Strategies for case-based training with virtual patients: An experimental study of the impact of integrating mental model articulation and self-reflection.

Resilient system performance in high-stakes settings, which includes the ability to monitor, respond, anticipate, and learn, can be enhanced for trainees through simulation of realistic scenarios enhanced by augmented reality. Active learning strategies can enhance simulation-based training, particularly the mental model articulation principle where students are prompted to anticipate what will happen next and the reflection principle where students self-assess their performance compared to a gold standard expert model. In this paper, we compared simulation-based training for trauma care with and without active learning strategies during pauses in the simulated action for progressively deteriorating patients. The training was conducted online and real-time without a facilitator, with 42 medical students viewing training materials and then immediately taking an online quiz for three types of trauma cases: hemorrhage, airway obstruction, and tension pneumothorax. Participants were randomly assigned to either the experimental or control condition in a between-subjects design. We compared performance in the control and experimental conditions based on: A) the proportion of cues correctly recognized, B) the proportion of accurate diagnoses, C) the proportion of appropriate treatment interventions, and D) verbal briefing quality on a 1-5 scale. We found that the training intervention increased recognition of subtle cues critical for accurate diagnosis and appropriate treatment interventions; the training did not improve the accuracy of diagnoses or the quality of the verbal briefing. We conclude that incorporating active learning strategies in simulation-based training improved foundational capabilities in detecting subtle cues and intervening to rescue deteriorating patients that can increase the readiness for trainees to contribute to resilient system performance in the high-stakes setting of emergency care in hospitals.

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.

Exploring how caregivers for people living with dementia use strategies to overcome work system constraints.

Informal caregivers for persons living with dementia (PLWD) require interventions that incorporate caregiving context. We used the Patient Work System model to characterize caregiving context by identifying work system constraints experienced by caregivers during dementia care events (e.g., managing behavioral symptoms of dementia) and strategies used to overcome constraints. We conducted twenty semi-structured interviews with caregivers. We performed upward abstraction and strategy mapping and identified seven work system constraints and eight strategies used to overcome constraints across three care events. We found that strategies used by caregivers either directly modified a constraint or emphasized other positive work system components to overcome a constraint. For example a caregiver modified their bathroom to support the PLWD in bathing themselves properly and safely. These findings provide an understanding of how real-world context influences how caregivers deliver dementia care and the design and implementation of systems that support dementia caregivers.

How opioid prescribing policies influence primary care clinicians' treatment decisions and conversations with patients with chronic pain.

OBJECTIVE: The 2016 Centers for Disease Control and Prevention guideline for prescribing opioids for chronic pain aimed to assist primary care clinicians in safely and effectively prescribing opioids for chronic noncancer pain. Individual states, payers, and health systems issued similar policies imposing various regulations around opioid prescribing for patients with chronic pain. Experts argued that healthcare organizations and clinicians may be misapplying the federal guideline and subsequent opioid prescribing policies, leading to an inadequate pain management. The objective of this study was to understand how primary care clinicians involve opioid prescribing policies in their treatment decisions and in their conversations with patients with chronic pain. DESIGN: We conducted a secondary qualitative analysis of data from 64 unique primary care visits and 87 post-visit interviews across 20 clinicians from three healthcare systems in the Midwestern United States. Using a multistep process and thematic analysis, we systematically analyzed data excerpts addressing opioid prescribing policies. RESULTS: Opioid prescribing policies influenced clinicians' treatment decisions to not initiate opioids, prescribe fewer opioids overall (theme #1), and begin tapering and discontinuation of opioids (theme #2) for most patients with chronic pain. Clinical precautions, described in the opioid prescribing policies to monitor use, were directly invoked during visits for patients with chronic pain (theme #3). CONCLUSIONS: Opioid prescribing policies have multidimensional influence on clinician treatment decisions for patients with chronic pain. Our findings may inform future studies to explore mechanisms for aligning pressures around opioid prescribing, stemming from various opioid prescribing policies, with the need to deliver individualized pain care.

Barriers to single-dose intravesical chemotherapy in non-muscle invasive bladder cancer: what's the problem?

INTRODUCTION: The intravesical instillation of mitomycin C immediately following surgery for non-muscle invasive bladder cancer has been shown to be efficacious in reducing cancer recurrence. As a result, the American Urological Association adopted guidelines for non-muscle invasive bladder cancer care to support its use in low to intermediate risk patients. Despite this, urologists' use of this drug following transurethral resection of a bladder tumor (TURBT) has been reported as low as 5% or less. Our study objective was to better understand the barriers urologists experience in using mitomycin C. METHODS: Semi-structured interviews were conducted with 13 practicing urologists at 4 geographically distinct practice locations throughout Indiana between 2017 and 2018. Cognitive task analysis was used to explore factors that influenced their clinician decision-making about Mitomycin C use following TURBT in specific patient cases. Interview transcripts were coded and analyzed using immersion/crystallization to identify emergent themes. RESULTS: The median age of the urologists interviewed was 44 (IQR 40-48). Eighty-five percent were male. Approximately 30% had completed urologic fellowship training; 62% were in private practice. Three major themes related to the use of mitomycin C emerged: cumbersome workflow processes, urologists' fears of side effects, and issues of identifying patients most likely to benefit. CONCLUSION: Workflow, fear, and value are key factors and also represent complexities of translating efficacy into effectiveness for a drug with known benefits to patients. Areas of potential intervention development to improve the use of mitomycin C to reduce recurrence of bladder cancer are suggested. Alternatives such as gemcitabine may also help overcome these barriers.

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.

Cognitive requirements for primary care providers during the referral process: Information needed from and interactions with an electronic health record system.

OBJECTIVES: This study sought to identify and describe the cognitive requirements and associated information needs of referring primary care providers (PCPs) during the referral process as well as characterize referring PCPs' experiences with current health information technology. MATERIALS AND METHODS: We interviewed 62 referring PCPs. Our four-member analysis team used hierarchical task analysis to construct a goal-directed hierarchy. We utilized extensions of the task analysis to describe PCPs' common experiences with health information technologies throughout the referral process. RESULTS: The resultant goal hierarchy includes one main goal (Referral for Additional Care), two sub-goals (Assess Patient's Condition and Manage Referrals), and four major tasks with respective decisions (What consultation is warranted; What information should I provide; What additional action is needed; and How to integrate specialists' findings). Approximately 22 information needs were commonly identified and PCPs described their use of various sources - other PCPs, electronic health records, chat software, and paper- to satisfy those information needs. CONCLUSION: Cognitive demand for referring PCPs is high throughout the referral process. They have to search, identify, compose, track, and integrate information across multiple screens, systems, and people. Existing interfaces do not adequately support the communication, information exchange, or care coordination related to the referral process. Results from this study provide an important foundation for developing patient-centered displays that support PCPs' decision-making process and reduce cognitive challenges.

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.