Diagnostic error in mental health: a review.

Diagnostic errors are associated with patient harm and suboptimal outcomes. Despite national scientific efforts to advance definition, measurement and interventions for diagnostic error, diagnosis in mental health is not well represented in this ongoing work. We aimed to summarise the current state of research on diagnostic errors in mental health and identify opportunities to align future research with the emerging science of diagnostic safety. We review conceptual considerations for defining and measuring diagnostic error, the application of these concepts to mental health settings, and the methods and subject matter focus of recent studies of diagnostic error in mental health. We found that diagnostic error is well understood to be a problem in mental healthcare. Although few studies used clear definitions or frameworks for understanding diagnostic error in mental health, several studies of missed, wrong, delayed and disparate diagnosis of common mental disorders have identified various avenues for future research and development. Nevertheless, a lack of clear consensus on how to conceptualise, define and measure errors in diagnosis will pose a barrier to advancement. Further research should focus on identifying preventable missed opportunities in the diagnosis of mental disorders, which may uncover generalisable opportunities for improvement.

Medical Home Implementation and Follow-Up of Cancer-Related Abnormal Test Results in the Veterans Health Administration.

Importance: Lack of timely follow-up of cancer-related abnormal test results can lead to delayed or missed diagnoses, adverse cancer outcomes, and substantial cost burden for patients. Care delivery models, such as the Veterans Affairs' (VA) Patient-Aligned Care Team (PACT), which aim to improve patient-centered care coordination, could potentially also improve timely follow-up of abnormal test results. PACT was implemented nationally in the VA between 2010 and 2012. Objective: To evaluate the long-term association between PACT implementation and timely follow-up of abnormal test results related to the diagnosis of 5 different cancers. Design, Setting, and Participants: This multiyear retrospective cohort study used 14 years of VA data (2006-2019), which were analyzed using panel data-based random-effects linear regressions. The setting included all VA clinics and facilities. The participants were adult patients who underwent diagnostic testing related to 5 different cancers and had abnormal test results. Data extraction and statistical analyses were performed from September 2021 to December 2023. Exposure: Calendar years denoting preperiods and postperiods of PACT implementation, and the PACT Implementation Progress Index Score denoting the extent of implementation in each VA clinic and facility. Main Outcome and Measure: Percentage of potentially missed timely follow-ups of abnormal test results. Results: This study analyzed 6 data sets representing 5 different types of cancers. During the initial years of PACT implementation (2010 to 2013), percentage of potentially missed timely follow-ups decreased between 3 to 7 percentage points for urinalysis suggestive of bladder cancer, 12 to 14 percentage points for mammograms suggestive of breast cancer, 19 to 22 percentage points for fecal tests suggestive of colorectal cancer, and 6 to 13 percentage points for iron deficiency anemia laboratory tests suggestive of colorectal cancer, with no statistically significant changes for α-fetoprotien tests and lung cancer imaging. However, these beneficial reductions were not sustained over time. Better PACT implementation scores were associated with a decrease in potentially missed timely follow-up percentages for urinalysis (0.3-percentage point reduction [95% CI, -0.6 to -0.1] with 1-point increase in the score), and laboratory tests suggestive of iron deficiency anemia (0.5-percentage point reduction [95% CI,-0.8 to -0.2] with 1-point increase in the score). Conclusions and Relevance: This cohort study found that implementation of PACT in the VA was associated with a potential short-term improvement in the quality of follow-up for certain test results. Additional multifaceted sustained interventions to reduce missed test results are required to prevent care delays.

Managing Interruptions to Improve Diagnostic Decision-Making: Strategies and Recommended Research Agenda.

Interruptions are an inevitable occurrence in health care. Interruptions in diagnostic decision-making are no exception and can have negative consequences on both the decision-making process and well-being of the decision-maker. This may result in inaccurate or delayed diagnoses. To date, research specific to interruptions on diagnostic decision-making has been limited, but strategies to help manage the negative impacts of interruptions need to be developed and implemented. In this perspective, we first present a modified model of interruptions to visualize the interruption process and illustrate where potential interventions can be implemented. We then consider several empirically tested strategies from the fields of health care and cognitive psychology that can lay the groundwork for additional research to mitigate effects of interruptions during diagnostic decision-making. We highlight strategies to minimize the negative impacts of interruptions as well as strategies to prevent interruptions altogether. Additionally, we build upon these strategies to propose specific research priorities within the field of diagnostic safety. Identifying effective interventions to help clinicians better manage interruptions has the potential to minimize diagnostic errors and improve patient outcomes.

Electronic Health Records' Support for Primary Care Physicians' Situation Awareness: A Metanarrative Review.

OBJECTIVE: Situation awareness (SA) refers to people's perception and understanding of their dynamic environment. In primary care, reduced SA among physicians increases errors in clinical decision-making and, correspondingly, patients' risk of experiencing adverse outcomes. Our objective was to understand the extent to which electronic health records (EHRs) support primary care physicians (PCPs)' SA during clinical decision-making. METHOD: We conducted a metanarrative review of papers in selected academic databases, including CINAHL and MEDLINE. Eligible studies included original peer-reviewed research published between January 2012 and August 2020 on PCP-EHR interactions. We iteratively queried, screened, and summarized literature focused on EHRs supporting PCPs' clinical decision-making and care management for adults. Then, we mapped findings to an established SA framework to classify external factors (individual, task, and system) affecting PCPs' levels of SA (1-Perception, 2-Comprehension, and 3-Projection) and identified SA barriers. RESULTS: From 1504 articles identified, we included and synthesized 19 studies. Study designs were largely noninterventional. Studies described EHR workflow misalignments, usability issues, and communication challenges. EHR information, including lab results and care plans, was characterized as incomplete, untimely, or irrelevant. Unmet information needs made it difficult for PCPs to obtain even basic SA, Level 1 SA. Prevalent barriers to PCPs developing SA with EHRs were errant mental models, attentional tunneling, and data overload. CONCLUSION: Based on our review, EHRs do not support the development of higher levels of SA among PCPs. Review findings suggest SA-oriented design processes for health information technology could improve PCPs' SA, satisfaction, and decision-making.

Cancer Evaluations During the COVID-19 Pandemic: An Observational Study Using National Veterans Affairs Data.

INTRODUCTION: Fewer cancer diagnoses have been made during the COVID-19 pandemic. Pandemic-related delays in cancer diagnosis could occur from limited access to care or patient evaluation delays (e.g., delayed testing after abnormal results). Follow-up of abnormal test results warranting evaluation for cancer was examined before and during the pandemic. METHODS: Electronic trigger algorithms were applied to the Department of Veterans Affairs electronic health record data to assess follow-up of abnormal test results before (March 10, 2019-March 7, 2020) and during (March 8, 2020-March 6, 2021) the pandemic. RESULTS: Electronic triggers were applied to 8,021,406 veterans' electronic health records to identify follow-up delays for abnormal results warranting evaluation for 5 cancers: bladder (urinalysis with high-grade hematuria), breast (abnormal mammograms), colorectal (positive fecal occult blood tests/fecal immunochemical tests or results consistent with iron deficiency anemia), liver (elevated alpha-fetoprotein), and lung (chest imaging suggestive of malignancy) cancers. Between prepandemic and pandemic periods, test quantities decreased by 12.6%-27.8%, and proportions of abnormal results lacking follow-up decreased for urinalyses (-0.8%), increased for fecal occult blood tests/fecal immunochemical test (+2.3%) and chest imaging (+1.8%), and remained constant for others. Follow-up times decreased for most tests; however, control charts suggested increased delays at 2 stages: early (pandemic beginning) for urinalyses, mammograms, fecal occult blood tests/fecal immunochemical test, iron deficiency anemia, and chest imaging and late (30-45 weeks into pandemic) for mammograms, fecal occult blood tests/fecal immunochemical test, and iron deficiency anemia. CONCLUSIONS: Although early pandemic delays in follow-up may have led to reduced cancer rates, the significant decrease in tests performed is likely a large driver of these reductions. Future emergency preparedness efforts should bolster essential follow-up and testing procedures to facilitate timely cancer diagnosis.

Electronic Co-design (ECO-design) Workshop for Increasing Clinician Participation in the Design of Health Services Interventions: Participatory Design Approach.

BACKGROUND: Participation from clinician stakeholders can improve the design and implementation of health care interventions. Participatory design methods, especially co-design methods, comprise stakeholder-led design activities that are time-consuming. Competing work demands and increasing workloads make clinicians' commitments to typical participatory methods even harder. The COVID-19 pandemic further exacerbated barriers to clinician participation in such interventions. OBJECTIVE: The aim of this study was to explore a web-based participatory design approach to conduct economical, electronic co-design (ECO-design) workshops with primary care clinicians. METHODS: We adapted traditional in-person co-design workshops to web-based delivery and adapted co-design workshop series to fit within a single 1-hour session. We applied the ECO-design workshop approach to codevelop feedback interventions regarding abnormal test result follow-up in primary care. We conducted ECO-design workshops with primary care clinicians at a medical center in Southern Texas, using videoconferencing software. Each workshop focused on one of three types of feedback interventions: conversation guide, email template, and dashboard prototype. We paired electronic materials and software features to facilitate participant interactions, prototyping, and data collection. The workshop protocol included four main activities: problem identification, solution generation, prototyping, and debriefing. Two facilitators were assigned to each workshop and one researcher resolved technical problems. After the workshops, our research team met to debrief and evaluate workshops. RESULTS: A total of 28 primary care clinicians participated in our ECO-design workshops. We completed 4 parallel workshops, each with 5-10 participants. We conducted traditional analyses and generated a clinician persona (ie, representative description) and user interface prototypes. We also formulated recommendations for future ECO-design workshop recruitment, technology, facilitation, and data collection. Overall, our adapted workshops successfully enabled primary care clinicians to participate without increasing their workload, even during a pandemic. CONCLUSIONS: ECO-design workshops are viable, economical alternatives to traditional approaches. This approach fills a need for efficient methods to involve busy clinicians in the design of health care interventions.

Patient and clinician experiences of uncertainty in the diagnostic process: Current understanding and future directions.

OBJECTIVE: Uncertainty occurs throughout the diagnostic process and must be managed to facilitate accurate and timely diagnoses and treatments. Better characterization of uncertainty can inform strategies to manage it more effectively in clinical practice. We provide a comprehensive overview of current literature on diagnosis-related uncertainty describing (1) where patients and clinicians experience uncertainty within the diagnostic process, (2) how uncertainty affects the diagnostic process, (3) roots of uncertainty related to probability/risk, ambiguity, or complexity, and (4) strategies to manage uncertainty. DISCUSSION: Each diagnostic process step involves uncertainty, including patient engagement with the healthcare system; information gathering, interpretation, and integration; formulating working diagnoses; and communicating diagnoses to patients. General management strategies include acknowledging uncertainty, obtaining more contextual information from patients (e.g., gathering occupations and family histories), creating diagnostic safety nets (e.g., informing patients what red flags to look for), engaging in worst case/best case scenario planning, and communicating diagnostic uncertainty to patients, families, and colleagues. Potential strategies tailored to various aspects of diagnostic uncertainty are also outlined. CONCLUSION: Scientific knowledge on diagnostic uncertainty, while previously elusive, is now becoming more clearly defined. Next steps include research to evaluate relationships between management and communication of diagnostic uncertainty and improved patient outcomes.

Advancing Diagnostic Safety Research: Results of a Systematic Research Priority Setting Exercise.

BACKGROUND: Diagnostic errors are a major source of preventable harm but the science of reducing them remains underdeveloped. OBJECTIVE: To identify and prioritize research questions to advance the field of diagnostic safety in the next 5 years. PARTICIPANTS: Ninety-seven researchers and 42 stakeholders were involved in the identification of the research priorities. DESIGN: We used systematic prioritization methods based on the Child Health and Nutrition Research Initiative (CHNRI) methodology. We first invited a large international group of expert researchers in various disciplines to submit research questions while considering five prioritization criteria: (1) usefulness, (2) answerability, (3) effectiveness, (4) potential for translation, and (5) maximal potential for effect on diagnostic safety. After consolidation, these questions were prioritized at an in-person expert meeting in April 2019. Top-ranked questions were subsequently reprioritized through scoring on the five prioritization criteria using an online questionnaire. We also invited non-research stakeholders to assign weights to the five criteria and then used these weights to adjust the final prioritization score for each question. KEY RESULTS: Of the 207 invited researchers, 97 researchers responded and 78 submitted 333 research questions which were then consolidated. Expert meeting participants (n = 21) discussed questions in different breakout sessions and prioritized 50, which were subsequently reduced to the top 20 using the online questionnaire. The top 20 questions addressed mostly system factors (e.g., implementation and evaluation of information technologies), teamwork factors (e.g., role of nurses and other health professionals in the diagnostic process), and strategies to engage patients in the diagnostic process. CONCLUSIONS: Top research priorities for advancing diagnostic safety in the short-term include strengthening systems and teams and engaging patients to support diagnosis. High-priority areas identified using these systematic methods can inform an actionable research agenda for reducing preventable diagnostic harm.

A Program to Provide Clinicians with Feedback on Their Diagnostic Performance in a Learning Health System.

PROBLEM: Reducing diagnostic errors requires improving both systems and individual clinical reasoning. One strategy to achieve diagnostic excellence is learning from feedback. However, clinicians remain uncomfortable receiving feedback on their diagnostic performance. Thus, a team of researchers and clinical leaders aimed to develop and implement a diagnostic performance feedback program for learning that mitigates potential clinician discomfort. APPROACH: The program was developed as part of a larger project to create a learning health system around diagnostic safety at Geisinger, a large, integrated health care system in rural Pennsylvania. Steps included identifying potential missed opportunities in diagnosis (MODs) from various sources (for example, risk management, clinician reports, patient complaints); confirming MODs through chart review; and having trained facilitators provide feedback to clinicians about MODs as learning opportunities. The team developed a guide for facilitators to conduct effective diagnostic feedback sessions and surveyed facilitators and recipients about their experiences and perceptions of the feedback sessions. OUTCOMES: 28 feedback sessions occurred from January 2019 to June 2020, involving MODs from emergency medicine, primary care, and hospital medicine. Most facilitators (90.6% [29/32]) reported that recipients were receptive to learning and discussing MODs. Most recipients reported that conversations were constructive and nonpunitive (83.3% [25/30]) and allowed them to take concrete steps toward improving diagnosis (76.7% [23/30]). Both groups believed discussions would improve future diagnostic safety (93.8% [30/32] and 70.0% [21/30], respectively). KEY INSIGHTS AND NEXT STEPS: An institutional program was developed and implemented to deliver diagnostic performance feedback. Such a program may facilitate learning and improvement to reduce MODs. Future efforts should assess long-term effects on diagnostic performance and patient outcomes.

Patient Perspectives on the Usefulness of an Artificial Intelligence-Assisted Symptom Checker: Cross-Sectional Survey Study.

BACKGROUND: Patients are increasingly seeking Web-based symptom checkers to obtain diagnoses. However, little is known about the characteristics of the patients who use these resources, their rationale for use, and whether they find them accurate and useful. OBJECTIVE: The study aimed to examine patients' experiences using an artificial intelligence (AI)-assisted online symptom checker. METHODS: An online survey was administered between March 2, 2018, through March 15, 2018, to US users of the Isabel Symptom Checker within 6 months of their use. User characteristics, experiences of symptom checker use, experiences discussing results with physicians, and prior personal history of experiencing a diagnostic error were collected. RESULTS: A total of 329 usable responses was obtained. The mean respondent age was 48.0 (SD 16.7) years; most were women (230/304, 75.7%) and white (271/304, 89.1%). Patients most commonly used the symptom checker to better understand the causes of their symptoms (232/304, 76.3%), followed by for deciding whether to seek care (101/304, 33.2%) or where (eg, primary or urgent care: 63/304, 20.7%), obtaining medical advice without going to a doctor (48/304, 15.8%), and understanding their diagnoses better (39/304, 12.8%). Most patients reported receiving useful information for their health problems (274/304, 90.1%), with half reporting positive health effects (154/302, 51.0%). Most patients perceived it to be useful as a diagnostic tool (253/301, 84.1%), as a tool providing insights leading them closer to correct diagnoses (231/303, 76.2%), and reported they would use it again (278/304, 91.4%). Patients who discussed findings with their physicians (103/213, 48.4%) more often felt physicians were interested (42/103, 40.8%) than not interested in learning about the tool's results (24/103, 23.3%) and more often felt physicians were open (62/103, 60.2%) than not open (21/103, 20.4%) to discussing the results. Compared with patients who had not previously experienced diagnostic errors (missed or delayed diagnoses: 123/304, 40.5%), patients who had previously experienced diagnostic errors (181/304, 59.5%) were more likely to use the symptom checker to determine where they should seek care (15/123, 12.2% vs 48/181, 26.5%; P=.002), but they less often felt that physicians were interested in discussing the tool's results (20/34, 59% vs 22/69, 32%; P=.04). CONCLUSIONS: Despite ongoing concerns about symptom checker accuracy, a large patient-user group perceived an AI-assisted symptom checker as useful for diagnosis. Formal validation studies evaluating symptom checker accuracy and effectiveness in real-world practice could provide additional useful information about their benefit.

Recommendations for using the Revised Safer Dx Instrument to help measure and improve diagnostic safety.

The medical record continues to be one of the most useful and accessible sources of information to examine the diagnostic process. However, medical record review studies of diagnostic errors have often used subjective judgments and found low inter-rater agreement among reviewers when determining the presence or absence of diagnostic error. In our previous work, we developed a structured data-collection instrument, called the Safer Dx Instrument, consisting of objective criteria to improve the accuracy of assessing diagnostic errors in primary care. This paper proposes recommendations on how clinicians and health care organizations could use the Revised Safer Dx Instrument in identifying and understanding missed opportunities to make correct and timely diagnoses. The instrument revisions addressed both methodological and implementation issues identified during initial use and included refinements to the instrument to allow broader application across all health care settings. In addition to leveraging knowledge from piloting the instrument in several health care settings, we gained insights from multiple researchers who had used the instrument in studies involving emergency care, inpatient care and intensive care unit settings. This allowed us to enhance and extend the scope of this previously validated data collection instrument. In this paper, we describe the refinement process and provide recommendations for application and use of the Revised Safer Dx Instrument across a broad range of health care settings. The instrument can help users identify potential diagnostic errors in a standardized way for further analysis and safety improvement efforts as well as provide data for clinician feedback and reflection. With wider adoption and use by clinicians and health systems, the Revised Safer Dx Instrument could help propel the science of measuring and reducing diagnostic errors forward.

Pediatric clinician perspectives on communicating diagnostic uncertainty.

OBJECTIVE: Diagnosis often evolves over time, involves uncertainty, and is vulnerable to errors. We examined pediatric clinicians' perspectives on communicating diagnostic uncertainty to patients' parents and how this occurs. DESIGN: We conducted semi-structured interviews, which were audiotaped, transcribed, and analyzed using content analysis. Two researchers independently coded transcripts and then discussed discrepancies to reach consensus. SETTING: A purposive sample of pediatric clinicians at two large academic medical institutions in Texas. PARTICIPANTS: Twenty pediatric clinicians participated: 18 physicians, 2 nurse practitioners; 7 males, 13 females; 7 inpatient, 11 outpatient, and 2 practicing in mixed settings; with 0-16 years' experience post-residency. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Pediatric clinician perspectives on communication of diagnostic uncertainty. RESULTS: Pediatric clinicians commonly experienced diagnostic uncertainty and most were comfortable seeking help and discussing with colleagues. However, when communicating uncertainty to parents, clinicians used multiple considerations to adjust the degree to which they communicated. Considerations included parent characteristics (education, socioeconomic status, emotional response, and culture) and strength of parent-clinician relationships. Communication content included setting expectations, explaining the diagnostic process, discussing most relevant differentials, and providing reassurance. Responses to certain parent characteristics, however, were variable. For example, some clinicians were more open to discussing diagnostic uncertainty with more educated parents- others were less. CONCLUSIONS: While pediatric clinicians are comfortable discussing diagnostic uncertainty with colleagues, how they communicate uncertainty to parents appears variable. Parent characteristics and parent-clinician relationships affect extent of communication and content discussed. Development and implementation of optimal strategies for managing and communicating diagnostic uncertainty can improve the diagnostic process.

Impact of a national QI programme on reducing electronic health record notifications to clinicians.

BACKGROUND: Emerging evidence suggests electronic health record (EHR)-related information overload is a risk to patient safety. In the US Department of Veterans Affairs (VA), EHR-based 'inbox' notifications originally intended for communicating important clinical information are now cited by 70% of primary care practitioners (PCPs) to be of unmanageable volume. We evaluated the impact of a national, multicomponent, quality improvement (QI) programme to reduce low-value EHR notifications. METHODS: The programme involved three steps: (1) accessing daily PCP notification load data at all 148 facilities operated nationally by the VA; (2) standardising and restricting mandatory notification types at all facilities to a recommended list; and (3) hands-on training for all PCPs on customising and processing notifications more effectively. Designated leaders at each of VA's 18 regional networks led programme implementation using a nationally developed toolkit. Each network supervised technical requirements and data collection, ensuring consistency. Coaching calls and emails allowed the national team to address implementation challenges and monitor effects. We analysed notification load and mandatory notifications preintervention (March 2017) and immediately postintervention (June-July 2017) to assess programme impact. RESULTS: Median number of mandatory notification types at each facility decreased significantly from 15 (IQR: 13-19) to 10 (IQR: 10-11) preintervention to postintervention, respectively (P<0.001). Mean daily notifications per PCP decreased significantly from 128 (SEM=4) to 116 (SEM=4; P<0.001). Heterogeneity in implementation across sites led to differences in observed programme impact, including potentially beneficial carryover effects. CONCLUSIONS: Based on prior estimates on time to process notifications, a national QI programme potentially saved 1.5 hours per week per PCP to enable higher value work. The number of daily notifications remained high, suggesting the need for additional multifaceted interventions and protected clinical time to help manage them. Nevertheless, our project suggests feasibility of using large-scale 'de-implementation' interventions to reduce unintended safety or efficiency consequences of well-intended electronic communication systems.

Inter-rater Agreement for the Diagnosis of Stroke Versus Stroke Mimic.

BACKGROUND AND PURPOSE: Patients who present emergently with acute neurological signs and symptoms represent unique diagnostic challenges for clinicians. We sought to characterize the reliability of physician diagnosis in differentiating aborted or imaging-negative acute ischemic stroke from stroke mimic. METHODS: We constructed 10 case-vignettes of patients treated with thrombolysis with subsequent clinical improvement who lacked radiographic evidence of infarction. Using an online survey, we asked physicians to select a most likely final diagnosis after reading each case-vignette. Inter-rater agreement was evaluated using percent agreement and κ statistic for multiple raters with 95% confidence intervals reported. RESULTS: Sixty-five physicians participated in the survey. Most participants were in practice for ≥5 years and over half were vascular neurologists. Physicians agreed on the most likely final diagnosis 71% of the time, κ of 0.21 (95% confidence interval, 0.06-0.54). Percent agreement was similar across participant practice locations, years of experience, subspecialty training, and personal experience with thrombolysis. CONCLUSIONS: We found modest agreement among surveyed physicians in distinguishing ischemic stroke syndromes from stroke mimics in patients without radiographic evidence of infarction and clinical improvement after thrombolysis. Methods to improve diagnostic consensus after thrombolysis are needed to assure acute ischemic stroke patients and stroke mimics are treated safely and accurately.

Evaluating a mobile application for improving clinical laboratory test ordering and diagnosis.

Objective: Mobile applications for improving diagnostic decision making often lack clinical evaluation. We evaluated if a mobile application improves generalist physicians' appropriate laboratory test ordering and diagnosis decisions and assessed if physicians perceive it as useful for learning. Methods: In an experimental, vignette study, physicians diagnosed 8 patient vignettes with normal prothrombin times (PT) and abnormal partial thromboplastin times (PTT). Physicians made test ordering and diagnosis decisions for 4 vignettes using each resource: a mobile app, PTT Advisor, developed by the Centers for Disease Control and Prevention (CDC)'s Clinical Laboratory Integration into Healthcare Collaborative (CLIHC); and usual clinical decision support. Then, physicians answered questions regarding their perceptions of the app's usefulness for diagnostic decision making and learning using a modified Kirkpatrick Training Evaluation Framework. Results: Data from 368 vignettes solved by 46 physicians at 7 US health care institutions show advantages for using PTT Advisor over usual clinical decision support on test ordering and diagnostic decision accuracy (82.6 vs 70.2% correct; P < .001), confidence in decisions (7.5 vs 6.3 out of 10; P < .001), and vignette completion time (3:02 vs 3:53 min.; P = .06). Physicians reported positive perceptions of the app's potential for improved clinical decision making, and recommended it be used to address broader diagnostic challenges. Conclusions: A mobile app, PTT Advisor, may contribute to better test ordering and diagnosis, serve as a learning tool for diagnostic evaluation of certain clinical disorders, and improve patient outcomes. Similar methods could be useful for evaluating apps aimed at improving testing and diagnosis for other conditions.

Patient perspectives on how physicians communicate diagnostic uncertainty: An experimental vignette study.

OBJECTIVE: We evaluated the effects of three different strategies for communicating diagnostic uncertainty on patient perceptions of physician competence and visit satisfaction. DESIGN/SETTING: Experimental vignette-based study design involving pediatric cases presented to a convenience sample of parents living in a large US city. PARTICIPANTS/INTERVENTION(S): Three vignettes were developed, each describing one of three different ways physicians communicated diagnostic uncertainty to parents-(i) explicit expression of uncertainty ('not sure' about diagnosis), (ii) implicit expression of uncertainty using broad differential diagnoses and (iii) implicit expression of uncertainty using 'most likely' diagnoses. Participants were randomly assigned to one of the three vignettes and then answered a 37-item web-based questionnaire. MAIN OUTCOME MEASURE(S): Outcome variables included parent-perceived technical competence of physician, trust and confidence, visit satisfaction and adherence to physician instructions. Differences between the three groups were compared using analysis of variance, followed by individual post hoc analyses with Bonferroni correction. RESULTS: Seventy-one participants completed the vignette questions. Demographic characteristics and scores on activation (parent activation measure [PAM]) and intolerance to uncertainty were similar across the three groups. Explicit expression of uncertainty was associated with lower perceived technical competence, less trust and confidence, and lower patient adherence as compared to the two groups with implicit communication. These latter two groups had comparable outcomes. CONCLUSION: Parents may react less negatively in terms of perceived competence, physician confidence and trust, and intention to adhere when diagnostic uncertainty is communicated using implicit strategies, such as using broad differential diagnoses or most likely diagnoses. Evidence-based strategies to communicate diagnostic uncertainty to patients need further development.

Development and Validation of Trigger Algorithms to Identify Delays in Diagnostic Evaluation of Gastroenterological Cancer.

BACKGROUND & AIMS: Colorectal cancer (CRC) and hepatocellular cancer (HCC) are common causes of death and morbidity, and patients benefit from early detection. However, delays in follow-up of suspicious findings are common, and methods to efficiently detect such delays are needed. We developed, refined, and tested trigger algorithms that identify patients with delayed follow-up evaluation of findings suspicious of CRC or HCC. METHODS: We developed and validated two trigger algorithms that detect delays in diagnostic evaluation of CRC and HCC using laboratory, diagnosis, procedure, and referral codes from the Department of Veteran Affairs National Corporate Data Warehouse. The algorithm initially identified patients with positive test results for iron deficiency anemia or fecal immunochemical test (for CRC) and elevated α-fetoprotein results (for HCC). Our algorithm then excluded patients for whom follow-up evaluation was unnecessary, such as patients with a terminal illness or those who had already completed a follow-up evaluation within 60 days. Clinicians reviewed samples of both delayed and nondelayed records, and review data were used to calculate trigger performance. RESULTS: We applied the algorithm for CRC to 245,158 patients seen from January 1, 2013, through December 31, 2013 and identified 1073 patients with delayed follow up. In a review of 400 randomly selected records, we found that our algorithm identified patients with delayed follow-up with a positive predictive value of 56.0% (95% CI, 51.0%-61.0%). We applied the algorithm for HCC to 333,828 patients seen from January 1, 2011 through December 31, 2014, and identified 130 patients with delayed follow-up. During manual review of all 130 records, we found that our algorithm identified patients with delayed follow-up with a positive predictive value of 82.3% (95% CI, 74.4%-88.2%). When we extrapolated the findings to all patients with abnormal results, the algorithm identified patients with delayed follow-up evaluation for CRC with 68.6% sensitivity (95% CI, 65.4%-71.6%) and 81.1% specificity (95% CI, 79.5%-82.6%); it identified patients with delayed follow-up evaluation for HCC with 89.1% sensitivity (95% CI, 81.8%-93.8%) and 96.5% specificity (95% CI, 94.8%-97.7%). Compared to nonselective methods, use of the algorithm reduced the number of records required for review to identify a delay by more than 99%. CONCLUSIONS: Using data from the Veterans Affairs electronic health record database, we developed an algorithm that greatly reduces the number of record reviews necessary to identify delays in follow-up evaluations for patients with suspected CRC or HCC. This approach offers a more efficient method to identify delayed diagnostic evaluation of gastroenterological cancers.