Failure mode and effects analysis for proactive healthcare risk evaluation: A systematic literature review

Improving the safety of radiotherapy treatment processes via incident-driven FMEA feedback loops

BACKGROUND

Failure mode and effects analysis (FMEA) is a valuable tool for radiotherapy risk assessment, yet its outputs might be unreliable due to failures not being identified or due to a lack of accurate error rates.

PURPOSE

A novel incident reporting system (IRS) linked to an FMEA database was tested and evaluated. The study investigated whether the system was suitable for validating a previously performed analysis and whether it could provide accurate error rates to support the expert occurrence ratings of previously identified failure modes.

METHODS

Twenty-three pre-identified failure modes of our external beam radiotherapy process, covering the process steps from patient admission to treatment delivery, were proffered on dedicated FMEA feedback and incident reporting terminals generated by the IRS. The clinical setting involved a computed tomography scanner, dosimetry, and five linacs. Incoming reports were used as basis to identify additional failure modes or confirm initial ones. The Kruskal-Wallis H test was applied to compare the risk priorities of the retrospective and prospective failure modes. Wald's sequential probability ratio test was used to investigate the correctness of the experts' occurrence ratings by means of the number of incoming reports.

RESULTS

Over a 15-month period, 304 reports were submitted. There were 0.005 (confidence interval [CI], 0.0014-0.0082) reported incidents per imaging study and 0.0006 (CI, 0.0003-0.0009) reported incidents per treatment fraction. Sixteen additional failure modes could be identified, and their risk priorities did not differ from those of the initial failure modes (p = 0.954). One failure mode occurrence rating could be increased, whereas the other 22 occurrence ratings could not be disproved.

CONCLUSIONS

Our approach is suitable for validating FMEAs and deducing additional failure modes on a continual basis. Accurate error rates can only be provided if a sufficient number of reports is available.

Risk management of radioiodine treatment in differentiated thyroid cancer

INTRODUCTION

Patient safety is paramount in providing quality healthcare and constitutes a global concern for healthcare systems. Radioiodine treatment to patients with well-differentiated thyroid cancer is not without risks. The aim of this study is to identify, evaluate and mitigate the risks associated with this procedure.

MATERIALS AND METHODS

A single-centre descriptive study was conducted in which risk management was carried out by establishing a risk map using FMEA methodology.

RESULTS

Based on the process map 6 sub-processes and 23 failure modes in the three phases of the treatment process were analysed. According to risk priority number (RPN), the sub-process with the highest risk was administrative management (RPN 82), followed by treatment per se and post-treatment imaging (both with RPN 70). An overall process RPN of 300 (156 pre-treatment, 74 treatment and 70 post-treatment) was obtained. Failures directly related to the patient pose a high risk. The implementation of verification systems, performing tasks earlier and providing quality medical information are the most relevant preventive measures to be implemented.

CONCLUSIONS

The application of the FMEA methodology in the risk management for radioiodine treatment is a valuable tool for improving the quality and safety of this process. The risk map has been able to identify failures at different stages, assess their causes and effects, prioritise the risks identified and implement preventive and corrective measures that can be monitored, ensuring the effectiveness of the actions taken.

Proactive patient safety: enhancing hospital readiness through simulation-based clinical systems testing and healthcare failure mode and effect analysis

BACKGROUND

Recognizing and identifying latent safety threats (LSTs) before patient care commences is crucial, aiding leaders in ensuring hospital readiness and extending its impact beyond patient safety alone. This study evaluated the effectiveness of a combination of Simulation-based Clinical Systems Testing (SbCST) with Healthcare Failure Mode and Effect Analysis (HFMEA) with regard to mitigating LSTs within a newly constructed hospital.

METHODS

Three phases of the combined SbCST and HFMEA approach were implemented across all hospital settings. The scenarios tested system functionalities, team responses, and resource availability. The threats thus identified were categorized into system-related issues, human issues, and resource issues, after which they were prioritized and addressed using mitigation strategies. Reassessment confirmed the effectiveness of these strategies before hospital commissioning.

RESULTS

More than 76% of the LSTs were mitigated through the combined approach. System-related issues, such as nonfunctional communication devices and faulty elevators, were addressed by leadership. Human issues such as miscommunication and nonadherence to hospital policy led to improvements in interprofessional communication and teamwork. Resource issues, including missing equipment and risks of oxygen explosion, were addressed through procurement, maintenance, and staff training for equipment preparation.

CONCLUSION

The SbCST and HFMEA were highly effective with regard to proactively identifying and mitigating LSTs across all aspects of hospital preparedness. This systematic and comprehensive approach offers a valuable tool for enhancing patient safety in new healthcare facilities, thereby potentially setting a new standard for proactive hazard identification and risk management in the context of healthcare construction and commissioning.

A novel decision support system for proactive risk management in healthcare based on fuzzy inference, neural network and support vector machine

BACKGROUND

The nature of activities practiced in healthcare organizations makes risk management the most crucial issue for decision-makers, especially in developing countries. New technologies provide effective solutions to support engineers in managing risks.

PURPOSE

This study aims to develop a Decision Support System (DSS) adapted to the healthcare constraints of developing countries that enables the provision of decisions about risk tolerance classes and prioritizations of risk treatment.

METHODS

Failure Modes and Effects Analysis (FMEA) is a popular method for risk assessment and quality improvement. Fuzzy logic theory is combined with this method to provide a robust tool for risk evaluation. The fuzzy FMEA provides fuzzy Risk Priority Number (RPN) values. The artificial neural network is a powerful algorithm used in this study to classify identified risk tolerances. The risk treatment process is taken into consideration in this study by improving FMEA. A new factor is added to evaluate the feasibility of correcting the intolerable risks, named the control factor, to prioritize these risks and start with the easiest. The new factor is combined with the fuzzy RPN to obtain intolerable risk prioritization. This prioritization is classified using the support vector machine.

FINDINGS

Results prove that our DSS is effective according to these reasons: (1) The fuzzy-FMEA surmounts classical FMEA drawbacks. (2) The accuracy of the risk tolerance classification is higher than 98%. (3) The second fuzzy inference system developed (the control factor for intolerable risks with the fuzzy RPN) is useful because of the imprecise situation. (4) The accuracy of the fuzzy-priority results is 74% (mean of testing and training data).

CONCLUSIONS

Despite the advantages, our DSS also has limitations: There is a need to generalize this support to other healthcare departments rather than one case study (the sterilization unit) in order to confirm its applicability and efficiency in developing countries.

Is It Still Time for Safety Walkaround? Pilot Project Proposing a New Model and a Review of the Methodology

Background and Objectives: Healthcare facilities are complex systems due to the interaction between different factors (human, environmental, management, and technological). As complexity increases, it is known that the possibility of error increases; therefore, it becomes essential to be able to analyze the processes that occur within these contexts to prevent their occurrence, which is the task of risk management. For this purpose, in this feasibility study, we chose to evaluate the application of a new safety walkaround (SWA) model. Materials and Methods: A multidisciplinary working group made up of experts was established and then the subsequent phases of the activity were divided into three stages, namely the initial meeting, the operational phase, and the final meeting, to investigate knowledge regarding patient safety before and subsequently through visits to the department: the correct compilation of the medical record, adherence to evidence-based medicine (EBM) practices, the overall health and the degree of burnout of the various healthcare professionals, as well as the perception of empathy of staff by patients. Results: This working group chose to start this pilot project in the vascular surgery ward, demonstrating the ability of the tool used to capture the different aspects it set out to collect. In detail, the new version of SWA proposed in this work has made it possible to identify risk situations and system vulnerabilities that have allowed the introduction of corrective tools; detect adherence to existing company procedures, reschedule training on these specific topics after reviewing, and possibly update the same procedures; record the patient experience about the doctor-patient relationship and communication to hypothesize thematic courses on the subject; evaluate workers' perception of their health conditions about work, and above all reassure operators that their well-being is in the interest of the management of the healthcare company, which is maintained. Conclusions: Therefore, the outcome of the present study demonstrates the versatility and ever-present usefulness of the SWA tool.

Using Failure Mode and Effects Analysis to Decrease Risk When Developing a Home Health Nurse Residency Program

BACKGROUND

New graduate nurses are traditionally not recruited for home health care (HHC).

LOCAL PROBLEM

Due to staffing shortages, a HHC agency was interested in hiring graduate nurses, but there was concern about associated risks.

METHODS

The purpose of this quality improvement project was to develop a nurse residency program to safely transition graduate nurses to the HHC setting. After initial program design, analysis using a failure mode effects analysis (FMEA) was conducted, and risk mitigation strategies were applied.

RESULTS

The overall risk of onboarding graduate nurses in HHC was reduced by 42% after applying harm reduction tactics identified from the FMEA.

CONCLUSION

The FMEA was found to be a useful tool to prospectively identify areas of concern and apply harm reduction tactics prior to nurse residency implementation.

Identification of key potential risk areas and key potential failure modes in hemodialysis rooms by the FMEA method following routine prevention and control of the COVID-19 pandemic

Hemodialysis is an important part of nosocomial infection prevention and control (IPC). This study aimed to identify the key potential risk areas and failure modes in hemodialysis rooms in hospitals and put forward a series of improvement measures to prevent and control the spread of the coronavirus disease 2019 (COVID-19). Hemodialysis patients are highly susceptible to COVID-19 and usually have a high incidence of severe illness and mortality after infection with COVID-19. Therefore, IPC in hemodialysis patients is of crucial strategic significance. Based on 30 domain experts' interviews and careful analysis of prevention and control documents, we constructed a comprehensive failure system for a model that identifies the potential risks for nosocomial COVID-19 infection in the hemodialysis room. Subsequently, a thorough risk assessment of the potential failure factors identified in our model was conducted. The failure key factors corresponding to the human element in medical waste (garbage) disposal (C2) are verified to be the highest risk factors. They are as follows: The cleaning staff did not dispose of different types of medical waste (garbage) (C21), did not wear masks according to the regulations (C22), and lacked knowledge and norms of nosocomial IPC (C23). This study provides valuable insights for hospital decision-makers on the potential failure factors related to COVID-19 infections in hemodialysis rooms. By working with hospital infection specialists, the suggested improvement measures can help reduce the risk of virus exposure among hospital medical staff, patients, and cleaning staff.

Identification of key potential infection processes and risk factors in the computed tomography examination process by FMEA method under COVID-19

PURPOSE

To identify the key infection processes and risk factors in Computed Tomography (CT) examination process within the standard prevention and control measures for the COVID-19 epidemic, aiming to mitigate cross-infection occurrences in the hospital.

METHOD

The case hospital has assembled a team of 30 experts specialized in CT examination. Based on the CT examination process, the potential failure modes were assessed from the perspective of severity (S), occurrence probability (O), and detectability (D); they were then combined with corresponding risk prevention measures. Finally, key infection processes and risk factors were identified according to the risk priority number (RPN) and expert analysis.

RESULTS

Through the application of RPN and further analysis, four key potential infection processes were identified, including "CT request form (A1)," "during the scan of CT patient (B2)," "CT room and objects disposal (C2)," and "medical waste (garbage) disposal (C3)". In addition, eight key risk factors were also identified, including "cleaning personnel does not wear masks normatively (C32)," "nurse does not select the vein well, resulting in extravasation of the peripheral vein for enhanced CT (B25)," "patient cannot find the CT room (A13)," "patient has obtained a CT request form but does not know the procedure (A12)," "patient is too unwell to continue with the CT scan (B24)," "auxiliary staff (or technician) does not have a good grasp of the sterilization and disinfection standards (C21)," "auxiliary staff (or technician) does not sterilize the CT machine thoroughly (C22)," and "cleaning personnel lacks of knowledge of COVID-19 prevention and control (C33)".

CONCLUSION

Hospitals can publicize the precautions regarding CT examination through various channels, reducing the incidence of CT examination failure. Hospitals' cleaning services are usually outsourced, and the educational background of the staff employed in these services is generally not high. Therefore, during training and communication, it is more necessary to provide a series of scope and training programs that are aligned with their understanding level. The model developed in this study effectively identifies the key infection prevention process and critical risk factors, enhancing the safety of medical staff and patients. This has significant research implications for the potential epidemic of major infectious diseases.

Application of Failure Mode and Effects Analysis to Improve the Quality of the Front Page of Electronic Medical Records in China: Cross-Sectional Data Mapping Analysis

BACKGROUND

The completeness and accuracy of the front pages of electronic medical records (EMRs) are crucial for evaluating hospital performance and for health insurance payments to inpatients. However, the quality of the first page of EMRs in China's medical system is not satisfactory, which can be partly attributed to deficiencies in the EMR system. Failure mode and effects analysis (FMEA) is a proactive risk management tool that can be used to investigate the potential failure modes in an EMR system and analyze the possible consequences.

OBJECTIVE

The purpose of this study was to preemptively identify the potential failures of the EMR system in China and their causes and effects in order to prevent such failures from recurring. Further, we aimed to implement corresponding improvements to minimize system failure modes.

METHODS

From January 1, 2020, to May 31, 2022, 10 experts, including clinicians, engineers, administrators, and medical record coders, in Zhejiang People's Hospital conducted FMEA to improve the quality of the front page of the EMR. The completeness and accuracy of the front page and the risk priority numbers were compared before and after the implementation of specific improvement measures.

RESULTS

We identified 2 main processes and 6 subprocesses for improving the EMR system. We found that there were 13 potential failure modes, including data messaging errors, data completion errors, incomplete quality control, and coding errors. A questionnaire survey administered to random physicians and coders showed 7 major causes for these failure modes. Therefore, we established quality control rules for medical records and embedded them in the system. We also integrated the medical insurance system and the front page of the EMR on the same interface and established a set of intelligent front pages in the EMR management system. Further, we revamped the quality management systems such as communicating with physicians regularly and conducting special training seminars. The overall accuracy and integrity rate of the front page (P<.001) of the EMR increased significantly after implementation of the improvement measures, while the risk priority number decreased.

CONCLUSIONS

In this study, we were able to identify the potential failure modes in the front page of the EMR system by using the FMEA method and implement corresponding improvement measures in order to minimize recurring errors in the health care services in China.

Flight safety risk assessment of self-medication among fighter pilots: a cross-sectional study

BACKGROUND

Fighter pilots are a specific population in which any adverse drug reaction can unpredictably interact with aeronautical constraints and thus compromise flight safety. This issue has not been evaluated in risk assessments.

AIM

To provide a semi-quantitative assessment of the risk to flight safety of self-medication in fighter pilots.

METHOD

A cross-sectional survey that aimed at identifying the determinants of self-medication in fighter pilots was conducted. All medications consumed within 8 h preceding a flight were listed. A modified Failure Mode and Effects Analysis was performed, and any adverse drug reaction reported in the French marketing authorization document of a drug was considered a failure mode. The frequency of occurrence and severity were evaluated using specific scales to assign each to three risk criticality categories: acceptable, tolerable, and unacceptable.

RESULTS

Between March and November 2020, the responses of 170 fighter pilots were analyzed, for an overall return rate of approximately 34%. Among them, 78 reported 140 self-medication events within 8 h preceding a flight. Thirty-nine drug trade names (48 different international nonproprietary names) were listed, from which 694 potential adverse drug reactions were identified. The risk criticality was considered unacceptable, tolerable and acceptable for 37, 325 and 332 adverse drug reactions, respectively. Thus, the risk criticality was considered unacceptable, tolerable and acceptable for 17, 17, and 5 drugs, respectively.

CONCLUSION

This analysis suggests that the overall risk to flight safety of the current practice of self-medication in fighter pilots may be considered at least tolerable, or even unacceptable.

Application of the FMEA Method in Improving the Quality Management of Emergency Complete Blood Count Testing

OBJECTIVE

Failure mode and effects analysis (FMEA) was used to identify factors that contribute to quality management deficiencies in laboratory testing of emergency complete blood count (CBC).

METHODS

Improvements included instrument updates, personnel training, and laboratory information system optimization. We used operational data from January 2021 (control group) and January 2022 (FMEA group) to compare the risk priority number (RPN) of FMEA, emergency CBC laboratory turnaround time (TAT), error report rate, and specimen failure rate.

RESULTS

After the implementation of FMEA, the average RPN dropped from 36.24 ± 9.68 to 9.45 ± 2.25, (t = 20.89, P < .05). Additionally, the median TAT for emergency CBCs decreased from 23 min to 11 min as did the interquartile distance (17-34 min to 8-16 min) (P < .05). The rate of emergency CBC error reports decreased from 1.39% to 0.71% (P < .05), and the specimen failure rate decreased from 0.95% to 0.32% (P < .05). Patient satisfaction also increased from 43% to 74% (P < .05), and the technician-performed morphology assessment pass rate increased from 16.7% to 100% (P < .05).

CONCLUSION

Improving the emergency CBC testing process with FMEA can shorten emergency CBC laboratory TAT and reduce specimen failure rates and reporting error rates. The FMEA can be used to improve quality management in emergency CBC laboratories.

Examination of the Protein Drug Supply Chain in a Swedish University Hospital: Focus on Handling Risks and Mitigation Measures

Protein drugs, such as monoclonal antibodies, have proved successful in treating cancer and immune system diseases. The structural complexity of these molecules requires careful handling to ensure integrity and stability of the drug. In this study, a failure mode and effects analysis was performed based on a Gemba Walk method in a Swedish University Hospital. The Gemba Walk is focused on pharmacists observing the actual supply process steps from distributor, pharmacy cleanroom to patient administration. Relevant protein drugs are chosen based on sales statistics within the hospital and the corresponding wards were observed. Further is the Double Diamond design method used to identify major risks and deliver mitigation strategies. The study identified potential stress factors such as temperature, shock by impact, shaking, vibration and light exposure. There were also risks associated with porters' and healthcare professionals' lack of awareness and access to information. These risk factors may cause loss of efficacy and quality of the protein drug, potentially leading to patient safety concerns. In this study, a simulation is also performed to list measures that theoretically should be in place to ensure the quality of the protein drug, for example validated and protocol-based compounding in cleanroom, training and validated transports.

Improving the quality of hospital sterilization process using failure modes and effects analysis, fuzzy logic, and machine learning: experience in tertiary dental centre

Activities practiced in the hospital generate several types of risks. Therefore, performing the risk assessment is one of the quality improvement keys in the healthcare sector. For this reason, healthcare managers need to design and perform efficient risk assessment processes. Failure modes and effects analysis (FMEA) is one of the most used risk assessment methods. The FMEA is a proactive technique consisting of the evaluation of failure modes associated with a studied process using three factors: occurrence, non-detection, and severity, in order to obtain the risk priority number using fuzzy logic approach and machine learning algorithms, namely the support vector machine and the k-nearest neighbours. The proposed model is applied in the case of the central sterilization unit of a tertiary national reference centre of dental treatment, where its efficiency is evaluated compared to the classical approach. These comparisons are based on expert advice and machine learning performance metrics. Our developed model proved high effectiveness throughout the results of the expert's vote (she agrees with 96% fuzzy-FMEA results against 6% with classical FMEA results). Furthermore, the machine learning metrics show a high level of accuracy in both training data (best rate is 96%) and testing data (90%). This study represents the first study that aims to perform artificial intelligence approach to risk management in the Moroccan healthcare sector. The perspective of this study is to promote the application of the artificial intelligence in Moroccan health management, especially in the field of quality and safety management.

Challenges experienced during pharmacy automation and robotics implementation in JCI accredited hospital in the Arabian Gulf area: FMEA analysis-qualitative approach

Background

Pharmacy automation and robotics implementation are essential aspects of healthcare facilities. It streamlines the medication dispensing process and significantly reduces medication errors. However, implementing automation and robotics in pharmacies comes with its challenges. We aim to detect and rectify potential dangers in the pharmacy workflow by utilizing the Failure Mode and Effects Analysis (FMEA) methodology; this is expected to augment performance and increase profitability.

Materials and methods

In this study, we conducted an FMEA analysis using a qualitative approach to identify the challenges experienced during pharmacy automation and robotics implementation in a Joint Commission International (JCI) accredited hospital in the Arabian Gulf area. The pharmacy processes and procedures were mapped in a Flow chart to visualize the pharmacy workflow, including highlighting the risks that were found. Then these risks were arranged as Potential failure modes and added to the table as 9 main points for each RPNs were calculated, and then the 9 points were prioritized for the action plans.

Results

Via applying traditional Risk Priority Number (RPN) FMEA, the Pharmacy board identified the process stages marked risky failure modes through several FMEAs, calculating the total RPNs at the implementation phase. It revealed several challenges, including staff training, technical issues, and inadequate communication. Furthermore, the study resulted in corrective and intervention steps.

Conclusion

Pharmacy automation and robotics implementation is a complex process that requires proper planning, preparation, and execution. The FMEA approach effectively identifies potential problems and evaluates their impact on the pharmacy system. Nine major failure modes appeared to be risky stages with high RPN scores. Therefore, multiple interventions were done during the implementation to enhance the knowledge of challenges faced during the implementation of the automation process and solve it. Future studies should address the identified challenges and develop strategies to mitigate them.

Integrated System for the Proactive Analysis on Infection Risk at a University Health Care Establishment Servicing a Large Area in the South of Italy

OBJECTIVES

Our study proposes the use of a proactive system to manage risk combining the new Risk Identification Framework by the World Health Organization, the Lean method, and the hospital's Procedure Analysis.The system was tested for the prevention of surgical site infections in the University Hospital of Naples "Federico II" on the surgical paths, where they were usually applied individually.

METHODS

We conducted a retrospective observational study from March 18, 2019, to June 30, 2019, at the University Hospital "Federico II" of Naples, Italy (Europe).The study is structured in 3 phases: phase 1, application of each proactive risk management tool (March 18-April 15, 2019); phase 2, analysis and integration of the results, and elaboration of an overview of critical and control points (April 15-20, 2019); and phase 3, evaluation of the outcomes as variation of surgical site infection's incidence between the 3-month period of the 2019 and the same period of the 2018, when each tool was implemented separately (April 30-June 30, 2019).

RESULTS

(1) The application of the single tool has detected different criticalities; (2) the combined system allowed us to draw a risk map and identify "improving" macroareas; and (3) the infection rate, with the application of this system, was equal to 1.9%; in the same period of the previous year, it was equal to 4%.

CONCLUSIONS

Our study demonstrates that "integrated system" has been more effective to proactively identify surgical route risks compared with the application of each single instrument.

Failure mode and effect analysis applied to improve the medication management process in a pharmacy of a teaching hospital and a proposal for a simplified rating system

BACKGROUND

Healthcare is not as safe as it should be and medication error remains a significant source of preventable morbidity and mortality among patients.

OBJECTIVES

To present a failure mode and effect analysis (FMEA) of the medication management process in the pharmacy of the largest teaching hospital in Tunisia. Secondly, to examine the validity of a proposed simplified risk rating method by comparing the degree of concordance with the FMEA rating system in classifying failure modes related to the studied process.

METHODS

The FMEA method was applied to the medication management process in the pharmacy for 5 months from January 2020. For the traditional FMEA rating system, failure modes were prioritised according to the risk priority number, which considers severity, occurrence and non-detectability. Failure modes were classified for the traditional method considering three categories: accepted, requiring control and critical. The proposed rating system was based on two indices: the number of parts, which reflected severity, and the number of causes according to the 5M method (manpower, machines, material, methods and medium), which reflected occurrence. Failure modes were classified for the proposed method considering three categories: low, medium and high. Failure modes were independently analysed to determine the degree of agreement in ranking of risk between the two studied methods. Prioritised failure modes were targeted by decisions and solutions aiming to reduce risk and enhance safety.

RESULTS

Twenty-four failure modes were identified for the six-step process of medication management in a pharmacy (overall criticality=2607). The most critical failure modes were: data error in drugs reception (risk priority number (RPN)=432), break in the cold chain (RPN=320) and non-optimal pharmaceutical analysis (RPN=280). A good agreement was found between the classic FMEA and the proposed rating methods (κ=0.795). A high correlation was shown between the two scorings (r=0.785). Three failure modes were underestimated by the proposed rating method.

CONCLUSIONS

An FMEA study on the medication management process in a teaching pharmacy showed that FMEA is an effective, proactive risk assessment that enables a better understanding of the studied process. The proposed risk scoring permits a good concordance with the classic method, with the advantage of being fast. Targeting the identified risks will allow integration into a continuous process of improvement and increase patient safety.

Operating Room Performance Optimization Metrics: a Systematic Review

Literature proposes numerous initiatives for optimization of the Operating Room (OR). Despite multiple suggested strategies for the optimization of workflow on the OR, its patients and (medical) staff, no uniform description of 'optimization' has been adopted. This makes it difficult to evaluate the proposed optimization strategies. In particular, the metrics used to quantify OR performance are diverse so that assessing the impact of suggested approaches is complex or even impossible. To secure a higher implementation success rate of optimisation strategies in practice we believe OR optimisation and its quantification should be further investigated. We aim to provide an inventory of the metrics and methods used to optimise the OR by the means of a structured literature study. We observe that several aspects of OR performance are unaddressed in literature, and no studies account for possible interactions between metrics of quality and efficiency. We conclude that a systems approach is needed to align metrics across different elements of OR performance, and that the wellbeing of healthcare professionals is underrepresented in current optimisation approaches.

Quality improvement in urological care: Core methodological principles

Objectives:

The aim of this article is to summarise core quality improvement (QI) methodologies and concepts to assist urology teams in conducting well-designed improvement projects.

Materials and Methods:

We provide an introduction to the methodological foundations of QI, including the model for improvement, plan-do-study-act, lean and six sigma and present some useful QI tools such as process modelling and pareto charts with examples of how they might be applied to urological care. We also introduce the concept of measurement for QI and describe how this differs from the more traditional measurement approaches used in research.

Results:

The key to successful QI work undoubtedly lies in the careful planning and appropriate selection of the available QI tools and methods, alongside pragmatic approaches to measurement that yield enough data to spot meaningful variation in outcomes.

Conclusions:

To support these core methods, QI leadership and stakeholder engagement will be critical to embedding QI into urological care and ensuring that improvements can be sustained once QI projects come to an end.

Level of evidence:

Not applicable.

Proactive Risk Assessment through Failure Mode and Effect Analysis (FMEA) for Perioperative Management Model of Oral Anticoagulant Therapy: A Pilot Project

INTRODUCTION

Correct perioperative management of anticoagulant therapy is essential to prevent thromboembolic events and reduce the risk of bleeding. The lack of universally accepted guidelines makes perioperative anticoagulant therapy management difficult. The present study aims to identify the perioperative risks of oral anticoagulant therapy and to reduce adverse events through Failure Mode and Effect Analysis (FMEA).

MATERIALS AND METHODS

A multidisciplinary working group was set up, and four main phases of the process were identified. Each of these phases was divided into micro-activities to identify the related possible failure modes and their potential consequences. The Risk Priority Number was calculated for each failure mode.

RESULTS AND DISCUSSION

Seventeen failure modes were identified in the entire perioperative period; those with a higher priority of intervention concern the incorrect timing between therapy suspension and surgery, and the incorrect assessment of the bleeding risk related to the invasive procedure.

CONCLUSION

The FMEA method can help identify anticoagulant therapy perioperative failures and implement the management and patient safety of surgical procedures.

Administration approaches of nursing assistants in hospitals: a scoping review

OBJECTIVES

The administration of nursing assistants (NAs) is closely associated with patient outcomes, but studies evaluating intrahospital administration of NAs are limited. This study aimed to identify existing literature on intrahospital NAs' administration approaches.

DESIGN

Scoping review.

DATA SOURCES

PubMed, Embase, CINAHL, Scopus, ProQuest, CNKI, APA PsycInfo, Wanfang Med, SinoMed, Ovid Emcare, NICE, AHRQ, CADTH, JBI EBP and Cochrane DSR were searched for articles published between January 2011 and March 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Qualitative, quantitative or mixed-method studies and evidence syntheses that evaluate administration approaches, models and appraisal tools of intrahospital NAs were included.

DATA EXTRACTION AND SYNTHESIS

Two independent reviewers conducted search, data selection and data extraction according to Joanna Briggs Institute guidance and methodology for scoping review. The quality of included studies was assessed using Mixed Methods Appraisal Tool or AMSTAR V.2. Data were synthesised using narrative methods and frequency effect size analysis.

RESULTS

Thirty-six studies were eligible, with acceptable quality. We identified 1 administration model, 9 administration methods, 15 educational programmes and 7 appraisal tools from the included studies. The frequency effect size analysis yielded 15 topics of the main focus at four levels, suggesting that included articles were mainly (33%) focused on the competency of NAs, and the lectures were the most (80%) used strategy in quality improvement projects. Evidence from the studies was of low-to-moderate quality, indicating huge gaps between evidence-based research and management practice.

CONCLUSIONS

Practical intrahospital administration approaches were revealed, and fifteen primarily focused topics were identified. We should explore this area more thoroughly using structured frameworks and standardised methodology. This scoping review will help managers find more effective ways to improve the quality of care. Researchers may focus more on evidence-based practice in NA administration using the 15 topics as a breakthrough.

Use of Failure Mode and Effects Analysis (FMEA) for Risk Analysis of Drug Use in Patients with Lung Cancer

It is crucial to investigate the risk factors inherent in the medication process for cancer patients since improper antineoplastic drug use frequently has serious consequences. As a result, the Severity, Occurrence, and Detection rate of each potential failure mode in the drug administration process for patients with lung cancer were scored using the Failure Mode and Effect Analysis (FMEA) model in this study. Then, the risk level of each failure mode and the direction of improvement were investigated using the Slacks-based measure data envelopment analysis (SBM-DEA) model. According to the findings, the medicine administration process for lung cancer patients could be classified into five links, with a total of 60 failure modes. The risk of failure modes for patient medication and post-medication monitoring ranked highly, with unauthorized use of traditional Chinese medicine and folk prescription and unauthorized drug addition (incorrect self-medication) ranking first (1/60); doctor prescription was also prone to errors. The study advises actively looking at ways to decrease the occurrence and difficulty of failure mode detection to continually enhance patient safety when using medications.

A Clinical Risk Assessment of a 3D-Printed Patient-Specific Scaffold by Failure Modes and Effects Analysis

This study aims to carry out a risk assessment to identify and rectify potential clinical risks of a 3D-printed patient-specific scaffold for large-volume alveolar bone regeneration. A survey was used to assess clinicians' perceptions regarding the use of scaffolds in the treatment of alveolar defects and conduct a clinical risk assessment of the developed scaffold using the Failure Modes and Effects Analysis (FMEA) framework. The response rate was 69.4% with a total of 41 responses received. Two particular failure modes were identified as a high priority through the clinical risk assessment conducted. The highest mean Risk Priority Number was obtained by "failure of healing due to patient risk factors" (45.7 ± 27.7), followed by "insufficient soft tissue area" (37.8 ± 24.1). Despite the rapid developments, finding a scaffold that is both biodegradable and tailored to the patient's specific defect in cases of large-volume bone regeneration is still challenging for clinicians. Our results indicate a positive perception of clinicians towards this novel scaffold. The FMEA clinical risk assessment has revealed two failure modes that should be prioritized for risk mitigation (safe clinical translation). These findings are important for the safe transition to in-human trials and subsequent clinical use.

Failure Mode and Effects Analysis (FMEA) at the preanalytical phase for POCT blood gas analysis: proposal for a shared proactive risk analysis model

OBJECTIVES

Proposal of a risk analysis model to diminish negative impact on patient care by preanalytical errors in blood gas analysis (BGA).

METHODS

Here we designed a Failure Mode and Effects Analysis (FMEA) risk assessment template for BGA, based on literature references and expertise of an international team of laboratory and clinical health care professionals.

RESULTS

The FMEA identifies pre-analytical process steps, errors that may occur whilst performing BGA (potential failure mode), possible consequences (potential failure effect) and preventive/corrective actions (current controls). Probability of failure occurrence (OCC), severity of failure (SEV) and probability of failure detection (DET) are scored per potential failure mode. OCC and DET depend on test setting and patient population e.g., they differ in primary community health centres as compared to secondary community hospitals and third line university or specialized hospitals. OCC and DET also differ between stand-alone and networked instruments, manual and automated patient identification, and whether results are automatically transmitted to the patient's electronic health record. The risk priority number (RPN = SEV × OCC × DET) can be applied to determine the sequence in which risks are addressed. RPN can be recalculated after implementing changes to decrease OCC and/or increase DET. Key performance indicators are also proposed to evaluate changes.

CONCLUSIONS

This FMEA model will help health care professionals manage and minimize the risk of preanalytical errors in BGA.

Implementation of the failure modes and effects analysis in a Hospital Radiopharmacy Unit

AIM

The aim of this study is the implementation in a Hospital Radiopharmacy Unit of a risk analysis methodology in order to proactively identify possible failure modes and prioritize corrective measures.

MATERIALS AND METHODS

By means of the failure modes and effects analysis (FMEA), the possible failure modes of each of the stages of the processes of prescription, preparation, and administration of radiopharmaceuticals for diagnostic and therapy were identified. From the variables of severity, probability and detectability, the risk was quantified using the Risk Priority Number (RPN) for each failure mode, sub-process, and type of radiopharmaceutical. Improvement measures were established and the reduction in the RPN value was calculated.

RESULTS

A total of 96 failure modes were identified (58 for diagnostic radiopharmaceuticals and 38 for therapy). Biunivocal identification of the patient with the radiopharmaceutical is the failure mode with the highest RPN (60) and the radiolabeling cell sub-process the one that has the highest risk (RPN 286). As a result of the improvement measures, the overall RPN was reduced by 22% for diagnostic radiopharmaceuticals and 20% for therapy. This reduction would be 46% and 31% respectively if radiopharmacy software and a barcode technology in the administration were implemented.

CONCLUSIONS

The application of the FMEA methodology as a risk analysis tool allows to identify the critical points of the processes related to radiopharmaceuticals and prioritize measures to reduce the risk.

Risk management of smart healthcare systems: Delimitation, state-of-arts, process, and perspectives

Sensing, communication, computation, and control technologies are facilitating smart healthcare to improve efficiency and effectiveness of medical treatment and care. This study focuses on the risk issues relevant with the adverse events where novel technical systems do not serve as expected. We discuss the unique challenges, define the scope of risk management in healthcare and review the state-of-art research on diverse topics under the framework widely used in risk management. Then, we present a systematic approach to identify the hazards to patients and other asset of interest in the perception, cyber communication, and execution of smart technologies and their operational contexts. We also investigate different methods for scenario, likelihood, and consequence analyses for specifying the risks of adverse events, and categorize the approaches of risk reduction, as the main strategy of treating risks of smart healthcare systems, into four groups of design, operation, organization, and legislation. At the last, the article proposes some research perspectives responding to the developing trend of smart healthcare.

Application of Integrated Emergency Care Model Based on Failure Modes and Effects Analysis in Patients With Ischemic Stroke

Purpose

To explore the application value of an integrated emergency care model based on failure modes and effects analysis (FMEA) in patients with acute ischemic stroke (AIS).

Methods

According to the convenience sampling method, 100 patients with AIS who visited the emergency department in our hospital from October 2018 to March 2019 were randomly selected as the control group and received routine emergency care mode intervention. Another 100 AIS patients who visited the emergency department from April to October 2019 were selected as the intervention group and received the integrated emergency care model based on FMEA. The total time spent from admission to completion of each emergency procedure [total time spent from admission to emergency physician reception (T₀₋₁), total time spent from admission to stroke team reception (T₀₋₂), total time spent from admission to imaging report out (T₀₋₃), total time spent from admission to laboratory report out (T₀₋₄), and total time spent from admission to intravenous thrombolysis (T₀₋₅)] was recorded for both groups. The clinical outcome indicators (vascular recanalization rate, symptomatic intracerebral hemorrhage incidence, mortality rate) were observed for both groups. The National Institutes of Health Stroke Scale (NIHSS) score and Barthel score were evaluated for both groups after the intervention. The treatment satisfaction rate of the patients was investigated for both groups.

Results

The total time of T₀₋₁, T₀₋₂, T₀₋₃, T₀₋₄, T₀₋₅ in the intervention group (0.55 ± 0.15, 1.23 ± 0.30, 21.24 ± 3.01, 33.30 ± 5.28, 44.19 ± 7.02) min was shorter than that of the control group (1.22 ± 0.28, 4.01 ± 1.06, 34.12 ± 4.44, 72.48 ± 8.27, 80.31 ± 9.22) min (P < 0.05). The vascular recanalization rate in the intervention group (23.00%) was higher than that in the control group (12.00%) (P < 0.05). There was no statistical significance in the symptomatic intracerebral hemorrhage incidence and mortality rate in the two groups (P > 0.05). After intervention, the NIHSS score of the intervention group (2.95 ± 0.91) was lower than that of the control group (6.10 ± 2.02), and the Barthel score (77.58 ± 7.33) was higher than that of the control group (53.34 ± 5.12) (P < 0.05). The treatment satisfaction rate in the intervention group (95.00%) was higher than that of the control group (86.00%) (P < 0.05).

Conclusion

Through FMEA, the failure mode that affects the emergency time of AIS patients is effectively analyzed and the targeted optimization process is proposed, which are important to enhance the efficiency and success rate of resuscitation of medical and nursing staff and improve the prognosis and life ability of patients.

Adverse Events and Risk Management in Residential Aged Care Facilities: A Cross-Sectional Study in Hunan, China

Purpose

Adverse events threaten residents’ safety. Risk management is important to provide proper care and maintain quality in residential aged care facilities (RACFs). However, there is little data on adverse events, risk management, and risk early warning in RACFs in the Chinese mainland. This study aimed to fill this gap by investigating the prevalence of the aforementioned aspects and related factors in China.

Participants and Methods

Using a cross-sectional design, a field survey of 272 RACFs in Hunan Province was conducted from January 25 to June 1, 2020. Data were collected using four main tools on prevalence of nursing adverse events, risk management, risk early warning, and general information. Descriptive statistics were described by frequency (percentage) and median (interquartile range). Mann–Whitney U-test and Kruskal–Wallis H-test, and Spearman coefficient were used for statistical analysis.

Results

RACFs experienced an average of five (15) adverse events in 2019, with falls and pressure ulcers being the most common. The total average score of risk management in RACFs was 4.72 (0.98) out of 5, with the environment and personnel management dimensions scoring the highest with 4.75 (1) and the service management dimension scoring the lowest with 4.60 (1). Only 72.79% had trained their staff on ethical and legal knowledge and 84.56% had utilized pre-hospital first aid. Further, 30% to 40% were unprepared for contingency plans of suicide, electric shock, gas poisoning, and drowning. There were significant risk management differences among the following variables: facilities’ locations, accreditation with the Practice Certificate of Social Welfare Facilities, bed-size, nursing hours per resident day, requirement for nursing staff with certificates, and payment for nursing staff (p < 0.05).

Conclusion

RACFs are facing safety challenges with a high prevalence of nursing adverse events. These facilities need to improve risk early warning and management to ensure residents’ safety.

Blood Product Supply for a Helicopter Emergency Medical Service

Background

Long patient transport times to trauma centers are a well-known problem in sparsely populated regions with a low hospital density. Transfusion of red blood cell concentrates (RBC) and plasma improves outcome of trauma patients with severe bleeding. Helicopter emergency services (HEMS) are frequently employed to provide early advanced medical care and to reduce time to hospital admission. Supplying HEMS with blood products allows prehospital transfusion and may help to prevent exsanguination or prolonged hemorrhagic shock. We have investigated the maintenance of blood product quality under air transport conditions and the logistical steps to introduce a HEMS blood depot into routine practice.

Methods

A risk analysis was performed and a validation plan developed. A special, commercially available transport container for blood products was identified. Maintenance of temperature conditions between 2 and 6°C in the box were monitored at ambient temperatures up to 35°C over 48 h. Quality of blood products before and after helicopter air transport were evaluated including (1) for RBCs: hemoglobin, hematocrit, hemolysis rate; (2) for thawed plasma: aPTT, INR, single clotting factor activities. The logistics for blood supply of the regional HEMS were developed by the transfusion service of the Greifswald University Hospital in collaboration with the in-hospital transport team, the HEMS team, and the HEMS operator.

Results

The transport container maintained a temperature below 6°C up to 36 h at 35°C ambient temperature. Vibration during helicopter operation did not impair quality of RBC and thawed plasma. To provide blood products for HEMS at least two transport containers and an additional set of cooling tiles is needed as the cooling tiles need a special temperature priming over 20 h. The two boxes were used at alternate days. To reduce wastage, RBCs and thawed plasmas were exchanged every fourth day and reintegrated into the blood bank inventory for further in-hospital use.

Conclusions

Supplying HEMS with RBCs and plasma is feasible. Helicopter transport has no negative impact on blood product quality. The logistic challenges require close collaboration between the HEMS team and the blood transfusion service.

Using failure mode and Effects Analysis to increase patient safety in cancer chemotherapy

BACKGROUND

Medication errors may occur during chemotherapy and can have fatal consequences. Healthcare Failure Mode and Effects Analysis (FMEA) is a method used to detect potential risks and prevent them.

OBJECTIVE

Aim of this study was to evaluate the medication process of intravenous tumor therapy in order to guarantee a high standard of patient safety.

METHODS

The main part of the study was performed at the University Hospital of Bonn, Germany. After assembling a multidisciplinary team, the individual steps of prescription, compounding, transport, and administration of chemotherapy were mapped in a flow diagram. The possible failures were identified and analyzed by calculating the risk priority numbers (RPNs). Finally, corrective actions were developed and after hypothetical implementation re-analyzed to measure their effects on the process. Subsequently, a shortened FMEA based on the catalogue failure modes developed in Bonn was carried out at the University Hospital of Cologne in order to evaluate its transferability to another hospital.

RESULTS

A total of 52 potential failure modes was identified in Bonn. Relating to the RPNs the most critically steps in the process were associated with the prescription, namely, incorrect information about individual parameters of the patient; non-standardized chemotherapy protocols; and problems related to supportive therapy. A significant risk reduction for most of the failure modes was assessed by implementing suitable corrective actions. The shortened FMEA in Cologne led to a different ranking of failure modes.

CONCLUSION

The implementation of this analysis has not only identified various safety gaps, but also shows how patient safety during chemotherapy can be enhanced. Moreover, it has sensitized the practitioners to failure modes potentially occurring in their work routine.

Using a Patient Safety Analysis to Guide Infusion Therapy for Patients With COVID-19

In the United States, during the Coronavirus Disease 2019 (COVID-19) pandemic, patients with COVID-19 overwhelmed available intensive care beds, staffing levels were unpredictable, and personal protective equipment was limited. The safety of situating electronic infusion pumps outside patient rooms was evaluated using an internal risk assessment. Based on a low level of risk, a procedure was developed to direct clinicians as to when this process is appropriate during a national crisis. A standardized analysis, Healthcare Failure Mode and Effects Analysis, was conducted to identify all potential risks and implement actions that would eliminate or control the risk. No adverse events were reported. Safe systems and preparation can protect patients.

Failure modes and effects analysis to improve transitions of care in patients discharged on outpatient parenteral antimicrobial therapy

PURPOSE

To identify barriers to safe and effective completion of outpatient parenteral antimicrobial therapy (OPAT) in patients discharged from an academic medical center and to develop targeted solutions to potentially resolve or improve the identified barriers.

SUMMARY

A failure modes and effects analysis (FMEA) was conducted by a multidisciplinary OPAT task force to evaluate the processes for patients discharged on OPAT to 2 postdischarge dispositions: (1) home and (2) skilled nursing facility (SNF). The task force created 2 process maps and identified potential failure modes, or barriers, to the successful completion of each step. Thirteen and 10 barriers were identified in the home and SNF process maps, respectively. Task force members created 5 subgroups, each developing solutions for a group of related barriers. The 5 areas of focus included (1) the OPAT electronic order set, (2) critical tasks to be performed before patient discharge, (3) patient education, (4) patient follow-up and laboratory monitoring, and (5) SNF communication. Interventions involved working with information technology to update the electronic order set, bridging communication and ensuring completion of critical tasks by creating an inpatient electronic discharge checklist, developing patient education resources, planning a central OPAT outpatient database within the electronic medical record, and creating a pharmacist on-call pager for SNFs.

CONCLUSION

The FMEA approach was helpful in identifying perceived barriers to successful transitions of care in patients discharged on OPAT and in developing targeted interventions. Healthcare organizations may reproduce this strategy when completing quality improvement planning for this high-risk process.

Ferramentas para a organização do processo de trabalho na segurança do paciente

RESUMO Objetivo discutir acerca da utilização das ferramentas de Análise de Modo e Efeitos de Falha e sua aplicação na assistência à saúde. Método trata-se de um artigo de reflexão visando à apresentação do formato próprio de aplicação de ambas as ferramentas seguida das suas diferenças de execução nos processos de trabalho. Resultados ambos os modelos possuem a mesma finalidade, sendo direcionados para a detecção de falhas antes mesmo da sua manifestação, auxiliando diretamente na promoção da segurança. A análise do erro, com a participação das equipes e a geração de índices de falhas, repercute no planejamento e na implementação de ações práticas voltadas à segurança do paciente. Conclusão e implicações para a prática embora semelhantes, existem, entre eles, distinções quanto à priorização das falhas para elencar ações práticas corretivas, principalmente no cálculo do Índice de Prioridade de Risco relacionado à gravidade, na probabilidade de ocorrência e na detecção das falhas. Ambas as ferramentas se mostram como importantes aliadas dos gestores de saúde para a detecção de falhas graves que colocam em risco a assistência livre de eventos adversos.