RESUMEN
BACKGROUND: Systematic analysis of error recovery can provide hospitals with important information to help them improve their ability to detect and correct errors. Because errors will always crop up and 100% safety can never be achieved, hospitals should be able to prevent patient harm by timely and effective error recovery. METHODS: In this study, failed, missed and absent recovery opportunities were identified in 52 medication errors which all resulted in severe patient harm or patient death. For all identified recovery opportunities, the underlying failure factors were identified and classified according to the Eindhoven classification model. Those failure factors represent negative influences on error recovery. RESULTS: The number of recovery opportunities per error ranged from 0 to 11; on average, 2.4 recovery opportunities were identified. Of 127 identified recovery opportunities, 94 (74%) were planned and 33 (26%) were unplanned or ad hoc. Most failure factors underlying the planned recovery opportunities were organisational failure factors; most failure factors underlying the unplanned recovery opportunities were human failure factors. CONCLUSIONS: From this study, it can be concluded that actual accidents can be used as an alternative data source to near misses for the analysis and understanding of error recovery. By using both sources, hospitals can enhance their resilience by reinforcing the positive influences on error recovery as well as reducing the negative ones. Together with traditional error reduction methodologies, which only concentrate on eliminating failure factors, hospitals thus have numerous opportunities to improve patient safety.
Asunto(s)
Hospitales/normas , Errores de Medicación , Seguridad del Paciente/normas , Administración de la Seguridad/normas , Humanos , Países BajosRESUMEN
The aim of this study was to evaluate the use of Healthcare Failure Mode and Effect Analysis (HFMEA) in Dutch health care by means of user feedback. Thirteen HFMEA analyses of various health care processes were successfully concluded and on average took 69 person-hours (excluding reporting). These results show that HFMEA can successfully be applied in Dutch health care. However, the user feedback also uncovered several perceived drawbacks, such as the fact that HFMEA is very time-consuming and that, particularly, the risk assessment part of HFMEA is difficult to carry out. Moreover, a lack of guidance with regard to the identification of failure mode causes and effective actions might influence the quality of the outcomes of an HFMEA analysis. Several suggestions are put forward to improve the perceived utility and acceptance of HFMEA. Nevertheless, future research is necessary to evaluate the actual effects of these recommendations. Error modelling and risk analysis, and their contribution to explaining human performance in socio-technical systems, traditionally belong to the field of ergonomics. The user feedback on HFMEA and the suggestions that are put forward may also be useful for (H)FMEA and hazard analysis and critical control point applications in sectors other than health care.