Learn from what goes right: A demonstration of a new systematic method for identification of leading indicators in healthcare
| Autor: | Ditte Caroline Raben, Birgit Viskum, Erik Hollnagel, Kim Lyngby Mikkelsen, Søren Bie Bogh |
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| Rok vydání: | 2018 |
| Předmět: |
Complex systems
Engineering Leading indicators media_common.quotation_subject 0211 other engineering and technologies Early detection Context (language use) 02 engineering and technology computer.software_genre Industrial and Manufacturing Engineering Patient safety Economic indicator 021105 building & construction Health care 0501 psychology and cognitive sciences In patient Safety Risk Reliability and Quality Function (engineering) 050107 human factors media_common Healthcare processes business.industry Method development 05 social sciences Identification (information) FRAM Risk analysis (engineering) Data mining business computer |
| Zdroj: | Raben, C, Bie Bogh, S, Viskum, B, Mikkelsen, K L & Hollnagel, E 2018, ' Learn from what goes right: a demonstration of a new systematic method for identification of leading indicators in healthcare ', Reliability Engineering & System Safety, vol. 169, pp. 187-198 . https://doi.org/10.1016/j.ress.2017.08.019 |
| ISSN: | 0951-8320 |
| Popis: | The work in patient safety is often centred on adverse events and errors. Typical methods to improve patient safety are reactive and focus on understanding past failures. This article presents the development of a proactive method towards improving patient safety and understanding why processes function as intended on a daily basis. The paper presents the steps of how the method was developed and demonstrates it by using a former case study of early detection of sepsis. Emphasis is on understanding complex processes and identify aspects important for things going right and achieving intended outcomes. The study resulted in the development of six overall steps for identifying leading indicators in complex healthcare processes. These were (1) identification of relevant functions, (2) cluster of functions in sets, (3) identification of functions with variability, (4) identification of functions with upstream–downstream functions, (5) identification of leading indicators, and (6) confirmation of leading indicators through experts and adverse events. The study outlined the development a new method on the topic of leading indicators in the context of patient safety. |
| Databáze: | OpenAIRE |
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