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Diagnostic excellence underscores the patient-centered diagnosis and patient engagement in the diagnostic process. In contrast to a patient-centered diagnosis, a doctor-centered diagnosis with a lack of patient engagement may inhibit the diagnostic process due to the lack of responsibility, disrupted information, and increased effect of cognitive biases, particularly in a situation where multiple physicians are involved. In this paper, we suggest a promising idea to enhance patient engagement in the diagnostic process by using written information by a patient about their perspective and experience, which can fill the gaps needed for diagnosis that doctors cannot find alone.A 38-year-old woman developed chest pain, which gradually worsened during the following two years. For two years, she was evaluated in multiple departments; however, no definitive diagnosis was made, and her condition did not improve. During this evaluation, she searched her symptoms and image findings online. She reached a possible diagnosis of ‘esophageal achalasia.’ Still, she could not tell her concerns to any physicians because she felt that her concerns were not correctly recognized, although she showed her notes that her symptoms were recorded. She finally consulted the department of internal medicine, where her notes and previous test results were thoroughly reviewed. The final diagnosis of esophageal achalasia was confirmed.Doctors must organize an environment where patients can freely express their thoughts, emotions, and ideas regarding their diagnosis. Cogenerating visit notes using patient input through written communication can be a promising idea to facilitate patient engagement in the diagnostic process. [ABSTRACT FROM AUTHOR]

AbstractProblem: Misleading health information is detrimental to public health. Even physicians can be misled by biased health information; however, medical students and physicians are not taught some of the most effective techniques for identifying bias and misinformation online. Intervention: Using the stages of Kolb’s experiential learning cycle as a framework, we aimed to teach 117 third-year students at a United States medical school to apply a fact-checking technique for identifying bias and misinformation called “lateral reading” through a 50-minute learning cycle in a 90-minute class. Each student’s concrete experience was to independently read a biased article and rate its credibility, demonstrating their baseline skills at identifying bias. Students were given structured opportunities for reflective observation through individual and large group discussion. Students were guided through abstract conceptualization to determine techniques and frameworks utilized by fact checkers, specifically “lateral reading”—utilizing the internet to research the background of the author, organization, and citations using independent sources before exploring the article itself in depth. Students’ active experimentation included re-rating the credibility of the same article and discussing further implications with classmates and instructors. Context: In January 2020, sessions were offered to third-year medical students during their required, longitudinal transition-to-residency course. Impact: Compared to baseline, when using lateral reading, students deemed the article less credible. Students’ active experimentation changed whether they identified the organization and sources behind the article as credible. Notably, 86% (53/62) of students who viewed the organization positively pre-intervention did not describe the organization positively post intervention. Similarly, 66% (36/55) of students who cited the sources as positive pre-exercise changed their assessment after the exercise. While three students mentioned the author negatively pre-intervention, none of the 21 students who described the author in a negative fashion post-intervention described the author negatively pre-intervention. Positively describing the organization, author, or sources pre-intervention correlated with differences in credibility rating after the intervention. These findings indicate that teaching students to read laterally may increase their ability to detect bias in online medical information. Lessons Learned: Further research is needed to determine whether students who learned lateral reading via experiential learning will apply this skill in their education and career. Additionally, research should assess whether this skill helps future physicians counter bias and misinformation in ways that improve health. [ABSTRACT FROM AUTHOR]

Background: Attending physicians in academic hospitals work in supervisory team structures with medical residents to provide patient care. How attendings utilize the electronic health record (EHR) to support learning through supervision is not well understood., Objective: To compare EHR behavior on teaching versus direct care, including evidence of supervisory calibration to learners., Methods: Cross-sectional study analysis of EHR metadata from 1721 shifts of hospital medicine faculty at a large, urban academic medical center, January to June 2022. Measures included total EHR time per shift, EHR time outside shift, and time spent on: note-writing, note review/attestation, order entry, and other clinical review. We assessed within physician differences across these service types and used multilevel modeling to determine whether these behaviors varied with resident physicians' experience, accounting for physician-specific signature behavior patterns., Results: Attendings spent substantially less time in the EHR while on teaching service than on direct service (129 vs. 240 min; p < .001) and apportioned their work differently throughout the day. Physicians were less behaviorally consistent and varied more than their peers when on teaching service. Attendings calibrated their supervision to learners. Attendings logged 12.7% less EHR time when paired with more senior residents than postgraduate year 2 (PGY2) residents (137 vs. 120 min, p = .002). PGY1 presence was also associated with reduced EHR time, suggesting some delegation of supervision to senior trainees., Conclusion: EHR behaviors on teaching service are highly variable and differ substantially from direct care; a lack of consistency suggests important opportunities to establish best practices for EHR-based supervision and create an effective clinical learning environment., (© 2024 The Author(s). Journal of Hospital Medicine published by Wiley Periodicals LLC on behalf of Society of Hospital Medicine.)

Neurons typically release both a neurotransmitter and one or more neuropeptides, but how these signals are integrated within neural circuits to generate and tune behaviors remains poorly understood. We studied how the two hermaphrodite-specific neurons (HSNs) activate the egg-laying circuit of Caenorhabditis elegans by releasing both the neurotransmitter serotonin and NLP-3 neuropeptides. Egg laying occurs in a temporal pattern with approximately 2-min active phases, during which eggs are laid, separated by approximately 20-min inactive phases, during which no eggs are laid. To understand how serotonin and NLP-3 neuropeptides together help produce this behavior pattern, we identified the G-protein-coupled receptor neuropeptide receptor 36 (NPR-36) as an NLP-3 neuropeptide receptor using genetic and molecular experiments. We found that NPR-36 is expressed in, and promotes egg laying within, the egg-laying muscle cells, the same cells where two serotonin receptors also promote egg laying. During the active phase, when HSN activity is high, we found that serotonin and NLP-3 neuropeptides each have a different effect on the timing of egg laying. During the inactive phase, HSN activity is low, which may result in release of only serotonin, yet mutants lacking either serotonin or nlp-3 signaling have longer inactive phases. This suggests that NLP-3 peptide signaling may persist through the inactive phase to help serotonin signaling terminate the inactive phase. We propose a model for neural circuit function in which multiple signals with short- and long-lasting effects compete to generate and terminate persistent internal states, thus patterning a behavior over tens of minutes., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: To understand gender differences in factors affecting rural health care workforce to inform the development of effective policies and recruitment strategies to address rural health care workforce shortages., Methods: A cross-sectional survey of health care professionals (including Advanced practice registered nurses (APRNs), physicians, physician assistants (PAs), and registered nurses (RNs)) in Minnesota was administered by the Minnesota Department of Health from October 18, 2021, to July 25, 2022, during their professional license renewal. The main outcome was whether or not the respondent was practicing in a rural area. The effects of factors associated with rural practice were estimated using binary logistic regression models, and subsequently subgroup analysis was conducted by gender across the four health care professions., Findings: Results show that although there were significant gender differences in some factors (growing up in a rural area and family considerations were more likely to influence women's decisions than men's, whereas men were more likely to be influenced by the prospect of having autonomy and broad scope of practice than women), these differences became insignificant when the four health care professionals were analyzed separately suggesting that overall gender differences observed were almost entirely explained by profession differences., Conclusions: Gender differences do not significantly influence the factors impacting rural practice. However, being raised in a rural environment emerges as the most influential predictor of rural practice underscoring the importance of involving rural residents of all genders in health care practice., (© 2024 The Author(s). The Journal of Rural Health published by Wiley Periodicals LLC on behalf of National Rural Health Association.)

Importance: Large language model (LLM) artificial intelligence (AI) systems have shown promise in diagnostic reasoning, but their utility in management reasoning with no clear right answers is unknown., Objective: To determine whether LLM assistance improves physician performance on open-ended management reasoning tasks compared to conventional resources., Design: Prospective, randomized controlled trial conducted from 30 November 2023 to 21 April 2024., Setting: Multi-institutional study from Stanford University, Beth Israel Deaconess Medical Center, and the University of Virginia involving physicians from across the United States., Participants: 92 practicing attending physicians and residents with training in internal medicine, family medicine, or emergency medicine., Intervention: Five expert-developed clinical case vignettes were presented with multiple open-ended management questions and scoring rubrics created through a Delphi process. Physicians were randomized to use either GPT-4 via ChatGPT Plus in addition to conventional resources (e.g., UpToDate, Google), or conventional resources alone., Main Outcomes and Measures: The primary outcome was difference in total score between groups on expert-developed scoring rubrics. Secondary outcomes included domain-specific scores and time spent per case., Results: Physicians using the LLM scored higher compared to those using conventional resources (mean difference 6.5 %, 95% CI 2.7-10.2, p<0.001). Significant improvements were seen in management decisions (6.1%, 95% CI 2.5-9.7, p=0.001), diagnostic decisions (12.1%, 95% CI 3.1-21.0, p=0.009), and case-specific (6.2%, 95% CI 2.4-9.9, p=0.002) domains. GPT-4 users spent more time per case (mean difference 119.3 seconds, 95% CI 17.4-221.2, p=0.02). There was no significant difference between GPT-4-augmented physicians and GPT-4 alone (-0.9%, 95% CI -9.0 to 7.2, p=0.8)., Conclusions and Relevance: LLM assistance improved physician management reasoning compared to conventional resources, with particular gains in contextual and patient-specific decision-making. These findings indicate that LLMs can augment management decision-making in complex cases., Trial Registration: ClinicalTrials.gov Identifier: NCT06208423; https://classic.clinicaltrials.gov/ct2/show/NCT06208423.