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

Forecasting emergent risks in advanced AI systems: an analysis of a future road transport management system

Artificial Intelligence (AI) is being increasingly implemented within road transport systems worldwide. Next generation of AI, Artificial General Intelligence (AGI) is imminent, and is anticipated to be more powerful than current AI. AGI systems will have a broad range of abilities and be able to perform multiple cognitive tasks akin to humans that will likely produce many expected benefits, but also potential risks. This study applied the EAST Broken Links approach to forecast the functioning of an AGI system tasked with managing a road transport system and identify potential risks. In total, 363 risks were identified that could have adverse impacts on the stated goals of safety, efficiency, environmental sustainability, and economic performance of the road system. Further, risks beyond the stated goals were identified; removal from human control, mismanaging public relations, and self-preservation. A diverse set of systemic controls will be required when designing, implementing, and operating future advanced technologies.Practitioner summary: This study demonstrated the utility of HFE methods for formally considering risks associated with the design, implementation, and operation of future technologies. This study has implications for AGI research, design, and development to ensure safe and ethical AGI implementation.

Contribution of an anticancer drug compounding robot in reducing the risks of manual preparation in a hospital pharmacy unit specialized in oncology

INTRODUCTION

In the last few years, pharmaceutical technology has evolved. In the field of oncology pharmacy, robots for the preparation of anti-cancer drugs have appeared to progressively replace manual preparation. The objective of this study is to evaluate the contribution of the robot in reducing the risk of manual preparation.

METHODS

The study was conducted at the pharmacy of the National Institute of Oncology in Rabat (May-August 2021). The method used to compare the two types of preparation is the method of analysis of failure modes, their effects and their criticality (FMECA). It will calculate the criticality index (CI = severity × frequency × detectability). The risks have been categorized into human, technical, and environmental risks.

RESULTS

The anticancer drugs reconstitution step was the most critical in manual preparation (CI = 126.7) and robotic preparation (CI = 40.7). The robot has made it possible to reduce several CIs of manual preparation including: musculoskeletal disorders of pharmacy operators -93 (89%), error in cancer drug and diluent selection -72 (60%), as well as lack of traceability -145 (97%).

CONCLUSION

The preparation robot has made it possible to reduce many of the risks of manual preparation, and constitutes an important advance in the field of oncology pharmacy.

An operational maintenance approach for improving physiological monitor by HFMEA process: an empirical case study

This study explored the application of healthcare failure mode and effect analysis (HFMEA) to identify and evaluate risk-associated factors in the intensive care unit (ICU) through a clinical-based expert knowledge (decision) for the physiological monitor operational maintenance process.

METHODS AND INTERVENTION

A mixed qualitative and quantitative proactive approach to explore the HFMEA process by analyzing 20 units of physiological monitors in the ICU. An HFMEA expert team of six people was formed to perform a risk-based analysis and evaluate the potential hazard index, mitigating the hazard scores and risks.

RESULTS

From the main processes and possible failure reasons, one high-risk hazard index greater than or equal to 8 of the standard score was found. This standard score indicates the signed manufacturer's contract for maintenance was the hazard index failure mode on the parts not regularly replaced according to the contract. This systematic hazard index failure mode shows the highest hazard scores in the possible failure reason category, established as a standard maintenance procedure. In addition, the HFMEA expert analysis of the 20 units of physiological monitors within 6 months of the original and remanufactured part maintenance results in operational availability from 90.9% for self-repair to 99.2% for contract manufacturer repair.

CONCLUSIONS

This study concludes a systematic reference in malpractices caused by maintenance negligence. The HFMEA expert team agrees that hazard failure scores greater than or equal to 8 are vital assessments and evaluations for decision-making, especially in maintaining healthcare intensive unit care physiological monitors.

Evaluating Patient Identification Practices During Intrahospital Transfers: A Human Factors Approach

INTRODUCTION

Reliable patient identification is essential for safe care, and failures may cause patient harm. Identification can be interfered with by system factors, including working conditions, technology, organizational barriers, and inadequate communications protocols. The study aims to explore systems factors contributing to patient identification errors during intrahospital transfers.

METHODS

We conducted a qualitative study through direct observation and interviews with porters during intrahospital patient transfers. Data were analyzed using the Systems Engineering Initiative for Patient Safety human factors model. The patient transfer process was mapped and compared with the institutional Positive Patient Identification policy. Potential system failures were identified using a Failure Modes and Effects Analysis.

RESULTS

A total of 60 patient transfer handovers were observed. In none of the evaluable cases observed, patient identification was conducted correctly according to the hospital policy at every step of the process. The principal system factor responsible was organizational failure, followed by technology and team culture issues. The Failure Modes and Effects Analysis methodology revealed that miscommunication between staff and lack of key patient information put patient safety at risk.

CONCLUSIONS

Patient identification during intrahospital patient transfer is a high-risk event because several factors and many people interact. In this study, the disconnect between the policy and the reality of the workplace left staff and patients vulnerable to the consequences of misidentification. Where a policy is known to be substantially different from work as done, urgent revision is required to eliminate the serious risks associated with the unguided evolution of working practice.

Tenerife Accident Analysis: a comparison of Fault Tree Analysis, Failure Mode and Effects Analysis and Causal Analysis based on System Theory

Air transport is considered to be the safest means of transport. However, if an accident occurs, it often ends in catastrophe. Thus, significant efforts have been paid to sustain successful operations in aviation. Several studies have been carried out to understand the underlying reasons for accidents. This study used Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA) and Causal Analysis based on Systems Theory (CAST) methods to analyse Tenerife aircraft accident and to compare the findings of different methods. The findings showed that while all three methods provided some overlapping findings, the CAST method led to the identification of all causes that were identified by other methods. Considering the nature of the causal factors, FMEA provided more causal factors that are related to organisation and technology than FTA. This study indicates that CAST has a significant value to identify all causes that can be identified by the use of traditional methods.

Teaching Medical Students Health Care Failure Mode and Effect Analysis: A Case Study of Inpatient Pain Management Computerized Decision Support

There is a pressing need to provide health professional leaners experiential learning opportunities in health systems science and quality improvement. Moreover, there are several published tools to diagnose and treat health system vulnerabilities and hazards. The Health Care Failure Mode and Effect AnalysisTM (HFMEA) is a systems-engineering tool that the military and aerospace industries developed to proactively identify potential errors. While this technique has been used in a range of healthcare settings, there are few reports where health professional educators have used it with learners to teach quality improvement and systems engineering methods. We describe herewith an application of HFMEA in a medical informatics professional student rotation. In this manuscript, we briefly review HFMEA theory and methods, illustrate its application to address a quality improvement initiative, and reflect upon its value - and limitations - when used in an educational context.

Impact of failure mode and effects analysis-based emergency management on the effectiveness of craniocerebral injury treatment

BACKGROUND

Craniocerebral injuries encompass brain injuries, skull fractures, cranial soft tissue injuries, and similar injuries. Recently, the incidence of craniocerebral injuries has increased dramatically due to the increased numbers of traffic accidents and aerial work injuries, threatening the physical and mental health of patients.

AIM

To investigate the impact of failure modes and effects analysis (FMEA)-based emergency management on craniocerebral injury treatment effectiveness.

METHODS

Eighty-four patients with craniocerebral injuries, treated at our hospital from November 2019 to March 2021, were selected and assigned, using the random number table method, to study (n = 42) and control (n = 42) groups. Patients in the control group received conventional management while those in the study group received FMEA theory-based emergency management, based on the control group. Pre- and post-interventions, details regarding the emergency situation; levels of inflammatory stress indicators [Interleukin-6 (IL-6), C-reactive protein (CRP), and procalcitonin (PCT)]; incidence of complications; prognoses; and satisfaction regarding patient care were evaluated for both groups.

RESULTS

For the study group, the assessed parameters [pre-hospital emergency response time (9.13 ± 2.37 min), time to receive a consultation (2.39 ± 0.44 min), time needed to report imaging findings (1.15 ± 4.44 min), and test reporting time (32.19 ± 6.23 min)] were shorter than those for the control group (12.78 ± 4.06 min, 3.58 ± 0.71 min, 33.49 ± 5.51 min, 50.41 ± 11.45 min, respectively; P < 0.05). Pre-intervention serum levels of IL-6 (78.71 ± 27.59 pg/mL), CRP (19.80 ± 6.77 mg/L), and PCT (3.66 ± 1.82 ng/mL) in the study group patients were not significantly different from those in the control group patients (81.31 ± 32.11 pg/mL, 21.29 ± 8.02 mg/L, and 3.95 ± 2.11 ng/mL respectively; P > 0.05); post-intervention serum indicator levels were lower in both groups than pre-intervention levels. Further, serum levels of IL-6 (17.35 ± 5.33 pg/mL), CRP (2.27 ± 0.56 mg/L), and PCT (0.22 ± 0.07 ng/mL) were lower in the study group than in the control group (30.15 ± 12.38 pg/mL, 3.13 ± 0.77 mg/L, 0.38 ± 0.12 ng/mL, respectively; P < 0.05). The complication rate observed in the study group (9.52%) was lower than that in the control group (26.19%, P < 0.05). The prognoses for the study group patients were better than those for the control patients (P < 0.05). Patient care satisfaction was higher in the study group (95.24%) than in the control group (78.57%, P < 0.05).

CONCLUSION

FMEA-based craniocerebral injury management effectively shortens the time spent on emergency care, reduces inflammatory stress and complication risk levels, and helps improve patient prognoses, while achieving high patient care satisfaction levels.

Morbidity, mortality, and systems safety in non-operating room anaesthesia: a narrative review

Non-operating room anaesthesia (NORA) describes anaesthesia delivered outside a traditional operating room (OR) setting. Non-operating room anaesthesia cases have increased significantly in the last 20 yr and are projected to account for half of all anaesthetics delivered in the next decade. In contrast to most other medication administration contexts, NORA is performed in high-volume fast-paced environments not optimised for anaesthesia care. These predisposing factors combined with increasing case volume, less provider experience, and higher-acuity patients increase the potential for preventable adverse events. Our narrative review examines morbidity and mortality in NORA settings compared with the OR and the systems factors impacting safety in NORA. A review of the literature from January 1, 1994 to March 5, 2021 was conducted using PubMed, CINAHL, Scopus, and ProQuest. After completing abstract screening and full-text review, 30 articles were selected for inclusion. These articles suggested higher rates of morbidity and mortality in NORA cases compared with OR cases. This included a higher proportion of death claims and complications attributable to inadequate oxygenation, and a higher likelihood that adverse events are preventable. Despite relatively few attempts to quantify safety concerns, it was possible to find a range of systems safety concerns repeated across multiple studies, including insufficient lighting, noise, cramped workspace, and restricted access to patients. Old and unfamiliar equipment, lack of team familiarity, and limited preoperative evaluation are also commonly noted challenges. Applying a systems view of safety, it is possible to suggest a range of methods to improve NORA safety and performance.

A system safety approach to assessing risks in the sepsis treatment process

In healthcare, most accidents occur as a result of inadequate interactions between system components rather than component failures. In such cases traditional risk analysis methods are of limited use for analysing system safety, so methods such as Systems Theoretic Process Analysis (STPA) and the Functional Resonance Analysis Method (FRAM) have been developed. This study uses STPA to assess risks in the sepsis treatment process, discusses the potential value STPA adds and compares the results of STPA with the results of another study that used FRAM. The findings indicate that STPA and FRAM have different strengths which reflect the different scientific approaches behind these two methods. FRAM facilitates an in-depth understanding of a system, while STPA allows for more comprehensive risk analysis by identifying more risks, scenarios and safety recommendations. Nevertheless, it is reasonable to say that not only does STPA provide more comprehensive risk analysis; its terminology and philosophy are also closer to the current safety management applications employed in complex systems.

Developing a 3D decision-making grid based on failure modes and effects analysis with a case study in the steel industry

Purpose

The aim of this study is to develop a 3D model of decision- making grid (DMG) considering failure detection rate.

Design/methodology/approach

In a comparison between DMG and failure modes and effects analysis (FMEA), severity has been assumed as time to repair and occurrence as the frequency of failure. Detection rate has been added as the third dimension of DMG. Nine months data of 21 equipment of casting unit of Mobarakeh Steel Company (MSC) has been analyzed. Then, appropriate condition monitoring (CM) techniques and maintenance tactics have been suggested. While in 2D DMG, CM is used when downtime is high and frequency is low; its application has been developed for other maintenance tactics in a 3D DMG.

Findings

Findings indicate that the results obtained from the developed DMG are different from conventional grid results, and it is more capable in suggesting maintenance tactics according to the operating conditions of equipment.

Research limitations/implications

In failure detection, the influence of CM techniques is different. In this paper, CM techniques have been suggested based on their maximum influence on failure detection.

Originality/value

In conventional DMG, failure detection rate is not included. The developed 3D DMG provides this advantage by considering a new axis of detection rate in addition to mean time to repair (MTTR) and failure frequency, and it enhances maintenance decision-making by simultaneous selection of suitable maintenance tactics and condition-monitoring techniques.

Risk Management Assessments and Recommendations Among Students, Staffs, and Health Care Workers in Educational Biomedical Laboratories

BACKGROUND

Safety in laboratories is one of the most crucial topics for all educational institutes. All-hazards need to be identified, evaluated, and controlled whenever possible, following the risk management (RM) process. This study evaluates two academic laboratories' risks and safety in the Department of Biomedical Science (BMS) at Qatar University (QU). The goal is to eliminate or reduce any risks to the students, teaching assistants, laboratory technicians, faculties, and other related workers, following an RM process.

METHODS

A cross-sectional study was performed from January to March 2020 in the BMS at QU. The study sample comprised of microbiology and hematology laboratories. Checklists and data collection sheets were used for data collection. Hazard evaluation failure mode and effects analysis (FMEA) was used. The risk priority number (RPN) was calculated for all the identified hazards. For hazard control, the hierarchy of controls was followed.

RESULTS

The number of identified hazards was thirteen (n=13) in the hematology laboratory and sixteen (n=16) in the microbiology laboratory. Chemical and ergonomic hazards had the highest percentages in both laboratories, with 25% in the microbiology laboratory and 31% in the hematology laboratory. Both laboratories were free from radiation hazards. There is a significant difference between adopted and recommended control measures in each laboratory in terms of likelihood, severity, and risk priority number (RPN).

CONCLUSION

Both chemical and ergonomic hazards account for almost a quarter of the hazards in both laboratories. The recommended control measure can decrease the severity and likelihood of identified hazards.

Evaluation of System Modelling Techniques for Waste Identification in Lean Healthcare Applications

Purpose

Waste identification plays a vital role in lean healthcare applications. While the value stream map (VSM) is among the most commonly used tools for waste identification, it may be limited to visualize the behaviour of dynamic and complex healthcare systems. To address this limitation, system modelling techniques (SMTs) can be used to provide a comprehensive picture of various system-wide wastes. However, there is a lack of evidence in the current literature about the potential contribution of SMTs for waste identification in healthcare processes.

Methods

This study evaluates the usability and utility of six types of SMTs along with the VSM. For the evaluation, interview-based questionnaires were conducted with twelve stakeholders from the outpatient clinic at the Heart and Vascular Institute at Cleveland Clinic Abu Dhabi.

Results

VSM was found to be the most useful diagram in waste identification in general. However, some SMTs that represent the system behaviour outperformed the VSM in identifying particular waste types, e.g., communication diagram in identifying over-processing waste and flow diagram in identifying transportation waste.

Conclusion

As behavioural SMTs and VSM have unique strengths in identifying particular waste types, the use of multiple diagrams is recommended for a comprehensive waste identification in lean. However, limited resources and time, as well as limited experience of stakeholders with SMTs, may still present obstacles for their potential contribution in lean healthcare applications.