The next phase in patient safety education: Towards a standardized, tools-based pathology patient safety curriculum: A call to action from the Association of Pathology Chairs' Residency Program Directors Section Training Residents in Patient Safety Workgroup.

Patient safety education is a mandated Common Program Requirement of the Accreditation Council for Graduate Medical Education and for the Royal College of Physicians and Surgeons of Canada in all medical residency and fellowship programs. Although many hospitals and healthcare environments have general patient safety education tools for trainees, few to none focus on the unique training milieu of pathologists, including a mix of highly automated and manual error-prone processes, frequent multiplicity of events, and lack of direct patient relationships for error disclosure. We established a national Association of Pathology Chairs-Program Directors Section Workgroup focused on patient safety education for pathology trainees entitled Training Residents in Patient Safety (TRIPS). TRIPS included diverse representatives from across the United States, as well as representatives from pathology organizations including the American Board of Pathology, the American Society for Clinical Pathology, the United States and Canadian Academy of Pathology, the College of American Pathologists, and the Society to Improve Diagnosis in Medicine. Objectives of the workgroup included developing a standardized patient safety curriculum, designing teaching and assessment tools, and refining them with pilot sites. Here we report the establishment of TRIPS as well as data from national needs assessment of Program Directors across the country, who confirmed the need for a standardized patient safety curriculum.

Impact of clinical note format on diagnostic accuracy and efficiency.

BACKGROUND: Clinician notes are structured in a variety of ways. This research pilot tested an innovative study design and explored the impact of note formats on diagnostic accuracy and documentation review time. OBJECTIVE: To compare two formats for clinical documentation (narrative format vs. list of findings) on clinician diagnostic accuracy and documentation review time. METHOD: Participants diagnosed written clinical cases, half in narrative format, and half in list format. Diagnostic accuracy (defined as including correct case diagnosis among top three diagnoses) and time spent processing the case scenario were measured for each format. Generalised linear mixed regression models and bias-corrected bootstrap percentile confidence intervals for mean paired differences were used to analyse the primary research questions. RESULTS: Odds of correctly diagnosing list format notes were 26% greater than with narrative notes. However, there is insufficient evidence that this difference is significant (75% CI 0.8-1.99). On average the list format notes required 85.6 more seconds to process and arrive at a diagnosis compared to narrative notes (95% CI -162.3, -2.77). Of cases where participants included the correct diagnosis, on average the list format notes required 94.17 more seconds compared to narrative notes (75% CI -195.9, -8.83). CONCLUSION: This study offers note format considerations for those interested in improving clinical documentation and suggests directions for future research. Balancing the priority of clinician preference with value of structured data may be necessary. IMPLICATIONS: This study provides a method and suggestive results for further investigation in usability of electronic documentation formats.

Influence of comorbid depression and diagnostic workup on diagnosis of physical illness: a randomized experiment.

OBJECTIVES: Patients with mental illness are less likely to receive the same physical healthcare as those without mental illness and are less likely to be treated in accordance with established guidelines. This study employed a randomized experiment to investigate the influence of comorbid depression on diagnostic accuracy. METHODS: Physicians were presented with an interactive vignette describing a patient with a complex presentation of pernicious anemia. They were randomized to diagnose either a patient with or without (control) comorbid depression and related behaviors. All other clinical information was identical. Physicians recorded a differential diagnosis, ordered tests, and rated patient likeability. RESULTS: Fifty-nine physicians completed the study. The patient with comorbid depression was less likeable than the control patient (p=0.03, 95 % CI [0.09, 1.53]). Diagnostic accuracy was lower in the depression compared to control condition (59.4 % vs. 40.7 %), however this difference was not statistically significant χ2(1)=2.035, p=0.15. Exploratory analyses revealed that patient condition (depression vs. control) interacted with the number of diagnostic tests ordered to predict diagnostic accuracy (OR=2.401, p=0.038). Accuracy was lower in the depression condition (vs. control) when physicians ordered fewer tests (1 SD below mean; OR=0.103, p=0.028), but there was no difference for physicians who ordered more tests (1 SD above mean; OR=2.042, p=0.396). CONCLUSIONS: Comorbid depression and related behaviors lowered diagnostic accuracy when physicians ordered fewer tests - a time when more possibilities should have been considered. These findings underscore the critical need to develop interventions to reduce diagnostic error when treating vulnerable populations such as those with depression.

How insight contributes to diagnostic excellence.

In the quest to improve diagnosis, a great deal of attention has already been focused on how to optimize clinical reasoning, and the importance of System 1 and System 2 processing. In this essay we consider the role of 'insight', a relatively overlooked pathway for arriving at the correct diagnosis. Insight refers to spontaneous emergence of the correct answer at some later point in time. We discuss factors that might facilitate insight, and how these could be incorporated into the diagnostic process.

Development and Usability Testing of the Agency for Healthcare Research and Quality Common Formats to Capture Diagnostic Safety Events.

OBJECTIVES: A lack of consensus around definitions and reporting standards for diagnostic errors limits the extent to which healthcare organizations can aggregate, analyze, share, and learn from these events. In response to this problem, the Agency for Healthcare Research and Quality (AHRQ) began the development of the Common Formats for Event Reporting for Diagnostic Safety Events (CFER-DS). We conducted a usability assessment of the draft CFER-DS to inform future revision and implementation. METHODS: We recruited a purposive sample of quality and safety personnel working in 8 U.S. healthcare organizations. Participants were invited to use the CFER-DS to simulate reporting for a minimum of 5 cases of diagnostic safety events and then provide written and verbal qualitative feedback. Analysis focused on participants' perceptions of content validity, ease of use, and potential for implementation. RESULTS: Estimated completion time was 30 to 90 minutes per event. Participants shared generally positive feedback about content coverage and item clarity but identified reporter burden as a potential concern. Participants also identified opportunities to clarify several conceptual definitions, ensure applicability across different care settings, and develop guidance to operationalize use of CFER-DS. Findings led to refinement of content and supplementary materials to facilitate implementation. CONCLUSIONS: Standardized definitions of diagnostic safety events and reporting standards for contextual information and contributing factors can help capture and analyze diagnostic safety events. In addition to usability testing, additional feedback from the field will ensure that AHRQ's CFER-DS is useful to a broad range of users for learning and safety improvement.

Artificial intelligence and machine learning in emergency medicine: a narrative review.

AIM: The emergence and evolution of artificial intelligence (AI) has generated increasing interest in machine learning applications for health care. Specifically, researchers are grasping the potential of machine learning solutions to enhance the quality of care in emergency medicine. METHODS: We undertook a narrative review of published works on machine learning applications in emergency medicine and provide a synopsis of recent developments. RESULTS: This review describes fundamental concepts of machine learning and presents clinical applications for triage, risk stratification specific to disease, medical imaging, and emergency department operations. Additionally, we consider how machine learning models could contribute to the improvement of causal inference in medicine, and to conclude, we discuss barriers to safe implementation of AI. CONCLUSION: We intend that this review serves as an introduction to AI and machine learning in emergency medicine.

A call to action: next steps to advance diagnosis education in the health professions.

OBJECTIVES: Improving diagnosis-related education in the health professions has great potential to improve the quality and safety of diagnosis in practice. Twelve key diagnostic competencies have been delineated through a previous initiative. The objective of this project was to identify the next steps necessary for these to be incorporated broadly in education and training across the health professions. METHODS: We focused on medicine, nursing, and pharmacy as examples. A literature review was conducted to survey the state of diagnosis education in these fields, and a consensus group was convened to specify next steps, using formal approaches to rank suggestions. RESULTS: The literature review confirmed initial but insufficient progress towards addressing diagnosis-related education. By consensus, we identified the next steps necessary to advance diagnosis education, and five required elements relevant to every profession: 1) Developing a shared, common language for diagnosis, 2) developing the necessary content, 3) developing assessment tools, 4) promoting faculty development, and 5) spreading awareness of the need to improve education in regard to diagnosis. CONCLUSIONS: The primary stakeholders, representing education, certification, accreditation, and licensure, in each profession must now take action in their own areas to encourage, promote, and enable improved diagnosis, and move these recommendations forward.

Improving diagnostic performance through feedback: the Diagnosis Learning Cycle.

BACKGROUND: Errors in reasoning are a common cause of diagnostic error. However, it is difficult to improve performance partly because providers receive little feedback on diagnostic performance. Examining means of providing consistent feedback and enabling continuous improvement may provide novel insights for diagnostic performance. METHODS: We developed a model for improving diagnostic performance through feedback using a six-step qualitative research process, including a review of existing models from within and outside of medicine, a survey, semistructured interviews with individuals working in and outside of medicine, the development of the new model, an interdisciplinary consensus meeting, and a refinement of the model. RESULTS: We applied theory and knowledge from other fields to help us conceptualise learning and comparison and translate that knowledge into an applied diagnostic context. This helped us develop a model, the Diagnosis Learning Cycle, which illustrates the need for clinicians to be given feedback about both their confidence and reasoning in a diagnosis and to be able to seamlessly compare diagnostic hypotheses and outcomes. This information would be stored in a repository to allow accessibility. Such a process would standardise diagnostic feedback and help providers learn from their practice and improve diagnostic performance. This model adds to existing models in diagnosis by including a detailed picture of diagnostic reasoning and the elements required to improve outcomes and calibration. CONCLUSION: A consistent, standard programme of feedback that includes representations of clinicians' confidence and reasoning is a common element in non-medical fields that could be applied to medicine. Adapting this approach to diagnosis in healthcare is a promising next step. This information must be stored reliably and accessed consistently. The next steps include testing the Diagnosis Learning Cycle in clinical settings.

Learning from tragedy - The Jessica Barnett story: challenges in the diagnosis of long QT syndrome.

We describe the case of Jessica Barnett, an adolescent girl whose repeated episodes of syncope and near-syncope were ascribed to a seizure or anxiety disorder. The correct diagnoses (congenital long QT syndrome; arrythmogenic right ventricular cardiomyopathy) were established by autopsy and genetic studies only after her death at age 17. The perspective of the family is presented, along with an analysis of what went right and what went wrong in Jessica's diagnostic journey. Key lessons in this case include the value of family as engaged members of the diagnostic team, that a 'hyperventilation test' should not be used to exclude cardiac origins of syncope or pre-syncope, and the inherent challenges in the diagnosis of the long QT syndrome.

The critical need for nursing education to address the diagnostic process.

Diagnostic errors are among the most common medical errors and the deadliest. The National Academy of Medicine recently concluded that diagnostic errors represent an urgent national concern. Their first recommendation to address this issue called for promoting the key role of the nurse in the diagnostic process. Registered nurses across clinical settings significantly contribute to the medical diagnostic process, though their role in diagnosis has historically gone unacknowledged. In this paper, we review the history and current state of diagnostic education in pre-licensure registered nurse preparation, introduce interprofessional individual- and team-based competencies to improve diagnostic safety, and discuss the next steps for nursing education. Nurses educated and empowered to fully participate in the diagnostic process are essential for achieving better, safer patient outcomes.

Evidence That Nurses Need to Participate in Diagnosis: Lessons From Malpractice Claims.

OBJECTIVES: There is a pressing need for nurses to contribute as equals to the diagnostic process. The purpose of this article is twofold: (a) to describe the contributing factors in diagnosis-related and failure-to-monitor malpractice claims in which nurses are named the primary responsible party and (b) to describe actions healthcare leaders can take to enhance the role of nurses in diagnosis. METHODS: We conducted a review of the Controlled Risk Insurance Company Strategies' repository of malpractice claims, which contain approximately 30% of United States claims. We analyzed the malpractice claims related to diagnosis (n = 139) and physiologic monitoring (n = 647) naming nurses as the primary responsible party from 2007 to 2016. We used logistic regression to determine the association of contributing factors to likelihood of death, indemnity, and expenses incurred. RESULTS: Diagnosis-related cases listing communication among providers as a contributing factor were associated with a significantly higher likelihood of death (odds ratio [OR] = 3.01, 95% confidence interval [CI] = 1.50-6.03). Physiologic monitoring cases listing communication among providers as a contributing factor were associated with significantly higher likelihood of death (OR = 2.21, 95% CI = 1.49-3.27), higher indemnity incurred (U.S. $86,781, 95% CI = $18,058-$175,505), and higher expenses incurred (U.S. $20,575, 95% CI = $3685-$37,465). CONCLUSIONS: Nurses are held legally accountable for their role in diagnosis. Raising system-wide awareness of the critical role and responsibility of nurses in the diagnostic process and enhancing nurses' knowledge and skill to fulfill those responsibilities are essential to improving diagnosis.

Identifying trigger concepts to screen emergency department visits for diagnostic errors.

OBJECTIVES: The diagnostic process is a vital component of safe and effective emergency department (ED) care. There are no standardized methods for identifying or reliably monitoring diagnostic errors in the ED, impeding efforts to enhance diagnostic safety. We sought to identify trigger concepts to screen ED records for diagnostic errors and describe how they can be used as a measurement strategy to identify and reduce preventable diagnostic harm. METHODS: We conducted a literature review and surveyed ED directors to compile a list of potential electronic health record (EHR) trigger (e-triggers) and non-EHR based concepts. We convened a multidisciplinary expert panel to build consensus on trigger concepts to identify and reduce preventable diagnostic harm in the ED. RESULTS: Six e-trigger and five non-EHR based concepts were selected by the expert panel. E-trigger concepts included: unscheduled ED return to ED resulting in hospital admission, death following ED visit, care escalation, high-risk conditions based on symptom-disease dyads, return visits with new diagnostic/therapeutic interventions, and change of treating service after admission. Non-EHR based signals included: cases from mortality/morbidity conferences, risk management/safety office referrals, ED medical director case referrals, patient complaints, and radiology/laboratory misreads and callbacks. The panel suggested further refinements to aid future research in defining diagnostic error epidemiology in ED settings. CONCLUSIONS: We identified a set of e-trigger concepts and non-EHR based signals that could be developed further to screen ED visits for diagnostic safety events. With additional evaluation, trigger-based methods can be used as tools to monitor and improve ED diagnostic performance.

Closing the loop on test results to reduce communication failures: a rapid review of evidence, practice and patient perspectives.

BACKGROUND: Communication failures involving test results contribute to issues of patient harm and sentinel events. This article aims to synthesise review evidence, practice insights and patient perspectives addressing problems encountered in the communication of diagnostic test results. METHODS: The rapid review identified ten systematic reviews and four narrative reviews. Five practitioner interviews identified insights into interventions and implementation, and a citizen panel with 15 participants explored the patient viewpoint. RESULTS: The rapid review provided support for the role of technology to ensure effective communication; behavioural interventions such as audit and feedback could be effective in changing clinician behaviour; and point-of-care tests (bedside testing) eliminate the communication breakdown problem altogether. The practice interviews highlighted transparency, and clarifying the lines of responsibility as central to improving test result communication. Enabling better information sharing, implementing adequate planning and utilising technology were also identified in the practice interviews as viable strategies to improve test result communication. The citizen panel highlighted technology as critical to improving communication of test results to both health professionals and patients. Patients also highlighted the importance of having different ways of accessing test results, which is particularly pertinent when ensuring suitability for vulnerable populations. CONCLUSIONS: This paper draws together multiple perspectives on the problem of failures in diagnostic test results communication to inform appropriate interventions. Across the three studies, technology was identified as the most feasible option for closing the loop on test result communication. However, the importance of clear, consistent communication and more streamlined processes were also key elements that emerged. REVIEW REGISTRATION: The protocol for the rapid review was registered with PROSPERO CRD42018093316 .