Ashley N. D. Meyer

Cognitive interventions to reduce diagnostic error: a narrative review

Background Errors in clinical reasoning occur in most cases in which the diagnosis is missed, delayed or wrong. The goal of this review was to identify interventions that might reduce the likelihood of these cognitive errors. Design We searched PubMed and other medical and non-medical databases and identified additional literature through references from the initial data set and suggestions from subject matter experts. Articles were included if they either suggested a possible intervention or formally evaluated an intervention and excluded if they focused solely on improving diagnostic tests or provider satisfaction. Results We identified 141 articles for full review, 42 reporting tested interventions to reduce the likelihood of cognitive errors, 100 containing suggestions, and one article with both suggested and tested interventions. Articles were classified into three categories: (1) Interventions to improve knowledge and experience, such as simulation-based training, improved feedback and education focused on a single disease; (2) Interventions to improve clinical reasoning and decision-making skills, such as reflective practice and active metacognitive review; and (3) Interventions that provide cognitive ‘help’ that included use of electronic records and integrated decision support, informaticians and facilitating access to information, second opinions and specialists. Conclusions We identified a wide range of possible approaches to reduce cognitive errors in diagnosis. Not all the suggestions have been tested, and of those that have, the evaluations typically involved trainees in artificial settings, making it difficult to extrapolate the results to actual practice. Future progress in this area will require methodological refinements in outcome evaluation and rigorously evaluating interventions already suggested, many of which are well conceptualised and widely endorsed.

The frequency of diagnostic errors in outpatient care: estimations from three large observational studies involving US adult populations

Background The frequency of outpatient diagnostic errors is challenging to determine due to varying error definitions and the need to review data across multiple providers and care settings over time. We estimated the frequency of diagnostic errors in the US adult population by synthesising data from three previous studies of clinic-based populations that used conceptually similar definitions of diagnostic error. Methods Data sources included two previous studies that used electronic triggers, or algorithms, to detect unusual patterns of return visits after an initial primary care visit or lack of follow-up of abnormal clinical findings related to colorectal cancer, both suggestive of diagnostic errors. A third study examined consecutive cases of lung cancer. In all three studies, diagnostic errors were confirmed through chart review and defined as missed opportunities to make a timely or correct diagnosis based on available evidence. We extrapolated the frequency of diagnostic error obtained from our studies to the US adult population, using the primary care study to estimate rates of diagnostic error for acute conditions (and exacerbations of existing conditions) and the two cancer studies to conservatively estimate rates of missed diagnosis of colorectal and lung cancer (as proxies for other serious chronic conditions). Results Combining estimates from the three studies yielded a rate of outpatient diagnostic errors of 5.08%, or approximately 12 million US adults every year. Based upon previous work, we estimate that about half of these errors could potentially be harmful. Conclusions Our population-based estimate suggests that diagnostic errors affect at least 1 in 20 US adults. This foundational evidence should encourage policymakers, healthcare organisations and researchers to start measuring and reducing diagnostic errors.

Electronic Trigger-Based Intervention to Reduce Delays in Diagnostic Evaluation for Cancer: A Cluster Randomized Controlled Trial

PURPOSE We tested whether prospective use of electronic health record-based trigger algorithms to identify patients at risk of diagnostic delays could prevent delays in diagnostic evaluation for cancer. METHODS We performed a cluster randomized controlled trial of primary care providers (PCPs) at two sites to test whether triggers that prospectively identify patients with potential delays in diagnostic evaluation for lung, colorectal, or prostate cancer can reduce time to follow-up diagnostic evaluation. Intervention steps included queries of the electronic health record repository for patients with abnormal findings and lack of associated follow-up actions, manual review of triggered records, and communication of this information to PCPs via secure e-mail and, if needed, phone calls to ensure message receipt. We compared times to diagnostic evaluation and proportions of patients followed up between intervention and control cohorts based on final review at 7 months. RESULTS We recruited 72 PCPs (36 in the intervention group and 36 in the control group) and applied the trigger to all patients under their care from April 20, 2011, to July 19, 2012. Of 10,673 patients with abnormal findings, the trigger flagged 1,256 patients (11.8%) as high risk for delayed diagnostic evaluation. Times to diagnostic evaluation were significantly lower in intervention patients compared with control patients flagged by the colorectal trigger (median, 104 v 200 days, respectively; n = 557; P < .001) and prostate trigger (40% received evaluation at 144 v 192 days, respectively; n = 157; P < .001) but not the lung trigger (median, 65 v 93 days, respectively; n = 19; P = .59). More intervention patients than control patients received diagnostic evaluation by final review (73.4% v 52.2%, respectively; relative risk, 1.41; 95% CI, 1.25 to 1.58). CONCLUSION Electronic trigger-based interventions seem to be effective in reducing time to diagnostic evaluation of colorectal and prostate cancer as well as improving the proportion of patients who receive follow-up. Similar interventions could improve timeliness of diagnosis of other serious conditions.

Challenges of making a diagnosis in the outpatient setting: a multi-site survey of primary care physicians

Background Although misdiagnosis in the outpatient setting leads to significant patient harm and wasted resources, it is not well studied. The authors surveyed primary care physicians (PCPs) about barriers to timely diagnosis in the outpatient setting and assessed their perceptions of diagnostic difficulty. Methods Surveys of PCPs practicing in an integrated health system across 10 geographically dispersed states in 2005. The survey elicited information on key cognitive failures (including in clinical knowledge or judgement) for a specific case, and solicited strategies for reducing diagnostic delays. Content analysis was used to categorise cognitive failures and strategies for improvement. The authors examined the extent and predictors of diagnostic difficulty, defined as reporting >5% patients difficult to diagnose. Results Of 1817 physicians surveyed, 1054 (58%) responded; 848 (80%) respondents primarily practiced in outpatient settings and had an assigned patient panel (inclusion sample). Inadequate knowledge (19.9%) was the most commonly reported cognitive factor. Half reported >5% of their patients were difficult to diagnose; more experienced physicians reported less diagnostic difficulty. In adjusted analyses, problems with information processing (information availability and time to review it) and the referral process were associated with greater diagnostic difficulty. Strategies for improvement most commonly involved workload issues (panel size, non-visit tasks). Conclusions PCPs report a variety of reasons for diagnostic difficulties in primary care practice. In this study, knowledge gaps appear to be a prominent concern. Interventions that address these gaps as well as practice level issues such as time to process diagnostic information and better subspecialty input may reduce diagnostic difficulties in primary care.

The Burden of Inbox Notifications in Commercial Electronic Health Records

The Burden of Inbox Notifications in Commercial Electronic Health Records With wider use of electronic health records (EHRs), physicians increasingly receive notifications via EHR-based inboxes (eg, Epic’s In-Basket and General Electric Centricity’s Documents). Examples of types of notifications include test results, responses to referrals, requests for medication refills, and messages from physicians and other healthcareprofessionals.1,2 PreviousworkwithintheDepartment of Veterans Affairs found that health care professionals receive large quantities of EHR-based notifications, making it harder to discern important vs irrelevant information and increasing their risk of overlooking abnormal test results.3-6 Information overload is of emerging concern because new types of notifications and “FYI” (for your information) messages can be easily created in the EHR (vs in a paper-based system). Furthermore, the additional workload to read and process these messages remains uncompensated in an environment of reduced reimbursements for office-based care.1,2,4 Conversely, EHRs make it easier to measure the amount of information received. We quantified the notifications that physicians received via inboxes of commercial EHRs to estimate their burden.

Patient-Initiated Second Opinions: Systematic Review of Characteristics and Impact on Diagnosis, Treatment, and Satisfaction

The impact of second opinions on diagnosis in radiology and pathology is well documented; however, the value of patient-initiated second opinions for diagnosis and treatment in general medical practice is unknown. We conducted a systematic review of patient-initiated second opinions to assess their impact on clinical outcomes and patient satisfaction and to determine characteristics and motivating factors of patients who seek a second opinion. We searched PubMed, EMBASE, Cochrane, and Academic OneFile databases using Medical Subject Headings (MeSH) indexes and keyword searches. Search terms included referral and consultation, patient-initiated, patient preference, patient participation, second opinion, second review, and diagnosis. Multiple reviewers screened abstracts and articles to determine eligibility and extract data. We assessed risk of bias using the Cochrane Risk of Bias Tool and rated study quality using Cochranes GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach. We screened 1342 abstracts and reviewed full text of 41 articles, identifying 7 articles that reported clinical agreement data and 10 that discussed patient characteristics, motivation, and satisfaction. We found that a second opinion typically confirms the original diagnosis or treatment regimen but that 90% of patients with poorly defined conditions remain undiagnosed. However, 10% to 62% of second opinions yield a major change in the diagnosis, treatment, or prognosis. A larger fraction of patients receive different advice on treatment than on diagnosis. Factors motivating a second opinion include diagnosis or treatment confirmation, dissatisfaction with a consultation, desire for more information, persistent symptoms, or treatment complications. Patients generally believed that second opinions were valuable. Second opinions can result in diagnostic and treatment differences. The literature on patient-initiated second opinions is limited, and the accuracy of the second opinion through follow-up is generally unknown. Standardized methods and outcome measures are needed to determine the value of second opinions, and the potential of second opinions to reduce diagnostic errors merits more rigorous evaluation.

Electronic health record–related safety concerns: A cross-sectional survey

Federal electronic health record (EHR)-related initiatives are leading to rapid increases in their adoption. Despite their benefits, EHRs also introduce new risks that can lead to serious safety events. We conducted a Web-based survey of the American Society for Healthcare Risk Management and the American Health Lawyers Association to elicit perceptions regarding the frequency and types of EHR-related serious safety events. We received 369 responses. The majority (66%) worked for large hospitals and health systems with varying degrees of EHR adoption. More than half (53%) of respondents reported at least one EHR-related serious safety event in the previous 5 years, and 10% reported more than 20 events. EHR workflow (63%), user familiarity with the EHR system (63%), and integration with existing systems (59%) were most frequently endorsed as variables associated with EHR-related serious safety events. Because EHR-related safety concerns are underreported, organizations should consider implementing robust measures of EHR safety within their institution as a key step for mitigating these concerns.

Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed

Background Despite visits to multiple physicians, many patients remain undiagnosed. A new online program, CrowdMed, aims to leverage the “wisdom of the crowd” by giving patients an opportunity to submit their cases and interact with case solvers to obtain diagnostic possibilities. Objective To describe CrowdMed and provide an independent assessment of its impact. Methods Patients submit their cases online to CrowdMed and case solvers sign up to help diagnose patients. Case solvers attempt to solve patients’ diagnostic dilemmas and often have an interactive online discussion with patients, including an exchange of additional diagnostic details. At the end, patients receive detailed reports containing diagnostic suggestions to discuss with their physicians and fill out surveys about their outcomes. We independently analyzed data collected from cases between May 2013 and April 2015 to determine patient and case solver characteristics and case outcomes. Results During the study period, 397 cases were completed. These patients previously visited a median of 5 physicians, incurred a median of US

Diagnostic errors related to acute abdominal pain in the emergency department

10,000 in medical expenses, spent a median of 50 hours researching their illnesses online, and had symptoms for a median of 2.6 years. During this period, 357 active case solvers participated, of which 37.9% (132/348) were male and 58.3% (208/357) worked or studied in the medical industry. About half (50.9%, 202/397) of patients were likely to recommend CrowdMed to a friend, 59.6% (233/391) reported that the process gave insights that led them closer to the correct diagnoses, 57% (52/92) reported estimated decreases in medical expenses, and 38% (29/77) reported estimated improvement in school or work productivity. Conclusions Some patients with undiagnosed illnesses reported receiving helpful guidance from crowdsourcing their diagnoses during their difficult diagnostic journeys. However, further development and use of crowdsourcing methods to facilitate diagnosis requires long-term evaluation as well as validation to account for patients’ ultimate correct diagnoses.

Developing checklists to prevent diagnostic error in Emergency Room settings

Objective Diagnostic errors in the emergency department (ED) are harmful and costly. We reviewed a selected high-risk cohort of patients presenting to the ED with abdominal pain to evaluate for possible diagnostic errors and associated process breakdowns. Design We conducted a retrospective chart review of ED patients >18 years at an urban academic hospital. A computerised ‘trigger’ algorithm identified patients possibly at high risk for diagnostic errors to facilitate selective record reviews. The trigger determined patients to be at high risk because they: (1) presented to the ED with abdominal pain, and were discharged home and (2) had a return ED visit within 10 days that led to a hospitalisation. Diagnostic errors were defined as missed opportunities to make a correct or timely diagnosis based on the evidence available during the first ED visit, regardless of patient harm, and included errors that involved both ED and non-ED providers. Errors were determined by two independent record reviewers followed by team consensus in cases of disagreement. Results Diagnostic errors occurred in 35 of 100 high-risk cases. Over two-thirds had breakdowns involving the patient–provider encounter (most commonly history-taking or ordering additional tests) and/or follow-up and tracking of diagnostic information (most commonly follow-up of abnormal test results). The most frequently missed diagnoses were gallbladder pathology (n=10) and urinary infections (n=5). Conclusions Diagnostic process breakdowns in ED patients with abdominal pain most commonly involved history-taking, ordering insufficient tests in the patient–provider encounter and problems with follow-up of abnormal test results.