Cognitive task analysis of clinicians' drug-drug interaction management during patient care and implications for alert design.

BACKGROUND: Drug-drug interactions (DDIs) are common and can result in patient harm. Electronic health records warn clinicians about DDIs via alerts, but the clinical decision support they provide is inadequate. Little is known about clinicians' real-world DDI decision-making process to inform more effective alerts. OBJECTIVE: Apply cognitive task analysis techniques to determine informational cues used by clinicians to manage DDIs and identify opportunities to improve alerts. DESIGN: Clinicians submitted incident forms involving DDIs, which were eligible for inclusion if there was potential for serious patient harm. For selected incidents, we met with the clinician for a 60 min interview. Each interview transcript was analysed to identify decision requirements and delineate clinicians' decision-making process. We then performed an inductive, qualitative analysis across incidents. SETTING: Inpatient and outpatient care at a major, tertiary Veterans Affairs medical centre. PARTICIPANTS: Physicians, pharmacists and nurse practitioners. OUTCOMES: Themes to identify informational cues that clinicians used to manage DDIs. RESULTS: We conducted qualitative analyses of 20 incidents. Data informed a descriptive model of clinicians' decision-making process, consisting of four main steps: (1) detect a potential DDI; (2) DDI problem-solving, sensemaking and planning; (3) prescribing decision and (4) resolving actions. Within steps (1) and (2), we identified 19 information cues that clinicians used to manage DDIs for patients. These cues informed their subsequent decisions in steps (3) and (4). Our findings inform DDI alert recommendations to improve clinicians' decision-making efficiency, confidence and effectiveness. CONCLUSIONS: Our study provides three key contributions. Our study is the first to present an illustrative model of clinicians' real-world decision making for managing DDIs. Second, our findings add to scientific knowledge by identifying 19 cognitive cues that clinicians rely on for DDI management in clinical practice. Third, our results provide essential, foundational knowledge to inform more robust DDI clinical decision support in the future.

Adapting Cognitive Task Analysis Methods for Use in a Large Sample Simulation Study of High-Risk Healthcare Events.

Cognitive task analysis (CTA) methods are traditionally used to conduct small-sample, in-depth studies. In this case study, CTA methods were adapted for a large multi-site study in which 102 anesthesiologists worked through four different high-fidelity simulated high-consequence incidents. Cognitive interviews were used to elicit decision processes following each simulated incident. In this paper, we highlight three practical challenges that arose: (1) standardizing the interview techniques for use across a large, distributed team of diverse backgrounds; (2) developing effective training; and (3) developing a strategy to analyze the resulting large amount of qualitative data. We reflect on how we addressed these challenges by increasing standardization, developing focused training, overcoming social norms that hindered interview effectiveness, and conducting a staged analysis. We share findings from a preliminary analysis that provides early validation of the strategy employed. Analysis of a subset of 64 interview transcripts using a decompositional analysis approach suggests that interviewers successfully elicited descriptions of decision processes that varied due to the different challenges presented by the four simulated incidents. A holistic analysis of the same 64 transcripts revealed individual differences in how anesthesiologists interpreted and managed the same case.

Decision-Making During High-Risk Events: A Systematic Literature Review.

Effective decision-making in crisis events is challenging due to time pressure, uncertainty, and dynamic decisional environments. We conducted a systematic literature review in PubMed and PsycINFO, identifying 32 empiric research papers that examine how trained professionals make naturalistic decisions under pressure. We used structured qualitative analysis methods to extract key themes. The studies explored different aspects of decision-making across multiple domains. The majority (19) focused on healthcare; military, fire and rescue, oil installation, and aviation domains were also represented. We found appreciable variability in research focus, methodology, and decision-making descriptions. We identified five main themes: (1) decision-making strategy, (2) time pressure, (3) stress, (4) uncertainty, and (5) errors. Recognition-primed decision-making (RPD) strategies were reported in all studies that analyzed this aspect. Analytical strategies were also prominent, appearing more frequently in contexts with less time pressure and explicit training to generate multiple explanations. Practitioner experience, time pressure, stress, and uncertainty were major influencing factors. Professionals must adapt to the time available, types of uncertainty, and individual skills when making decisions in high-risk situations. Improved understanding of these decisional factors can inform evidence-based enhancements to training, technology, and process design.

Study protocol for a type III hybrid effectiveness-implementation trial to evaluate scaling interoperable clinical decision support for patient-centered chronic pain management in primary care.

BACKGROUND: The US continues to face public health crises related to both chronic pain and opioid overdoses. Thirty percent of Americans suffer from chronic noncancer pain at an estimated yearly cost of over $600 billion. Most patients with chronic pain turn to primary care clinicians who must choose from myriad treatment options based on relative risks and benefits, patient history, available resources, symptoms, and goals. Recently, with attention to opioid-related risks, prescribing has declined. However, clinical experts have countered with concerns that some patients for whom opioid-related benefits outweigh risks may be inappropriately discontinued from opioids. Unfortunately, primary care clinicians lack usable tools to help them partner with their patients in choosing pain treatment options that best balance risks and benefits in the context of patient history, resources, symptoms, and goals. Thus, primary care clinicians and patients would benefit from patient-centered clinical decision support (CDS) for this shared decision-making process. METHODS: The objective of this 3-year project is to study the adaptation and implementation of an existing interoperable CDS tool for pain treatment shared decision making, with tailored implementation support, in new clinical settings in the OneFlorida Clinical Research Consortium. Our central hypothesis is that tailored implementation support will increase CDS adoption and shared decision making. We further hypothesize that increases in shared decision making will lead to improved patient outcomes, specifically pain and physical function. The CDS implementation will be guided by the Exploration, Preparation, Implementation, Sustainment (EPIS) framework. The evaluation will be organized by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. We will adapt and tailor PainManager, an open source interoperable CDS tool, for implementation in primary care clinics affiliated with the OneFlorida Clinical Research Consortium. We will evaluate the effect of tailored implementation support on PainManager's adoption for pain treatment shared decision making. This evaluation will establish the feasibility and obtain preliminary data in preparation for a multi-site pragmatic trial targeting the effectiveness of PainManager and tailored implementation support on shared decision making and patient-reported pain and physical function. DISCUSSION: This research will generate evidence on strategies for implementing interoperable CDS in new clinical settings across different types of electronic health records (EHRs). The study will also inform tailored implementation strategies to be further tested in a subsequent hybrid effectiveness-implementation trial. Together, these efforts will lead to important new technology and evidence that patients, clinicians, and health systems can use to improve care for millions of Americans who suffer from pain and other chronic conditions. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05256394 , Registered 25 February 2022.

Strategies prescribers and pharmacists use to identify and mitigate adverse drug reactions in inpatient and outpatient care: a cognitive task analysis at a US Veterans Affairs Medical Center.

OBJECTIVE: To develop a descriptive model of the cognitive processes used to identify and resolve adverse drug reactions (ADRs) from the perspective of healthcare providers in order to inform future informatics efforts SETTING: Inpatient and outpatient care at a tertiary care US Veterans Affairs Medical Center. PARTICIPANTS: Physicians, nurse practitioners and pharmacists who report ADRs. OUTCOMES: Descriptive model and emerging themes from interviews. RESULTS: We conducted critical decision method interviews with 10 physicians and 10 pharmacists. No nurse practitioners submitted ADR incidents. We generated a descriptive model of an ADR decision-making process and analysed emerging themes, categorised into four stages: detection of potential ADR, investigation of the problem's cause, risk/benefit consideration, and plan, action and follow-up. Healthcare professionals (HCPs) relied on several confirmatory or disconfirmatory cues to detect and investigate potential ADRs. Evaluating risks and benefits of related medications played an essential role in HCPs' pursuits of solutions CONCLUSIONS: This study provides an illustrative model of how HCPs detect problems and make decisions regarding ADRs. The design of supporting technology for potential ADR problems should align with HCPs' real-world cognitive strategies, to assist fully in detecting and preventing ADRs for patients.

Care Coordination Strategies and Barriers during Medication Safety Incidents: a Qualitative, Cognitive Task Analysis.

BACKGROUND: Medication errors are prevalent in healthcare institutions worldwide, often arising from difficulties in care coordination among primary care providers, specialists, and pharmacists. Greater knowledge about care coordination surrounding medication safety incidents can inform efforts to improve patient safety. OBJECTIVES: To identify strategies that hospital and outpatient healthcare professionals (HCPs) use, and barriers encountered, when they coordinate care during a medication safety incident involving an adverse drug reaction, drug-drug interaction, or drug-renal concern. DESIGN: We asked HCPs to complete a form whenever they encountered these incidents and intervened to prevent or mitigate patient harm. We stratified incidents across HCP roles and incident categories to conduct follow-up cognitive task analysis interviews with HCPs. PARTICIPANTS: We invited all physicians and pharmacists working in inpatient or outpatient care at a tertiary Veterans Affairs Medical Center. We examined 24 incidents: 12 from physicians and 12 from pharmacists, with a total of 8 incidents per category. APPROACH: Interviews were transcribed and analyzed via a two-stage inductive, qualitative analysis. In stage 1, we analyzed each incident to identify decision requirements. In stage 2, we analyzed results across incidents to identify emergent themes. KEY RESULTS: Most incidents (19, 79%) were from outpatient care. HCPs relied on four main strategies to coordinate care: cognitive decentering; collaborative decision-making; back-up behaviors; and contingency planning. HCPs encountered four main barriers: role ambiguity and constraints, breakdowns (e.g., delays) in care, challenges related to the electronic health record, and factors that increased coordination complexity. Each strategy and barrier occurred across all incident categories and HCP groups. Pharmacists went to extra effort to ensure safety plans were implemented. CONCLUSIONS: Similar strategies and barriers were evident across HCP groups and incident types. Strategies for enhancing patient safety may be strengthened by deliberate organizational support. Some barriers could be addressed by improving work systems.

Primary Care Clinicians' Beliefs and Strategies for Managing Chronic Pain in an Era of a National Opioid Epidemic.

BACKGROUND: Little is known about how primary care clinicians (PCCs) approach chronic pain management in the current climate of rapidly changing guidelines and the growing body of research about risks and benefits of opioid therapy. OBJECTIVE: To better understand PCCs' approaches to managing patients with chronic pain and explore implications for technological and administrative interventions. DESIGN: We conducted adapted critical decision method interviews with 20 PCCs. Each PCC participated in 1-5 interviews. PARTICIPANTS: PCCs interviewed had a mean of 14 years of experience. They were sampled from 13 different clinics in rural, suburban, and urban health settings across the state of Indiana. APPROACH: Interviews included discussion of participants' general approach to managing chronic pain, as well as in-depth discussion of specific patients with chronic pain. Interviews were audio recorded. Transcripts were analyzed thematically. KEY RESULTS: PCCs reflected on strategies they use to encourage and motivate patients. We identified four associated strategic themes: (1) developing trust, (2) eliciting information from the patient, (3) diverting attention from pain to function, and (4) articulating realistic goals for the patient. In discussion of chronic pain management, PCCs often explained their beliefs about opioid therapy. Three themes emerged: (1) Opioid use tends to reduce function, (2) Opioids are often not effective for long-term pain treatment, and (3) Response to pain and opioids is highly variable. CONCLUSIONS: PCC beliefs about opioid therapy generally align with the clinical evidence, but may have some important gaps. These findings suggest the potential value of interventions that include improved access to research findings; organizational changes to support PCCs in spending time with patients to develop rapport and trust, elicit information about pain, and manage patient expectations; and the need for innovative clinical cognitive support.

Factors That Influence Changes to Existing Chronic Pain Management Plans.

BACKGROUND: The objective of this qualitative study is to better understand primary care clinician decision making for managing chronic pain. Specifically, we focus on the factors that influence changes to existing chronic pain management plans. Limitations in guidelines and training leave clinicians to use their own judgment and experience in managing the complexities associated with treating patients with chronic pain. This study provides insight into those judgments based on clinicians' first-person accounts. Insights gleaned from this study could inspire innovations aimed at supporting primary care clinicians (PCCs) in managing chronic pain. METHODS: We conducted 89 interviews with PCCs to obtain their first-person perspective of the factors that influenced changes in treatment plans for their patients. Interview transcripts were analyzed thematically by a multidisciplinary team of clinicians, cognitive scientists, and public health researchers. RESULTS: Seven themes emerged through our analysis of factors that influenced a change in chronic pain management: 1) change in patient condition; 2) outcomes related to treatment; 3) nonadherent patient behavior; 4) insurance constraints; 5) change in guidelines, laws, or policies; 6) approaches to new patients; and 7) specialist recommendations. CONCLUSIONS: Our analysis sheds light on the factors that lead PCCs to change treatment plans for patients with chronic pain. An understanding of these factors can inform the types of innovations needed to support PCCs in providing chronic pain care. We highlight key insights from our analysis and offer ideas for potential practice innovations.

Decision-Centered Design of Patient Information Visualizations to Support Chronic Pain Care.

BACKGROUND: For complex patients with chronic conditions, electronic health records (EHRs) contain large amounts of relevant historical patient data. To use this information effectively, clinicians may benefit from visual information displays that organize and help them make sense of information on past and current treatments, outcomes, and new treatment options. Unfortunately, few clinical decision support tools are designed to support clinical sensemaking. OBJECTIVE: The objective of this study was to describe a decision-centered design process, and resultant interactive patient information displays, to support key clinical decision requirements in chronic noncancer pain care. METHODS: To identify key clinical decision requirements, we conducted critical decision method interviews with 10 adult primary care clinicians. Next, to identify key information needs and decision support design seeds, we conducted a half-day multidisciplinary design workshop. Finally, we designed an interactive prototype to support the key clinical decision requirements and information needs uncovered during the previous research activities. RESULTS: The resulting Chronic Pain Treatment Tracker prototype summarizes the current treatment plan, past treatment history, potential future treatments, and treatment options to be cautious about. Clinicians can access additional details about each treatment, current or past, through modal views. Additional decision support for potential future treatments and treatments to be cautious about is also provided through modal views. CONCLUSION: This study designed the Chronic Pain Treatment Tracker, a novel approach to decision support that presents clinicians with the information they need in a structure that promotes quick uptake, understanding, and action.

Alerts for community pharmacist-provided medication therapy management: recommendations from a heuristic evaluation.

BACKGROUND: Medication therapy management (MTM) is a service, most commonly provided by pharmacists, intended to identify and resolve medication therapy problems (MTPs) to enhance patient care. MTM is typically documented by the community pharmacist in an MTM vendor's web-based platform. These platforms often include integrated alerts to assist the pharmacist with assessing MTPs. In order to maximize the usability and usefulness of alerts to the end users (e.g., community pharmacists), MTM alert design should follow principles from human factors science. Therefore, the objectives of this study were to 1) evaluate the extent to which alerts for community pharmacist-delivered MTM align with established human factors principles, and 2) identify areas of opportunity and recommendations to improve MTM alert design. METHODS: Five categories of MTM alerts submitted by community pharmacists were evaluated: 1) indication, 2) effectiveness; 3) safety; 4) adherence; and 5) cost-containment. This heuristic evaluation was guided by the Instrument for Evaluating Human-Factors Principles in Medication-Related Decision Support Alerts (I-MeDeSA) which we adapted and contained 32 heuristics. For each MTM alert, four analysts' individual ratings were summed and a mean score on the modified I-MeDeSA computed. For each heuristic, we also computed the percent of analyst ratings indicating alignment with the heuristic. We did this for all alerts evaluated to produce an "overall" summary of analysts' ratings for a given heuristic, and we also computed this separately for each alert category. Our results focus on heuristics where ≤50% of analysts' ratings indicated the alerts aligned with the heuristic. RESULTS: I-MeDeSA scores across the five alert categories were similar. Heuristics pertaining to visibility and color were generally met. Opportunities for improvement across all MTM alert categories pertained to the principles of alert prioritization; text-based information; alarm philosophy; and corrective actions. CONCLUSIONS: MTM alerts have several opportunities for improvement related to human factors principles, resulting in MTM alert design recommendations. Enhancements to MTM alert design may increase the effectiveness of MTM delivery by community pharmacists and result in improved patient outcomes.

Medication decision-making for patients with renal insufficiency in inpatient and outpatient care at a US Veterans Affairs Medical Centre: a qualitative, cognitive task analysis.

BACKGROUND: Many studies identify factors that contribute to renal prescribing errors, but few examine how healthcare professionals (HCPs) detect and recover from an error or potential patient safety concern. Knowledge of this information could inform advanced error detection systems and decision support tools that help prevent prescribing errors. OBJECTIVE: To examine the cognitive strategies that HCPs used to recognise and manage medication-related problems for patients with renal insufficiency. DESIGN: HCPs submitted documentation about medication-related incidents. We then conducted cognitive task analysis interviews. Qualitative data were analysed inductively. SETTING: Inpatient and outpatient facilities at a major US Veterans Affairs Medical Centre. PARTICIPANTS: Physicians, nurses and pharmacists who took action to prevent or resolve a renal-drug problem in patients with renal insufficiency. OUTCOMES: Emergent themes from interviews, as related to recognition of renal-drug problems and decision-making processes. RESULTS: We interviewed 20 HCPs. Results yielded a descriptive model of the decision-making process, comprised of three main stages: detect, gather information and act. These stages often followed a cyclical path due largely to the gradual decline of patients' renal function. Most HCPs relied on being vigilant to detect patients' renal-drug problems rather than relying on systems to detect unanticipated cues. At each stage, HCPs relied on different cognitive cues depending on medication type: for renally eliminated medications, HCPs focused on gathering renal dosing guidelines, while for nephrotoxic medications, HCPs investigated the need for particular medication therapy, and if warranted, safer alternatives. CONCLUSIONS: Our model is useful for trainees so they can gain familiarity with managing renal-drug problems. Based on findings, improvements are warranted for three aspects of healthcare systems: (1) supporting the cyclical nature of renal-drug problem management via longitudinal tracking mechanisms, (2) providing tools to alleviate HCPs' heavy reliance on vigilance and (3) supporting HCPs' different decision-making needs for renally eliminated versus nephrotoxic medications.

Adapting Cognitive Task Analysis to Investigate Clinical Decision Making and Medication Safety Incidents.

OBJECTIVES: Cognitive task analysis (CTA) can yield valuable insights into healthcare professionals' cognition and inform system design to promote safe, quality care. Our objective was to adapt CTA-the critical decision method, specifically-to investigate patient safety incidents, overcome barriers to implementing this method, and facilitate more widespread use of cognitive task analysis in healthcare. METHODS: We adapted CTA to facilitate recruitment of healthcare professionals and developed a data collection tool to capture incidents as they occurred. We also leveraged the electronic health record (EHR) to expand data capture and used EHR-stimulated recall to aid reconstruction of safety incidents. We investigated 3 categories of medication-related incidents: adverse drug reactions, drug-drug interactions, and drug-disease interactions. Healthcare professionals submitted incidents, and a subset of incidents was selected for CTA. We analyzed several outcomes to characterize incident capture and completed CTA interviews. RESULTS: We captured 101 incidents. Eighty incidents (79%) met eligibility criteria. We completed 60 CTA interviews, 20 for each incident category. Capturing incidents before interviews allowed us to shorten the interview duration and reduced reliance on healthcare professionals' recall. Incorporating the EHR into CTA enriched data collection. CONCLUSIONS: The adapted CTA technique was successful in capturing specific categories of safety incidents. Our approach may be especially useful for investigating safety incidents that healthcare professionals "fix and forget." Our innovations to CTA are expected to expand the application of this method in healthcare and inform a wide range of studies on clinical decision making and patient safety.

"Do You Know What I Know?": How Communication Norms and Recipient Design Shape the Content and Effectiveness of Patient Handoffs.

BACKGROUND: Poor communication during end-of-shift transfers of care (handoffs) is associated with safety risks and patient harm. Despite the common perception that handoffs are largely a one-way transfer of information, researchers have documented that they are complex interactions, guided by implicit social norms and mental frameworks. OBJECTIVES: We investigated communication strategies that resident physicians report deploying to tailor information during face-to-face handoffs that are often based on their implicit inferences about the perceived information needs and potential harm to patients. METHODS/PARTICIPANTS: We interviewed 35 residents in Medicine and Surgery wards at three VA Medical Centers (VAMCs). MAIN MEASURES: We conducted qualitative interviews using audio-recorded semi-structured cognitive task interviews. KEY RESULTS: The effectiveness of handoff communication depends upon three factors: receiver characteristics, type of shift, and patient's condition and perceived acuity. Receiver characteristics, including subjective perceptions about an incoming resident's training or ability levels and their assumed preferences for information (e.g., detailed/comprehensive vs. minimal/"big picture"), influenced content shared during handoffs. Residents handing off to the night team provided more information about patients' medical histories and care plans than residents handing off to the day team, and higher patient acuity merited more detailed information and the medical service(s) involved dictated the types of information conveyed. CONCLUSIONS: We found that handoff communication involves a complex combination of socio-technical information where residents balance relational factors against content and risk. It is not a mechanistic process of merely transferring clinical data but rather is based on learned habits of communication that are context-sensitive and variable, what we refer to as "recipient design." Interventions should focus on raising awareness of times when information is omitted, customized, or expanded based on implicit judgments, the emerging threats such judgments pose to patient care and quality, and the competencies needed to be more explicit in handoff interactions.

Content counts, but context makes the difference in developing expertise: a qualitative study of how residents learn end of shift handoffs.

BACKGROUND: Handoff education is both formal and informal and varies widely across medical school and residency training programs. Despite many efforts to improve clinical handoffs, little evidence has shown meaningful improvement. The objective of this study was to identify residents' perspectives and develop a deeper understanding on the necessary training to conduct safe and effective patient handoffs. METHODS: A qualitative study focused on the analysis of cognitive task interviews targeting end-of-shift handoff experiences with 35 residents from three geographically dispersed VA facilities. The interview data were analyzed using an iterative, consensus-based team approach. Researchers discussed and agreed on code definitions and corresponding case examples. Grounded theory was used to analyze the transcripts. RESULTS: Although some residents report receiving formal training in conducting handoffs (e.g., medical school coursework, resident boot camp/workshops, and handoff debriefing), many residents reported that they were only partially prepared for enacting them as interns. Experiential, practice-based learning (i.e., giving handoffs, covering night shift to match common issues to handoff content) was identified as the most suited and beneficial for delivering effective handoff training. Six skills were described as critical to learning effective handoffs: identifying pertinent information, providing anticipatory guidance, applying acquired clinical knowledge, being concise, incorporating delivery strategies, and appreciating the styles/preferences of handoff recipients. CONCLUSIONS: Residents identified the immersive performance and the experience of covering night shifts as the most important aspects of learning to execute effective handoffs. Formal education alone can miss the critical role of real-time sense-making throughout the process of handing off from one trainee to another. Interventions targeting senior resident mentoring and night shift could positively influence the cognitive and performance capacity for safe, effective handoffs.

A cognitive systems engineering design approach to improve the usability of electronic order forms for medical consultation.

BACKGROUND: During medical referrals, communication barriers between referring and consulting outpatient clinics delay patients' access to health care. One notable opportunity for reducing these barriers is improved usefulness and usability of electronic medical consultation order forms. The cognitive systems engineering (CSE) design approach focuses on supporting humans in managing cognitive complexity in sociotechnical systems. Cognitive complexity includes communication, decision-making, problem solving, and planning. OBJECTIVE: The objective of this research was to implement a CSE design approach to develop a template that supports the cognitive needs of referring clinicians and improves referral communication. METHODS: We conducted interviews and observations with primary care providers and specialists at two major tertiary, urban medical facilities. Using qualitative analysis, we identified cognitive requirements and design guidelines. Next, we designed user interface (UI) prototypes and compared their usability with that of a currently implemented UI at a major Midwestern medical facility. RESULTS: Physicians' cognitive challenges were summarized in four cognitive requirements and 13 design guidelines. As a result, two UI prototypes were developed to support order template search and completion. To compare UIs, 30 clinicians (referrers) participated in a consultation ordering simulation complemented with the think-aloud elicitation method. Oral comments about the UIs were coded for both content and valence (i.e., positive, neutral, or negative). Across 619 comments, the odds ratio for the UI prototype to elicit higher-valenced comments than the implemented UI was 13.5 (95% CI = [9.2, 19.8]), p < .001. CONCLUSION: This study reinforced the significance of applying a CSE design approach to inform the design of health information technology. In addition, knowledge elicitation methods enabled identification of physicians' cognitive requirements and challenges when completing electronic medical consultation orders. The resultant knowledge was used to derive design guidelines and UI prototypes that were more useful and usable for referring physicians. Our results support the implementation of a CSE design approach for electronic medical consultation orders.

"Workin' on Our Night Moves": How Residents Prepare for Shift Handoffs.

BACKGROUND: Poor-quality handoffs have been associated with serious patient consequences. Researchers and educators have answered the call with efforts to increase system safety and resilience by supporting handoffs using increased communication standardization. The focus on strategies for formalizing the content and delivery of patient handoffs has considerable intuitive appeal; however, broader conceptual framing is required to both improve the process and develop and implement effective measures of handoff quality. METHODS: Cognitive task interviews were conducted with internal medicine and surgery residents at three geographically diverse US Department of Veterans Affairs medical centers. Thirty-five residents participated in semistructured interviews using a recent handoff as a prompt for in-depth discussion of goals, strategies, and information needs. Transcribed interview data were analyzed using thematic analysis. RESULTS: Six cognitive tasks emerged during handoff preparation: (1) communicating status and care plan for each patient; (2) specifying tasks for the incoming night shift; (3) anticipating questions and problems likely to arise during the night shift; (4) streamlining patient care task load for the incoming resident; (5) prioritizing problems by acuity across the patient census, and (6) ensuring accurate and current documentation. CONCLUSION: Our study advances the understanding of the influence of the cognitive tasks residents engage in as they prepare to hand off patients from day shift to night shift. Cognitive preparation for the handoff includes activities critical to effective coordination yet easily overlooked because they are not readily observable. The cognitive activities identified point to strategies for cognitive support via improved technology, organizational interventions, and enhanced training.

A Validation Argument for a Simulation-Based Training Course Centered on Assessment, Recognition, and Early Management of Pediatric Sepsis.

INTRODUCTION: Early recognition of sepsis remains one of the greatest challenges in medicine. Novice clinicians are often responsible for the recognition of sepsis and the initiation of urgent management. The aim of this study was to create a validity argument for the use of a simulation-based training course centered on assessment, recognition, and early management of sepsis in a laboratory-based setting. METHODS: Five unique simulation scenarios were developed integrating critical sepsis cues identified through qualitative interviewing. Scenarios were piloted with groups of novice, intermediate, and expert pediatric physicians. The primary outcome was physician recognition of sepsis, measured with an adapted situation awareness global assessment tool. Secondary outcomes were physician compliance with pediatric advanced life support (PALS) guidelines and early sepsis management (ESM) recommendations, measured by two internally derived tools. Analysis compared recognition of sepsis by levels of expertise and measured association of sepsis recognition with the secondary outcomes. RESULTS: Eighteen physicians were recruited, six per study group. Each physician completed three sepsis simulations. Sepsis was recognized in 19 (35%) of 54 simulations. The odds that experts recognized sepsis was 2.6 [95% confidence interval (CI) = 0.5-13.8] times greater than novices. Adjusted for severity, for every point increase in the PALS global performance score, the odds that sepsis was recognized increased by 11.3 (95% CI = 3.1-41.4). Similarly, the odds ratio for the PALS checklist score was 1.5 (95% CI = 0.8-2.6). Adjusted for severity and level of expertise, the odds of recognizing sepsis was associated with an increase in the ESM checklist score of 1.8 (95% CI = 0.9-3.6) and an increase in ESM global performance score of 4.1 (95% CI = 1.7-10.0). CONCLUSIONS: Although incomplete, evidence from initial testing suggests that the simulations of pediatric sepsis were sufficiently valid to justify their use in training novice pediatric physicians in the assessment, recognition, and management of pediatric sepsis.

Information Needs and Requirements for Decision Support in Primary Care: An Analysis of Chronic Pain Care.

Decision support system designs often do not align with the information environments in which clinicians work. These work environments may increase Clinicians' cognitive workload and harm their decision making. The objective of this study was to identify information needs and decision support requirements for assessing, diagnosing, and treating chronic noncancer pain in primary care. We conducted a qualitative study involving 30 interviews with 10 primary care clinicians and a subsequent multidisciplinary systems design workshop. Our analysis identified four key decision requirements, eight clinical information needs, and four decision support design seeds. Our findings indicate that clinicians caring for chronic pain need decision support that aggregates many disparate information elements and helps them navigate and contextualize that information. By attending to the needs identified in this study, decision support designers may improve Clinicians' efficiency, reduce mental workload, and positively affect patient care quality and outcomes.

UNDERSTANDING HOW PRIMARY CARE CLINICIANS MAKE SENSE OF CHRONIC PAIN.

Chronic pain leads to reduced quality of life for patients, and strains health systems worldwide. In the U.S. and some other countries, the complexities of caring for chronic pain are exacerbated by individual and public health risks associated with commonly used opioid analgesics. To help understand and improve pain care, this article uses the data-frame theory of sensemaking to explore how primary care clinicians in the U.S. manage their patients with chronic noncancer pain. We conducted Critical Decision Method interviews with 10 primary care clinicians about 30 individual patients with chronic pain. In these interviews, we identified several patient, social/environmental, and clinician factors that influence the frames clinicians use to assess their patients and determine a pain management plan. Findings suggest significant ambiguity and uncertainty in clinical pain management decision making. Therefore, interventions to improve pain care might focus on supporting sensemaking in the context of clinical evidence rather than attempting to provide clinicians with decontextualized and/or algorithm-based decision rules. Interventions might focus on delivering convenient and easily interpreted patient and social/environmental information in the context of clinical practice guidelines.