The Diagnostic Error in Medicine 13th Annual International Conference

<span title="2021-03-26">2021</span> <i title="Walter de Gruyter GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2qqdhyfp5bhxtdqtwiq3ncbavy" style="color: black;">Diagnosis</a> </i> &nbsp;
Selection Committee Purpose/Problem: Electronic health record (EHR) based simulation provides an opportunity to teach and evaluate clinical reasoning and decision-making skills in a high-fidelity environment. We developed an EHR-simulation session for pediatric residents aimed at introducing diagnostic decision-making tools to overcome cognitive bias; participation was associated with persistent changes to EHR use patterns in clinical practice. Using the Situation Awareness Global Assessment
more &raquo; ... hnique (SAGAT), we developed an instrument to stratify simulation performance across three domains: perception of relevant information, comprehension of information, and projection of potential outcomes. In this study, we conducted the session in a new population, clerkship medical students. Methods: The simulation and assessment were administered to clerkship medical students at the Perelman School of Medicine, as part of a required online course. Students were directed to assume the role of an admitting resident and were given 15 minutes to review a simulated EHR chart of an infant with physiologic hyperbilirubinemia and complete a simplified SAGAT. While documentation suggests the patient is stable, embedded safety probes, including unstable vital signs and labs, suggest neonatal sepsis. The session concluded with a virtual debriefing session to review the case and emphasize the utility of data visualization and information retrieval tools in the EHR. Outcomes: Five cohorts of clerkship medical students (n=106) participated in the simulation. The vast majority (96.2%) correctly perceived the heart rate. In the comprehension domain, 38.1% of students included abnormal vital signs and/or sepsis in a problem representation of the case. Responses on the projection item were mixed-58.5% of students concluded that the patient was stable for transfer to the floor, while the remainder thought more discussion was needed (34%) or that the patient was not stable for transfer (7.5%). Discussion: We implemented an EHR based simulation and decision-making assessment in clerkship medical students. Initial results indicate that medical students perform similarly to pediatrics residents in the perception and comprehension domains of the instrument. More detailed analysis is required to confirm and explore this trend. This study demonstrates that this simulation and assessment tool can be applied to different levels of learner. Significance: EHR based simulation provides an opportunity to evaluate and address deficits in diagnostic decisionmaking. A simulation-based strategy for assessment of clinical decision-making in medical students can be used to enhance clinical reasoning and diagnostic error education. Background: The patient-centered definition of diagnostic error encompasses a failure to establish a timely explanation for a patient's problem and failure to communicate that explanation to the patient. However, little is known from a linguistic perspective about how diagnostic statements are delivered to patients, i.e. how clinicians name, describe or explain the health problem to patients, and how these statements relate to diagnostic accuracy. eA2 Methods: To identify temporal and discursive features in diagnostic statements, we analysed transcripts from 16 videorecorded interactions. Interactions were part of an objective structured clinical examination (OSCE) station conducted as part of a practice high-stakes exam for internationally trained clinicians (25% female, n=4) to gain accreditation to practice in Australia. The 8-minute OSCE revolved around a 3yo child with trouble settling at night, increased irritability and pulling at his ear. The ear examination depicted a bright blue object in the child's ear canal. We analysed time spent on history-taking, examination and delivery of diagnostic statements. We then extracted and deductively analysed types of diagnostic statements informed by literature, ranging from a) plain assertion, to b) epistemic modality (modal verbs and personal judgements), c) evidentialised (alluding to diagnostic process or explicitly describing observations) and d) epidemiological generalisations. Results: Fifty percent of participants communicated the accurate diagnosis 'foreign body' (FB) (n=8). Seven clinicians incorrectly diagnosed Otitis Media (OM) after ear examination and one diagnosed behavioural issues without ear examination. Total duration for history taking ranged from 85 to 210 seconds (s), and for diagnostic statements from 10 to 105s. On average, clinicians who made a diagnostic error took 30s less in history taking (140s, SD: 44s) and 30s more in providing diagnosis (68s, SD: 25s) than clinicians who accurately diagnosed FB (History: 170s, SD: 36s; Diagnosis: 37s, SD: 22s). The majority of diagnostic statements were evidentialised (describing specific observations (n=23) or alluding to diagnostic processes (n=7)), followed by epistemic modality (n=8), generalisations (n=6) and assertions (n=4). Overall, clinicians who misdiagnosed provided more specific observations (n=14) than those who diagnosed correctly (n=9). Conclusion: Evidentialised diagnostic statements provide evidence to support a diagnosis and make diagnostic reasoning explicit to the patient. Our preliminary results suggest that in interactions where there is a diagnostic error, clinicians made longer diagnostic statements that featured more evidence. It appears clinicians might use more evidence statements to support uncertain diagnoses. Larger future studies are needed to explore links between evidentialised diagnostic statements and diagnostic uncertainty. Background: Diagnostic errors in critical illness remain poorly understood in patient safety research, which limits our understanding and ability to design future interventions aimed at reducing diagnostic errors in the acute care setting. The primary objectives of this study were to explore clinicians' perceptions of the occurrence and factors associated with diagnostic errors in patients evaluated during a rapid response team (RRT) activation or unplanned admission to the intensive care unit (ICU). Methods: A multicenter prospective survey study was conducted among multi-professional clinicians involved in the care of patients with RRT activations and/or unplanned ICU admissions at two academic medical centers and one community-based hospital between April 2019 and March 2020. A study investigator screened eligible patients every day. Within 24 hours of the event, a research coordinator administered the survey to clinicians, who were asked: whether diagnostic errors contributed to the reason for evaluation; whether any new diagnosis was made following evaluation; if there were any failures to communicate the diagnosis; and if involvement of specialists earlier would have benefited that patient. Patient clinical data were extracted from the electronsic health record. All data were collected in REDCap and analyzed using JMP Pro 14.1.0 software. Results: A total of 1815 patients experienced RRT activations and 1024 patients experienced unplanned ICU admissions, with 798 and 440 respectively deemed eligible. Surveys were sent out to clinicians in 963 patient care episodes in total. We received at least one survey on 522 patients (54.2%). Among completed surveys, clinicians reported that 18.2% (95/522) of patients experienced diagnostic errors; 8.0% (42/522) experienced a failure of communication; 16.7% (87/522) may have benefitted from earlier involvement of specialists. Compared to academic settings, clinicians in the community hospital eA3 were less likely to report diagnostic errors (7.0% vs 22.8%, P=0.002). When the analysis was restricted to perceptions from attending physicians only, the median SOFA score was significantly higher in patients considered to have errors compared to those who were not (7 vs 4, P=0.004). Clinicians reported that more patients with errors experienced failure of communication and failure to involve a specialist earlier (26.9% vs 5.2%, P<0.001 and 53.9% vs 5.1%, P<0.001, respectively), compared to patients without errors. Conclusions: Critical care clinicians report a high rate of diagnostic errors in patients they evaluate during RRT activations or unplanned ICU admissions. Efforts that are likely to reduce diagnostic errors may benefit from focusing on improving communication and multidisciplinary team cooperation. Statement of Problem: The incidence and impact of diagnostic errors (DxEs) among children evaluated in emergency departments (EDs) and urgent cares (UCs) has not been described. DxEs arising during ED/UC visits rarely come to the attention of individual providers or hospital systems unless the error results in significant harm or medico-legal action. Defining the incidence of DxEs in the ED/UC will improve the ability to identify specific and recurrent vulnerabilities in the diagnostic process amenable to systematic improvement in diagnostic performance. Description of the Intervention: Using the framework described by H. Singh and colleagues, we developed an e-trigger process to identify patients at high risk of DxEs evaluated in a large pediatric hospital system (5 satellite ED/UCs; 1 regional pediatric trauma center ED) with ∼162,000 combined annual visits and ∼12,000 admissions. Attention focused on episodes that included evaluation and discharge from an index ED/UC visit with an unplanned admission within the subsequent 14 days. A clinical research informaticist developed an algorithm to identify candidate encounters and extract demographic information and up to three diagnoses from the ED encounter and subsequent discharge summary. A physician or nurse screened candidate encounters for those in which the index visit diagnosis differed from the hospital discharge diagnosis (i.e. detection criteria for possible DxE). Encounters were then reviewed by a physician using the Revised SaferDx instrument to determine if the episode constituted a DxE. Findings to Date: In 2018, the algorithm identified 926 cases (7.9% of all ED/UC admissions) of which 251 (27.1%) screened in for review using SaferDx. Reviewers identified 47 DxEs (5.07%); 25.5% required ICU care; one patient died. Figure 1: Study flow for rapid response team activations (RRTs) and unplanned ICU admissions (UIAs) cohorts used in this study with inclusion and exclusion criteria. Purpose/Problem: Despite many dermatology residency programs incorporating teledermatology into their curriculums, few studies have analyzed its impact on resident experience and education. To address this gap, we evaluated the teledermatology program at the Zuckerberg San Francisco General Hospital and Trauma Center (ZSFG). Description of Program, Assessment, or Study: Following teledermatology implementation in January 2015, referring providers were required to upload patient photographs and a brief history through a web-based telemedicine platform for all dermatology patient referrals at ZSFG. During a dedicated weekly session that averaged 100 minutes, a team of 3-4 dermatology residents and an attending dermatologist met to review an average of 70 teledermatology cases. Cases were first reviewed by a resident and then presented to the attending who helped finalize the assessment and plan in the telemedicine platform. For the qualitative analysis, we asked current and former UCSF dermatology residents to provide narrative comments about their teledermatology experiences at ZSFG. These responses were coded emergently and evaluated through inductive thematic analysis with focus on manifest content. For the quantitative analysis, we compared the number of patient cases managed per hour by residents at the in-person dermatology clinic and through teledermatology sessions between June 2017 and December 2017. Outcomes: Fifteen out of twenty-one potential respondents (71%) provided narrative comments. Our coding unearthed five primary content areas about teledermatology providing high case volume, a low-stress learning environment, opportunities to consider a wider differential, focused teaching on visual skills and practice triaging cases. During our study period, residents managed 4.55 cases per hour in dermatology clinic and 11.49 cases per hour in teledermatology sessions. Discussion: Our thematic analysis highlighted the features of teledermatology that residents found most beneficial. Pinpointing the aspects of teledermatology that are most educationally salient is an important first step towards establishing guidelines for teledermatology-based education best practices. Our finding that teledermatology enabled more than double the amount of patient cases to be evaluated per unit of resident time is novel, suggesting that teledermatology can be an effective tool in helping dermatology residents develop pattern recognition and visual diagnostic abilities. A potential limitation in the external validity of these findings relates to differences in electronic record systems and the process of implementing teledermatology software across different healthcare settings. Significance of findings: Teledermatology can be an effective component of dermatology residency curriculums by enabling residents to efficiently evaluate a high volume of cases while developing pattern recognition abilities. Background: Providing patients access to OpenNotes presents a unique opportunity to engage them in diagnostic safety initiatives. We developed and tested a methodology to allow patients to identify diagnostic concerns by accessing OpenNotes to evaluate their progress notes from their recent visits. We also identified predictors of patient-identified diagnostic concerns. Methods: We created the 'Safer Dx Patient,' a questionnaire adapted from the Safer Dx instrument, to help patients evaluate problems within the diagnostic process (i.e., accuracy of symptoms, physical exam, testing concerns, follow-up instructions, care plan, and diagnosis). Safer Dx Patient also collected variables related to trust in the provider and general feeling about the visit. We identified at-risk patients at Geisinger, a large integrated healthcare system, from October 2019 to April 2020 using an electronic algorithm based on patient visit patterns (index primary care visit followed by an unplanned return visit or admission within 14 days). Patients that were included were 18-85 years old and used Geisinger's patient portal at least once to view their notes. On a daily basis, patients that met the inclusion criteria were sent the questionnaire link in a secure message with instructions to review their clinician's note and a reminder at week 2. Patients were given a $25 gift card for their time. A multivariate logistic regression model was used to evaluate the association between main outcome, "I feel I was correctly diagnosed during my first visit", and the dimensions of the diagnostic process and patient-level variables (trust and feeling about the visits). Results: Of 418 patients, 12.2% (n=51) indicated they felt their diagnosis was incorrect. Multivariate logistic regression showed that patients who indicated that the care plan developed by the provider did not address all medical concerns were 2.8 times more likely to indicate an incorrect diagnosis (95% confidence interval [CI]=1.61-4.68). Additionally, patients who reported an incorrect diagnosis were 2.0 times more likely to not trust the provider (95% CI=1.21-3.36), and 1.4 times more likely to indicate they did not have a good feeling about the visit (95% CI=1.09-1.78). Conclusion: The 'Safer Dx Patient' enables patients to identify diagnostic concerns based on their evaluation of visit notes. Perceptions of care planning, trust in the clinician, and general feeling about a visit play important roles in patients' perception of a diagnosis. The 'Safer Dx Patient' engagement strategy has potential to improve transparency in the diagnostic process, highlight concerns, and lead to better patient-provider relationships. Background: Optimal diagnostic follow-up is critical in order to address the Institute of Medicine's (IOM) mandate for health care professionals to improve diagnostic testing processes. Standardized follow-up of pulmonary nodules often requires diagnostic imaging testing, but the diagnostic imaging process requires multiple steps prior to completion. A eA6 better understanding of the follow-up of pulmonary nodules is needed, as well as identification of factors that might account for variation in the completion of follow-up. Therefore, we sought to assess factors associated with follow-up completion in patients with incidental pulmonary nodules (IPN) on CT scan. Methods: We conducted a 12-month retrospective cohort study at an academic medical center upon IRB approval. All radiology reports of chest, abdomen and pelvis, or spine CT in 2016 were assessed to determine whether a report contained a pulmonary nodule (excluding those with lung cancer) using a previously-validated natural language processing tool. 278 patients with IPN were then randomly selected and follow-up completion (primary outcome measure), defined as either lung biopsy or chest CT performed within 1 year from the index imaging, was assessed using manual review. The institutional Research Data Warehouse was used to extract: 1) patient-specific features including social determinants of health; and 2) organization-related features (e.g. inpatient). Univariate analysis and multivariable logistic regression were used to determine features associated with follow-up completion. Results: 278 study patients (chest=90, abdomen=92, spine=96) were randomly-sampled from 6,283 patients with incidental pulmonary nodules, and no known lung malignancy during the study period. The rate of follow-up completion was 80/278 (28.8%). On multivariable analysis, follow-up testing completion of orders for follow-up from the Emergency Department (ED) (OR: 0.16) was associated with decreased follow-up. Other patient-specific features were not associated with follow-up completion (Table 1) . Conclusion: Follow-up completion for IPN on CT scan remains low. Further initiatives should address transitions in care settings and patient hand-offs, especially for ED patients. Interventions that can promote follow-up completion in patients with pulmonary nodules should be addressed comprehensively. eA8 The processes of early recognition and treatment of pediatric sepsis patients are ever changing within our Emergency Department (ED). Decreasing variability and sustaining improvement in the practice of sepsis care delivery has been challenging and a major focus for meeting the timeliness goals for fluid and antibiotics of the Surviving Sepsis Campaign. To address knowledge gaps among staff and identify new barriers, a Rapid-Cycle Deliberate Practice (RCDP) simulation strategy was used to improve performance. RCDP focuses on rapid acquisition of skills through a practice-pause-teachrepeat model (Fig 1) . Teams worked through the sepsis care algorithm until all steps were accomplished without error and within time goals. Prior to this intervention, barriers to efficient team performance were identified by staff during multiple sepsis huddles and a key driver diagram was developed to address these issues. A simulated sepsis patient scenario was developed for training purposes. Using the RCDP method, a disciplined approach to care delivery was introduced. The need for additional communication surrounding team expectations, continued gaps in knowledge surrounding the vital-sign based electronic sepsis alert and clarification of roles and responsibilities involved in sepsis care were highlighted by this exercise. Through simulated team-based training, variability in care was decreased and marked improvements were noted in staff performance from the initial to final simulation for all teams. In addition, information gained was used to inform further interventions and plan-do-study-act (PDSA) cycles, improving the process of care for pediatric sepsis patients. Conclusion/Implication Rapid cycle deliberate practice simulation was a novel approach in our emergency department. This environment engaged the multidisciplinary team members to learn from each other and improve team performance through repetition and shared, goal-directed objectives. By decreasing the variability of the process of care delivery, our team was able to improve treatment timeliness for both fluid and antibiotic delivery in pediatric sepsis patients. Figure 1: Conceptual Model of Rapid Cycle Deliberate Practice training for sepsis care process improvement. Background: Doctors use diseases probabilities often during their clinical decision making, but in many instances ing the understanding of the concept of probability discloses misunderstanding. Identifying Subadditivity (i.e., the sum of probabilities concerning a single case scenario exceeding 100%) is a way that can uncover this problem. eA46 Background: The incidence diagnostic errors (DxEs) among children evaluated in emergency departments (EDs) and urgent cares (UCs) has not been described. DxEs are infrequently submitted to traditional incident reporting systems precluding opportunities to learn from them. Defining the incidence of DxEs in the ED/UC and describing predisposing patient demographic and clinical characteristics will improve the ability to identify vulnerabilities in the diagnostic process amenable to systematic improvement in diagnostic performance and provide context for measuring improvement. Methods: Retrospective chart review of patients initially evaluated (index visit) in a large pediatric hospital ED/UC system (5 satellite ED/UCs; 1 regional pediatric trauma center ED; 162,347 annual visits) followed by hospital admission within 14 days from January 1 to December 31, 2018. An e-trigger identified cases meeting this definition which were then screened to determine if a possible DxE occurred. Cases screened in were reviewed by two reviewers [Cohen's ? = 0.60 eA52
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