Clinical Diagnostic Reasoning Research Articles

Effectiveness of SNAPPS Implementation in the Family Medicine Residency Program in Erbil: A Randomized Controlled Trial.

Background and objectives There is a crucial need to embrace modern methodologies for enhancing medical education in disciplines such as Family Medicine. The study introduces the SNAPPS (Summarize, Narrow, Analyze, Probe, Plan, and Select) model, a six-step mnemonic representing a learner-centered case presentation approach that streamlines fact reporting while encouraging clinical reasoning, aiming to evaluate the effectiveness of the SNAPPS method as compared to the traditional model of case presentation in Family Medicine outpatient clinics and to gain insights into how students and preceptors perceive it. Methods A randomized controlled trial was conducted in Family Medicine outpatient clinics in Erbil, Iraq, from March 15, 2023, to August 30, 2023. Using convenience sampling, all Family Medicine board residents (n=30) in Erbiland six preceptors from the Community and Family Medicine department/College of Medicine/Hawler Medical University were randomly assigned into two groups by using the RAND function in Microsoft Excel (Microsoft Corporation, Redmond, Washington, United States). The SNAPPS method was introduced to the SNAPPS group employing approved tools and methods, while no intervention was needed in the control group. Subsequently, 30 cases were presented in each group with a total of 60 case presentations; the case presentations served as the units for data analysis. Feedback and data were gathered after each presentation using validated data recording sheets. Results The study showed a significant advantage for the SNAPPS group over the control group in terms of time efficiency, number of basic clinical attributes covered, and justified diagnoses (P value < 0.001). In the SNAPPS group,90% of the students sought clarification and information, surpassing 30% in the control group (P-value < 0.001). Almost all SNAPPS group students (96.7%) discussed case-related topics, compared to 43.3% in the controls (P-value<0.001). The SNAPPS group received superior overall ratings from both preceptors and students. Conclusion The SNAPPS method enhances clinical diagnostic reasoning in Family Medicine outpatient clinics. It is time-efficient and encourages students to articulate uncertainties, pose questions, and identify case-related topics for self-study.

DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing

The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by artificial intelligence. A priority in improving provider experience is to overcome information overload and reduce the cognitive burden so fewer medical errors and cognitive biases are introduced during patient care. One major type of medical error is diagnostic error due to systematic or predictable errors in judgement that rely on heuristics. The potential for clinical natural language processing (cNLP) to model diagnostic reasoning in humans with forward reasoning from data to diagnosis and potentially reduce cognitive burden and medical error has not been investigated. Existing tasks to advance the science in cNLP have largely focused on information extraction and named entity recognition through classification tasks. We introduce a novel suite of tasks coined as Diagnostic Reasoning Benchmarks, Dr.Bench, as a new benchmark for developing and evaluating cNLP models with clinical diagnostic reasoning ability. The suite includes six tasks from ten publicly available datasets addressing clinical text understanding, medical knowledge reasoning, and diagnosis generation. DR.BENCH is the first clinical suite of tasks designed to be a natural language generation framework to evaluate pre-trained language models for diagnostic reasoning. The goal of DR. BENCH is to advance the science in cNLP to support downstream applications in computerized diagnostic decision support and improve the efficiency and accuracy of healthcare providers during patient care. We fine-tune and evaluate the state-of-the-art generative models on DR.BENCH. Experiments show that with domain adaptation pre-training on medical knowledge, the model demonstrated opportunities for improvement when evaluated in DR. BENCH. We share DR. BENCH as a publicly available GitLab repository with a systematic approach to load and evaluate models for the cNLP community. We also discuss the carbon footprint produced during the experiments and encourage future work on DR.BENCH to report the carbon footprint.

Clinical pathways and diagnostic reasoning: A qualitative study of pediatric residents' and hospitalists' perceptions.

Clinical pathways are evidence-based guidelines adapted to local settings. They have been shown to improve patient outcomes and reduce resource utilization. However, it is unknown how physicians integrate clinical pathways into their clinical reasoning. We conducted a single-center qualitative study involving one-on-one semi-structured interviews of pediatric residents and pediatric hospitalist attendings between August 2021 and March 2022. Interviews were audio-recorded and professionally transcribed. We utilized a qualitative descriptive framework to code data and identify themes. We interviewed 15 pediatric residents and 12 pediatric hospitalists. Thematic analysis of interview transcripts revealed four themes related to physician utilization of and experience with clinical pathways: (1) utility as a tool, (2) means of standardizing care, (3) reflection of institutional culture, and (4) element of the dynamic relationship with the clinician diagnostic process. These themes were generally common to both residents and attending physicians; however, some differences existed and are noted when they occurred. Clinical pathways are part of many clinicians' diagnostic processes. Pathways can standardize care, influence the diagnostic process, and express local institutional culture. Further research is required to ascertain the optimal clinical pathway design to augment and not inhibit the clinician's diagnostic process.

Necrotizing Enterocolitis in a Term Newborn: A Case Report

This case report describes a 5-day-old term infant with necrotizing enterocolitis (NEC). The clinical presentation, diagnostic reasoning, current literature, hospital course, and follow-up are discussed. Necrotizing enterocolitis is a gastrointestinal emergency characterized by severe inflammation and ischemic necrosis of the intestinal mucosa. Usually a condition of prematurity, NEC primarily occurs in very low birth weight premature infants. Necrotizing enterocolitis can be managed medically or surgically, depending on the severity. Although the etiology of NEC is unknown, the clinical presentation includes abdominal distention and tenderness, feeding intolerance, grossly bloody stools, and severe hypotension and acidosis.

Science, Medicine, and the Anesthesiologist

Science, Medicine, and the Anesthesiologist

Emulating Clinical Diagnostic Reasoning for Jaw Cysts with Machine Learning.

The detection and classification of cystic lesions of the jaw is of high clinical relevance and represents a topic of interest in medical artificial intelligence research. The human clinical diagnostic reasoning process uses contextual information, including the spatial relation of the detected lesion to other anatomical structures, to establish a preliminary classification. Here, we aimed to emulate clinical diagnostic reasoning step by step by using a combined object detection and image segmentation approach on panoramic radiographs (OPGs). We used a multicenter training dataset of 855 OPGs (all positives) and an evaluation set of 384 OPGs (240 negatives). We further compared our models to an international human control group of ten dental professionals from seven countries. The object detection model achieved an average precision of 0.42 (intersection over union (IoU): 0.50, maximal detections: 100) and an average recall of 0.394 (IoU: 0.50–0.95, maximal detections: 100). The classification model achieved a sensitivity of 0.84 for odontogenic cysts and 0.56 for non-odontogenic cysts as well as a specificity of 0.59 for odontogenic cysts and 0.84 for non-odontogenic cysts (IoU: 0.30). The human control group achieved a sensitivity of 0.70 for odontogenic cysts, 0.44 for non-odontogenic cysts, and 0.56 for OPGs without cysts as well as a specificity of 0.62 for odontogenic cysts, 0.95 for non-odontogenic cysts, and 0.76 for OPGs without cysts. Taken together, our results show that a combined object detection and image segmentation approach is feasible in emulating the human clinical diagnostic reasoning process in classifying cystic lesions of the jaw.

Diagnostic Reasoning of Resident Physicians in the Age of Clinical Pathways.

Development of skills in diagnostic reasoning is paramount to the transition from novice to expert clinicians. Efforts to standardize approaches to diagnosis and treatment using clinical pathways are increasingly common. The effects of implementing pathways into systems of care during diagnostic education and practice among pediatric residents are not well described. To characterize pediatric residents' perceptions of the tradeoffs between clinical pathway use and diagnostic reasoning. We conducted a qualitative study from May to December 2019. Senior pediatric residents from a high-volume general pediatric inpatient service at an academic hospital participated in semi-structured interviews. We utilized a basic interpretive qualitative approach informed by a dual process diagnostic reasoning framework. Nine residents recruited via email were interviewed. Residents reported using pathways when admitting patients and during teaching rounds. All residents described using pathways primarily as management tools for patients with a predetermined diagnosis, rather than as aids in formulating a diagnosis. As such, pathways primed residents to circumvent crucial steps of deliberate diagnostic reasoning. However, residents relied on bedside assessment to identify when patients are "not quite fitting the mold" of the current pathway diagnosis, facilitating recalibration of the diagnostic process. This study identifies important educational implications at the intersection of residents' cognitive diagnostic processes and use of clinical pathways. We highlight potential challenges clinical pathways pose for skill development in diagnostic reasoning by pediatric residents. We suggest opportunities for educators to leverage clinical pathways as a framework for development of these skills.

Learning Analytics Applied to Clinical Diagnostic Reasoning Using a Natural Language Processing-Based Virtual Patient Simulator: Case Study.

BackgroundVirtual patient simulators (VPSs) log all users’ actions, thereby enabling the creation of a multidimensional representation of students’ medical knowledge. This representation can be used to create metrics providing teachers with valuable learning information.ObjectiveThe aim of this study is to describe the metrics we developed to analyze the clinical diagnostic reasoning of medical students, provide examples of their application, and preliminarily validate these metrics on a class of undergraduate medical students. The metrics are computed from the data obtained through a novel VPS embedding natural language processing techniques.MethodsA total of 2 clinical case simulations (tests) were created to test our metrics. During each simulation, the students’ step-by-step actions were logged into the program database for offline analysis. The students’ performance was divided into seven dimensions: the identification of relevant information in the given clinical scenario, history taking, physical examination, medical test ordering, diagnostic hypothesis setting, binary analysis fulfillment, and final diagnosis setting. Sensitivity (percentage of relevant information found) and precision (percentage of correct actions performed) metrics were computed for each issue and combined into a harmonic mean (F1), thereby obtaining a single score evaluating the students’ performance. The 7 metrics were further grouped to reflect the students’ capability to collect and to analyze information to obtain an overall performance score. A methodological score was computed based on the discordance between the diagnostic pathway followed by students and the reference one previously defined by the teacher. In total, 25 students attending the fifth year of the School of Medicine at Humanitas University underwent test 1, which simulated a patient with dyspnea. Test 2 dealt with abdominal pain and was attended by 36 students on a different day. For validation, we assessed the Spearman rank correlation between the performance on these scores and the score obtained by each student in the hematology curricular examination.ResultsThe mean overall scores were consistent between test 1 (mean 0.59, SD 0.05) and test 2 (mean 0.54, SD 0.12). For each student, the overall performance was achieved through a different contribution in collecting and analyzing information. Methodological scores highlighted discordances between the reference diagnostic pattern previously set by the teacher and the one pursued by the student. No significant correlation was found between the VPS scores and hematology examination scores.ConclusionsDifferent components of the students’ diagnostic process may be disentangled and quantified by appropriate metrics applied to students’ actions recorded while addressing a virtual case. Such an approach may help teachers provide students with individualized feedback aimed at filling competence drawbacks and methodological inconsistencies. There was no correlation between the hematology curricular examination score and any of the proposed scores as these scores address different aspects of students’ medical knowledge.

Teaching and assessment of clinical diagnostic reasoning in medical students

Background Teaching diagnostic reasoning and giving feedback has an important role in medical education. Clinicians who teach may recognise errors, but be unfamiliar with the terminology used to describe them, leading to a lack of consistent and useful student feedback. Objective This prospective project evaluation study aimed to develop an examiner training package regarding errors in diagnostic reasoning, utilising consistent language and feedback tool, and report on diagnostic reasoning errors in second year medical students over the transition from preclinical to early clinical training at objective structured clinical exams (OSCEs). Results Likert questionnaire regarding examining, assessment and feedback pre- and post-training showed improvement in all measures, including examiner feedback confidence post training (p < .001). Students (n = 235) within the cohort were examined at the first preclinical OSCE 12 weeks into the teaching year and 236 students at the end of year OSCE. A range of 0–6 diagnostic reasoning errors were reported for individual students. When comparing mean history station scores at the preclinical OSCE for students who were observed to have diagnostic reasoning errors, students with ‘poor pattern recognition’ had a 4.2% lower score than those without this error type (p = .04, 95% CI of difference .14, 8.32), while those with ‘unfocused data collection’ error had a station score 7.7% lower than those without this error (p < .001, 95% CI of difference 3.50, 11.99). At the end of teaching year clinical OSCE, all common error types were associated with poorer performance. Error pattern shifted through the two longitudinal assessments, resulting in ‘poor pattern recognition’ having reduced and ‘too narrow’ and ‘premature closure’ increased rates. Conclusions Incorporating the identification and feedback of common diagnostic reasoning errors into existing clinical assessments was feasible and easy to implement. Understanding, identifying and providing consistent feedback on common errors assists educators and could guide curriculum design.

Teaching with a PURPOSE: An NGN approach to clinical instruction and evaluation

A clinical teaching and evaluation tool was created to improve clinical judgment and diagnostic reasoning for Practical Nursing (PN) and Associate Degree in Nursing (ADN) students in preparation for the Next-Generation National Council Licensure Examination (NCLEX). Implementation of the PURPOSE tool offers a structured approach for nursing students to obtain and retain necessary clinical information in a variety of populations and settings. In addition, the PURPOSE tool provides all levels of faculty a consistent method to contribute to clinical evaluation. Integration of the PURPOSE tool at a large community college in the Southeast resulted in a 100% NCLEX pass rate for new stand-alone program PN graduates.

Cognitive load and processes during chest radiograph interpretation in the emergency department across the spectrum of expertise.

In the emergency department (ED), chest radiographs (CXRs) provide essential information for clinical diagnostic reasoning. Errors in interpretation by emergency physicians can lead to negative patient outcomes. To aid in teaching this important skill, an understanding of cognitive processes and cognitive load (CL) in CXR interpretation in emergency medicine (EM) personnel is warranted. This study adopted a concurrent mixed-methods research design. Participant groups included medical students (M), junior (J) and senior (S) EM residents, and attending emergency physicians (P) in the ED at an academic hospital. To elucidate cognitive processes, a real-time cognitive task analysis during CXR interpretation was performed. Interviews were audio recorded, transcribed verbatim, and analyzed thematically. The interview was followed by a questionnaire, where participants rated their CL, stress, and confidence level. Levels of CL (M vs. S and M vs. P, p=0.002; J vs. S, p=0.004; J vs. P, p=0.005) and stress (J vs. P, p=0.002) decreased, while confidence levels increased (M vs. S, p=0.006; J vs. S, p≤0.001; J vs. P, p=0.003) as experience level increased. Qualitative analysis of interviews revealed four themes: checking behavior, information reduction, pattern recognition versus systematic viewing, and recognizing scope of practice. Experts commonly utilized checking behavior (e.g., comparison to prior radiographs) and deprioritized task irrelevant data. Experts used a general overview technique as their initial approach as opposed to a systematic viewing approach, and they more readily recognized an EM physicians' scope of practice in this task. This study characterized differences in cognition that led to increased CL, stress, and lower level of confidence in EM learners during CXR interpretation and provided insight into expertise development in this important skill.

Clinician Gestalt in Managing Pediatric Pneumonia: Can We Predict the Future?

* Abbreviation: CAP — : community acquired pneumonia > It’s tough to make predictions, especially about the future. > > Yogi Berra In this issue of Pediatrics , Gao et al1 examine the value of clinical gestalt in predicting the progression to severe disease in children presenting to an urban pediatric emergency department with suspected community acquired pneumonia (CAP). CAP is one of the most common serious infections of childhood, accounting for ∼2 million annual ambulatory visits and 124 000 annual hospitalizations in the United States alone.2–5 Globally, childhood pneumonia accounts for significant morbidity and mortality, particularly in low- and middle-income countries.6 Complications of CAP include pleural effusions, empyema, sepsis, and others that may require additional procedures, ICU stays, and prolonged antibiotic courses. The management of CAP relies on appropriate diagnosis as well as thoughtful risk stratification to inform decisions, such as antimicrobial choice, patient disposition, and follow-up timing. Clinicians are often required to make these types of diagnoses and initial management decisions on the basis of brief encounters with patients. The impressions made on these visits often rely on a heuristic (ie, shortcut) approach to diagnosis and management. Much of medical decision-making relies on pattern recognition, which can include gestalt, gut feeling, or intuition.7 In this prospective cohort study, pediatric emergency medicine physicians were asked to estimate the probability that patients with suspected pneumonia (based on initial patient encounter and chest radiograph findings) will develop a complicated and/or severe pneumonia.1 The authors found that clinician gestalt was most sensitive (>90%) when the estimate for a complicated pneumonia was low and most specific (>90%) when the probability for complications to develop was judged to be … Address correspondence to Louis M. Bell, MD, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104. E-mail: belll{at}chop.edu

A Natural Language Processing-Based Virtual Patient Simulator and Intelligent Tutoring System for the Clinical Diagnostic Process: Simulator Development and Case Study.

BackgroundShortage of human resources, increasing educational costs, and the need to keep social distances in response to the COVID-19 worldwide outbreak have prompted the necessity of clinical training methods designed for distance learning. Virtual patient simulators (VPSs) may partially meet these needs. Natural language processing (NLP) and intelligent tutoring systems (ITSs) may further enhance the educational impact of these simulators.ObjectiveThe goal of this study was to develop a VPS for clinical diagnostic reasoning that integrates interaction in natural language and an ITS. We also aimed to provide preliminary results of a short-term learning test administered on undergraduate students after use of the simulator.MethodsWe trained a Siamese long short-term memory network for anamnesis and NLP algorithms combined with Systematized Nomenclature of Medicine (SNOMED) ontology for diagnostic hypothesis generation. The ITS was structured on the concepts of knowledge, assessment, and learner models. To assess short-term learning changes, 15 undergraduate medical students underwent two identical tests, composed of multiple-choice questions, before and after performing a simulation by the virtual simulator. The test was made up of 22 questions; 11 of these were core questions that were specifically designed to evaluate clinical knowledge related to the simulated case.ResultsWe developed a VPS called Hepius that allows students to gather clinical information from the patient’s medical history, physical exam, and investigations and allows them to formulate a differential diagnosis by using natural language. Hepius is also an ITS that provides real-time step-by-step feedback to the student and suggests specific topics the student has to review to fill in potential knowledge gaps. Results from the short-term learning test showed an increase in both mean test score (P<.001) and mean score for core questions (P<.001) when comparing presimulation and postsimulation performance.ConclusionsBy combining ITS and NLP technologies, Hepius may provide medical undergraduate students with a learning tool for training them in diagnostic reasoning. This may be particularly useful in a setting where students have restricted access to clinical wards, as is happening during the COVID-19 pandemic in many countries worldwide.

Designing and Implementing a Novel Virtual Rounds Curriculum for Medical Students' Internal Medicine Clerkship During the COVID-19 Pandemic.

IntroductionDuring the COVID-19 pandemic, third-year medical students were temporarily unable to participate in onsite clinical activities. We identified the curricular components of an internal medicine (IM) clerkship that would be compromised if students learned solely from online didactics, case studies, and simulations (i.e., prerounding, oral presentations, diagnostic reasoning, and medical management discussions). Using these guiding principles, we created a virtual rounds (VR) curriculum to provide IM clerkship students with clinical exposure during a virtual learning period.MethodsHeld three times a week for 2 weeks, VR consisted of three curricular components. First, clerkship students prerounded on an assigned hospitalized patient by remotely accessing the electronic health record and calling into hospital rounds. Second, each student prepared an oral presentation on their assigned patient. Third, using videoconferencing, students delivered these oral presentations to telemedicine VR small groups consisting of three to four students and three tele-instructors. Tele-instructors then provided feedback on oral presentations and taught clinical concepts. We assessed the effectiveness of VR by anonymously surveying students and tele-instructors.ResultsTwenty-nine students and 34 volunteer tele-instructors participated in VR over four blocks. A majority of students felt VR improved their prerounding abilities (86%), oral presentation abilities (93%), and clinical reasoning skills (62%). All students found small group to be useful.DiscussionVR allowed students to practice rounding skills in a supportive team-based setting. The lessons learned from its implementation could facilitate education during future pandemics and could also supplement in-person clerkship education.

Assessing Resident Diagnostic Skills Using a Modified Bronchiolitis Score.

Resident milestones are objective instruments that assess the resident's growth, progression in knowledge, and clinical diagnostic reasoning; but they rely on the subjective appraisal of the supervising attending. Little is known about the use of standardized instruments that may complement the evaluation of resident diagnostic skills in the academic setting. Evaluate a modified bronchiolitis severity assessment tool by appraising the inter-rater variability and reliability between pediatric attendings and pediatric residents. Cross-sectional study of children under 24 months of age who presented to a Community Hospital's Emergency Department with bronchiolitis between January-June 2014. A paired pediatric attending and resident evaluated each patient. Evaluation included age-based respiratory rate (RR), retractions, peripheral saturation, and auscultation. Cohen's kappa (K) measured inter-rater agreement. Inter-rater reliability (IRR) was assessed using a one-way random, average measures intra-class correlation (ICC) to evaluate the degree of consistency and magnitude of disagreement between inter-raters. Value of >0.6 was considered substantial for kappa and good internal consistency for ICC. Twenty patients were evaluated. Analysis showed fair agreement for the presence of retractions (K=0.31), auscultation (K=0.33), and total score (K=0.3). The RR (ICC=0.97), SpO2 (ICC=1.0), auscultation (ICC=0.77), and total score (ICC=0.84) were scored similarly across both raters, indicating excellent IRR. Identification of retractions had the least agreement across all statistical analysis. The use of a standardized instrument, in conjunction with a trained resident-teaching staff, can help identify deficiencies in clinical competencies among residents and facilitate the learning process for the identification of pertinent clinical findings.

SAFER PRACTICES in the COVID-19 pandemic

COVID-19 has created a wave of uncertainty for nurses and healthcare practitioners, with new information on the virus being released constantly. Paul Silverston discusses the assessment of patients with symptoms of COVID-19 and how to reduce the risk of misdiagnosis Errors in diagnosis are relatively common in primary care which often result in serious harm to patients. The majority of these errors are preventable. This article describes a diagnostic error checklist, SAFER PRACTICES, which can be used to help clinicians prepare themselves for consulting in patients with suspected or confirmed COVID-19 disease so that they come to the consultation with the correct medical knowledge, clinical assessment plan and diagnostic reasoning required to reduce the risk of diagnostic error. It can also be used during the consultation to deliver a systematic approach to the prevention and detection of diagnostic errors.

Developing Medical Students' Broad Clinical Diagnostic Reasoning Through GP-Facilitated Teaching in Hospital Placements.

PurposeGraduating medical students need broad clinical diagnostic reasoning skills that integrate learning across clinical specialties to deal with undifferentiated patient problems. The opportunity to acquire these skills may be limited during clinical placements on increasingly specialized hospital wards. We developed an intervention of regular general practitioner (GP) facilitated teaching in hospital placements to enable students to develop broad clinical diagnostic reasoning. The intervention was piloted, refined and delivered to a whole cohort of medical students at the start of their third year. This paper examines whether students perceived opportunities to improve their broad diagnostic clinical reasoning through our intervention.MethodsGP-facilitated teaching sessions were delivered weekly in hospital placements to small groups of 6–8 students for 90 mins over 6 weeks. Students practiced clinical reasoning with real patient cases that they encountered on their placements. Evaluation of learning outcomes was conducted through a student questionnaire using Likert scales with free-text boxes for additional explanation. Focus groups were conducted to gain a more in-depth understanding of student perspectives.ResultsAs high as 87% of students agreed that their broad clinical diagnostic reasoning ability had improved. Thematic analysis of the qualitative data revealed four factors supporting this improvement: practicing the hypothetico-deductive method, using real patient cases, composing student groups from different speciality placements and the breadth of the facilitators’ knowledge. Students additionally reported enhanced person-centredness in terms of understanding the patient’s perspective and journey. Students perceived that the added value of general practitioner facilitators lay in their broad knowledge base and knowledge of patient needs in the community.ConclusionOur results suggest that medical students can develop broad clinical diagnostic reasoning skills in hospital settings through regular GP-facilitated teaching. Our approach has the advantage of working within the established curricular format of hospital placements and being deliverable at scale to whole student cohorts.

Clinical judgment and diagnostic reasoning of nursing students in clinical simulation.

to determine the degree of association between clinical judgment and diagnostic reasoning of nursing students in clinical simulation. this is a correlational research design using a quantitative approach. The sample consisted of 41 nursing students who assisted a patient with vaso-occlusive crisis in a high-fidelity clinical simulation setting. The instruments used included the Lasater Clinical Judgment Rubric - Brazilian Version and the Diagnostic Thinking Inventory. clinical judgment was associated with diagnostic reasoning (r=0.313; p=0.046), as well as the "noticing" aspect of clinical judgment with diagnostic reasoning (r=0.312; p=0.047). the results show that skills to interpret patient data are associated with diagnostic reasoning skills. Teaching clinical judgment skills is necessary to develop the diagnostic reasoning of nursing students.

Reorganizing the History of Present Illness to Improve Verbal Case Presenting and Clinical Diagnostic Reasoning Skills of Medical Students: The All-Inclusive History of Present Illness.

The Institute of Medicine states that most diagnostic errors are caused by flaws in clinician diagnostic thinking. Accurately inferring the correct diagnosis from the patient history is the best way to improve diagnostic accuracy and efficiency. Such an improvement is contingent upon training early phase medical learners how to organize data from a patient history to arrive at the most likely diagnosis of the patient’s chief health concern (CC). We describe how organizing the traditional history of present illness into what our trainees have come to call the “All-Inclusive History of Present Illness” (AIHPI) by applying the Bayesian statistical concepts of chronologically sequencing, as suggested by Skeff, both relevant historical risks and known medical events generate a series of pre-event probabilities of the most likely disease causing a patient’s CC. Our trainees have enthusiastically recognized that the AIHPI organization process helps them improve both their ability to deliver well-organized, succinct verbal case presentations and the efficiency of generating and communicating what they think is the most likely disease causing a patient’s CC.

Effectiveness of SNAPPS for improving clinical reasoning in postgraduates: randomized controlled trial

BackgroundIn-patient postgraduate teaching suffers with issues like long and unstructured presentations inclusive of a lot of historical information and time constraints due to increasing workload. A six-step pneumonic SNAPPS a learner-centered model modifies the learning encounter by condensing the reporting of facts while encouraging clinical reasoning. This study was planned with the aim to evaluate the effectiveness of SNAPPS as compared to traditional case presentation for facilitating clinical reasoning in inpatient setting. We also wanted to understand perceptions of postgraduates and teachers about this new method of case presentation.MethodsThis open labeled randomized controlled trial was carried amongst the 18 residents of department of Medicine, MGIMS. The teachers and residents in the SNAPPS were sensitized to SNAPPS technique by using videos, role plays and handouts over 2 sessions of 30 min each. Twenty-seven case presentations (3/resident) were carried out in each group (total 54 case presentations). Data was recorded into validated data recording sheet after each presentation and feedback was taken from the teacher as well as residents regarding their perception.ResultsThe SNAPPS model heralds a change in the preceptor training, pairing faulty development and learner development as companions in education. Guided by the SNAPPS technique, students summarized patient findings concisely (7 vs. 2.7 vs. 5.22vs. 2.33, p = 0.0057) while maintaining the same degree of thoroughness as in traditional case presentations. The students in the SNAPPS group were clearer about their diagnostic hypothesis and compared and contrasted their different diagnosis well (2.56 vs. 1.74, p value =0.002). The students in the SNAPPS group initiated patient management discussion almost 20% more times as compared to the control group.ConclusionWe conclude that SNAPPS a learner centered technique for case presentations facilitated the expression of clinical diagnostic reasoning and case based uncertainties in the inpatient setting without extending the unusual length of the student case presentations. It also paved way for enhanced self-directed learning.