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.

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 .

Interventions to prevent iatrogenic anemia: a Laboratory Medicine Best Practices systematic review.

BACKGROUND: As many as 90% of patients develop anemia by their third day in an intensive care unit (ICU). We evaluated the efficacy of interventions to reduce phlebotomy-related blood loss on the volume of blood lost, hemoglobin levels, transfusions, and incidence of anemia. METHODS: We conducted a systematic review and meta-analysis using the Laboratory Medicine Best Practices (LMBP) systematic review methods for rating study quality and assessing the body of evidence. Searches of PubMed, Embase, Cochrane, Web of Science, PsychINFO, and CINAHL identified 2564 published references. We included studies of the impact of interventions to reduce phlebotomy-related blood loss on blood loss, hemoglobin levels, transfusions, or anemia among hospital inpatients. We excluded studies not published in English and studies that did not have a comparison group, did not report an outcome of interest, or were rated as poor quality. Twenty-one studies met these criteria. We conducted a meta-analysis if > 2 homogenous studies reported sufficient information for analysis. RESULTS: We found moderate, consistent evidence that devices that return blood from flushing venous or arterial lines to the patient reduced blood loss by approximately 25% in both neonatal ICU (NICU) and adult ICU patients [pooled estimate in adults, 24.7 (95% CI = 12.1-37.3)]. Bundled interventions that included blood conservation devices appeared to reduce blood loss by at least 25% (suggestive evidence). The evidence was insufficient to determine if these devices reduced hemoglobin decline or risk of anemia. The evidence suggested that small volume tubes reduced the risk of anemia, but was insufficient to determine if they affected the volume of blood loss or the rate of hemoglobin decline. CONCLUSIONS: Moderate, consistent evidence indicated that devices that return blood from testing or flushing lines to the patient reduce the volume of blood loss by approximately 25% among ICU patients. The results of this systematic review support the use of blood conservation systems with arterial or venous catheters to eliminate blood waste when drawing blood for testing. The evidence was insufficient to conclude the devices impacted hemoglobin levels or transfusion rates. The use of small volume tubes may reduce the risk of anemia.

Tracking Progress in Improving Diagnosis: A Framework for Defining Undesirable Diagnostic Events.

Diagnostic error is a prevalent, harmful, and costly phenomenon. Multiple national health care and governmental organizations have recently identified the need to improve diagnostic safety as a high priority. A major barrier, however, is the lack of standardized, reliable methods for measuring diagnostic safety. Given the absence of reliable and valid measures for diagnostic errors, we need methods to help establish some type of baseline diagnostic performance across health systems, as well as to enable researchers and health systems to determine the impact of interventions for improving the diagnostic process. Multiple approaches have been suggested but none widely adopted. We propose a new framework for identifying "undesirable diagnostic events" (UDEs) that health systems, professional organizations, and researchers could further define and develop to enable standardized measurement and reporting related to diagnostic safety. We propose an outline for UDEs that identifies both conditions prone to diagnostic error and the contexts of care in which these errors are likely to occur. Refinement and adoption of this framework across health systems can facilitate standardized measurement and reporting of diagnostic safety.

The next organizational challenge: finding and addressing diagnostic error.

BACKGROUND: Although health care organizations (HCOs) are intensely focused on improving the safety of health care, efforts to date have almost exclusively targeted treatment-related issues. The literature confirms that the approaches HCOs use to identify adverse medical events are not effective in finding diagnostic errors, so the initial challenge is to identify cases of diagnostic error. WHY HEALTH CARE ORGANIZATIONS NEED TO GET INVOLVED: HCOs are preoccupied with many quality- and safety-related operational and clinical issues, including performance measures. The case for paying attention to diagnostic errors, however, is based on the following four points: (1) diagnostic errors are common and harmful, (2) high-quality health care requires high-quality diagnosis, (3) diagnostic errors are costly, and (4) HCOs are well positioned to lead the way in reducing diagnostic error. FINDING DIAGNOSTIC ERRORS: Current approaches to identifying diagnostic errors, such as occurrence screens, incident reports, autopsy, and peer review, were not designed to detect diagnostic issues (or problems of omission in general) and/or rely on voluntary reporting. The realization that the existing tools are inadequate has spurred efforts to identify novel tools that could be used to discover diagnostic errors or breakdowns in the diagnostic process that are associated with errors. New approaches--Maine Medical Center's case-finding of diagnostic errors by facilitating direct reports from physicians and Kaiser Permanente's electronic health record--based reports that detect process breakdowns in the followup of abnormal findings--are described in case studies. CONCLUSION: By raising awareness and implementing targeted programs that address diagnostic error, HCOs may begin to play an important role in addressing the problem of diagnostic error.

Hospital commitments to address diagnostic errors: An assessment of 95 US hospitals.

BACKGROUND: Diagnostic errors are a leading cause of patient harm. In 2022, the Leapfrog Group published a report containing 29 evidence-based practices that hospitals can adopt to reduce diagnostic errors. OBJECTIVES: To understand the extent to which US hospitals have already implemented these practices, we conducted a national pilot survey of Leapfrog-participating hospitals. METHODS: To reduce respondent burden, we divided the 29 practices across two surveys: one focused on organizational culture and structure (Domain 1), and the second focused on the diagnostic process itself (Domain 2). RESULTS: A total of 95 hospitals from 23 states responded to one or both surveys. On average, hospitals reported implementing 9 of the 16 practices (56%) in Domain 1 and 8 of the 13 practices (62%) in Domain 2. The rate of practice implementation varied greatly, with some hospitals implementing as few as three practices in their domain. The most commonly implemented practices were ensuring access to medical interpreters, continuous access to radiologists, ensuring staff and patients can report diagnostic errors and concerns, and having a formal process to identify and notify patients when diagnostic errors occur. The least implemented practices included convening a multidisciplinary team focused on diagnostic safety and quality, a CEO commitment to diagnostic excellence, conducting diagnosis-focused risk assessments, and training clinicians to optimize clinical reasoning in the diagnostic process. CONCLUSIONS: The findings suggest large and important implementation gaps for practices related to diagnostic excellence and can inform new initiatives to promote diagnostic excellence in US hospitals.

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.

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.

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.

Differential diagnosis generators: an evaluation of currently available computer programs.

BACKGROUND: Differential diagnosis (DDX) generators are computer programs that generate a DDX based on various clinical data. OBJECTIVE: We identified evaluation criteria through consensus, applied these criteria to describe the features of DDX generators, and tested performance using cases from the New England Journal of Medicine (NEJM©) and the Medical Knowledge Self Assessment Program (MKSAP©). METHODS: We first identified evaluation criteria by consensus. Then we performed Google® and Pubmed searches to identify DDX generators. To be included, DDX generators had to do the following: generate a list of potential diagnoses rather than text or article references; rank or indicate critical diagnoses that need to be considered or eliminated; accept at least two signs, symptoms or disease characteristics; provide the ability to compare the clinical presentations of diagnoses; and provide diagnoses in general medicine. The evaluation criteria were then applied to the included DDX generators. Lastly, the performance of the DDX generators was tested with findings from 20 test cases. Each case performance was scored one through five, with a score of five indicating presence of the exact diagnosis. Mean scores and confidence intervals were calculated. KEY RESULTS: Twenty three programs were initially identified and four met the inclusion criteria. These four programs were evaluated using the consensus criteria, which included the following: input method; mobile access; filtering and refinement; lab values, medications, and geography as diagnostic factors; evidence based medicine (EBM) content; references; and drug information content source. The mean scores (95% Confidence Interval) from performance testing on a five-point scale were Isabel© 3.45 (2.53, 4.37), DxPlain® 3.45 (2.63-4.27), Diagnosis Pro® 2.65 (1.75-3.55) and PEPID™ 1.70 (0.71-2.69). The number of exact matches paralleled the mean score finding. CONCLUSIONS: Consensus criteria for DDX generator evaluation were developed. Application of these criteria as well as performance testing supports the use of DxPlain® and Isabel© over the other currently available DDX generators.

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.

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.

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.