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Cancer will affect more than one in three U.S. residents in their lifetime, and although the diagnosis will be made efficiently in most of these cases, roughly one in five patients will experience a delayed or missed diagnosis. In this integrative review, we focus on missed opportunities in the diagnosis of breast, lung, and colorectal cancer in the ambulatory care environment. From a review of 493 publications, we summarize the current evidence regarding the contributing factors to missed or delayed cancer diagnosis in ambulatory care, as well as evidence to support possible strategies for intervention. Cancer diagnoses are made after follow-up of a positive screening test or an incidental finding, or most commonly, by following up and clarifying non-specific initial presentations to primary care. Breakdowns and delays are unacceptably common in each of these pathways, representing failures to follow-up on abnormal test results, incidental findings, non-specific symptoms, or consults. Interventions aimed at ‘closing the loop’ represent an opportunity to improve the timeliness of cancer diagnosis and reduce the harm from diagnostic errors. Improving patient engagement, using ‘safety netting,’ and taking advantage of the functionality offered through health information technology are all viable options to address these problems.

Introduction Synthetic magnetic resonance imaging (SyMRI) is a non-invasive, robust MRI technique that generates multiple contrast-weighted images by acquiring a single MRI sequence within a few minutes, along with quantitative maps, automatic brain segmentation, and volumetry. Since its inception, it has undergone technical advancements and has also been tested for feasibility in various organs and pathological conditions. This scoping review comprehensively pinpoints the critical technical aspects and maps the wide range of clinical applications/benefits of SyMRI. Content A comprehensive search was conducted across five databases, PubMed, Scopus, Web of Science, Embase, and CINAHL Ultimate, using appropriate keywords related to SyMRI. A total of 99 studies were included after a 2-step screening process. Data related to the technical factors and clinical application was charted. Summary SyMRI provides quantitative maps and segmentation techniques comparable to conventional MRI and has demonstrated feasibility and applications across neuroimaging, musculoskeletal, abdominal and breast pathologies spanning the entire human lifespan, from prenatal development to advanced age. Certain drawbacks related to image quality have been encountered that can be overcome with technical advances, especially AI-based algorithms. Outlook SyMRI has immense potential for being incorporated into routine imaging for various pathologies due to its added advantage of providing quantitative measurements for more robust diagnostic and prognostic work-up with faster acquisitions and greater post-processing options.

Personalized medicine, aiming to tailor treatments based on individual patient characteristics, holds immense potential in oncology. However, its widespread adoption in Europe faces numerous challenges, as illustrated by the case study of the Oncotype DX Breast Recurrence Score ® assay, a genomic test for breast cancer. This manuscript delineates the multifaceted obstacles encountered during the introduction of the Oncotype DX ® test (Oncotype DX Breast Recurrence Score test) in Europe from 2004 to 2018. In June 2018, the TAILORx results were published in the New England Journal of Medicine (Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, et al. Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N Engl J Med 2018;379:111–21, Sparano JA, Gray RJ, Ravdin PM, Makower DF, Pritchard KI, Albain KS, et al. Clinical and genomic risk to guide the use of adjuvant therapy for breast cancer. N Engl J Med 2019;380:2395–405), and reported that among 6,711 women with hormone-receptor–positive, HER2–negative, node–negative breast cancer and a midrange recurrence score of 11–25 on the Oncotype DX assay, endocrine therapy was not inferior to chemoendocrine therapy, which provides evidence that adjuvant chemotherapy was not beneficial in these patients. Through a comprehensive analysis of clinical evidence, commercial presence, reimbursement mechanisms, guideline recommendations, regulatory pathways, and local experiences, this study sheds light on the intricate dynamics influencing the adoption of personalized medicine technologies. This article examines the various obstacles encountered during the introduction of the Oncotype DX Breast Cancer Assay in Europe from 2004 to 2018. By analyzing clinical evidence, commercial presence, reimbursement mechanisms, guideline recommendations, regulatory pathways, and local experiences, this study reveals the complex factors that influence the adoption of personalized medicine technologies. By highlighting these challenges, this article offers valuable insights into strategies to facilitate the integration of innovative diagnostic tools into clinical practice across Europe, ultimately leading to improved treatment decision-making for cancer patients.

Clinical reasoning is a quintessential aspect of medical training and practice, and is a topic that has been studied and written about extensively over the past few decades. However, the predominant conceptualisation of clinical reasoning has insofar been extrapolated from cognitive psychological theories that have been developed in other areas of human decision-making. Till date, the prevailing model of understanding clinical reasoning has remained as the dual process theory which views cognition as a dichotomous two-system construct, where intuitive thinking is fast, efficient, automatic but error-prone, and analytical thinking is slow, effortful, logical, deliberate and likely more accurate. Nonetheless, we find that the dual process model has significant flaws, not only in its fundamental construct validity, but also in its lack of practicality and applicability in naturistic clinical decision-making. Instead, we herein offer an alternative Bayesian-centric, intuitionist approach to clinical reasoning that we believe is more representative of real-world clinical decision-making, and suggest pedagogical and practice-based strategies to optimise and strengthen clinical thinking in this model to improve its accuracy in actual practice.

Background Diagnostic scope is the range of diagnoses found in a clinical setting. Although the diagnostic scope is an essential feature of training and evaluating artificial intelligence (AI) systems to promote diagnostic excellence, its impact on AI systems and the diagnostic process remains under-explored. Content We define the concept of diagnostic scope, discuss its nuanced role in building safe and effective AI-based diagnostic decision support systems, review current challenges to measurement and use, and highlight knowledge gaps for future research. Summary The diagnostic scope parallels the differential diagnosis although the latter is at the level of an encounter and the former is at the level of a clinical setting. Therefore, diagnostic scope will vary by local characteristics including geography, population, and resources. The true, observed, and considered scope in each setting may also diverge, both posing challenges for clinicians, patients, and AI developers, while also highlighting opportunities to improve safety. Further work is needed to systematically define and measure diagnostic scope in terms that are accurate, equitable, and meaningful at the bedside. AI tools tailored to a particular setting, such as a primary care clinic or intensive care unit, will each require specifying and measuring the appropriate diagnostic scope. Outlook AI tools will promote diagnostic excellence if they are aligned with patient and clinician needs and trained on an accurately measured diagnostic scope. A careful understanding and rigorous evaluation of the diagnostic scope in each clinical setting will promote optimal care through human-AI collaborations in the diagnostic process.

Nearly a decade after the National Academy of Medicine released the “Improving Diagnosis in Health Care” report, diagnostic errors remain common, often leading to physical, psychological, emotional, and financial harm. Despite a robust body of research on potential solutions and next steps, the translation of these efforts to patient care has been limited. Improvement initiatives are still narrowly focused on selective themes such as diagnostic stewardship, preventing overdiagnosis, and enhancing clinical reasoning without comprehensively addressing vulnerable systems and processes surrounding diagnosis. To close this implementation gap, the US Centers for Disease Control and Prevention (CDC) released the Core Elements of Hospital Diagnostic Excellence programs on September 17, 2024. This initiative aligns with the World Health Organization’s (WHO) 2024 World Patient Safety Day focus on improving diagnosis. These Core Elements provide guidance for the formation of hospital programs to improve diagnosis and aim to integrate various disparate efforts in hospitals. By creating a shared mental model of diagnostic excellence, the Core Elements of Diagnostic Excellence supports actions to break down silos, guide hospitals toward multidisciplinary diagnostic excellence teams, and provide a foundation for building diagnostic excellence programs in hospitals.

Objectives To investigate longitudinal trends in the incidence, preventability, and causes of DAEs (diagnostic adverse events) between 2008 and 2019 and compare DAEs to other AE (adverse event) types. Methods This study investigated longitudinal trends of DAEs using combined data from four large Dutch AE record review studies. The original four AE studies included 100–150 randomly selected records of deceased patients from around 20 hospitals in each study, resulting in a total of 10,943 patient records. Nurse reviewers indicated cases with potential AEs using a list of triggers. Subsequently, experienced physician reviewers systematically judged the occurrence of AEs, the clinical process in which these AEs occurred, and the preventability and causes. Results The incidences of DAEs, potentially preventable DAEs and potentially preventable DAE-related deaths initially declined between 2008 and 2012 (2.3 vs. 1.2; OR=0.52, 95 % CI: 0.32 to 0.83), after which they stabilized up to 2019. These trends were largely the same for other AE types, although compared to DAEs, the incidence of other AE types increased between 2016 (DAE: 1.0, other AE types: 8.5) and 2019 (DAE: 0.8, other AE types: 13.0; rate ratio=1.88, 95 % CI: 1.12 to 2.13). Furthermore, DAEs were more preventable (p<0.001) and were associated with more potentially preventable deaths (p=0.016) than other AE types. In addition, DAEs had more and different underlying causes than other AE types (p<0.001). The DAE causes remained stable over time, except for patient-related factors, which increased between 2016 and 2019 (29.5 and 58.6 % respectively, OR=3.40, 95 % CI: 1.20 to 9.66). Conclusions After initial improvements of DAE incidences in 2012, no further improvement was observed in Dutch hospitals in the last decade. Similar trends were observed for other AEs. The high rate of preventability of DAEs suggest a high potential for improvement, that should be further investigated.

Objectives Competency in diagnostic reasoning is integral to medical training and patient safety. Situativity theory highlights the importance of contextual factors on learning and performance, such as being informed of a provisional diagnosis prior to a patient encounter. This study aims to determine how being informed of a provisional diagnosis affects an intern’s approach to diagnostic reasoning. Methods This mixed methods study was conducted in a real-time workplace learning environment at a large teaching hospital. Interns were randomized to the Chief Complaint (CC) only or chief complaint with Provisional Diagnosis (PD) group. One blinded researcher assessed intern diagnostic reasoning using a validated tool. Mean group scores were compared using the two-sample t-test. The researcher was unblinded for think aloud interviews analyzed via thematic analysis. Results There was no difference in performance between the CC and PD groups (mean ± SD): 47.8 ± 8.1 vs. 43.9 ± 10.9, p=0.24. Thematic analysis identified that interns aware of the provisional diagnosis 1) invested less effort in diagnostic reasoning, 2) formulated a differential through a narrowly focused frame, 3) accepted a provisional diagnosis as definitive, and 4) sought to confirm rather than refute the provisional diagnosis. Conclusions Our discordant results highlight the complex interplay between a provisional diagnosis and diagnostic reasoning performance in early learners. Though an accurate provisional diagnosis may enhance diagnostic reasoning outcomes, our qualitative results suggest that it may pose certain risks to the diagnostic reasoning process. Metacognitive strategies may be a ripe field for exploration to optimize this complex interplay.

Objectives Diagnostic error is a global emergency. Context specificity is likely a source of the alarming rate of error and refers to the vexing phenomenon whereby a physician can see two patients with the same presenting complaint, identical history and examination findings, but due to the presence of contextual factors, decides on two different diagnoses. Studies have not empirically addressed the potential role of context specificity in management reasoning and errors with a diagnosis may not consistently translate to actual patient care. Methods We investigated the effect of context specificity on management reasoning in individuals working within a simulated internal medicine environment. Participants completed two ten minute back to back common encounters. The clinical content of each encounter was identical. One encounter featured the presence of carefully controlled contextual factors (CF+ vs. CF−) designed to distract from the correct diagnosis and management. Immediately after each encounter participants completed a post encounter form. Results Twenty senior medical students participated. The leading diagnosis score was higher (mean 0.88; SEM 0.07) for the CF− encounter compared with the CF+ encounter (0.58; 0.1; 95 % CI 0.04–0.56; p=0.02). Management reasoning scores were higher (mean 5.48; SEM 0.66) for the CF− encounter compared with the CF+ encounter (3.5; 0.56; 95 % CI 0.69–3.26; p=0.01). We demonstrated context specificity in both diagnostic and management reasoning. Conclusions This study is the first to empirically demonstrate that management reasoning, which directly impacts the patient, is also influenced by context specificity, providing additional evidence of context specificity’s role in unwanted variance in health care.

Objectives Diagnostic errors frequently represent significant adverse events that can occur in any medical setting, particularly in rushed handovers and constrained timing. Cases that result in emergency hospitalization at the time of the initial outpatient visit are more likely to have complex or serious patient conditions and more detrimental diagnostic errors. Our study investigated diagnostic errors in these under reported situations. Methods We conducted a retrospective study using electronic medical record data on patients who were directly admitted to a newly established outpatient clinic at a single university hospital in Japan. Diagnostic errors were assessed independently by two physicians using the Revised Safer Dx instrument. We analyzed patient demographics, symptoms, referrals, and resident doctor (postgraduate-year-1) involvement using logistic regression to compare groups with and without diagnostic error. Additionally, we employed the Diagnostic Error Evaluation and Research (DEER) taxonomy and Generic Diagnostic Pitfalls (GDP) to examine the factors associated with diagnostic errors. Results The study included 321 patients, with diagnostic errors identified in 39 cases (12.1 %). Factors contributing to diagnostic errors included the involvement of young residents, male patients, the number of symptoms, and atypical presentation. The most common causes of diagnostic errors were “too much weight given to competing/coexisting diagnosis” as indicated by DEER and “atypical presentation” by GDP. Conclusions The frequency of diagnostic errors in this study was higher than those in previous studies of new outpatient visits, underscoring the imperative for heightened scrutiny in cases involving medical residents especially when patients present with multiple or atypical symptoms. This vigilance is crucial to mitigating the risk of diagnostic inaccuracies in these settings. Cases that result in emergency hospitalization at the time of the initial outpatient visit are more likely to have complex or serious patient conditions and more detrimental diagnostic errors.

Objectives To examine factors impacting diagnostic evaluation of suspected deep vein thrombosis (DVT) by analyzing the test ordering patterns and provider decision-making within a universal health coverage system in Hungary. Methods We analyzed test orders for suspected DVT between 2007 and 2020, and the financial framework influencing diagnostic practices. An anonymous survey was also conducted among Emergency Department physicians to explore factors influencing diagnostic decision-making. Results A total of 6,821 patients were identified. From 2008 to 2013, the most common diagnostic approach combined D-dimer and duplex ultrasound tests (64.5 %), followed by sole ultrasound (20.5 %) and sole D-dimer (15 %) testing. A marked shift occurred from 2014 onward, with sole ultrasound rising to 88 % of cases by 2018–2020, while combined testing and sole D-dimer orders decreased to 7.9 and 4 %, respectively. In survey results, time efficiency emerged as a key factor for bypassing D-dimer testing, cited by 75 % of physicians. 45 % believed D-dimer costs were comparable to or higher than duplex ultrasound. Financial analysis revealed that the outdated performance points system misrepresented actual costs, resulting in duplex ultrasound being significantly underfunded, which impacts the Radiology Department. This discrepancy contributes to higher national level expenses, driven by the increased reliance on ultrasound. Conclusions We found diagnostic practices deviating from international diagnostic guidelines, with an increase in duplex ultrasound over D-dimer. This shift, allowed by an outdated financing structure, increases overall costs for the healthcare system. Revising financial frameworks to reflect true costs is essential for sustainable operations in universal health coverage systems.

Objectives To identify clinical presentations that acted as harbingers for future sepsis hospitalizations in pediatric patients evaluated in the emergency department (ED) using the Symptom Disease Pair Analysis of Diagnostic Error (SPADE) methodology. Methods We identified patients in the Pediatric Health Information Systems (PHIS) database admitted for sepsis between January 1, 2004 and December 31, 2023 and limited the study cohort to those patients who had an ED treat-and-release visit in the 30 days prior to admission. Using the look-back approach of the SPADE methodology, we identified the most common clinical presentations at the initial ED visit and used an observed to expected (O:E) analysis to determine which presentations were overrepresented. We then employed a graphical, temporal analysis with a comparison group to identify which overrepresented presentations most likely represented harbingers for future sepsis hospitalization. Results We identified 184,157 inpatient admissions for sepsis, of which 15,331 hospitalizations (8.3 %) were preceded by a treat-and-release ED visit in the prior 30 days. Based on the O:E and temporal analyses, the presentations of fever and dehydration were both overrepresented in the study cohort and temporally clustered close to sepsis hospitalization. ED treat-and-release visits for fever or dehydration preceded 1.2 % of all sepsis admissions. Conclusions In pediatric patients presenting to the ED, fever and dehydration may represent harbingers for future sepsis hospitalization. The SPADE methodology could be applied to the PHIS database to develop diagnostic performance measures across a wide range of pediatric hospitals.

Objectives The purpose of this study was to determine the actual diagnostic status of aseptic meningitis and consider the factors that cause difficulties in its diagnosis. Methods This study retrospectively reviewed the medical records of aseptic meningitis treated at our hospital from 2013 to 2022 and compared biometric data to distinguish between timely diagnose and difficult diagnose cases. Results This retrospective observational study included 127 patients aged 18 years or older. 66 (52.0 %) were female, with a median age of 35.9±15.9 years. The main symptoms were headache (122, 96.1 %), general malaise (110, 86.6 %), vomiting (79, 62.2 %). The 127 patients were classified into two groups: A timely diagnosis group diagnosed within 6 days of symptom onset, and a difficult diagnosis group diagnosed within 7 days or longer. There were significant differences between the two groups in the proportion of patients with a history of antimicrobial treatment and fever above 38 °C, and in the positive rates of neck stiffness and jolt accentuation of headache (JAH). The total number of hospitals involved in the process of diagnosis was significantly higher in the difficult diagnosis group and the length of inpatient stay was significantly longer. Multivariate analysis revealed significant differences in neck stiffness, JAH, and prior antibacterial therapy. Conclusions Atypical cases, such as neck stiffness and JAH negativity, may make the diagnosis difficult. Clinicians should be aware of this atypical presentation of aseptic meningitis.

Objectives To describe rare genetic interactions of α-thalassemia alleles causing Hb H disease and Hb Bart’s hydrops fetalis which could lead to diagnostic errors in a routine practice. Methods Hematological and molecular characterization were carried out in a Thai family with a risk of having fetus with Hb Bart’s hydrops fetalis. Results Both parents were found to be the thalassemia intermedia patients associated with unusual forms of Hb H disease. DNA analysis of common α-thalassemia mutations in Thailand identified α + -thalassemia (-α 3.7 kb del ) and unknown α 0 -thalassemia in the father and α 0 -thalassemia (-- SEA ) with unknown α + -thalassemia in the mother. Fetal DNA analysis unlikely identified a homozygosity for α 0 -thalassemia (-- SEA /-- SEA ). Further analysis identified that the father carried a rare South African α 0 -thalassemia in combination with α + -thalassemia (-- SA /-α), whereas the mother was a patient with Hb H-Queens Park disease (-- SEA /αα QP ). The fetus was, in fact, a compound heterozygote for (-- SA /-- SEA ). Conclusions As shown in this study, routine screening for α-thalassemia at prenatal diagnosis in the region should include both common and rare α 0 -thalassemia alleles found in the population to effectively prevent a fatal condition of Hb Bart’s hydrops fetalis syndrome.

Objectives The measurement of fasting glucose is a common practice for lowering the risk of hyperglycemia before an oral glucose tolerance test (OGTT). In this study we analyze advantages and limitations of near-patient measurement of capillary fasting glucose with a portable glucometer or blood sampling and measurement of plasma glucose with laboratory instrumentation. Methods The final study population consisted of 241 subjects (mean age: 36 ± 8 years; 97.9 % pregnant women) referred to our local phlebotomy center for an OGTT. Fasting glucose was measured in capillary blood using a near-patient glucometer (glucometer-based strategy) and in plasma with laboratory instrumentation using the hexokinase reference assay (laboratory-based strategy). Results The mean turnaround time from sample collection to obtaining the glucose value was longer with the laboratory-based strategy (32 min 8 vs. 8 s). The imprecision of the glucometer was higher than that of the laboratory assay (3.4 vs. 0.8 %). A negative bias of −3.3 % in fasting glucose was found with the glucometer compared to the laboratory measurement. The diagnostic accuracy, sensitivity and specificity of the glucometer for detecting fasting glucose values ≥7.0 mmol/L were 99.2 , 50.0 and 100.0 % compared to the laboratory assay. The glucometer-based strategy had an incremental cost of 0.17€ per patient compared to the laboratory-based strategy. Conclusions Screening fasting glucose in capillary blood with a near-patient glucometer instead of measuring fasting plasma glucose with laboratory instrumentation allows faster patient management in the phlebotomy center but is associated with higher imprecision, inaccuracy, costs and avoidable finger pricks.

Objectives Validation and performance assessment of novel ESR analyzer is required before implementation. The objective of this study was to assess the correlation between three ESR measurement methods. Full validation and performance assessment of an alternate method (TEST1) were also evaluated. Methods Three-way correlation assessment for the Westergren (WG), modified Westregren (Mixrate), and alternate (TEST1) methods were performed. Analytical performance of TEST1 including precision, carryover, sample stability, potential interferences as well as effect of hematocrit (Hct) and mean corpuscular volume (MCV) were also determined. Results Strong correlation between three ESR measurement methods were observed. Correlation coefficient (r) was 0.902, 0.977, and 0.949 for WG vs. TEST1, WG vs. Mixrate, and TEST1 vs. Mixrate, respectively with absolute bias <5 mm. For TEST1, precision and carryover were within the manufacturer’s claim. Samples were stable upto 24 h and 48 h when they were stored at room temperature or 2–8 °C, respectively. No effect of trigyceride and cholesterol was observed. In low Hct samples, no significant different between the results obtained from Fabry’s formula corrected WG values and from TEST1. Conclusions Three-way comparison study yielded a strong correlation between methods. As part of the method validation before implementing a new analyzer, full validation of TEST1 showed that all validated parameters met the manufacturer’s specifications. A negative bias was observed but remains within the acceptable criteria. Difference in values for samples with low hematocrit were noted, but these can be corrected by Fabry’s formula applied to the values from WG method.

Objectives Evaluate the impact of problem representation (PR) characteristics on Generative Artificial Intelligence (GAI) diagnostic accuracy. Methods Internal medicine attendings and residents from two academic medical centers were given a clinical vignette and instructed to write a PR. Deductive content analysis described the characteristics comprising each PR. Individual PRs were input into ChatGPT-4 (OpenAI, September 2023) which was prompted to generate a ranked three-item differential. The ranked differential and the top-ranked diagnosis were scored on a 3-part scale, ranging from incorrect, partially correct, to correct. Logistic regression evaluated individual PR characteristic’s impact on ChatGPT accuracy. Results For a three-item differential, accuracy was associated with including fewer comorbidities (OR 0.57, p=0.010), fewer past historical items (OR 0.60, p=0.019), and more physical examination items (OR 1.66, p=0.015). For ChatGPT’s ability to rank the true diagnosis as the single-best diagnosis, utilizing temporal semantic qualifiers, more semantic qualifiers overall, and adhering to a typical 3-part PR format all correlated with diagnostic accuracy: OR 3.447, p=0.046; OR 1.300, p=0.005; OR 3.577, p=0.020, respectively. Conclusions Several distinct PR factors improved ChatGPT diagnostic accuracy. These factors have previously been associated with expertise in creating PR. Future studies should explore how clinical input qualities affect GAI diagnostic accuracy prospectively.

Objectives We primarily assessed differences in differential diagnosis (DDx) efficacy of initial and refined top diagnoses (tDDx) and “can’t miss” DDx (CMDx) between 3 MMTs (Constellations, Mental CT, and VINDICATES). Methods Pediatric clerkship students participated in two 1-h case-based sessions. The case was presented in three aliquots. Students were randomly assigned to MMT groups. Assigned MMTs were used to generate the initial tDDx and CMDx following aliquot 1. tDDx and CMDx were refined following both aliquots 2 and 3. Group DDx responses and student affective data were collected via survey. DDx efficacy was defined using pooled faculty responses and scoring was done by consensus. Results There was no significant difference in scores between MMT groups, except the second iteration of CMDx in Case A (Constellations 50 % [interquartile range, IQR, 50–100], Mental CT 50 % [50−100], VINDICATES 0 % [0-50], p=0.02). Students’ self-reported confidence in generating (p<0.001) and refining (p<0.001) their DDx significantly increased after the curriculum. Conclusions Although prior studies identified a differential effect of MMTs on DDx generation, we did not observe a difference in initial or refined DDx efficacy between MMTs.