aDepartment of Health Policy and Management, Ben-Gurion University of the Negev, Beer-Sheva, Israel bDepartment of Anesthesia and Critical Care, The University of Chicago, Chicago, Illinois cDepartments of Anesthesiology, Perioperative Care and Pain Medicine, Neurology, Surgery and Medicine, NYU Langone Health, New York, New York Address Correspondence to: Yuval Bitan, PhD, 1 Ben-Gurion Ave., Be’er Sheva, Israel 8443944. E-mail: [email protected]

Dr. Richard Cook was a physician, educator, scholar, and researcher. He was a brilliant thinker and writer. Richard's CV lists 41 peer reviewed publications, 39 conference proceedings, 6 technical reports, 30 books/book chapters that were cited about 10,000 times (as of September 2022). Richard has excelled in multiple careers and was remarkably giving of his time, devoting 100s of thousands of hours of his life presenting, debating, corresponding, mentoring, and challenging the world, in formal and informal settings, to mature toward more complex, realistic thinking about the world as a sociotechnical entity. Our community recognizes him mainly for his key role in the start and expansion of the patient safety movement. This paper presents quintessence from a panel session that honors Richard’s work. The 7 panelists and moderator present Richard’s legacy, introduce varied aspects of his work, and consider how we can take his legacy forward to cope with future challenges. It is a moment to step back, remind ourselves of patient safety’s evolution from the 90’s until today, the power of resilience for the future of healthcare complex systems, and how to build momentum that can succeed at scale.

OBJECTIVE:To explore cognitive strategies clinicians apply while performing a medication reconciliation task, handling incomplete and conflicting information.BACKGROUND:Medication reconciliation is a method clinicians apply to find and resolve inconsistencies in patients' medications and medical conditions lists. The cognitive strategies clinicians use during reconciliation are unclear. Controlled lab experiments can explore how clinicians make sense of uncertain, missing, or conflicting information and therefore support the development of a human performance model. We hypothesize that clinicians apply varied cognitive strategies to handle this task and that profession and experience affect these strategies.METHOD:130 clinicians participated in a tablet-based experiment conducted in a large American teaching hospital. They were asked to simulate medication reconciliation using a card sorting task (CaST) to organize medication and medical condition lists of a specific clinical case. Later on, they were presented with new information and were asked to add it to their arrangements. We quantitatively and qualitatively analyzed the ways clinicians arranged patient information.RESULTS:Four distinct cognitive strategies were identified ("Conditions first": n = 76 clinicians, "Medications first": n = 7, "Crossover": n = 17, and "Alternating": n = 10). The strategy clinicians applied was affected by their experience (p = .02) but not by their profession. At the appearance of new information, clinicians moved medication cards more frequently (75.2 movements vs. 49.6 movements, p < .001), suggesting that they match medications to medical conditions.CONCLUSION:Clinicians apply various cognitive strategies while reconciling medications and medical conditions.APPLICATION:Clinical information systems should support multiple cognitive strategies, allowing flexibility in organizing information.

Introduction: High-stakes industries, such as healthcare, are complex systems prone to influence by various constraining factors. Expert practitioners in these domains work at the “sharp end” of these constraints and must reconcile limitations in the context of operations. When a major constraining factor is changed abruptly, it can induce a rapid sequence of adaptations. We observed the cognitive artifacts of post hoc signage, posted inside the space of the operating rooms of a new hospital facility, to help identify the way clinicians adapt to a new physical plant. Methods: In the first six months of operation of a new hospital facility, a clinician (MN) photographed signage posted on the operatory floor of the hospital. The photographs were classified into general categories to uncover the sorts of adaptive behaviors they represented. Results: We identified 28 signs that fit into four categories: way finding (7); appropriation and item localization (6); equipment activation, instruction and upkeep (9); and malfunction or breakage (6). Way finding and equipment activation, instruction and upkeep signs appeared earlier, and malfunction signs appeared later over the course of observation. Discussion: The physical layout of a building is a concrete example of operational constraints influencing clinical behavior (“sharp end”). Clinicians adapt to several needs when faced with a new workspace. Way finding and operational instructions are important components of this adaptation, but so too is resource appropriation. Physical failings of equipment become evident during operations, and the signage suggests that communicating these failures visually is important. The signs show the way clinicians adapt to constraints, effectively documenting the deficiencies in the interface between the physical structure and the people who work there. They are useful to direct research into new, helpful signage and also to signal the “brittle” aspects of the workplace. They should be celebrated as opportunities for improvement.

Medication omissions and dosing failures are frequent during transitions in patient care. Medication reconciliation (MR) requires bridging discrepancies in a patient’s medical history as a setting for care changes. MR has been identified as vulnerable to failure, and a clinician’s cognition during MR remains poorly described in the literature. We sought to explore cognition in MR tasks. Specifically, we sought to explore how clinicians make sense of conditions and medications. We observed 24 anesthesia providers performing a card-sorting task to sort conditions and medications for a fictional patient. We analyzed the spatial properties of the data using statistical methods. Most of the participants (58%) arranged the medications along a straight line (p < 0.001). They sorted medications by organ systems (Friedman’s χ 2(54) = 325.7, p < 0.001). These arrangements described the clinical correspondence between each two medications (Wilcoxon W = 192.0, p < 0.001). A cluster analysis showed that the subjects matched conditions and medications related to the same organ system together (Wilcoxon W = 1917.0, p < 0.001). We conclude that the clinicians commonly arranged the information into two groups (conditions and medications) and assigned an internal order within these groups, according to organ systems. They also matched between conditions and medications according to similar criteria. These findings were also supported by verbal protocol analysis. The findings strengthen the argument that organ-based information is pivotal to a clinician’s cognition during MR. Understanding the strategies and heuristics, clinicians employ through the MR process may help to develop practices to promote patient safety.

Patients are most at risk during transitions in care across settings and providers. The communication and reconciliation of an accurate medication list throughout the care continuum are essential in the reduction in transition-related adverse drug events. Most current research focuses on the outcomes of reconciliation interventions, yet not on the clinician’s perspective. We aimed to explore clinicians’ cognitive processes and heuristics of making sense of patients’ disease histories. We used the affinity diagram method to simulate real-life medication reconciliation with 24 clinicians. The participants were given paper cards with diseases and medications representing a real case from an anesthesiology department. The task was to sort the cards in a set that made sense to the clinician. The experiment was video-recorded, and the data were analyzed using a quantitative spatial analysis technique. Levene’s test for equality of variance showed that 79% of the 24 participants arranged the diseases along a straight line (p < 0.001). With only few exceptions, the diseases were arranged along the line in a fixed order, from cardiac conditions to depression (Friedman’s χ2(44) = 291.9, p < 0.001). We learn from this study that although clinicians employ a variety of coping strategies while reconciling patients’ medical histories, there are common reconciliation strategies. Understanding heuristics and the mental models clinicians have for the reconciliation process may help to develop and implement methods and tools to promote safety research and practice.

OBJECTIVES:We report on a human factors evaluation project at a major urban teaching hospital that was intended to use human factors methods to assist the selection of a new infusion device among 4 commercially available models.METHODS:The project provided an expert evaluation of the pumps, collected data on programming each pump by a sample of practitioners, tabulated recent adverse event reports in the US Food and Drug Administration Manufacturer and User Device Experience database, and observed actual use in intensive care and hematology/oncology units.RESULTS:Programming by clinicians showed no correlation between clinical experience and ability to program any of the pumps under consideration. Field observations reflected diverse use patterns across services that required ease of use pumps did not offer. Upon review of a final candidate pump, purchasing preferences superceded clinical considerations.CONCLUSIONS:Equipment and systems that are intended for use by clinicians must necessarily reflect an understanding of actual clinical practice to be well suited for use at the sharp (operator) end. However, purchase decisions for medical equipment including infusion devices are typically made by hospital staff members who are experienced in administrative and clinical matters but have no expertise in the evaluation of complex equipment. This project demonstrates how collaboration by human factors and clinical professionals can inform equipment decisions and assist clinician performance to improve patient safety. It also reveals how technical decisions that directly influence anesthesia staff performance and patient safety are subject to organizational factors such as social and political pressure.

The flow of technical work in acute healthcare varies unpredictably, in patterns that occur regularly enough that they can be managed. Acute care organizations develop ways to hedge resources so that they are available if they are needed. This pragmatic approach to the distribution of work among and across groups shows how rules can be used to manage a response to irregular demands for care. However, no rule set can be complete enough to cover this setting’s variety of care demands. Expertise is also needed to tie together the loose ends of conflicts that remain where rules no longer suffice. Many informal solutions to systemic problems go unnoticed unless they are the subjects of study. Naturalistic decision making (NDM) methods such as observational study, interviews, and process tracing reveal the activities of workers in their natural settings. Results of findings from such explorations of technical work can improve understanding of large scale work processes and, ultimately, patient safety. We have explored how practitioners cope with the demands that the system presents to them. While not all succeed, successful initiatives workers have developed demonstrate how their solutions create resilience at large scale.

University of Chicago, Department of Anesthesia and Critical Care, Chicago, IL The authors have not disclosed any potential conflicts of interest. *See also p. 2792.

Objective: This study sought to determine whether infusion device event logs could support accident investigation. Methods: An incident reporting database was searched for information about log file use in investigations. Log file data from devices in clinical use were downloaded and electronically searched for characteristics (signatures) matching specific function queries. Different programming sequences were simulated, and device logs were downloaded for analysis. Results: Database reports mentioned difficulties resolving log file data to the incident report and used log file data to confirm programming failures. Log file search revealed that, aside from alarm types and times, the devices were unable to adequately satisfy functional queries. Different simulated programming scenarios could not be easily differentiated by log file analysis. Conclusions: The device logs we studied collect data that are poorly suited to accident investigation. We conclude that infusion device logs cannot function as black boxes do in aviation accidents. Logs would be better applied to assist routine operations.

Objectives: Automated piggybacks are purported to make drug administration safer and more reliable. We evaluated the human factors of piggyback infusion, investigated the practice in our institution, and analyzed incidents from an anonymous database to better characterize the practice and substantiate these assertions. Methods: To find examples of problems with piggyback, or secondary infusions, we searched the Food and Drug Administration's on-line incident database for incidents involving piggybacks. As part of a task analysis, 19 senior nurses each programmed 2 of 4 different pumps for a simulated piggyback infusion. To characterize infusion practice, we evaluated data logs from 55 infusion devices used in our institution. Results: Incidents from the database provided strong evidence that potential problems existed with piggyback infusions. Nurse behaviors suggested mismatches between the task, user, and devices that can lead to adverse events. Log files showed piggybacks were a common practice, and that available safeguards were not used. Conclusions: Our multiple data sources suggest automated piggyback infusion practice is neither simple nor safe. Incident report analysis suggests these findings contribute to adverse events. Further study is needed to understand and improve the safety of this practice.

OPERATIVE CANDIDATES for vascular surgery have a high incidence of coronary artery disease (CAD), which is responsible for 50% of their perioperative mortality. 1 Kragsterman B. Logason K. Ahari A. et al. Risk factors for complications after carotid endarterectomy—A population-based study. Eur J Vasc Endovasc Surg. 2004; 28: 98-103 Abstract Full Text Full Text PDF PubMed Scopus (60) Google Scholar , 2 Hertzer N.R. Young J.R. Kramer J.R. et al. Routine coronary angiography prior to elective aortic reconstruction Results of selective myocardial revascularization in patients with peripheral vascular disease . Arch Surg. 1979; 114: 1336-1344 Crossref PubMed Scopus (193) Google Scholar The authors present a patient scheduled for carotid endarterectomy (CEA) whose comprehensive preoperative cardiac evaluation showed him to be at low cardiac risk yet he suffered intraoperative catastrophic cardiovascular collapse. Appropriate preoperative evaluation of CEA patients, in whom CAD is prevalent, 3 Fleisher L.A. Eagle K.A. Shaffer T. et al. Perioperative and long-term mortality rates after major vascular surgery The relationship to preoperative testing in the medicare population . Anesth Analg. 1999; 89: 849-855 PubMed Google Scholar is discussed with regard to the American Heart Association (AHA)/American College of Cardiology (ACC) perioperative cardiovascular evaluation guidelines for noncardiac surgery. In addition, the authors describe the intraoperative course of this patient, review the pathophysiology that is often seen in perioperative myocardial infarction, and present results from postoperative coronary arteriography.

Objectives: Automated piggybacks are purported to make drug administration safer and more reliable. We evaluated the human factors of piggyback infusion, investigated the practice in our institution, and analyzed incidents from an anonymous database to better characterize the practice and substantiate these assertions. Methods: To find examples of problems with piggyback, or secondary infusions, we searched the Food and Drug Administration’s on-line incident database for incidents involving piggybacks. As part of a task analysis, 19 senior nurses each programmed 2 of 4 different pumps for a simulated piggyback infusion. To characterize infusion practice, we evaluated data logs from 55 infusion devices used in our institution. Results: Incidents from the database provided strong evidence that potential problems existed with piggyback infusions. Nurse behaviors suggested mismatches between the task, user, and devices that can lead to adverse events. Log files showed piggybacks were a common practice, and that available safeguards were not used. Conclusions: Our multiple data sources suggest automated piggyback infusion practice is neither simple nor safe. Incident report analysis suggests these findings contribute to adverse events. Further study is needed to understand and improve the safety of this practice.