Volume 11, Issue 1

Background Diagnostic imaging decision support (DI-DS) systems could be effective tools for reducing inappropriate diagnostic imaging examinations. Since effective design and evaluation of these systems requires in-depth understanding of their features and functions, the present study aims to map the existing literature on DI-DS systems to identify features and functions of these systems. Methods The search was performed using Scopus, Embase, PubMed, Web of Science, and Cochrane Central Registry of Controlled Trials (CENTRAL) and was limited to 2000 to 2021. Analytical studies, descriptive studies, reviews and book chapters that explicitly addressed the functions or features of DI-DS systems were included. Results A total of 6,046 studies were identified. Out of these, 55 studies met the inclusion criteria. From these, 22 functions and 22 features were identified. Some of the identified features were: visibility, content chunking/grouping, deployed as a multidisciplinary program, clinically valid and relevant feedback, embedding current evidence, and targeted recommendations. And, some of the identified functions were: displaying an appropriateness score, recommending alternative or more appropriate imaging examination(s), providing recommendations for next diagnostic steps, and providing safety alerts. Conclusions The set of features and functions obtained in the present study can provide a basis for developing well-designed DI-DS systems, which could help to improve adherence to diagnostic imaging guidelines, minimize unnecessary costs, and improve the outcome of care through appropriate diagnosis and on-time care delivery.

Objectives No framework currently exists to guide how payers and providers can collaboratively develop and implement incentives to improve diagnostic safety. We conducted a literature review and interviews with subject matter experts to develop a multi-component ‘Payer Relationships for Improving Diagnoses (PRIDx)’ framework, that could be used to engage payers in diagnostic safety efforts. Content The PRIDx framework, 1) conceptualizes diagnostic safety links to care provision, 2) illustrates ways to promote payer and provider engagement in the design and adoption of accountability mechanisms, and 3) explicates the use of data analytics. Certain approaches suggested by PRIDx were refined by subject matter expert interviewee perspectives. Summary The PRIDx framework can catalyze public and private payers to take specific actions to improve diagnostic safety. Outlook Implementation of the PRIDx framework requires new types of partnerships, including external support from public and private payer organizations, and requires creation of strong provider incentives without undermining providers’ sense of professionalism and autonomy. PRIDx could help facilitate collaborative payer-provider approaches to improve diagnostic safety and generate research concepts, policy ideas, and potential innovations for engaging payers in diagnostic safety improvement activities.

Differences in tumors related to location, tissue type, and histological subtype have been well documented for decades. Tumors are also molecularly very diverse. In this short review we describe the current classification schemes for tumor heterogeneity. We enlist the various drivers of tumor heterogeneity generation and comment on their clinical significance. New molecular techniques promise to assess tumor heterogeneity at affordable cost, so that these techniques can soon enter the clinic. While tumor heterogeneity currently represents a major unfavorable barrier in the field of oncology, it may also be a key in revolutionizing cancer diagnosis and treatment. Information regarding tumor heterogeneity has the potential to provide more thorough prognostic information, guide more efficacious combination treatment regimens, and lead to the development of novel therapeutic strategies and identification of new targets. For these gains to be realized, assessment of tumor heterogeneity needs to be incorporated into current diagnostic protocols but standardized and reproducible assessment methods are required. Fortunately, when these advances are realized, tumor heterogeneity has the potential to improve clinical outcomes.

Objectives Diagnostic errors are a source of morbidity and mortality in intensive care unit (ICU) patients. However, contextual factors influencing clinicians’ diagnostic performance have not been studied in authentic ICU settings. We sought to determine the accuracy of ICU clinicians’ diagnostic impressions and to characterize how various contextual factors, including self-reported stress levels and perceptions about the patient’s prognosis and complexity, impact diagnostic accuracy. We also explored diagnostic calibration, i.e. the balance of accuracy and confidence, among ICU clinicians. Methods We conducted an observational cohort study in an academic medical ICU. Between June and August 2019, we interviewed ICU clinicians during routine care about their patients’ diagnoses, their confidence, and other contextual factors. Subsequently, using adjudicated final diagnoses as the reference standard, two investigators independently rated clinicians’ diagnostic accuracy and on each patient on a given day (“patient-day”) using 5-point Likert scales. We conducted analyses using both restrictive and conservative definitions of clinicians’ accuracy based on the two reviewers’ ratings of accuracy. Results We reviewed clinicians’ responses for 464 unique patient-days, which included 255 total patients. Attending physicians had the greatest diagnostic accuracy (77–90 %, rated as three or higher on 5-point Likert scale) followed by the team’s primary fellow (73–88 %). Attending physician and fellows were also least affected by contextual factors. Diagnostic calibration was greatest among ICU fellows. Conclusions Additional studies are needed to better understand how contextual factors influence different clinicians’ diagnostic reasoning in the ICU.

Objectives This study aimed to assess the prevalence of atypical presentations and their association with diagnostic errors in various diseases. Methods This retrospective observational study was conducted using cohort data between January 1 and December 31, 2019. Consecutive outpatients consulted by physicians from the Department of Diagnostic and Generalist Medicine at a university hospital in Japan were included. Patients for whom the final diagnosis was not confirmed were excluded. Primary outcomes were the prevalence of atypical presentations, and the prevalence of diagnostic errors in groups with typical and atypical presentations. Diagnostic errors and atypical presentations were assessed using the Revised Safer Dx Instrument. We performed primary analyses using a criterion; the average score of less than five to item 12 of two independent reviewers was an atypical presentation (liberal criterion). We also performed additional analyses using another criterion; the average score of three or less to item 12 was an atypical presentation (conservative criterion). Results A total of 930 patients were included out of a total of 2022 eligible. The prevalence of atypical presentation was 21.7 and 6.7 % when using liberal and conservative criteria for atypical presentation, respectively. Diagnostic errors (2.8 %) were most commonly observed in the cases with slight to moderate atypical presentation. Atypical presentation was associated with diagnostic errors with the liberal criterion for atypical presentation; however, this diminished with the conservative criterion. Conclusions An atypical presentation was observed in up to 20 % of outpatients with a confirmed diagnosis, and slight to moderate atypical presentation may be the highest risk population for diagnostic errors.

Objectives To investigate the relationship between language and diagnostic errors (DxE) in the pediatric emergency department (ED). Methods Electronic trigger identified ED encounters resulting in unplanned hospital admission that occurred within 10 days of an index visit from January 2018 through February 2022. Manual screening of each triggered encounter identified cases where the index visit diagnosis and hospitalization discharge diagnosis differed, and these were screened in for review using the Revised Safer Dx instrument to determine if a diagnostic error (DxE) occurred. Non-English primary language (NEPL) and English-proficient (EP) groups were established based on caregiver language. The primary outcome was the proportion of DxE each group. Data were analyzed using univariate analysis and multivariable logistic regression to identify independent predictors of DxE. Results Electronic trigger identified 3,551 patients, of which 806 (22.7 %) screened in for Safer Dx review. 172 (21.3 %) experienced DxE. The proportion of DxE was similar between EP and NEPL groups (21.5 vs. 21.7 %; p=0.97). Age≥12 years and fewer prior admissions in the preceding 6 months predicted higher odds of DxE. NEPL did not predict higher odds of DxE. Conclusions NEPL was not associated with increased odds DxE resulting in unplanned admission.

Objectives Fevers have been used as a marker of disease for hundreds of years and are frequently used for disease screening. However, body temperature varies over the course of a day and across individual characteristics; such variation may limit the detection of febrile episodes complicating the diagnostic process. Our objective was to describe individual variation in diurnal temperature patterns during episodes of febrile activity using millions of recorded temperatures and evaluate the probability of recording a fever by sex and for different age groups. Methods We use timestamped deidentified temperature readings from thermometers across the US to construct illness episodes where continuous periods of activity in a single user included a febrile reading. We model the mean temperature recorded and probability of registering a fever across the course of a day using sinusoidal regression models while accounting for user age and sex. We then estimate the probability of recording a fever by time of day for children, working-age adults, and older adults. Results We find wide variation in body temperatures over the course of a day and across individual characteristics. The diurnal temperature pattern differed between men and women, and average temperatures declined for older age groups. The likelihood of detecting a fever varied widely by the time of day and by an individual’s age or sex. Conclusions Time of day and demographics should be considered when using body temperatures for diagnostic or screening purposes. Our results demonstrate the importance of follow-up thermometry readings if infectious diseases are suspected.

Objectives Accurate and timely diagnosis relies on close collaboration between patients/families and clinicians. Just as patients have unique insights into diagnostic breakdowns, positive patient feedback may also generate broader perspectives on what constitutes a “good” diagnostic process (DxP). Methods We evaluated patient/family feedback on “what’s going well” as part of an online pre-visit survey designed to engage patients/families in the DxP. Patients/families living with chronic conditions with visits in three urban pediatric subspecialty clinics (site 1) and one rural adult primary care clinic (site 2) were invited to complete the survey between December 2020 and March 2022. We adapted the Healthcare Complaints Analysis Tool (HCAT) to conduct a qualitative analysis on a subset of patient/family responses with ≥20 words. Results In total, 7,075 surveys were completed before 18,129 visits (39 %) at site 1, and 460 surveys were completed prior to 706 (65 %) visits at site 2. Of all participants, 1,578 volunteered positive feedback, ranging from 1–79 words. Qualitative analysis of 272 comments with ≥20 words described: Relationships (60 %), Clinical Care (36 %), and Environment (4 %). Compared to primary care, subspecialty comments showed the same overall rankings. Within Relationships, patients/families most commonly noted: thorough and competent attention (46 %), clear communication and listening (41 %) and emotional support and human connection (39 %). Within Clinical Care, patients highlighted: timeliness (31 %), effective clinical management (30 %), and coordination of care (25 %). Conclusions Patients/families valued relationships with clinicians above all else in the DxP, emphasizing the importance of supporting clinicians to nurture effective relationships and relationship-centered care in the DxP.

Objectives Dizziness is a common medical symptom that is frequently misdiagnosed. While virtual patient (VP) education has been shown to improve diagnostic accuracy for dizziness as assessed by VPs, trainee performance has not been assessed on human subjects. The study aimed to assess whether internal medicine (IM) interns after training on a VP-based dizziness curriculum using a deliberate practice framework would demonstrate improved clinical reasoning when assessed in an objective structured clinical examination (OSCE). Methods All available interns volunteered and were randomized 2:1 to intervention (VP education) vs. control (standard clinical teaching) groups. This quasi-experimental study was conducted at one academic medical center from January to May 2021. Both groups completed pre-posttest VP case assessments (scored as correct diagnosis across six VP cases) and participated in an OSCE done 6 weeks later. The OSCEs were recorded and assessed using a rubric that was systematically developed and validated. Results Out of 21 available interns, 20 participated. Between intervention (n=13) and control (n=7), mean pretest VP diagnostic accuracy scores did not differ; the posttest VP scores improved for the intervention group (3.5 [SD 1.3] vs. 1.6 [SD 0.8], p=0.007). On the OSCE, the means scores were higher in the intervention (n=11) compared to control group (n=4) for physical exam (8.4 [SD 4.6] vs. 3.9 [SD 4.0], p=0.003) and total rubric score (43.4 [SD 12.2] vs. 32.6 [SD 11.3], p=0.04). Conclusions The VP-based dizziness curriculum resulted in improved diagnostic accuracy among IM interns with enhanced physical exam skills retained at 6 weeks post-intervention.

Objectives The present study aimed to identify optimal inflammatory biomarkers involved in cardiorenal risk in response to major lifestyle factors. Methods One hundred and twenty-nine adults aged 35–77 years participated voluntarily from 2017 to 2019 (Córdoba, Argentina) in a cross-sectional study to collect sociodemographic, clinical, and lifestyle data. Blood biomarkers (different cytokines, monocyte chemoattractant protein-1 [MCP-1], and high-sensitivity C-reactive protein [hs-CRP]) were measured using standard methods and then evaluated by principal component analysis and structural equation modeling (SEM) according to Mediterranean diet adherence, physical activity level, and waist circumference, while cardiorenal risk involved blood diastolic pressure, HDL-cholesterol, triacylglycerols, creatinine, and glycosylated hemoglobin. Results A principal component included TNF-α (tumor necrosis factor-alpha), IL-8 (interleukin-8), IL-6 (interleukin-6), hs-CRP, and MCP-1, with absolute rotated factor loadings >0.10. SEM showed that IL-6 (β=0.38, 95 % IC=0.08–0.68), hs-CRP (β=0.33, 95 % IC=0.17–0.48), and TNF-α (β=0.22, 95 % IC=0.11–0.32) were the mediators that better explained an inflammatory profile positively related to waist circumference (β=0.77, 95 % IC=0.61–0.94). Moreover, this profile was associated with an increased cardiorenal risk (β=0.78, 95 % IC=0.61–0.94), which was well-defined by the variable used. Conclusions Immune mediators are key elements in profiling the cardiorenal risk associated with lifestyle factors, for which the combination of hs-CRP, IL-6, and TNF-α has emerged as a robust indicator. This work reaffirms the need for biomarker optimization for early diagnosis and risk assessment.

Objectives There is limited information on the influence of collecting small amounts of blood on the quality of blood gas analysis. Therefore, the purpose of this study was to investigate the effects of different degrees of underfilling of syringes on test results of venous blood gas analysis. Methods Venous blood was collected by venipuncture from 19 healthcare workers in three 1.0 mL syringes for blood gas analysis, by manually aspirating different volumes of blood (i.e., 1.0, 0.5 and 0.25 mL). Routine blood gas analysis was then immediately performed with GEM Premier 5,000. The results of the two underfilled syringes were compared with those of the reference syringe filled with appropriate blood volume. Results The values of most assayed parameters did not differ significantly in the two underfilled syringes. Statistically significant variations were found for lactate, hematocrit and total hemoglobin, the values of which gradually increased as the fill volume diminished, as well as for sodium concentration, which decreased in both insufficiently filled blood gas syringes. The bias was clinically meaningful for lactate in syringe filled with 0.25 mL of blood, and for hematocrit, total hemoglobin and sodium in both syringes containing 0.5 and 0.25 mL of blood. Conclusions Collection of smaller volumes of venous blood than the specified filling volume in blood gas syringes may have an effect on the quality of some test results, namely lactate, hematocrit, total hemoglobin and sodium. Specific indications must be given for standardizing the volume of blood to be collected within these syringes.

Objectives Little is known about how patients perceive diagnostic uncertainty. We sought to understand how patients and care partners perceive uncertainty in an emergency or urgent care setting, where making a final diagnosis is often not possible. Methods We administered a survey to a nationally representative panel on patient-reported diagnostic excellence in an emergency department or urgent care setting. The survey included items specific to perceived diagnostic excellence, visit characteristics, and demographics. We analyzed responses to two open-ended questions among those who reported uncertainty in the explanation they were given. Themes were identified using an inductive approach, and compared by whether respondents agreed or disagreed the explanation they were given was true. Results Of the 1,116 respondents, 106 (10 %) reported that the care team was not certain in the explanation of their health problem. Five themes were identified in the open-ended responses: poor communication (73 %), uncertainty made transparent (10 %), incorrect information provided (9 %), inadequate testing equipment (4 %), and unable to determine (4 %). Of the respondents who reported uncertainty, 21 % (n=22/106) reported the explanation of their problem given was not true. Conclusions The findings of this analysis suggest that the majority of patients and their care partners do not equate uncertainty with a wrong explanation of their health problem, and that poor communication was the most commonly cited reason for perceived uncertainty.

Objectives This study aimed to elucidate effective methodologies for utilizing the generative artificial intelligence (AI) system, namely the Chat Generative Pre-trained Transformer (ChatGPT), in improving clinical reasoning abilities among clinicians. Methods We conducted a comprehensive exploration of the capabilities of ChatGPT, emphasizing two main areas: (1) efficient utilization of ChatGPT, with a focus on application and language selection, input methodology, and output verification; and (2) specific strategies to bolster clinical reasoning using ChatGPT, including self-learning via simulated clinical case creation and engagement with published case reports. Results Effective AI-based clinical reasoning development requires a clear delineation of both system roles and user needs. All outputs from the system necessitate rigorous verification against credible medical resources. When used in self-learning scenarios, capabilities of ChatGPT in clinical case creation notably enhanced disease comprehension. Conclusions The efficient use of generative AIs, as exemplified by ChatGPT, can impressively enhance clinical reasoning among medical professionals. Adopting these cutting-edge tools promises a bright future for continuous advancements in clinicians’ diagnostic skills, heralding a transformative era in digital healthcare.

Objectives Prevention of pre-analytical issues in coagulation testing is of paramount importance for good laboratory performance. In addition to common issues like hemolysed, icteric, or lipemic samples, some specific pre-analytical errors of coagulation testing include clotted specimens, improper blood-to-anticoagulant ratio, contamination with other anticoagulants, etc. Prothrombin time (PT) and activated partial thromboplastin time (aPTT) are very commonly affected tests due to pre-analytical variables. The impact these parameters possess on surgical decision-making and various life-saving interventions are substantial therefore we cannot afford laxity and casual mistakes in carrying out these critical investigations at all. Case presentation In this case series, a total of 4 cases of unexpectedly deranged coagulation profiles have been described which were reported incorrectly due to the overall casual approach towards these critical investigations. We have also mentioned how the treating clinician and lab physician retrospectively accessed relevant information in the nick of time to bring back reassurance. Conclusions Like every other critical investigation, analytical errors can occur in coagulation parameters due to various avoidable pre-analytical variables. The release of spurious results for coagulation parameters sets alarm bells ringing causing much agony to the treating doctor and patient. Only a disciplined and careful approach taken by hospital and lab staff towards each sample regardless of its criticality can negate these stressful errors to a large extent.