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.

Whole Spine CT Scan for the Detection of Acute Spinal Fractures in Diffuse Idiopathic Skeletal Hyperostosis Patients Who Sustained Low-energy Trauma.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: The aim of this study was to evaluate the role and value of whole-spine computerized tomography (WSCT) versus radiographs and targeted CT to tender spinal regions in patients with diffuse idiopathic skeletal hyperostosis (DISH) after low-energy trauma. SUMMARY OF BACKGROUND DATA: Subjects with DISH are prone to spinal fractures even after low-impact trauma due to a rigid spinal structure. METHODS: One-hundred forty-seven subjects (average age: 83 years, M:F 64/83) with verified DISH (Resnick and Niwayama radiographic criteria) on WSCT who were admitted to the emergency room (ER) after low-energy trauma and for whom there were radiographs of at least the thoracic and lumbar spine were evaluated for the presence of acute spinal fractures on both radiographs and WSCT. Agreement between fracture location and spinal tenderness location (cervical, thoracic, or lumbar) as reported in the medical record was evaluated. RESULTS: Significantly more acute fractures were detected on WSCT compared to radiographs (55 and 32, P < 0.00001, respectively). The site of tenderness was not indicative of the fractured spinal segment in 57% of all acute fractures (seven cervical, 15 thoracic, and 16 lumbar). No fracture was detected on WSCT in 10 subjects with an unspecified pain location. Multilevel distant fractures were detected in two patients with a specified pain location to only one of the fractures. CONCLUSION: WSCT in DISH subjects after low-impact trauma is mandatory due to the high prevalence of acute fractures and the low specificity for fracture detection on radiographs. A targeted CT approach to the tender spinal segment proved to be inadequate and would have missed 57% of the acute single fractures with incompatible spinal tenderness location. These results support the significant role of WSCT in the ER setting for detecting and pinpointing the spinal fracture site of DISH subjects who present with low-impact trauma. LEVEL OF EVIDENCE: 3.