Volume 9, Issue 3

Psychological research consistently demonstrates that affect can play an important role in decision-making across a broad range of contexts. Despite this, the role of affect in clinical reasoning and medical decision-making has received relatively little attention. Integrating the affect, social cognition, and patient safety literatures can provide new insights that promise to advance our understanding of clinical reasoning and lay the foundation for novel interventions to reduce diagnostic errors and improve patient safety. In this paper, we briefly review the ways in which psychologists differentiate various types of affect. We then consider existing research examining the influence of both positive and negative affect on clinical reasoning and diagnosis. Finally, we introduce an empirically supported theoretical framework from social psychology that explains the cognitive processes by which these effects emerge and demonstrates that cognitive interventions can alter these processes. Such interventions, if adapted to a medical context, hold great promise for reducing errors that emerge from faulty thinking when healthcare providers experience different affective responses.

Objectives Coronavirus disease 2019 (COVID-19) is a life-threatening infectious disorder characterized by a sustained prothrombotic state. Since homocysteine is a potential biomarker of thrombotic diseases, the aim of this article is to provide an updated overview on the possible role played by hyperhomocysteinemia in influencing an unfavorable COVID-19 progression. Methods We carried out an electronic search in Medline (PubMed interface) using the keywords (“COVID-19” OR “SARS-CoV-2”) AND “homocysteine”, between 2019 and the present time, with no language restrictions, to identify all articles which explored the concentration of homocysteine in COVID-19 patients with or without unfavorable disease progression. Results Three studies, totaling 694 hospitalized COVID-19 patients, were included in our systematic review. Overall, the differences between the mean homocysteine values in non-severe vs. severe COVID-19 patients were always positive (i.e., 15.1%, 24.1% and 22.8%, generating a positive weight mean difference of 1.75 μmol/L (95%CI, 1.26–2.25 μmol/L; p=0.011), which translates into a cumulative difference of approximately ∼1.2 μmol/L. Conclusions Despite the limited evidence that has been garnered so far, increased homocysteine ​​levels may be a potentially useful marker for predicting the risk of unfavorable progression in patients with COVID-19.

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.

Objectives To investigate from a linguistic perspective how clinicians deliver diagnosis to patients, and how these statements relate to diagnostic accuracy. Methods To identify temporal and discursive features in diagnostic statements, we analysed 16 video-recorded interactions collected during a practice high-stakes exam for internationally trained clinicians (25% female, n=4) to gain accreditation to practice in Australia. We recorded time spent on history-taking, examination, diagnosis and management. We extracted and deductively analysed types of diagnostic statements informed by literature. Results Half of the participants arrived at the correct diagnosis, while the other half misdiagnosed the patient. On average, clinicians who made a diagnostic error took 30 s less in history-taking and 30 s more in providing diagnosis than clinicians with correct diagnosis. The majority of diagnostic statements were evidentialised (describing specific observations (n=24) or alluding to diagnostic processes (n=7)), personal knowledge or judgement (n=8), generalisations (n=6) and assertions (n=4). Clinicians who misdiagnosed provided more specific observations (n=14) than those who diagnosed correctly (n=9). Conclusions Interactions where there is a diagnostic error, had shorter history-taking periods, longer diagnostic statements and featured more evidence. Time spent on history-taking and diagnosis, and use of evidentialised diagnostic statements may be indicators for diagnostic accuracy.

Objectives Podcasts have emerged as an efficient method for widespread delivery of educational clinical reasoning (CR) content. However, the impact of such podcasts on CR skills has not been established. We set out to determine whether exposure to expert reasoning in a podcast format leads to enhanced CR skills. Methods This is a pseudo-randomized study of third-year medical students (MS3) to either a control group (n=22) of pre-established online CR modules, or intervention group (n=26) with both the online modules and novel CR podcasts. The podcasts were developed from four “clinical unknown” cases presented to expert clinician educators. After completing these assignments in weeks 1–2, weekly history and physical (H&P) notes were collected and graded according to the validated IDEA rubric between weeks 3–7. A longitudinal regression model was used to compare the H&P IDEA scores over time. Usage and perception of the podcasts was also assessed via survey data. Results Ninety control and 128 intervention H&Ps were scored. There was no statistical difference in the change of average IDEA scores between intervention (0.92, p=0.35) and control groups (−0.33, p=0.83). Intervention participants positively received the podcasts and noted increased discussion of CR principles from both their ward (3.1 vs. 2.4, p=0.08) and teaching (3.2 vs. 2.5, p=0.05) attendings. Conclusions This is the first objective, pseudo-randomized assessment of CR podcasts in undergraduate medical education. While we did not demonstrate significant improvement in IDEA scores, our data show that podcasts are a well-received tool that can prime learners to recognize CR principles.

Objectives Diagnostic delays are a major source of morbidity and mortality. Despite the adverse outcomes associated with diagnostic delays, few studies have examined the incidence and factors that influence diagnostic delays for different infectious diseases. The objective of this study was to understand the relative frequency of diagnostic delays for six infectious diseases commonly seen by infectious diseases (ID) consultants and to examine contributing factors for these delays. Methods A 25-item survey to examine diagnostic delays in six infectious diseases was sent to all infectious diseases physicians in the Emerging Infections Network (EIN) who provide care to adult patients. Diseases included (1) tuberculosis, (2) non-tuberculous mycobacterial infections, (3) syphilis, (4) epidural abscess, (5) infective endocarditis, and (6) endemic fungal infections (e.g., histoplasmosis, blastomycosis). Results A total of 533 of 1,323 (40%) EIN members responded to the survey. Respondents perceived the diagnosis not being considered initially and the appropriate test not being ordered as the two most important contributors to diagnostic delays. Unusual clinical presentations and not consulting ID physicians early enough were also reported as a contributing factor to delays. Responses recorded in open-text fields also indicated errors related to testing as a likely cause of delays; specifically, test-related errors included ordering the wrong laboratory test, laboratory delays (specialized labs not available at the facility), and lab processing delays. Conclusions Diagnostic delays commonly occur for the infectious diseases we considered. The contributing factors we identified are potential targets for future interventions to decrease diagnostic delays.

Objectives Diagnostic programs and second opinion clinics have grown and evolved in the recent years to help patients with rare, puzzling, and complex conditions who often suffer prolonged diagnostic journeys, but there is a paucity of literature on the clinical characteristics of these patients and the efficacy of these diagnostic programs. This study aims to characterize the diagnostic journey, case features, and diagnostic outcomes of patients referred to a team-based second opinion clinic at Stanford. Methods Retrospective chart review was performed for 237 patients evaluated for diagnostic second opinion in the Stanford Consultative Medicine Clinic over a 5 year period. Descriptive case features and diagnostic outcomes were assessed, and correlation between the two was analyzed. Results Sixty-three percent of our patients were women. 49% of patients had a potential precipitating event within about a month prior to the start of their illness, such as medication change, infection, or medical procedure. A single clear diagnosis was determined in 33% of cases, whereas the remaining cases were assessed to have multifactorial contributors/diagnoses (20%) or remained unclear despite extensive evaluation (47%). Shorter duration of illness, fewer prior specialties seen, and single chief symptom were associated with higher likelihood of achieving a single clear diagnosis. Conclusions A single-site academic consultative service can offer additional diagnostic insights for about half of all patients evaluated for puzzling conditions. Better understanding of the clinical patterns and patient experiences gained from this study helps inform strategies to shorten their diagnostic odysseys.

Objectives Diagnostic errors are frequently the product of cognitive biases that arise when heuristic-based approaches fail. The efficiency-thoroughness tradeoff (ETTO) principle states sacrificing thoroughness for efficiency is normal and occurs frequently in medicine. The goal of a diagnostic timeout was to provide an actionable template for when providers transition to an analytical mindset and to help incorporate the ETTO principle during the diagnostic process. Methods A diagnostic time-out was adapted for use in pediatric hospital medicine (PHM). In this prospective study, a group of eight PHM providers piloted the time-out in the hospitalized setting. Data was collected over 12 months and descriptive statistics were used for analysis. Results Cases were most frequently chosen for time-out use due to clinician intuition. In more than half the cases the time-out didn’t confirm the initial diagnosis and alternate diagnoses for the wrong diagnosis were pursued. There was only one case of the time-out being burdensome from a time perspective. Learners participated in all cases. As a result of the diagnostic time-out, new actions were taken in all cases. Conclusions Implementation of a diagnostic time out provides an actionable template for providers to actively change their mindset to an analytical thinking process to counteract cognitive biases and potentially reduce diagnostic errors in the pediatric inpatient setting.

Objectives Diagnostic excellence is an important domain of healthcare quality. Delays in diagnosis have been described in 20–30% of children with abusive injuries. Despite the well characterized epidemiology, improvement strategies remain elusive. We sought to assess the applicability of diagnostic improvement instruments to cases of non-accidental trauma and to identify potential opportunities for system improvement in child physical abuse diagnosis. Methods We purposefully sampled 10 cases identified as having potential for system level interventions and in which the child had prior outpatient encounters to review. Experts in pediatrics, child abuse, and diagnostic improvement independently reviewed each case and completed SaferDx, a validated instrument used to evaluate the diagnostic process. Cases were subsequently discussed to map potential opportunities for improving the diagnostic process to the DEER Taxonomy, which classifies opportunities by type and phase of the diagnostic process. Results The most frequent improvement opportunities identified by the SaferDx were in recognition of potential alarm symptoms and in expanding differential diagnosis (5 of 10 cases). The most frequent DEER taxonomy process opportunities were in history taking (8 of 10) and hypothesis generation (7 of 10). Discussion elicited additional opportunities in reconsideration of provisional diagnoses, understanding biopsychosocial risk, and addressing information scatter within the electronic health record (EHR). Conclusions Applying a diagnostic excellence framework facilitated identification of systems opportunities to improve recognition of child abuse including integration of EHR information to support recognition of alarm symptoms, collaboration to support vulnerable families, and communication about diagnostic reasoning.

Objectives Identifying the causative bacterial pathogen for children with acute hematogenous musculoskeletal infections (MSKIs) allows for improved care. The purpose of our study was to determine if clinical markers could predict which patients will have a causative pathogen found on source culture alone, thus being highest yield to undergo operative diagnostic procedures. Methods A single-center, retrospective cohort study was performed. Medical records for patients between 6 months and 18 years of age admitted between July 2014 and September 2018 with a discharge diagnosis of acute osteomyelitis, septic arthritis, or pyomyositis were reviewed. Patients were stratified based on results of blood and source cultures. Predictors of interest were screened on a univariable basis with significant predictors retained in a multivariate analysis. Results There were 170 patients included. No predictors were significantly associated with increased odds of having a causative pathogen found on source culture alone. Degree of C-reactive protein elevation and history of fever were associated with decreased odds of being source culture positive, OR (95% CI); 0.92 (0.87, 0.98) and 0.39 (0.19, 0.81), respectively. Conclusions Predictive modeling failed to identify children with MSKIs whose causative pathogen was found by source culture alone. It is difficult to predict which MSKI patients will be highest yield for operative diagnostic procedures.

Objectives Antigen based rapid diagnostic tests possesses a potential to be utilized along with Gold standard methods to detect Covid-19 infection to cope with the demand of testing. The aim of this study was to determine diagnostic accuracy of electrochemiluminescence based automated antigen detection immunoassay comparing with molecular based test RT-PCR (Covid-19). Methods It was a cross-sectional study conducted in RMI Peshawar, from 1st April 2021 till 30th April 2021. The study comprised 170 individuals who were suspected of having Covid-19. Nasopharyngeal samples taken from suspected individuals were analyzed by RT-PCR and automated antigen test (Elecsys SARS-CoV-2 Antigen) simultaneously. The correlation of SARS-CoV-2 antigen with PCR positive and negative cases was analyzed for specificity, sensitivity respectively. Results The ECLIA based Elecsys antigen test (Roche) revealed overall sensitivity 72%, specificity 95% and accuracy of 94.9%. Sensitivity of antigen test progressively declined from 94.3% in Ct <25 to 70.8% in Ct 26–29 and then to 47.2% in Ct 30–35. Conclusions Based on the findings of our study we conclude that automated antigen testing (Elecsys SARS-CoV-2 Antigen) cannot replace molecular based testing like RT PCR. Elecsys SARS-CoV-2 Ag test should be used complementary to RT-PCR in testing algorithms. Frequent testing strategy should be adopted while using automated antigen testing to overcome its limitation in individuals with low viral loads.

Objectives Cellular analysis of body fluids (BFs) can assist clinicians for the diagnosis of many medical conditions. The aim of this work is the evaluation of the analytical performance of the UF-5000 body fluid mode (UF-BF) analyzer compared to the gold standard method (optical microscopy, OM) and to XN-1000 (XN-BF), another analyzer produced by the same manufacturer (Sysmex) and with a similar technology for BF analysis. Methods One hundred BF samples collected in K 3 EDTA tubes were analyzed by UF-BF, XN-BF and OM. The agreement was evaluated using Passing and Bablok regression and Bland–Altman plot analysis. The receiver operating characteristic (ROC) curves were selected for evaluating the diagnostic agreement between OM classification and UF-BF parameters. Results Comparison between UF-BF and OM, in all BF types, showed Passing and Bablok’s slope comprised between 0.99 (polymorphonuclear cells count, PMN-BF) and 1.39 (mononuclear cells count, MN-BF), the intercepts ranged between 26.47 (PMN-BF parameter) and 226.80 (white blood cell count). Bland–Altman bias was comprised between 7.3% (total cell count, TC-BF) and 52.9% (MN-BF). Comparison between UF-BF and XN-BF in all BF showed slopes ranged between 1.07 (TC-BF and PMN-BF) and 1.16 (MN-BF), intercepts ranged between 8.30 (PMN) and 64.78 (WBC-BF). Bland–Altman bias ranged between 5.8 (TC-BF) and 21.1% (MN-BF). The ROC curve analysis showed an area under the curve ranged between 0.9664 and 1.000. Conclusions UF-BF shows very good performance for the differential counts of cells in ascitic, pleural and synovial fluids and therefore it is useful to screen and count cells in this type of BF.

Objectives Intensivists and subspecialists often collaborate in diagnosing patients in the pediatric intensive care unit (PICU). Our objectives were to characterize critically ill children for whom subspecialty consultations were requested, describe consultation characteristics, and determine consultations’ impact on PICU diagnosis. Methods We performed a retrospective study using chart review in a single tertiary referral PICU including children admitted for acute illness. We collected data on patients with and without subspecialty consultations within the first three days of PICU admission and determined changes in PICU clinicians’ diagnostic evaluation or treatment after consultations. Results PICU clinicians requested 152 subspecialty consultations for 87 of 101 (86%) patients. Consultations were requested equally for assistance in diagnosis (65%) and treatment (66%). Eighteen of 87 (21%) patients with consultations had a change in diagnosis from PICU admission to discharge, 11 (61%) attributed to subspecialty input. Thirty-nine (45%) patients with consultations had additional imaging and/or laboratory testing and 48 (55%) had medication changes and/or a procedure performed immediately after consultation. Conclusions Subspecialty consultations were requested during a majority of PICU admissions. Consultations can influence the diagnosis and treatment of critically ill children. Future research should investigate PICU interdisciplinary collaborations, which are essential for teamwork in diagnosis.

We present two cases that highlight the role of pharmacists in the diagnostic process and illustrate how a culture of safety and teamwork between pharmacists and physicians can help prevent diagnostic errors.