning. For learning to occur, several conditions must be satisfied: Change in the team’s or unit’s repertoire of behaviors (the learning) must be a clear outcome of the event analysis; this learning must be shared by the team members (i.e., members must become aware of both the content of the learning as well as of the fact that other members are aware of this learning); the shared learning must be stored in repositories for future retrieval; the stored learning must be retrieved when the team subsequently encounters situations where the learning is relevant; and, finally, these processes of sharing, storing, and retrieving the learning must continue to occur over an extended period of time. These requirements pose major dilemmas or challenges for learning from event analysis. We discuss these challenges using examples from event analysis teams in two hospitals and in a computer emergency response center. We offer some potential strategies for addressing these challenges.Safety Science 01/2011; 49(1):83-89. DOI:10.1016/j.ssci.2010.03.019 · 1.83 Impact Factor
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