Pub Date : 2023-09-05eCollection Date: 2024-02-01DOI: 10.1515/dx-2023-0096
Giuseppe Lippi, Laura Pighi, Marco Tosi, Marco Vettori, Giovanni Celegon, Emmanuel J Favaloro, Gian Luca Salvagno
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.
目的:有关采集少量血液对血气分析质量的影响的信息十分有限。因此,本研究旨在探讨不同程度的注射器填充不足对静脉血气分析测试结果的影响:方法:通过静脉穿刺采集 19 名医护人员的静脉血,用三个 1.0 mL 注射器手动抽取不同体积的血液(即 1.0、0.5 和 0.25 mL)进行血气分析。然后立即使用 GEM Premier 5,000 进行常规血气分析。将两支未充分灌注的注射器的结果与注入适当血量的参照注射器的结果进行比较:结果:大部分检测参数的数值在两支充气不足的注射器中没有明显差异。乳酸、血细胞比容和总血红蛋白的数值随着充盈量的减少而逐渐增加,钠浓度也随着充盈量的减少而降低。在装有 0.25 毫升血液的注射器中,乳酸盐的偏差具有临床意义;在装有 0.5 毫升和 0.25 毫升血液的注射器中,血细胞比容、总血红蛋白和钠的偏差都具有临床意义:结论:采集的静脉血量少于血气分析仪规定的充盈量可能会影响某些检测结果的质量,如乳酸、血细胞比容、总血红蛋白和钠。必须给出具体说明,以规范这些注射器的采血量。
{"title":"Effect of syringe underfilling on the quality of venous blood gas analysis.","authors":"Giuseppe Lippi, Laura Pighi, Marco Tosi, Marco Vettori, Giovanni Celegon, Emmanuel J Favaloro, Gian Luca Salvagno","doi":"10.1515/dx-2023-0096","DOIUrl":"10.1515/dx-2023-0096","url":null,"abstract":"<p><strong>Objectives: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10137899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-05eCollection Date: 2023-11-01DOI: 10.1515/dx-2023-0089
Ralf E Harskamp, Lukas De Clercq, Lieke Veelers, Martijn C Schut, Henk C P M van Weert, M Louis Handoko, Eric P Moll van Charante, Jelle C L Himmelreich
Objectives: Heart failure (HF) is a prevalent syndrome with considerable disease burden, healthcare utilization and costs. Timely diagnosis is essential to improve outcomes. This study aimed to compare the diagnostic performance of B-type natriuretic peptide (BNP) and N-terminal proBNP (NT-proBNP) in detecting HF in primary care. Our second aim was to explore if personalized thresholds (using age, sex, or other readily available parameters) would further improve diagnostic accuracy over universal thresholds.
Methods: A retrospective study was performed among patients without prior HF who underwent natriuretic peptide (NP) testing in the Amsterdam General Practice Network between January 2011 and December 2021. HF incidence was based on registration out to 90 days after NP testing. Diagnostic accuracy was evaluated with AUROC, sensitivity and specificity based on guideline-recommended thresholds (125 ng/L for NT-proBNP and 35 ng/L for BNP). We used inverse probability of treatment weighting to adjust for confounding.
Results: A total of 15,234 patients underwent NP testing, 6,870 with BNP (4.5 % had HF), and 8,364 with NT-proBNP (5.7 % had HF). NT-proBNP was more accurate than BNP, with an AUROC of 89.9 % (95 % CI: 88.4-91.2) vs. 85.9 % (95 % CI 83.5-88.2), with higher sensitivity (95.3 vs. 89.7 %) and specificity (59.1 vs. 58.0 %). Differentiating NP cut-off by clinical variables modestly improved diagnostic accuracy for BNP and NT-proBNP compared with a universal threshold.
Conclusions: NT-proBNP outperforms BNP for detecting HF in primary care. Personalized instead of universal diagnostic thresholds led to modest improvement.
{"title":"Diagnostic properties of natriuretic peptides and opportunities for personalized thresholds for detecting heart failure in primary care.","authors":"Ralf E Harskamp, Lukas De Clercq, Lieke Veelers, Martijn C Schut, Henk C P M van Weert, M Louis Handoko, Eric P Moll van Charante, Jelle C L Himmelreich","doi":"10.1515/dx-2023-0089","DOIUrl":"10.1515/dx-2023-0089","url":null,"abstract":"<p><strong>Objectives: </strong>Heart failure (HF) is a prevalent syndrome with considerable disease burden, healthcare utilization and costs. Timely diagnosis is essential to improve outcomes. This study aimed to compare the diagnostic performance of B-type natriuretic peptide (BNP) and N-terminal proBNP (NT-proBNP) in detecting HF in primary care. Our second aim was to explore if personalized thresholds (using age, sex, or other readily available parameters) would further improve diagnostic accuracy over universal thresholds.</p><p><strong>Methods: </strong>A retrospective study was performed among patients without prior HF who underwent natriuretic peptide (NP) testing in the Amsterdam General Practice Network between January 2011 and December 2021. HF incidence was based on registration out to 90 days after NP testing. Diagnostic accuracy was evaluated with AUROC, sensitivity and specificity based on guideline-recommended thresholds (125 ng/L for NT-proBNP and 35 ng/L for BNP). We used inverse probability of treatment weighting to adjust for confounding.</p><p><strong>Results: </strong>A total of 15,234 patients underwent NP testing, 6,870 with BNP (4.5 % had HF), and 8,364 with NT-proBNP (5.7 % had HF). NT-proBNP was more accurate than BNP, with an AUROC of 89.9 % (95 % CI: 88.4-91.2) vs. 85.9 % (95 % CI 83.5-88.2), with higher sensitivity (95.3 vs. 89.7 %) and specificity (59.1 vs. 58.0 %). Differentiating NP cut-off by clinical variables modestly improved diagnostic accuracy for BNP and NT-proBNP compared with a universal threshold.</p><p><strong>Conclusions: </strong>NT-proBNP outperforms BNP for detecting HF in primary care. Personalized instead of universal diagnostic thresholds led to modest improvement.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10526720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-21eCollection Date: 2023-11-01DOI: 10.1515/dx-2023-0046
Ella G Cornell, Emily Harris, Emma McCune, Elle Fukui, Patrick G Lyons, Juan C Rojas, Lekshmi Santhosh
Objectives: The transition from the intensive care unit (ICU) to the medical ward is a high-risk period due to medical complexity, reduced patient monitoring, and diagnostic uncertainty. Standardized handoff practices reduce errors associated with transitions of care, but little work has been done to standardize the ICU to ward handoff. Further, tools that exist do not focus on preventing diagnostic error. Using Human-Centered Design methods we previously created a novel EHR-based ICU-ward handoff tool (ICU-PAUSE) that embeds a diagnostic pause at the time of transfer. This study aims to explore barriers and facilitators to implementing a diagnostic pause at the ICU-to-ward transition.
Methods: This is a multi-center qualitative study of semi-structured interviews with intensivists from ten academic medical centers. Interviews were analyzed iteratively through a grounded theory approach. The Sittig-Singh sociotechnical model was used as a unifying conceptual framework.
Results: Across the eight domains of the model, we identified major benefits and barriers to implementation. The embedded pause to address diagnostic uncertainty was recognized as a key benefit. Participants agreed that standardization of verbal and written handoff would decrease variation in communication. The main barriers fell within the domains of workflow, institutional culture, people, and assessment.
Conclusions: This study represents a novel application of the Sittig-Singh model in the assessment of a handoff tool. A unique feature of ICU-PAUSE is the explicit acknowledgement of diagnostic uncertainty, a practice that has been shown to reduce medical error and prevent premature closure. Results will be used to inform future multi-site implementation efforts.
{"title":"Scaling up a diagnostic pause at the ICU-to-ward transition: an exploration of barriers and facilitators to implementation of the ICU-PAUSE handoff tool.","authors":"Ella G Cornell, Emily Harris, Emma McCune, Elle Fukui, Patrick G Lyons, Juan C Rojas, Lekshmi Santhosh","doi":"10.1515/dx-2023-0046","DOIUrl":"10.1515/dx-2023-0046","url":null,"abstract":"<p><strong>Objectives: </strong>The transition from the intensive care unit (ICU) to the medical ward is a high-risk period due to medical complexity, reduced patient monitoring, and diagnostic uncertainty. Standardized handoff practices reduce errors associated with transitions of care, but little work has been done to standardize the ICU to ward handoff. Further, tools that exist do not focus on preventing diagnostic error. Using Human-Centered Design methods we previously created a novel EHR-based ICU-ward handoff tool (ICU-PAUSE) that embeds a diagnostic pause at the time of transfer. This study aims to explore barriers and facilitators to implementing a diagnostic pause at the ICU-to-ward transition.</p><p><strong>Methods: </strong>This is a multi-center qualitative study of semi-structured interviews with intensivists from ten academic medical centers. Interviews were analyzed iteratively through a grounded theory approach. The Sittig-Singh sociotechnical model was used as a unifying conceptual framework.</p><p><strong>Results: </strong>Across the eight domains of the model, we identified major benefits and barriers to implementation. The embedded pause to address diagnostic uncertainty was recognized as a key benefit. Participants agreed that standardization of verbal and written handoff would decrease variation in communication. The main barriers fell within the domains of workflow, institutional culture, people, and assessment.</p><p><strong>Conclusions: </strong>This study represents a novel application of the Sittig-Singh model in the assessment of a handoff tool. A unique feature of ICU-PAUSE is the explicit acknowledgement of diagnostic uncertainty, a practice that has been shown to reduce medical error and prevent premature closure. Results will be used to inform future multi-site implementation efforts.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10021918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-17eCollection Date: 2023-11-01DOI: 10.1515/dx-2023-0090
Mehdi Dadkhah, Marilyn H Oermann, Mihály Hegedüs, Raghu Raman, Lóránt Dénes Dávid
Objectives: Paper mills, companies that write scientific papers and gain acceptance for them, then sell authorships of these papers, present a key challenge in medicine and other healthcare fields. This challenge is becoming more acute with artificial intelligence (AI), where AI writes the manuscripts and then the paper mills sell the authorships of these papers. The aim of the current research is to provide a method for detecting fake papers.
Methods: The method reported in this article uses a machine learning approach to create decision trees to identify fake papers. The data were collected from Web of Science and multiple journals in various fields.
Results: The article presents a method to identify fake papers based on the results of decision trees. Use of this method in a case study indicated its effectiveness in identifying a fake paper.
Conclusions: This method to identify fake papers is applicable for authors, editors, and publishers across fields to investigate a single paper or to conduct an analysis of a group of manuscripts. Clinicians and others can use this method to evaluate articles they find in a search to ensure they are not fake articles and instead report actual research that was peer reviewed prior to publication in a journal.
目标:造纸厂,撰写科学论文并获得认可,然后出售这些论文的作者身份的公司,在医学和其他医疗保健领域提出了一个关键挑战。随着人工智能(AI)的出现,这一挑战变得更加严峻,人工智能撰写手稿,然后造纸厂出售这些论文的作者身份。目前研究的目的是提供一种检测假论文的方法。方法:本文报告的方法使用机器学习方法创建决策树来识别假论文。数据收集自Web of Science和多个领域的期刊。结果:本文提出了一种基于决策树结果的伪论文识别方法。在一个案例研究中使用这种方法表明了它在识别假论文方面的有效性。结论:这种识别假论文的方法适用于跨领域的作者、编辑和出版商调查一篇论文或对一组手稿进行分析。临床医生和其他人可以使用这种方法来评估他们在搜索中找到的文章,以确保它们不是假文章,而是报告在期刊上发表之前经过同行评审的实际研究。
{"title":"Detection of fake papers in the era of artificial intelligence.","authors":"Mehdi Dadkhah, Marilyn H Oermann, Mihály Hegedüs, Raghu Raman, Lóránt Dénes Dávid","doi":"10.1515/dx-2023-0090","DOIUrl":"10.1515/dx-2023-0090","url":null,"abstract":"<p><strong>Objectives: </strong>Paper mills, companies that write scientific papers and gain acceptance for them, then sell authorships of these papers, present a key challenge in medicine and other healthcare fields. This challenge is becoming more acute with artificial intelligence (AI), where AI writes the manuscripts and then the paper mills sell the authorships of these papers. The aim of the current research is to provide a method for detecting fake papers.</p><p><strong>Methods: </strong>The method reported in this article uses a machine learning approach to create decision trees to identify fake papers. The data were collected from Web of Science and multiple journals in various fields.</p><p><strong>Results: </strong>The article presents a method to identify fake papers based on the results of decision trees. Use of this method in a case study indicated its effectiveness in identifying a fake paper.</p><p><strong>Conclusions: </strong>This method to identify fake papers is applicable for authors, editors, and publishers across fields to investigate a single paper or to conduct an analysis of a group of manuscripts. Clinicians and others can use this method to evaluate articles they find in a search to ensure they are not fake articles and instead report actual research that was peer reviewed prior to publication in a journal.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10395008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-14eCollection Date: 2023-11-01DOI: 10.1515/dx-2023-0032
Lawrence B Afrin, Tania T Dempsey, Gerhard J Molderings
Objectives: To describe patterns observed in antibody titer trendlines in patients with mast cell activation syndrome (MCAS, a prevalent but underrecognized chronic multisystem inflammatory disorder of great clinical heterogeneity) and offer clinical lessons learned from such pattern recognition.
Methods: The available records of 104 MCAS patients drawn from the authors' practices were reviewed, including all antibody tests therein.
Results: All patients had positive/elevated antibodies of various sorts at various points, but for most of the antibodies which were found to be positive at least some points, the diseases classically associated with those antibodies were not present, marking such antibodies as clinically insignificant mimickers (likely consequent to inflammatory effects of MCAS on the immune system itself driving spurious/random antibody production) rather than "on-target" and pathogenic antibodies reflecting true disease warranting treatment. We also observed two distinct patterns in trendlines of the titers of the mimickers vs. the trendline pattern expected in a true case of an antibody-associated disease (AAD).
Conclusions: Our observations suggest most positive antibody tests in MCAS patients represent detection of clinically insignificant mimicking antibodies. As such, to reduce incorrect diagnoses of AADs and inappropriate treatment in MCAS patients, caution is warranted in interpreting positive antibody tests in these patients. Except in clinically urgent/emergent situations, patience in determining the trendline of a positive antibody in an MCAS patient, and more carefully assessing whether the AAD is truly present, is to be preferred.
{"title":"Learned cautions regarding antibody testing in mast cell activation syndrome.","authors":"Lawrence B Afrin, Tania T Dempsey, Gerhard J Molderings","doi":"10.1515/dx-2023-0032","DOIUrl":"10.1515/dx-2023-0032","url":null,"abstract":"<p><strong>Objectives: </strong>To describe patterns observed in antibody titer trendlines in patients with mast cell activation syndrome (MCAS, a prevalent but underrecognized chronic multisystem inflammatory disorder of great clinical heterogeneity) and offer clinical lessons learned from such pattern recognition.</p><p><strong>Methods: </strong>The available records of 104 MCAS patients drawn from the authors' practices were reviewed, including all antibody tests therein.</p><p><strong>Results: </strong>All patients had positive/elevated antibodies of various sorts at various points, but for most of the antibodies which were found to be positive at least some points, the diseases classically associated with those antibodies were not present, marking such antibodies as clinically insignificant mimickers (likely consequent to inflammatory effects of MCAS on the immune system itself driving spurious/random antibody production) rather than \"on-target\" and pathogenic antibodies reflecting true disease warranting treatment. We also observed two distinct patterns in trendlines of the titers of the mimickers vs. the trendline pattern expected in a true case of an antibody-associated disease (AAD).</p><p><strong>Conclusions: </strong>Our observations suggest most positive antibody tests in MCAS patients represent detection of clinically insignificant mimicking antibodies. As such, to reduce incorrect diagnoses of AADs and inappropriate treatment in MCAS patients, caution is warranted in interpreting positive antibody tests in these patients. Except in clinically urgent/emergent situations, patience in determining the trendline of a positive antibody in an MCAS patient, and more carefully assessing whether the AAD is truly present, is to be preferred.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10405731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-11eCollection Date: 2023-11-01DOI: 10.1515/dx-2023-0065
Justin J Choi, Michael A Rosen, Martin F Shapiro, Monika M Safford
Objectives: Achieving diagnostic excellence on medical wards requires teamwork and effective team dynamics. However, the study of ward team dynamics in teaching hospitals is relatively underdeveloped. We aim to enhance understanding of how ward team members interact in the diagnostic process and of the underlying behavioral, psychological, and cognitive mechanisms driving team interactions.
Methods: We used mixed-methods to develop and refine a conceptual model of how ward team dynamics in an academic medical center influence the diagnostic process. First, we systematically searched existing literature for conceptual models and empirical studies of team dynamics. Then, we conducted field observations with thematic analysis to refine our model.
Results: We present a conceptual model of how medical ward team dynamics influence the diagnostic process, which serves as a roadmap for future research and interventions in this area. We identified three underexplored areas of team dynamics that are relevant to diagnostic excellence and that merit future investigation (1): ward team structures (e.g., team roles, responsibilities) (2); contextual factors (e.g., time constraints, location of team members, culture, diversity); and (3) emergent states (shared mental models, psychological safety, team trust, and team emotions).
Conclusions: Optimizing the diagnostic process to achieve diagnostic excellence is likely to depend on addressing all of the potential barriers and facilitators to ward team dynamics presented in our model.
{"title":"Towards diagnostic excellence on academic ward teams: building a conceptual model of team dynamics in the diagnostic process.","authors":"Justin J Choi, Michael A Rosen, Martin F Shapiro, Monika M Safford","doi":"10.1515/dx-2023-0065","DOIUrl":"10.1515/dx-2023-0065","url":null,"abstract":"<p><strong>Objectives: </strong>Achieving diagnostic excellence on medical wards requires teamwork and effective team dynamics. However, the study of ward team dynamics in teaching hospitals is relatively underdeveloped. We aim to enhance understanding of how ward team members interact in the diagnostic process and of the underlying behavioral, psychological, and cognitive mechanisms driving team interactions.</p><p><strong>Methods: </strong>We used mixed-methods to develop and refine a conceptual model of how ward team dynamics in an academic medical center influence the diagnostic process. First, we systematically searched existing literature for conceptual models and empirical studies of team dynamics. Then, we conducted field observations with thematic analysis to refine our model.</p><p><strong>Results: </strong>We present a conceptual model of how medical ward team dynamics influence the diagnostic process, which serves as a roadmap for future research and interventions in this area. We identified three underexplored areas of team dynamics that are relevant to diagnostic excellence and that merit future investigation (1): ward team structures (e.g., team roles, responsibilities) (2); contextual factors (e.g., time constraints, location of team members, culture, diversity); and (3) emergent states (shared mental models, psychological safety, team trust, and team emotions).</p><p><strong>Conclusions: </strong>Optimizing the diagnostic process to achieve diagnostic excellence is likely to depend on addressing all of the potential barriers and facilitators to ward team dynamics presented in our model.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10345742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objectives: To assess the usefulness of case reports as sources for research on diagnostic errors in uncommon diseases and atypical presentations.
Content: We reviewed 563 case reports of diagnostic error. The commonality of the final diagnoses was classified based on the description in the articles, Orphanet, or epidemiological data on available references; the typicality of presentation was classified based on the description in the articles and the judgment of the physician researchers. Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC), and Generic Diagnostic Pitfalls (GDP) taxonomies were used to assess the factors contributing to diagnostic errors.
Summary and outlook: Excluding three cases in that commonality could not be classified, 560 cases were classified into four categories: typical presentations of common diseases (60, 10.7 %), atypical presentations of common diseases (35, 6.2 %), typical presentations of uncommon diseases (276, 49.3 %), and atypical presentations of uncommon diseases (189, 33.8 %). The most important DEER taxonomy was "Failure/delay in considering the diagnosis" among the four categories, whereas the most important RDC and GDP taxonomies varied with the categories. Case reports can be a useful data source for research on the diagnostic errors of uncommon diseases with or without atypical presentations.
{"title":"Diagnostic errors in uncommon conditions: a systematic review of case reports of diagnostic errors.","authors":"Yukinori Harada, Takashi Watari, Hiroyuki Nagano, Tomoharu Suzuki, Kotaro Kunitomo, Taiju Miyagami, Tetsuro Aita, Kosuke Ishizuka, Mika Maebashi, Taku Harada, Tetsu Sakamoto, Shusaku Tomiyama, Taro Shimizu","doi":"10.1515/dx-2023-0030","DOIUrl":"10.1515/dx-2023-0030","url":null,"abstract":"<p><strong>Objectives: </strong>To assess the usefulness of case reports as sources for research on diagnostic errors in uncommon diseases and atypical presentations.</p><p><strong>Content: </strong>We reviewed 563 case reports of diagnostic error. The commonality of the final diagnoses was classified based on the description in the articles, Orphanet, or epidemiological data on available references; the typicality of presentation was classified based on the description in the articles and the judgment of the physician researchers. Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC), and Generic Diagnostic Pitfalls (GDP) taxonomies were used to assess the factors contributing to diagnostic errors.</p><p><strong>Summary and outlook: </strong>Excluding three cases in that commonality could not be classified, 560 cases were classified into four categories: typical presentations of common diseases (60, 10.7 %), atypical presentations of common diseases (35, 6.2 %), typical presentations of uncommon diseases (276, 49.3 %), and atypical presentations of uncommon diseases (189, 33.8 %). The most important DEER taxonomy was \"Failure/delay in considering the diagnosis\" among the four categories, whereas the most important RDC and GDP taxonomies varied with the categories. Case reports can be a useful data source for research on the diagnostic errors of uncommon diseases with or without atypical presentations.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10021090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
James G Boyle, Matthew R Walters, Susan Jamieson, Steven J Durning
Context specificity refers to the vexing phenomenon whereby a physician can see two patients with the same presenting complaint, identical history and physical examination findings, but due to specific situational (contextual) factors arrives at two different diagnostic labels. Context specificity remains incompletely understood and undoubtedly leads to unwanted variance in diagnostic outcomes. Previous empirical work has demonstrated that a variety of contextual factors impacts clinical reasoning. These findings, however, have largely focused on the individual clinician; here we broaden this work to reframe context specificity in relation to clinical reasoning by an internal medicine rounding team through the lens of Distributed Cognition (DCog). In this model, we see how meaning is distributed amongst the different members of a rounding team in a dynamic fashion that evolves over time. We describe four different ways in which context specificity plays out differently in team-based clinical care than for a single clinician. While we use examples from internal medicine, we believe that the concepts we present apply equally to other specialties and fields in health care.
{"title":"Reframing context specificity in team diagnosis using the theory of distributed cognition.","authors":"James G Boyle, Matthew R Walters, Susan Jamieson, Steven J Durning","doi":"10.1515/dx-2022-0100","DOIUrl":"https://doi.org/10.1515/dx-2022-0100","url":null,"abstract":"<p><p>Context specificity refers to the vexing phenomenon whereby a physician can see two patients with the same presenting complaint, identical history and physical examination findings, but due to specific situational (contextual) factors arrives at two different diagnostic labels. Context specificity remains incompletely understood and undoubtedly leads to unwanted variance in diagnostic outcomes. Previous empirical work has demonstrated that a variety of contextual factors impacts clinical reasoning. These findings, however, have largely focused on the individual clinician; here we broaden this work to reframe context specificity in relation to clinical reasoning by an internal medicine rounding team through the lens of Distributed Cognition (DCog). In this model, we see how meaning is distributed amongst the different members of a rounding team in a dynamic fashion that evolves over time. We describe four different ways in which context specificity plays out differently in team-based clinical care than for a single clinician. While we use examples from internal medicine, we believe that the concepts we present apply equally to other specialties and fields in health care.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10055637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H Moses Murdock, Jarrod Ehrie, Nadia L Bennett, Jennifer R Kogan
Objectives: Describe medical student perspectives on framework learning and develop a free, online, mobile-friendly framework website.
Methods: Internal medicine clerkship students were surveyed at a single U.S. medical school regarding how they learn frameworks. We used Draw.io to create frameworks, which were edited by expert clinicians. Frameworks were hosted online through an academic server, and Google analytics was used to track website activity.
Results: Most medical students report learning frameworks from attending clinicians. We developed 87 frameworks on the "Penn Frameworks'' website, which was visited by 9,539 unique users from 124 countries over three years.
Conclusions: Most medical students perceive that they learn frameworks during clinical rotations from attending clinicians. We found that it is feasible to develop a low-cost, expert-curated, mobile-friendly resource to supplement in-person learning.
{"title":"Development of a student-created internal medicine frameworks website for healthcare trainees.","authors":"H Moses Murdock, Jarrod Ehrie, Nadia L Bennett, Jennifer R Kogan","doi":"10.1515/dx-2023-0020","DOIUrl":"https://doi.org/10.1515/dx-2023-0020","url":null,"abstract":"<p><strong>Objectives: </strong>Describe medical student perspectives on framework learning and develop a free, online, mobile-friendly framework website.</p><p><strong>Methods: </strong>Internal medicine clerkship students were surveyed at a single U.S. medical school regarding how they learn frameworks. We used Draw.io to create frameworks, which were edited by expert clinicians. Frameworks were hosted online through an academic server, and Google analytics was used to track website activity.</p><p><strong>Results: </strong>Most medical students report learning frameworks from attending clinicians. We developed 87 frameworks on the \"Penn Frameworks'' website, which was visited by 9,539 unique users from 124 countries over three years.</p><p><strong>Conclusions: </strong>Most medical students perceive that they learn frameworks during clinical rotations from attending clinicians. We found that it is feasible to develop a low-cost, expert-curated, mobile-friendly resource to supplement in-person learning.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10055873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}