Because the investigators were leading the timeouts as part of a research study, adherence to all of the checklist items was reportedly 100%. By excluding the part of the timeout when the nurses ...address their checklist items (eg, instruments are sterile,) followed by a final opportunity as the timeout ends to note any errors or concerns, the study may have underestimated the rate of error reporting. Because the study did not query team members individually after the timeout, we also do not know how many errors were detected but not annunciated. ...recognised errors that were attributed to ‘misspeaking’ and/or had no clinical significance may not have been verbally challenged. ...as is discussed by the authors, there was an unequivocal hierarchy effect—individuals with the least ‘power’ (ie, low in hierarchy within the current healthcare culture) were the least likely to report the error. ...how can we best design and implement checklists and other safety interventions to yield more consistent and sustained clinician behaviour change?
Current research suggests that the rate of adoption of health information technology (HIT) is low, and that HIT may not have the touted beneficial effects on quality of care or costs. The twin issues ...of the failure of HIT adoption and of HIT efficacy stem primarily from a series of fallacies about HIT. We discuss 12 HIT fallacies and their implications for design and implementation. These fallacies must be understood and addressed for HIT to yield better results. Foundational cognitive and human factors engineering research and development are essential to better inform HIT development, deployment, and use.
Abstract
Delivering high-quality, patient-centered cancer care remains a challenge. Both the National Academy of Medicine and the American Society of Clinical Oncology recommend shared decision ...making to improve patient-centered care, but widespread adoption of shared decision making into clinical care has been limited. Shared decision making is a process in which a patient and the patient’s health-care professional weigh the risks and benefits of different options and come to a joint decision on the best course of action for that patient on the basis of their values, preferences, and goals for care. Patients who engage in shared decision making report higher quality of care, whereas patients who are less involved in these decisions have statistically significantly higher decisional regret and are less satisfied. Decision aids can improve shared decision making—for example, by eliciting patient values and preferences that can then be shared with clinicians and by providing patients with information that may influence their decisions. However, integrating decision aids into the workflows of routine care is challenging. In this commentary, we explore 3 workflow-related barriers to shared decision making: the who, when, and how of decision aid implementation in clinical practice. We introduce readers to human factors engineering and demonstrate its potential value to decision aid design through a case study of breast cancer surgical treatment decision making. By better employing the methods and principles of human factors engineering, we can improve decision aid integration, shared decision making, and ultimately patient-centered cancer outcomes.
Background
Electronic health record (EHR) system transitions are challenging for healthcare organizations. High-volume, safety–critical tasks like barcode medication administration (BCMA) should be ...evaluated, yet standards for ensuring safety during transition have not been established.
Objective
Identify risks in common and problem-prone medication tasks to inform safe transition between BCMA systems and establish benchmarks for future system changes.
Design
Staff nurses completed simulation-based usability testing in the legacy system (R1) and new system pre- (R2) and post-go-live (R3). Tasks included (1) Hold/Administer, (2) IV Fluids, (3) PRN Pain, (4) Insulin, (5) Downtime/PRN, and (6) Messaging. Audiovisual recordings of task performance were systematically analyzed for time, navigation, and errors. The System Usability Scale measured perceived usability and satisfaction. Post-simulation interviews captured nurses’ qualitative comments and perceptions of the systems.
Participants
Fifteen staff nurses completed 2–3-h simulation sessions. Eleven completed both R1 and R2, and seven completed all three rounds. Clinical experience ranged from novice (< 1 year) to experienced (> 10 years). Practice settings included adult and pediatric patient populations in ICU, stepdown, and acute care departments.
Main Measures
Task completion rates/times, safety and non-safety-related use errors (interaction difficulties), and user satisfaction.
Key Results
Overall success rates remained relatively stable in all tasks except two: IV Fluids task success increased substantially (R1: 17%, R2: 54%, R3: 100%) and Downtime/PRN task success decreased (R1: 92%, R2: 64%, R3: 22%). Among the seven nurses who completed all rounds, overall safety-related errors decreased 53% from R1 to R3 and 50% from R2 to R3, and average task times for successfully completed tasks decreased 22% from R1 to R3 and 38% from R2 to R3.
Conclusions
Usability testing is a reasonable approach to compare different BCMA tasks to anticipate transition problems and establish benchmarks with which to monitor and evaluate system changes going forward.
Distractions in the perioperative work environment can adversely affect vigilance, situation awareness, and the ability to respond promptly to changes in the patient's condition and pose a risk to ...patient safety. The Anesthesia Patient Safety Foundation (APSF) believes that the role of all types of distractions, and their potential adverse effects, needs to be addressed through open discussion, education, research, policy, and possibly other interventions. To make progress in this area, APSF convened a conference entitled "Distractions in the Anesthesia Work Environment: Impact on Patient Safety" in Phoenix, Arizona, on September 7, 2016, comoderated by the authors. Robert Stoelting, APSF immediate past president, welcomed over 100 participants who represented anesthesia professionals, surgeons, operating room (OR) and perioperative nurses, the nuclear power and surface transportation industries, and risk management. The goals of the conference were to (1) delineate the most important types of external and self-induced distractions occurring in anesthesia professionals' different work environments, (2) identify those distractions most likely to pose patient safety risks (ie, high-risk distractions), and (3) develop recommendations for decreasing the incidence of high-risk distractions and to reduce the risk to patient safety when distractions of all types occur.
Burnout affects all medical specialists, and concern about it has become common in today's health care environment. The gold standard of burnout measurement in health care professionals is the ...Maslach Burnout Inventory-Human Services Survey (MBI-HSS), which measures emotional exhaustion, depersonalization (DP), and personal accomplishment. Besides affecting work quality, burnout is thought to affect health problems, mental health issues, and substance use negatively, although confirmatory data are lacking. This study evaluates some of these effects.
In 2011, the American Society of Anesthesiologists and the journal Anesthesiology cosponsored a webinar on burnout. As part of the webinar experience, we included access to a survey using MBI-HSS, 12-item Short Form Health Survey (SF-12), Social Support and Personal Coping (SSPC-14) survey, and substance use questions. Results were summarized using sample statistics, including mean, standard deviation, count, proportion, and 95% confidence intervals. Adjusted linear regression methods examined associations between burnout and substance use, SF-12, SSPC-14, and respondent demographics.
Two hundred twenty-one respondents began the survey, and 170 (76.9%) completed all questions. There were 266 registrants total (31 registrants for the live webinar and 235 for the archive event), yielding an 83% response rate. Among respondents providing job titles, 206 (98.6%) were physicians and 2 (0.96%) were registered nurses. The frequency of high-risk responses ranged from 26% to 59% across the 3 MBI-HSS categories, but only about 15% had unfavorable scores in all 3. Mean mental composite score of the SF-12 was 1 standard deviation below normative values and was significantly associated with all MBI-HSS components. With SSPC-14, respondents scored better in work satisfaction and professional support than in personal support and workload. Males scored worse on DP and personal accomplishment and, relative to attending physicians, residents scored worse on DP. There was no significant association between MBI-HSS and substance use.
Many anesthesiologists exhibit some high-risk burnout characteristics, and these are associated with lower mental health scores. Personal and professional support were associated with less emotional exhaustion, but overall burnout scores were associated with work satisfaction and professional support. Respondents were generally economically satisfied but also felt less in control at work and that their job kept them from friends and family. The association between burnout and substance use may not be as strong as previously believed. Additional work, perhaps with other survey instruments, is needed to confirm our results.
•An information fusion framework is proposed to fuse multiple heterogeneous data.•A novel quantitative model is developed based on empirical data.•Ensemble of models are built to predict the ...performance of crew team.
Control room operators respond to abnormal situations through a series of cognitively demanding activities, e.g., monitoring, detection, diagnosis, and response. However, variability among operators in terms of prior experience and current operational context affects their response to the malfunction. A machine learning framework was employed to integrate multiple data sources and develop an empirical model of operator performance in responding to malfunction events. A human-in-the-loop within-subjects experiment was performed using a high-fidelity Generic Pressurized Water Reactor simulator. The study recruited nine licensed operators in three-person crews completing ten scenarios, each incorporating two to four malfunction events. Individual operator performance was assessed using eye tracking technology and physiological recordings of skin conductance response and respiratory function. Expert-rated event management performance was the primary study outcome. These heterogeneous data sources were fused using an approach that integrated a support vector machine with bootstrap aggregation to develop a trained quantitative prediction model. While no single variable predicted operator performance, the fused model’s predictions using independent verification data was very good (prediction accuracy of 75–83%). The proposed methodology offers a quantitative approach to evaluate the crew performance through fusing the heterogeneous data collected from experiment.
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