Better patient safety: implementing exploration and exploitation learning in daily medical practice

Algorithmic prediction of failure modes in healthcare

BACKGROUND

Preventing medical errors is crucial, especially during crises like the COVID-19 pandemic. Failure Modes and Effects Analysis (FMEA) is the most widely used prospective hazard analysis in healthcare. FMEA relies on brainstorming by multi-disciplinary teams to identify hazards. This approach has two major weaknesses: significant time and human resource investments, and lack of complete and error-free results.

OBJECTIVES

To introduce the algorithmic prediction of failure modes in healthcare (APFMH) and to examine whether APFMH is leaner in resource allocation in comparison to the traditional FMEA and whether it ensures the complete identification of hazards.

METHODS

The patient identification during imaging process at the emergency department of Sheba Medical Center was analyzed by FMEA and APFMH, independently and separately. We compared between the hazards predicted by APFMH method and the hazards predicted by FMEA method; the total participants' working hours invested in each process and the adverse events, categorized as 'patient identification', before and after the recommendations resulted from the above processes were implemented.

RESULTS

APFMH is more effective in identifying hazards (P < 0.0001) and is leaner in resources than the traditional FMEA: the former used 21 h whereas the latter required 63 h. Following the implementation of the recommendations, the adverse events decreased by 44% annually (P = 0.0026). Most adverse events were preventable, had all recommendations been fully implemented.

CONCLUSION

In light of our initial and limited-size study, APFMH is more effective in identifying hazards (P < 0.0001) and is leaner in resources than the traditional FMEA. APFMH is suggested as an alternative to FMEA since it is leaner in time and human resources, ensures more complete hazard identification and is especially valuable during crisis time, when new protocols are often adopted, such as in the current days of the COVID-19 pandemic.

Stop! Check your initial assumptions: Frozen patient management in obstetrical practice

At times, leaping from one patient management routine to an alternative one may be required to mitigate medical errors. "Frozen patient management" is the resultant situation, when, in the face of an obvious gap between the expected and the actual phenomena, leaping from current patient management to an alternative one is not considered or done. Frozen patient management can lead to a significant delay of the correct definitive intervention, be it surgical or pharmacological. The significance of this delay is especially important in time-dependent dynamic situations. In delivery ward, this may cost the life of either the fetus or the mother.In this study, we describe a sequence in which frozen patient management occurred in the delivery ward. Using "thinking protocol" (herein termed "de-freezing" questionnaire) made the team stop and consider a leap when gaps became apparent, and saved the mother's life.We believe that adopting the "de-freezing questionnaire" as a routine adjunct for all medical activities would lead to a timely change of treatment line, which, in turn, will save lives and unnecessary suffer.