Objective: To map the physician approach when determining disposition for a patient who presents without the level of definite medical acuity that would generally warrant hospitalisation.
Data Sources/study Setting: Since 2018, our US academic county hospital/trauma centre has maintained a database in which hospitalists ('triage physicians') document the rationale and outcomes of requests for admission to the acute care medical ward during each shift.
Study Design: Narrative text from the database was analysed using a grounded theory approach to identify major themes and subthemes, and a conceptual model of the admission decision-making process was constructed.
Participants: Database entries were included (n=300) if the admission call originated from the emergency department and if the triage physician characterised the request as potentially inappropriate because the patient did not have definite medical acuity.
Results: Admission decision making occurs in three main phases: evaluation of unmet needs, assessment of risk and re-evaluation. Importantly, admission decision making is not solely based on medical acuity or clinical algorithms, and patients without a definite medical need for admission are hospitalised when physicians believe a potential issue exists if discharged. In this way, factors such as homelessness, substance use disorder, frailty, etc, contribute to admission because they raise concern about patient safety and/or barriers to appropriate treatment. Physician decision making can be altered by activities such as care coordination, advocacy by the patient or surrogate, interactions with other physicians or a change in clinical trajectory.
Conclusions: The decision to admit ultimately remains a clinical determination constructed between physician and patient. Physicians use a holistic process that incorporates broad consideration of the patient's medical and social needs with emphasis on risk assessment; thus, any analysis of hospitalisation trends or efforts to impact such should seek to understand this individual-level decision making.
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http://dx.doi.org/10.1136/bmjopen-2020-046598 | DOI Listing |
Background: The purpose of this study was to evaluate the performance and evolution of Chat Generative Pre-Trained Transformer (ChatGPT; OpenAI) as a resource for shoulder and elbow surgery information by assessing its accuracy on the American Academy of Orthopaedic Surgeons shoulder-elbow self-assessment questions. We hypothesized that both ChatGPT models would demonstrate proficiency and that there would be significant improvement with progressive iterations.
Materials And Methods: A total of 200 questions were selected from the 2019 and 2021 American Academy of Orthopaedic Surgeons shoulder-elbow self-assessment questions.
Am J Hosp Palliat Care
January 2025
Department of Pediatrics, University of Chicago, Comer Children's Hospital, Chicago, IL, USA.
Pediatric neuro-oncology patients have one of the highest mortality rates among all children with cancer. Our study examines the potential relationship between palliative care consultation and intensity of in-hospital care and determines if racial and ethnic differences are associated with palliative care consultations during their terminal admission. Retrospective observational study using the Pediatric Health Information System (PHIS) database with data from U.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Cancer Screening, American Cancer Society, Atlanta, GA, United States.
Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.
Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.
Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.
JMIR Res Protoc
January 2025
Division of Services and Interventions Research, National Institute of Mental Health, Bethesda, MD, United States.
Background: Although substantial progress has been made in establishing evidence-based psychosocial clinical interventions and implementation strategies for mental health, translating research into practice-particularly in more accessible, community settings-has been slow.
Objective: This protocol outlines the renewal of the National Institute of Mental Health-funded University of Washington Advanced Laboratories for Accelerating the Reach and Impact of Treatments for Youth and Adults with Mental Illness Center, which draws from human-centered design (HCD) and implementation science to improve clinical interventions and implementation strategies. The Center's second round of funding (2023-2028) focuses on using the Discover, Design and Build, and Test (DDBT) framework to address 3 priority clinical intervention and implementation strategy mechanisms (ie, usability, engagement, and appropriateness), which we identified as challenges to implementation and scalability during the first iteration of the center.
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