Healthcare Failure Mode and Effect Analysis (HFMEA) as an Effective Mechanism in Preventing Infection Caused by Accompanying Caregivers During COVID-19-Experience of a City Medical Center in Taiwan.

BACKGROUND AND OBJECTIVES: In response to the COVID-19 pandemic outbreak and to ensure the safety of epidemic prevention in the hospital, the hospital has established mitigation strategies in advance including risk assessment and effect analysis to control hospital visitors and accompanying persons. The study aims to assess the effectiveness of mitigation strategies implemented to effectively prevent the invasion and spread of the virus. METHOD: Conduct a status analysis in accordance with the Healthcare Failure Mode and Effect Analysis (HFMEA) 4-step model, construct a response workflow, confirm the failure mode and potential causes, perform hazard matrix analysis and decision tree analysis, and formulate risk control management measures. RESULTS: For the 4 main processes and 9 subprocesses of the accompanying carers and contract caregivers entering the hospital, 26 potential failure modes and 42 potential causes of failure were analyzed. Following implementing improvement measures including strategies targeting the accompanying person, mitigation workflow failure rates decreased from 42 to 13 items, the pass rate for the maximum body temperature cutoff increased from 53.1% to 90.8%, and the compliance rate of hand washing increased from 89.5% to 100%. CONCLUSION: The HFMEA model can effectively implement preventive risk assessment and workflow management of high-risk medical procedures. The model can adjudicate the health of hospital visitors during the epidemic/pandemic, provide epidemic/pandemic education training and preventive measure health education guidance for hospital visits, and improve their epidemic prevention cognition. When combined, these strategies can prevent nosocomial infection to achieve the best anti-epidemic effect.

Health Care Failure Mode and Effect Analysis in the Operating Room Setting.

OBJECTIVES: Operating rooms (ORs) and surgical settings are potential sources of sentinel adverse events. To better understand the characteristics of errors in OR processes, we performed prospective risk analysis. METHODS: The study was mixed qualitative and quantitative research. We used the Healthcare Failure Mode and Effect Analysis (HFMEA) method to analyze the selected perioperative, operative, and postoperative processes in the OR via a 2-round Delphi technique. We identified the most prominent failure modes according to a Hazard Decision Matrix, analyzed and categorized proposed possible causes, and provided solutions to mitigate hazard scores. RESULTS: Ten important processes and 7 subprocesses within the OR were selected and mapped, and 187 failure modes were identified and scored on the basis of severity and probability. A total of 36 potential failure modes were highlighted as high-risk failures and moved to decision trees for further analyses. CONCLUSION: Developing policy for the familiarization of new personnel designing a checklist for accurate gases counting; drafting comprehensive presurgical posters; preparing all necessary equipment in difficult intubation; developing instruction for monthly checking of the OR equipment; and developing the evaluation criteria of staff performance are examples of solutions that are proposed to improve the quality of OR processes.

Using Failure Mode and Effects Analysis in Blood Administration Process in Surgical Care Units: New Categories of Errors.

BACKGROUND: Blood administration failures and errors have been a crucial issue in health care settings. Failure mode and effects analysis is an effective tool for the analysis of failures and errors in such lifesaving procedures. These failures or errors would lead to adverse outcomes for patients during blood administration. OBJECTIVES: The study aimed to: use health care failure mode and effect analysis (HFMEA) for assessing potential failure modes associated with blood administration processes among nurses; develop a categorization of blood administration errors; and identify underlying reasons, proactive measures for identified failure modes, and corrective actions for identified high-risk failures. METHODS: A cross-sectional descriptive study was conducted in surgical care units by using observation, HFMEA, and brainstorming techniques. Prioritization of detected potential failures was performed by Pareto analysis. RESULTS: Eleven practical steps and 38 potential failure modes associated with 11 categories of errors were detected in this process. These categories of errors were newly developed in this study. In total, 17 of 38 potential failures were detected as high-risk failures that occurred during the sample-drawing, checking, preparing, administering, and monitoring steps. For cause analysis of failures and errors, proactive suggested actions were undertaken for 38 potential failure modes, and corrective actions for 17 high-risk failures. CONCLUSION: HFMEA is an efficient and well-organized tool for identification of and reduction in high-risk failures and errors in the blood administration process among nurses without building punitive culture. This tool also helps pay attention to redesigning and standardizing the blood administration process as well as providing training and educational programs for providing knowledge.

Implementing a new scale for failure mode and effects analysis (FMEA) for risk analysis in a radiation oncology department.

PURPOSE: Patients and staffs are endangered by different failure modes during clinical routine in radiation oncology and risks are difficult to stratify. We implemented the method of failure mode and effects analysis (FMEA) via questionnaires in our institution and introduced an adapted scale applicable for radiation oncology. METHODS: Failure modes in physical treatment planning and daily routine were detected and stratified by ranking occurrence, severity, and detectability in a questionnaire. Multiplication of these values offers the risk priority number (RPN). We implemented an ordinal rating scale (ORS) as a combination of earlier published scales from the literature. This scale was optimized for German radiation oncology. We compared RPN using this ORS versus use of a rather subjective visual analogue rating scale (VRS). RESULTS: Mean RPN using ORS was 62.3 vs. 67.5 using VRS (p = 0.7). Use of ORS led to improved completeness of questionnaires (91 vs. 79%) and stronger agreement among the experts, especially concerning failure modes during radiation routine. The majority of interviewed experts found the analysis by using the ORS easier and expected a saving of time as well as higher intra- and interobserver reliability. CONCLUSION: The introduced rating scale together with a questionnaire survey provides merit for conducting FMEA in radiation oncology as results are comparable to the use of VRS and the process is facilitated.

Development of Rapid Response Capabilities in a Large COVID-19 Alternate Care Site Using Failure Modes and Effect Analysis with In Situ Simulation.

Preparedness measures for the anticipated surge of coronavirus disease 2019 (COVID-19) cases within eastern Massachusetts included the establishment of alternate care sites (field hospitals). Boston Hope hospital was set up within the Boston Convention and Exhibition Center to provide low-acuity care for COVID-19 patients and to support local healthcare systems. However, early recognition of the need to provide higher levels of care, or critical care for the potential deterioration of patients recovering from COVID-19, prompted the development of a hybrid acute care-intensive care unit. We describe our experience of implementing rapid response capabilities of this innovative ad hoc unit. Combining quality improvement tools for hazards detection and testing through in situ simulation successfully identified several operational hurdles. Through rapid continuous analysis and iterative change, we implemented appropriate mitigation strategies and established rapid response and rescue capabilities. This study provides a framework for future planning of high-acuity services within a unique field hospital setting.

Modified Early Warning System: Quality Improvement with the Help of Healthcare Failure Modes and Effect Analysis.

Introduction: Hospitals struggle to implement MEWS. This study aims to improve MEWS implementation in the studied hospital.Objective: Improve the implementation of MEWS with the help of HFMEA.Materials: HFMEA together with training is used to improve the implementation.Results: The pre-intervention RPN got reduced from 1558 to 516 in the post-implementation phase.Application: This demonstrates improvement in the implementation of MEWS with the help of HFMEA, this study design can be widely used.Conclusion: The HFMEA is an effective tool to use for the improvement of MEWS implementation by the hospital nurses.

Healthcare failure mode and effect analysis (HFMEA) for improving the qualification rate of disinfection quality monitoring process.

BACKGROUND: This study aimed to assess potential failure mode, implement countermeasures against risks and improve disinfection quality monitoring using healthcare failure mode and effect analysis (HFMEA). METHODS: Between July 2017 and March 2018, a multidisciplinary team was formed to conduct HFMEA and implement improvement interventions. Fourteen monitoring departments and seven monitoring items were involved. The qualification rate of monitoring process was used to evaluate the influence of HFMEA on the standardization monitoring management of disinfection quality. RESULTS: After HFMEA, the qualification rate of overall monitoring process of disinfection quality improved from 16.5% to 78.7% (P < 0.001), and the qualification rates of each monitoring step were all significantly improved. The qualification rate implemented by the clinical laboratory improved from 20.1% to 100.0% (P < 0.001). The qualification rate implemented by thirteen monitoring departments improved from 20.1% to 78.7% (P < 0.001), where seven reached 100%. Out of seven monitored items, three had the qualification rate of 100.0%, while the remaining four items showed significant rising in qualification rates (P < 0.001). CONCLUSION: HFMEA were helpful in improving the qualification rate of disinfection effect monitoring process.

Critical Care Helicopter Overtriage: A Failure Mode and Effects Analysis.

OBJECTIVE: Overtriage (OT) of helicopter emergency medical services (HEMS) poses significant burden to multiple stakeholders. The project aims were to identify the following: 1) associated factors, 2) downstream effects, and 3) focus areas for change. METHODS: We undertook a failure mode and effects analysis (FMEA) to evaluate our HEMS interfacility transport process. Data were collected from organizational finances and 3 key stakeholder groups: 1) interfacility patients transferred by HEMS in 2017 who were discharged from the receiving facility within 24 hours (n = 149), 2) flight registered nurses (n = 19), and 3) referring emergency medicine providers (EMPs) (n = 30) from the top HEMS users of 2017. The completed FMEA identified failure modes, the frequency and severity of effects, and unique risk profile numbers (RPNs). RESULTS: Twelve failure modes were identified with 30 potential causes. Leading failure modes included inappropriate HEMS requests by EMPs (RPN = 343), inappropriate activation by EMS for interfacility transport (RPN = 343), and minimizing patient/family involvement in decision making (RPN = 315). Significant burdens to organizational finances and flight registered nurse satisfaction were identified. CONCLUSION: Associated factors for interfacility HEMS OT, downstream effects, and areas for change were identified. EMP and emergency medical services practices, HEMS processes, and shared decision making may affect regional OT rates.

Evaluation and improvement the safety of total marrow irradiation with helical tomotherapy using repeat failure mode and effects analysis.

BACKGROUND & PURPOSE: Helical tomotherapy has been applied to total marrow irradiation (HT-TMI). Our objective was to apply failure mode and effects analysis (FMEA) two times separated by 1 year to evaluate and improve the safety of HT-TMI. MATERIALS AND METHODS: A multidisciplinary team was created. FMEA consists of 4 main steps: (1) Creation of a process map; (2) Identification of all potential failure mode (FM) in the process; (3) Evaluation of the occurrence (O), detectability (D) and severity of impact (S) of each FM according to a scoring criteria (1-10), with the subsequent calculation of the risk priority number (RPN=O*D*S) and (4) Identification of the feasible and effective quality control (QC) methods for the highest risks. A second FMEA was performed for the high-risk FMs based on the same risk analysis team in 1 year later. RESULTS: A total of 39 subprocesses and 122 FMs were derived. First time RPN ranged from 3 to 264.3. Twenty-five FMs were defined as being high-risk, with the top 5 FMs (first RPN/ second RPN): (1) treatment couch movement failure (264.3/102.8); (2) section plan dose junction error in delivery (236.7/110.4); (3) setup check by megavoltage computed tomography (MVCT) failure (216.8/94.6); (4) patient immobilization error (212.5/90.2) and (5) treatment interruption (204.8/134.2). A total of 20 staff members participated in the study. The second RPN value of the top 5 high-risk FMs were all decreased. CONCLUSION: QC interventions were implemented based on the FMEA results. HT-TMI specific treatment couch tests; the arms immobilization methods and strategy of section plan dose junction in delivery were proved to be effective in the improvement of the safety.

Application of the healthcare failure mode and effects analysis system to reduce the incidence of posture syndrome of thyroid surgery.

This study aimed to investigate the application of the healthcare failure mode and effect analysis (HFMEA) to reduce the incidence of posture syndrome of thyroid surgery (PSTS).Subjects before (n = 78, July 2017-December 2017) and after (n = 114, January 2018-June 2018) HFMEA implementation (The Second Hospital of Nanjing, Nanjing University of Chinese Medicine) were selected. The training for PSTS was optimized using HFMEA.The occurrence of PSTS was reduced from 59% to 18% after HFMEA (P < .001). Symptoms of pain and nausea and vomiting were also decreased after HFMEA (all P < .001). The critical thinking ability of 34 medical personnel to evaluate the reduction of thyroid postoperative posture syndrome increased from 246 ±â€Š19 to 301 ±â€Š14 (P < .001) after HFMEA.HFMEA was used to create preoperative posture training procedures for PSTS, bedside cards for training, innovative preoperative posture training equipment, and a diversified preoperative posture training health education model.

[How to manage risk in the surgical area. A Modal Analysis of Failures and Surgical Effects]. / Cómo gestionar el riesgo en el área quirúrgica. Análisis modal de fallos y efectos quirúrgicos.

OBJECTIVE: First to identify the areas of improvement in the surgical area before and during the performance of a surgical procedure in general surgery through the application of a Modal Analysis of Failures and Effects. Second to establish preventive measures to avoid adverse events in the surgical area. METHOD: A multidisciplinary working group was created in a university hospital for risk management in the General Surgery Operating Room Unit. The Modal Analysis of Faults and Effects was used. Potential risks for the patient in the ante-surgery and within the operating room were identified. The Risk Priority Index was calculated and preventive measures were established for all of them, with special interest when the Risk Priority Index was higher than 100. Preventive measures were developed based on the detected risks as well as those responsible for them. RESULTS: We identified a greater number of risks when the patient is in the operating room than in the ante-surgery room. Those with a higher risk priority index were: anticoagulated or antiaggregated patients, urinary tract infections, osteoarticular or neuropathic problems, patients not prepared for colon surgery, errors in laterality and leaving compresses in the operative field. CONCLUSIONS: A risk map has been developed in our organization, allowing the design of strategies to improve Patient Safety in the Surgical area. Training is a key aspect to improve Patient Safety.

[Risk analysis of a complex sociotechnical system: Case of radiotherapy]. / L'analyse des risques d'un système sociotechnique complexe : le cas de la radiothérapie.

The increasing complexity of radiotherapy work situations (technological developments, dynamics of change, increased constraints, evolution of collective actions, of professions, of interfaces between people, of human-machine interfaces, etc.) and the limits of traditional FMEA method (Failure Mode and Effects Analysis) for analysing the risks incurred by radiotherapy patients generate difficulties in identifying how the work situations of a healthcare team can generate risky situations for patients. This observation has led us to develop a new method of risk analysis: the Work Complexity Sharing and Exploration Spaces (EPECT in French). The objective of this article is to better secure a care process (making practices more reliable, updating prescribed work, defining preventive and corrective measures, continuing reflections) based on an understanding of the complexity of radiotherapy work situations and a change in our way of thinking about risks.

Establishment of a Comprehensive Inpatient Suicide Prevention Network by Using Health Care Failure Mode and Effect Analysis.

Inpatient suicide is a common sentinel event. However, evidence supporting effective inpatient suicide prevention measures is currently lacking. In this project, health care failure mode and effect analysis was used in a general hospital quality improvement process to identify suicide risk and reduce inpatient suicide behavior. Interventions were designed to improve steps in the process with the highest risk of failure, resulting in significantly higher consultation rates and reduction of attempted suicide.

Evaluating inputs of failure modes and effects analysis in identifying patient safety risks.

PURPOSE: There is a growing awareness on the use of systems approaches to improve patient safety and quality. While earlier studies evaluated the validity of such approaches to identify and mitigate patient safety risks, so far only little attention has been given to their inputs, such as structured brainstorming and use of system mapping approaches (SMAs), to understand their impact in the risk identification process. To address this gap, the purpose of this paper is to evaluate the inputs of a well-known systems approach, failure modes and effects analysis (FMEA), in identifying patient safety risks in a real healthcare setting. DESIGN/METHODOLOGY/APPROACH: This study was conducted in a newly established adult attention deficit hyperactivity disorder service at Cambridge and Peterborough Foundation Trust in the UK. Three stakeholders of the chosen service together with the facilitators conducted an FMEA exercise along with a particular system diagram that was initially found as the most useful SMA by eight stakeholders of the service. FINDINGS: In this study, it was found that the formal structure of FMEA adds value to the risk identification process through comprehensive system coverage with the help of the system diagram. However, results also indicates that the structured brainstorming refrains FMEA participants from identifying and imagining new risks since they follow the process predefined in the given system diagram. ORIGINALITY/VALUE: While this study shows the potential contribution of FMEA inputs, it also suggests that healthcare organisations should not depend solely on FMEA results when identifying patient safety risks; and therefore prioritising their safety concerns.

Retrospective analysis of suspended surgeries and influencing factors during an 8-year period. / Análisis retrospectivo de las suspensiones quirúrgicas y de los factores influyentes durante 8 años.

INTRODUCTION: The main objective was the description and analysis of suspended surgeries and their causes for suspension at our hospital from the year 2010 to the present. As a secondary objective, we evaluated the effectiveness of a series of measures for improvement. METHODS: A retrospective study was conducted to analyze patients who were scheduled to undergo surgery that was finally suspended. A Failure Mode and Effects Analysis (FMEA) was carried out to analyze the causes of the suspensions and their consequences, any existing barriers and possible measures that have been implemented over time. The causes were classified as attributable to the patient, administrative causes and medical causes. RESULTS: 105,403 surgeries were scheduled, 3,867 of which were suspended (3.66%). Factors that influenced the suspensions included: surgical specialty, ASA 4 patients, elderly patients, ambulatory patients and surgeries scheduled during the winter. The most frequent medical cause was infection or fever (17.6%), while the most frequent administrative and patient causes were lack of time (26.8%) and no-show (6.3%), respectively. The avoidable causes were 64.8% versus 35.2% unavoidable causes. In the multivariate analysis, risk factors included age, shift, season and surgical service. CONCLUSIONS: Surgical cancellations have repercussions on the consumption of material and human resources. Any means to reduce their incidence should be our future priority in order improve the quality of care.

Algorithm-based reduction of inappropriate defibrillator shock: Results of the Inappropriate Shock Reduction wIth PARAD+ Rhythm DiScrimination-Implantable Cardioverter Defibrillator Study.

BACKGROUND: Inappropriate shocks (IS) continue to have a major negative impact on patients implanted with defibrillators. OBJECTIVE: The purpose of this study was to assess IS reduction with the PARAD+ discrimination algorithm in a general population implanted for primary or secondary prevention. METHODS: ISIS-ICD (Inappropriate Shock Reduction wIth PARAD+ Rhythm DiScrimination-Implantable Cardioverter Defibrillator) was a 2-year international, interventional study in patients implanted with a dual implantable cardioverter-defibrillator (ICD) or triple-chamber defibrillator (cardiac resynchronization therapy-defibrillator [CRT-D]) featuring PARAD+. IS (shocks not delivered for ventricular tachycardia or fibrillation) were independently adjudicated. The primary endpoint was percentage of IS-free patients at 24 months. Primary and worst-case analyses of annual incidence rates of patients with ≥1 IS, overall and per defibrillator type, were conducted. RESULTS: In total, 1013 patients (80.7% male; age 67.1 ± 11.4 years; 68%/30%/2% primary/secondary/other indication) were enrolled and followed for a median of 552 days (interquartile range 354; 725). Of 993 analyzed patients programmed with PARAD+, 14 had ≥1 IS, corresponding to a percentage free from IS of 98.1% (95% confidence interval [CI] 96.8%- 98.9%). Annual incidence rates (per 100 person-years) of patients with IS were 1.0 (95% CI 0.59-1.69) and 2.1 (95% CI 1.46-3.02) in the primary and worst-case analyses, respectively. In ICD patients, rates were 1.2 (95% CI 0.68-2.23) and 2.3 (95% CI 1.47-3.53), and in CRT-D patients 0.59 (95% CI 0.19-1.83) and 1.8 (95% CI 0.93-3.44) per 100 person-years. CONCLUSION: The annual rate of defibrillator patients with IS using the enhanced PARAD+ discrimination algorithm alone ranged from 1.0 to 2.1 per 100 person-years in a general population implanted for primary or secondary prevention.

A novel risk analysis of clinical reference dosimetry based on failure modes and effects analysis.

PURPOSE: The output of a linear accelerator (linac) is one of the most important quality assurance (QA) factors in radiotherapy. However, there is no quantitative rationale for frequency and tolerance. The purpose of this study is to develop a novel risk analysis of clinical reference dosimetry based on failure modes and effects analysis (FMEA). METHODS: Clinical reference dosimetry data and the daily output data of two linacs (Clinac iX and Clinac 6EX) at Hiroshima University Hospital were analyzed. The analysis involved the number of patients per year for five types of fractionations. Risk priority number (RPN) is defined as the product of occurrence (O), severity (S), and detectability (D) in standard FMEA. In addition, we introduced "severity due to output drifting" (mean output change per day) (S') and the number of patients per year for five types of fractionations (W). We calculated the RPN = O × S × D × S' × W and quantitatively evaluated the risk for clinical reference dosimetry. RESULTS: Fewer fractions and less output calibration frequency resulted in higher RPN. Since clinical reference dosimetry data has a drift effect, which is missing in human processes, it was essential to use S' in addition to standard FMEA. Moreover, the parameter W was important in evaluating interinstitutional QA for clinical reference dosimetry. The relative risk of Clinac 6EX to Clinac iX was different approximately by twofold. CONCLUSIONS: We developed a novel index that can quantitatively evaluate risk for clinical reference dosimetry of each facility and machines in common on the basis of FMEA.

Análisis bioquímico como método eficiente para aumentar la seguridad de la nutrición parenteral en neonatos / Biochemical test as an efficient system to improve safety in parenteral nutrition for premature infants

Objetivo: Se describe el proceso de validación del control bioquímico de las bolsas de nutrición parenteral para verificar la correcta composición de ingredientes críticos antes de la administración, así como su impacto en la seguridad tras dos años desde la implantación en una población de recién nacidos prematuros. Método: Para la validación de la técnica se usaron 35 muestras de nutrición parenteral sin lípidos, que se procesaron en el laboratorio de Urgencias, siguiendo los procedimientos rutinarios utilizados para medir las concentraciones de glucosa y electrolitos en plasma y orina. Para analizar su impacto en la seguridad se realizaron análisis pre y post implantación mediante análisis modal de falla, efectos y criticidad. También se evaluaron los resultados fuera de rango y sus potenciales repercusiones en la seguridad del paciente. Resultados: El análisis de regresión no muestra error sistemático de medida para glucosa, calcio y potasio; en cambio, para el sodio y el magnesio sí existe un error sistemático, por lo que ambos fueron descartados para los análisis rutinarios. Los resultados del análisis modal de fallos y efectos, atribuibles a la implantación del control bioquímico, mostraron una disminución del riesgo del proceso del 11%. Se analizaron 1.734 nutriciones, correspondientes a 218 neonatos prematuros; se encontraron 58 (3,3%) resultados fuera del rango de aceptación, de los cuales 7 se consideraron errores de preparación potencialmente peligrosos. Conclusiones: El control bioquímico de glucosa y electrolitos es un método eficiente y reproducible que evita que posibles errores de preparación afecten al paciente

Objective: The biochemical test validation process of parenteral nutrition bags is described to verify the correct composition of critical compounds before its administration, as well as its impact on safety after two years since its implantation in a population of premature infants. Method: For the validation of the technique, 35 samples of parenteral nutrition without lipids were processed by the emergency laboratory, following the routine procedures used to measure the concentrations of glucose and electrolytes in plasma and urine. To analyze its impact on safety, pre-implantation and post-implantation risk analysis was carried out using failure mode, effects and criticality analysis (FMECA). Likewise, all out-of-range results and their potential repercussions on patient safety were evaluated. Results: Regression analysis showed no systematic measurement error for glucose, calcium and potassium; however, there is a constant systematic error for sodium and magnesium, thus both were discarded for routine analysis. Failure mode, effects and criticality analysis results showed a decrease in the risk of the process of 11% for the biochemical test. We tested 1,734 parenteral nutritions from 218 premature neonates; 58 (3.3%) results were out of the acceptance range, and 7 were considered to be potentially dangerous compounding errors. Conclusions: The biochemical test of glucose and electrolytes is an efficient and reproducible method that prevents possible compounding errors from reaching the patient