Systematic Human Error Reduction Research Articles

Human error identification and risk assessment in loading and unloading of petroleum products by road trucks using the SHERPA and fuzzy inference system method

Human error constitutes one of the primary causes of accidents, particularly in the context of loading and unloading operations involving road trucks, especially those carrying petroleum products. The process of identifying and evaluating human errors within these operations involves several key steps. Initially, all sub-tasks associated with loading and unloading are meticulously identified and analyzed utilizing Hierarchical Task Analysis (HTA), achieved through direct observation, document examination, and interviews. Subsequently, potential human error modes within each task are delineated using the Systematic Human Error Reduction and Prediction Approach (SHERPA). Finally, essential data for determining the criticality, probability, and severity of each error are gathered through expert elicitation and the application of Fuzzy Inference Systems (FIS).Through the analysis of SHERPA worksheets, a total of 37 errors during loading operations and 14 errors during unloading operations of petroleum products were identified. Among these errors, the predominant category during loading operations was action errors, comprising 31 instances, while communication errors were the least frequent, occurring only twice. Similarly, action errors were most prevalent during unloading operations, constituting 13 instances. These errors were further categorized and ranked based on their risk levels, resulting in 27 levels for loading operations and 12 levels for unloading operations.The consistent occurrence of action errors underscores the need for implementing control measures to mitigate their frequency and severity. Such strategies may include periodic training sessions to reinforce proper work procedures and the development of monitoring checklists, among other interventions.

Potential errors during final inspection and certification process of an aircraft component

PurposeAccording to regulations, aircraft must be in an airworthy condition before they can be operated. To ensure airworthiness, they must be maintained by an approved component maintenance organisation. This study is aimed to identify potential errors that may arise during the final inspection and certification process of aircraft components, categorise them, determine their consequences and quantify the associated risks. Any removed aircraft components must be sent to an approved aircraft component maintenance organisation for further maintenance and issuance of European Union Aviation Safety Agency (EASA) Form 1. Thereafter, a final inspection and certification process must be conducted by certifying staff to receive an EASA Form 1. This process is crucial because any errors during this stage can result in the installation of unsafe components in an aircraft.Design/methodology/approachThe Systematic Human Error Reduction and Prediction Approach (SHERPA) method was used to identify potential errors. This method involved a review of the procedures of three maintenance organisations, individual interviews with ten subject matter experts and a consensus group of 14 certifying staff from different maintenance organisations to achieve the desired results.FindingsIn this study, 39 potential errors were identified during the final inspection and certification process. Furthermore, analysis revealed that 48.7% of these issues were attributed to checking errors, making it the most common type of error observed.Originality/valueThis study pinpoints the potential errors in the final inspection and certification of aircraft components. It offers maintenance organisations a roadmap to assess procedures, implement preventive measures and reduce the likelihood of these errors.

The application of human reliability analysis to carpal tunnel decompression.

Many surgical procedures are prone to human error, particularly in the learning phase of skills acquisition. Task standardisation has been suggested as an approach to reducing errors, but it fails to account for the human factors associated with learning. Human reliability analysis (HRA) is a structured approach to assess human error during surgery. This study used HRA methodologies to examine skills acquisition associated with carpal tunnel decompression. The individual steps or subtasks required to complete a carpal tunnel decompression were identified using hierarchical task analysis (HTA). The systematic human error reduction and prediction approach (SHERPA) was carried out by consensus of subject matter experts. This identified the potential human errors at each subgoal, the level of risk associated with each task and how these potential errors could be prevented. Carpal tunnel decompression was broken down into 46 subtasks, of which 21 (45%) were medium risk and 25 (55%) were low risk. Of the 46 subtasks, 4 (9%) were assigned high probability and 18 (39%) were assigned medium probability. High probability errors (>1/50 cases) included selecting incorrect tourniquet size, failure to infiltrate local anaesthetic in a proximal-to-distal direction and completion of the World Health Organization (WHO) surgical sign-out. Three (6%) of the subtasks were assigned high criticality, which included failure to aspirate before anaesthetic injection, whereas 21 (45%) were assigned medium criticality. Remedial strategies for each potential error were devised. The use of HRA techniques provides surgeons with a platform to identify critical steps that are prone to error. This approach may improve surgical training and enhance patient safety.

How do medication errors occur in the nursing communication process? Investigating the relationship between error types and error factors.

Human error types and error factors are two important elements of error analysis. Understanding the relationship between them can contribute to new case analyses, the tendency of error occurrence statistics, error factor identification, and prevention of error recurrence. To provide evidence and guidance for the prevention and improvement of medication communication errors by quantitatively exploring the relationship between error types and error factors. Data were collected on self-reported errors in the medication administration process by nurses in all departments of three cooperative medical institutions, and an error sheet of specified style was adopted. Error types were determined by the systematic human error reduction and prediction approach method and human cognition processes. Error factors were extracted using the root cause analysis combined with Berlo's communication model, and the relationship between error types and error factors was quantitatively studied using the partial least-squares regression method. After a one-by-one analysis of 303 error cases, the communication errors occurring in the nursing medication process could be explained by six error types and 12 error factors. In addition, 20 correlation patterns between the error types and error factors were quantitatively obtained, and their path coefficient distributions ranged from 0.088 to 0.467. The results of this study may provide reference to understand errors and establish countermeasures from the statistics of error occurrence trends, extract error factors related to error types and determine key error factors.

Human reliability analysis in deep excavation projects using a fuzzy Bayesian HEART-5M integrated method: case of a residential tower in north Tehran

Objectives. Numerous labourers lose their lives or suffer from injuries and disabilities yearly due to the lack of safety enforcement in construction projects and accidents caused by excavation collapses. The identification and ranking of human errors have always been a central concern in civil engineering. Previous studies on excavation work and related risks have focused on retaining structure methods, while human errors may be a significant contributor to accidents and near misses. Methods. This study identified human errors in deep excavation projects using hierarchical task analysis (HTA) and a systematic human error reduction and prediction approach (SHERPA). Results. The fuzzy Bayesian human error assessment and reduction technique (HEART)-5M method was implemented to determine the human error probability (HEP) for all case-study tasks. Critical tasks were obtained as ‘drainage system execution’, ‘water and wastewater pipes’, ‘gas pipes’, ‘checking cracks in surrounding buildings’ and ‘checking soil slippage’ with probability levels of 0.46, 0.44, 0.44, 0.37 and 0.37, respectively. Finally, remedial measures were presented for crucial tasks. Conclusions. Six unbiased experts approved the model’s desirability. The suggested approach can serve as a valuable guide for all project stakeholders in identifying, evaluating and taking corrective actions in similar projects.

Totally endoscopic cartilage tympanoplasty: a hierarchical task analysis.

Totally endoscopic ear surgery is a novel method of conducting otological surgery. Hierarchical task analysis and the systematic human error reduction and prediction approach ('SHERPA') are valuable tools that can effectively deconstruct the technical and non-technical skills required to successfully complete a surgical procedure. Twenty-five endoscopic tragal cartilage tympanoplasties were observed, to identify the tasks and subtasks required for completion of totally endoscopic tragal cartilage tympanoplasty. The systematic human error reduction and prediction approach was used to identify the potential risks and methods, to reduce or remediate these risks. A hierarchical task analysis was performed, identifying 8 tasks and 50 subtasks for a safe approach to completing totally endoscopic tragal cartilage tympanoplasty. A risk score for each subtask was calculated to produce a systematic human error reduction and prediction approach and to highlight potential errors. This hierarchical task analysis allowed for quick reference to a correct method of endoscopic tympanoplasty. The systematic human error reduction and prediction approach was employed to reduce the risks associated with undergoing endoscopic tympanoplasty, to improve patient safety.

Quantitative and Qualitative Assessment of Safety Status in a Medical Centre: Experience from Implementing Standard Safety System

Background: An accident is an unforeseen occurrence that happens in all organs, including medical centers, due to unsafe conditions and practices which cause damage and sometimes irreparable injuries. Establishing safety system in the medical center seek to prevent harm to both patients and health care professionals. Objectives: The aim of this study was to assess safety status in a medical center before and after implementing standard safety system. Materials & Methods: This case-study was carried out among the staff of a hospital in Guilan province, Iran in 2018-2019. The information was collected through observation and interview with staff and checking the observance of instructions and safety tips. Then, the possibility of needle stick injury was identified by calculating accident indices. human errors were assessed using risk assessment using Systematic human error reduction and prediction approach (SHERPA). Results: A total of 9 departments of a selected hospital were studied and the accident and human errors were identified. The recurrence rate of the accident in 2019 compared to 2018 had a decreasing rate from 11.36 to 4.09 (safe_T_score=-3.14). Risk assessment using SHERPA method in the gynecology ward revealed 4 important types of errors in this department. Conclusion: There was considerable reduction in frequency and severity of needle stick injuries after establishment of safety system in the hospital. The SHERPA method, detailed the task errors and specific remedial measure to correct the task. The results of this study can be helpful for medical staff, managers, employers, and safety experts in identifying and preventing the causes of the accident.

Human error identification and risk prioritization in LPG unloading operations

Objectives. Errors due to human activities in any operation are analyzed using human reliability analysis in which the principal step is to identify potential human errors followed by quantification and analysis of the error. This work intends to apply a methodology for identifying human errors and to prioritize the risk associated with them in a liquefied petroleum gas (LPG) unloading operation. Methods. The methodology uses hierarchical task analysis which provides the basic framework, along with a systematic human error reduction and prediction approach which aids in identification and categorization of the errors associated with each task with the help of predefined error taxonomy. Also, in order to quantify the risk associated with each identified error, fuzzy failure mode and effect analysis has been adopted. To rank and prioritize the risk associated with each identified error where the individual constituent components are non-commensurable in nature, the VIseKriterijumska Optimizacija I Kompromisno Resenje method has been incorporated. Results and conclusions. Applicability of the methodology presented will help comprehend the severity of risk corresponding to each error at different levels, and the ranking mechanism thus developed in this work aids to prioritize the action to minimize the likelihood of errors.

A practical application of the Hierarchical Task Analysis (HTA) and Human Error Assessment and Reduction Technique (HEART) to identify the major errors with mitigating actions taken after fire detection onboard passenger vessels

Fire onboard passenger ships is a major hazard not only for the personnel, passengers, and the environment, but also for the vessel itself. Therefore, the response actions carried out by crewmembers after a fire has been detected onboard a passenger vessel are of outermost importance. SAFEMODE project aims to promote contemporary safety thinking through a collection of carefully selected Human Factors (HFs) Fact Sheets that includes the most-known HFs techniques for accident investigations, to help accident investigators and safety managers within maritime organisations. Therefore, this paper proposes to apply two of the above-mentioned Fact Sheets, namely Hierarchical Task Analysis (HTA) and Human Error Assessment and Reduction Technique (HEART). Hence, this paper initially demonstrates how HTA can be applied to model the human response actions to a fire onboard a passenger vessel, and secondly, it utilises a systematic human error reduction and prediction approach, namely HEART, to predict and quantify which errors are likely to occur. Results from this paper reveal that six human response errors are most likely to occur, with a Human Error Probability of 0.16 according to the HEART analysis. Finally, this paper also suggests remedial measures to mitigate each error identified.

Exploring the human factors of medication errors in community pharmacy: a mixed methods study

Abstract Introduction Medication errors and near misses in the community pharmacy dispensing process have the potential to adversely impact patient safety. The World Health Organisation has identified the importance of Human factors (HF) in the Patient Safety Curriculum guide (1). However, there is a lack of knowledge on how HF principles have or could be applied in the community pharmacy setting. Adopting a HF approach and using qualitative methods can provide in-depth understanding of factors that contribute to these errors, and contribute to intervention development that may improve patient safety. Aim The study aims to investigate the factors contributing to medication dispensing errors and near misses in community pharmacy, and to gather pharmacists’ views of these factors and how these could be mitigated. Methods Three Irish community pharmacies were recruited and provided details of the last ten dispensing errors or near misses which occurred. Each error was mapped to the Hierarchical Task Analysis (HTA) steps developed for this study, and mapped to the Systematic Human Error Reduction and Prediction Approach (SHERPA) framework (2). A detailed report was prepared for each pharmacy outlining the error analysis, with recommendations to prevent the errors in future. A qualitative semi-structured interview was conducted with the three pharmacists in the recruited pharmacies to discuss the report, and analysed by thematic analysis. Results A total of 30 medication errors/near misses were analysed (10 errors reached the patients and were not administered). The HTA developed outlines 185 subtasks potentially involved in dispensing a prescribed medication. On mapping to the SHERPA framework, selection-based errors were the most frequently reported error category (21/30, 70%); this included incorrect product selection from the shelf (17/30, 56.7%) and incorrect product selection at the point of computer entry (4/30, 13.3%). Of the 75 HTA steps involved across the 30 errors, the most frequent point of error was in the gathering medication steps (47/75, 62.7%), followed by the pharmacist accuracy check steps (16/75, 21.3%) and patient mix up errors (5/30, 16.7%). The pharmacist interview themes found that cognitive burden, fatigue, distraction and staffing deficiencies were reported as increasing the risk of error and near miss. Knowledge gaps and inexperience with certain medications were also reported as contributing to errors. Recommendations to prevent errors included changes to the physical environment (e.g. using product shelf alerts), improved checking processes and taking short mental breaks. Conclusion This study found that the most common errors/near misses were at the product selection stage of dispensing, with pharmacy accuracy checks sometimes, but not always, detecting these before they reached the patient. Medication errors occur due to several varying and often interacting factors; cognitive burden and lack of standardised medication checking processes. Despite the small sample size and potential for social desirability bias in the interviews, this study has demonstrated how HF techniques can be applied to the dispensing process as a means of understanding and preventing error occurrence in the community pharmacy. References (1) Vosper H, Hignett S. A UK perspective on human factors and patient safety education in pharmacy Curricula. Am J Pharm Educ. 2017;82:6184. (2) Sutherland A, Ashcroft DM, Phipps DL. Exploring the human factors of prescribing errors in paediatric intensive care units. Arch Dis Child 2019;104:588-595.

Predicting and mitigating failures on the flight deck: an aircraft engine bird strike scenario

Engine damage as a consequence of foreign object debris (FOD) during flight is frequently caused by birds. One approach to minimising disruption caused by this damage is to provide flight crew with accurate information relating to the continuing operational status of the aircraft’s engines. Before designing such avionic systems however, understanding of current procedures is needed. Hierarchical Task Analysis (HTA) and Systematic Human Error Reduction and Prediction Approach (SHERPA) were used to identify potential failures that flight crew may make when managing an engine bird strike. Workshops with commercial pilots generated insights into current practice and a commercial pilot SME reviewed outputs for accuracy. Over 200 potential failures were identified, most commonly related to communication. Remedial measures, considering future avionic systems, are proposed to mitigate identified failures. This analysis provides a starting point for future design concepts for assisting flight crew in dealing with engine malfunction due to FOD strikes. Practitioner summary: Hierarchical Task Analysis was conducted to show all tasks involved in dealing with an in-flight aircraft engine bird strike. Systematic Human Error Reduction and Prediction Approach analysis was performed and over 200 possible failures were identified when managing this event. Remedial measures are proposed to help mitigate possible failures.

Measurement of Human Work Reliability Using Systematic Human Error Reduction and Prediction Approach and Human Error Assessment and Reduction Technique Method

CV. Raja Hati is a company that is engaged in the process of refinishing tires that have been bald into new ones. The tire retreading process has a relatively high percentage of defects, such as 14.8% Printing Process, 12.3% Surface Leveling, 8.6% Tire Curing, and so on. The problems in this study are the factors that cause defects in terms of human aspects, the types of errors that most often occur in the production process, and the value of human error probability (HEP) in the production process at CV. Raja Hati. This study aims to determine the factors that cause defects in terms of human aspects, the types of errors that most often occur in the production process and the value of human error probability (HEP) in the production process. The research was conducted using the SHERPA and HEART methods. The SHERPA method’s study results show that the types of errors that often occur in the tire retreading process are many wrong operator actions. Still, on the proper object (A7), the operator is wrong in dividing the time in doing work (A2), and the operator is not suitable for doing his job (A5). This study concludes that the factors that cause product defects in the tire retreading process are the absence of a procedure for correcting errors by 21.63%, the need for different techniques in doing work to facilitate operators by 27.04%, inexperienced operators by 12.36%, and inexperience and independent inspection has a percentage of 12.36%. The results of the calculation of the HEP value show that the average HEP value in the tire retreading process is 0.8552 or 85.52%, while the operator reliability value is 14.48%.

Predicting dispensing errors in community pharmacies: An application of the Systematic Human Error Reduction and Prediction Approach (SHERPA).

IntroductionThe objective of this study was to use a prospective error analysis method to examine the process of dispensing medication in community pharmacy settings and identify remedial solutions to avoid potential errors, categorising them as strong, intermediate, or weak based on an established patient safety action hierarchy tool.MethodFocus group discussions and non-participant observations were undertaken to develop a Hierarchical Task Analysis (HTA), and subsequent focus group discussions applied the Systematic Human Error Reduction and Prediction Approach (SHERPA) focusing on the task of dispensing medication in community pharmacies. Remedial measures identified through the SHERPA analysis were then categorised as strong, intermediate, or weak based on the Veteran Affairs National Centre for Patient Safety action hierarchy. Non-participant observations were conducted at 3 pharmacies, totalling 12 hours, based in England. Additionally, 7 community pharmacists, with experience ranging from 8 to 38 years, participated in a total of 4 focus groups, each lasting between 57 to 85 minutes, with one focus group discussing the HTA and three applying SHERPA. A HTA was produced consisting of 10 sub-tasks, with further levels of sub-tasks within each of them.ResultsOverall, 88 potential errors were identified, with a total of 35 remedial solutions proposed to avoid these errors in practice. Sixteen (46%) of these remedial measures were categorised as weak, 14 (40%) as intermediate and 5 (14%) as strong according to the Veteran Affairs National Centre for Patient Safety action hierarchy. Sub-tasks with the most potential errors were identified, which included ‘producing medication labels’ and ‘final checking of medicines’. The most common type of error determined from the SHERPA analysis related to omitting a check during the dispensing process which accounted for 19 potential errors.DiscussionThis work applies both HTA and SHERPA for the first time to the task of dispensing medication in community pharmacies, detailing the complexity of the task and highlighting potential errors and remedial measures specific to this task. Future research should examine the effectiveness of the proposed remedial solutions to improve patient safety.

Investigation of Human Errors in Emergency Department of Imam Khomeini Hospital Emergency Department of Jiroft Using Systematic Human Error Reduction and Prediction Approach

Introduction: In examining the unfortunate events that have taken place in the industrial and health sectors, human error is considered as the main cause of these events. Given the sensitivity and importance of medical careers, the occurrence of errors can lead to irreparable consequences. The purpose of this study was to investigate the human error in the emergency department of Imam Khomeini Hospital in Jiroft.
 Methods: This study was a cross-sectional and descriptive one. Emergency nurses' job duties have been analyzed by interviewing emergency nurses and studying nursing job guidelines and procedures using hierarchical task analysis. Finally, using the Systematic Human Error Reduction and Prediction Approach, human errors in nursing care were analyzed.
 Results: Generally, 4 tasks, 18 sub-tasks and 91 types of errors related to nursing activities were identified. Number of errors found, 27 (30%) Action errors, 18 (20%) Checking errors, 19 (21%) Retrieval errors, 12 (13%) communication errors, and 15 (16%) selection errors Were. As can be seen, the largest number of errors was related to the type of Action errors.
 Conclusion: Considering the results of the present study, the highest numbers of errors were related to Action and Checking errors respectively, which due to the sensitivity of nursing jobs and especially in the emergency department, require the use of highly skilled people to perform tasks that require high concentration and accuracy.

Prospective risk assessments of patient safety events related to drug shortages in hospitals: Three actor-level perspectives

Background: The increasing number of drug shortages (DSs) worldwide calls for more proactive solutions to prevent the negative impacts of DSs on patient care. Such solutions require in-depth knowledge about potential patient safety risks related to DSs, the processes of recognizing and managing DSs, the contextual setting in which DSs occur, and the actors involved.Objective: The aim of the study is to use prospective risk assessment to identify patient safety risks in hospitals associated with the management of DSs among actors at national, regional and local level in Denmark.Methods: Healthcare Failure Mode and Effect Analysis (HFMEA) was employed in composition with elements from the Systematic Human Error Reduction and Prediction Approach (SHERPA) and the Systems-Theoretic Accident Model and Processes (STAMP). Potential risks related to DS management across three actor levels (national, regional and local) in the Danish healthcare system were described. Each actor level consisted of six participants that were identified using a purposive sampling strategy. Processes and sub-processes related to managing critical DSs were outlined and the actors identified, prioritized and rated potential failure modes, causes and consequences related to the processes. Recommendations to mitigate failures were proposed for high risk failures modes.Results: Overall, a total of 167 failure modes were identified across the three actor levels. At the national level, the process of DS management consisted of 17 sub-processes, from which 71 failure modes were identified. Nine of them were rated as high risk. At regional level, 7 sub-processes and 33 failure modes were identified, of which 9 were rated as high risk. At local level, 14 sub-processes and 63 failure modes were identified, of which 32 were rated as high risk. The high-risk failures were related to a lack of IT support in the medication modules, underestimation of patient safety aspects, and insufficient personnel training and patient information.Conclusion: Exploring DS management failure modes across actor levels provided an overview of interrelated failures. Potential solutions related to high risk failures were developed to ensure that actors ensure patient safety related to DS in healthcare.

SHERPA기법을 이용한 항공기 착륙상황에서 발생 가능한 인적오류 예측

This study aims to examine probable human errors when landing an airplane by the use of SHERPA(systematic human error reduction and prediction approach) and propose methods for preventing the predictive human errors. It has been reported that human errors are concerned with a lot of accidents or incidents of an airplane. It is significant to predict presumable human errors, particularly in the operation mode of human-automation interaction, and attempt to reduce the likelihood of predicted human error. By referring to task procedures and interviewing domain experts, we analyzed airplane landing task by using HTA(hierarchical task analysis) method. In total, 6 sub-tasks and 19 operations were identified from the task analysis. SHERPA method was used for predicting probable human error types for each task. As a result, we identified 31 human errors and predicted their occurrence probability and criticality. Based on them, we suggested a set of methods for minimizing the probability of the predicted human errors. From this study, it can be said that SHERPA can be effectively used for predicting probable human error types in the context of human-automation interaction needed for navigating an airplane.

Task, usability, and error analyses of ambulance-based telemedicine for stroke care

Past research has established that telemedicine improves stroke care through decreased time to treatment and more accurate diagnoses. The goals of this study were to 1) study how clinicians complete stroke assessment using a telemedicine system integrated in ambulances, 2) determine potential errors and usability issues when using the system, and 3) develop recommendations to mitigate these issues. This study investigated use of a telemedicine platform to evaluate a stroke patient in an ambulance with a geographically distributed caregiving team comprised of a paramedic, nurse, and neurologist. It first determined the tasks involved based on 13 observations of a simulated stroke using 39 care providers. Based on these observational studies, a Hierarchical Task Analysis (HTA) was developed, and subsequently, a heuristic evaluation was conducted to determine the usability issues in the interface of the telemedicine system. This was followed by a Systematic Human Error Reduction and Prediction Approach (SHERPA) to determine the possibility of human error while providing care using the telemedicine work system. The results from the HTA included 6 primary subgoals categorizing the 97 tasks to complete the stroke evaluation. The heuristic evaluation found 123 unique violations to heuristics, with an average severity of 2.38. One hundred and thirty-one potential human errors were found with SHERPA, the two most common being miscommunication and selecting an incorrect option. Several recommendations are proposed, including improvement of labeling, consistent formatting, rigid or suggested formatting for data input, automation of task structure and camera movement, and audio/visual improvements to support communication.

HUMAN ERROR IDENTIFICATION IN BUS DRIVER WORK USING SHERPA AND HEART

Traffic accidents, especially with a large capacity such as bus, can be caused by several factors. According to the Indonesian Directorate General of Land Transportation of the Ministry of Transportation in 2012, the factors causing traffic accidents in Indonesia are a human factor of 93.52%, vehicle factor by 2.76%, road factor 3.23%, and environmental factor by 0.49%. Therefore, research is needed to identify which human error has the greatest probability of accident cause using Systematic Human Error Reduction and Prediction Approach (SHERPA) method to identify job desk using Hierarchical Task Analysis (HTA) and Human Error Assessment Reduction Technique (HEART) method to calculate Human Error Probability (HEP). Based on the calculation of Human Error Probability value known the highest HEP value is not running the vehicle in accordance with the provisions of the speed that has been set with 0.375. Next is not to record or forget to record the damage that occurred during the trip with a value of 0.21. It did not check Bus equipment with a HEP value of 0.19, did not report when there was a problem on the street with a HEP value of 0.18 and did not break for the next preparation for departure with a HEP value of 0.15

Human reliability analysis of bronchoscope-assisted percutaneous dilatational tracheostomy: implications for simulation-based education

BackgroundTeaching and assessing clinical procedures requires a clear delineation of the individual steps required to successfully complete the procedure. For decades, human reliability analysis (HRA) has been used to identify the steps required to complete technical procedures in higher risk industries. However, the use of HRA is uncommon in healthcare. HRA has great potential supporting simulation-based education (SBE) in two ways: (1) to support training through the identification of the steps required to complete a clinical procedure; and (2) to support assessment by providing a framework for evaluating performance of a clinical procedure. The goal of this study was to use HRA to identify the steps (and the risk associated with each of these steps) required to complete a bronchoscope-assisted percutaneous dilatational tracheostomy (BPDT). BPDT is a potentially high-risk minimally invasive procedure used to facilitate tracheostomy placement at the bedside or in the operating theatre.MethodsThe subgoals, or steps, required to complete the BPDT procedure were identified using hierarchical task analysis. The Systematic Human Error Reduction and Prediction Approach (SHERPA) was then used to identify potential human errors at each subgoal, the level of risk and how these potential errors could be prevented.ResultsThe BPDT procedure was broken down into 395 subgoals, of which 18% were determined to be of high-risk. The most commonly identified remediation strategies for reducing the risk of the procedure included: checklist implementation and audit, statutory and mandatory training modules, simulation training, consultant involvement in all procedures, and fostering a safety-focused hospital culture.ConclusionThis study provides an approach for how to systematically identify the steps required to complete a clinical procedure for both training and assessment. An understanding of these steps is the foundation of SBE. HRA can identify ‘a correct way’ for teaching learners how to complete a technical procedure, and support teachers to give systematic and structured feedback on performance.

The application of human reliability analysis to three critical care procedures

BackgroundProcedures carried out in the intensive care unit are prone to human error. Standardisation has been suggested as an approach for reducing errors. This study used human reliability analysis methodologies to examine commonly performed critical care procedures: endotracheal suctioning; ultrasound-guided right internal jugular vein cannulation; and rapid-sequence intubation. MethodsThe subgoals, or individual steps, required to complete the three procedures were identified using hierarchical task analysis. The systematic human error reduction and prediction approach was then used to identify potential human errors at each subgoal, the level of risk and how these potential errors could be prevented. ResultsEndotracheal suctioning procedure was broken down into 129 subgoals, of which 49 (38.0%) were high-risk. Ultrasound-guided right internal jugular venous cannulation was divided into 224 subgoals, of which 131 (58.4%) were medium-risk, and 20 (8.9%) were identified as high-risk. Rapid sequence intubation was divided into 167 subgoals. A total of 73 (43.7%) of these subgoals were judged to be high-risk. ConclusionsThe use of human reliability analysis techniques can support healthcare professionals to gain an in-depth understanding of how particular procedures are carried out in order to reduce the risk of, and improve training in, how to perform these procedures.