Journal of hospital medicine最新文献

Logic models are an accessible tool to organize the planning, management, and evaluation of programs across healthcare disciplines. This methodological progress note describes the five standard components of a logic model (Inputs, Activities, Outputs, Outcomes, and Impact) and provides guidance for developing a logic model. Logic models offer a visual representation of the work and theory of a program and should be created with input from all interested parties. Logic models are living tools that need to be revised as programs evolve and new information becomes available.

Background: Hospital discharge summaries are critical for ensuring continuity of care, but their quality often varies. Large language models (LLMs) have the potential to standardize and enhance the efficiency of this documentation process.

Objectives: To evaluate the quality of hospital discharge summaries created by an LLM-based hospital course drafting tool created by Epic Systems compared with human-written summaries.

Methods: Retrospective study at a single tertiary-care institution in 2024. The cohort included 100 adult hospitalizations lasting >72 hours across medical and surgical dismissing services. No interventions were performed. Summaries (LLM-generated vs human-written) were independently reviewed using a standardized rubric covering nine domains (e.g., comprehensiveness, clarity, relevance). Scores were normalized and compared. Readability was assessed using Flesch Reading Ease.

Results: LLM-generated summaries outperformed human-written summaries across all criteria (p < .05), with the greatest difference observed in comprehensiveness (LLM median 0.62 vs. human -0.23). Human-written summaries from surgical services scored lower than those from medical services, but LLM performance was consistent across both. Human summaries had higher Flesch Reading Ease scores (33.11 vs. 26.2; p < .05), reflecting simpler language.

Conclusions: LLM-generated summaries demonstrated superior quality, consistency, and clinical utility compared with human-written summaries, highlighting their potential to improve documentation efficiency and standardization.

Hospitalizations can offer key opportunities to provide focused pediatric-to-adult healthcare transition planning for adolescents and young adults with childhood-onset chronic conditions. Here, we describe the components of our standardized, comprehensive inpatient transition consultation. We review pilot data and discuss formal implementation of the consultation in an academic hospital setting.

Despite a decline in hepatitis A virus (HAV) incidence following vaccine introduction, HAV remains a public health concern in the United States. Recent multi-state outbreaks have demonstrated that HAV can re-emerge and highlight inequities in vaccine coverage or access, outbreak response, and in those with social or health risk factors. Continued investment in prevention, particularly vaccination and surveillance, is essential to prevent resurgence. Hospitalization offers a critical opportunity to address these gaps and provide equitable protection for at-risk populations.

Background: Against medical advice (AMA) discharges are associated with adverse clinical outcomes and can be stigmatizing to patients. Most prior work has described patient characteristics associated with AMA discharges, with little attention to interpersonal clinician-patient dynamics that culminate in a discharge being designated AMA.

Objective: To describe clinical documentation about patients whose hospitalizations ended in an AMA discharge, attending to both what was written and how it was written.

Methods: We performed a qualitative description using inductive thematic analysis of 185 free-text notes from hospitalizations administratively identified as ending with an AMA discharge from Internal Medicine services at an urban academic medical center in the mid-Atlantic region in 2017.

Results: Common features of notes regarding patients leaving AMA included documentation of: (1) the clinician becoming aware of the patient leaving before planned discharge, (2) the patient's reasons for leaving, (3) the clinical team's response to a patient's decision to leave, (4) the patient's capacity, and (5) insinuation of the patient's character flaws. While some note writers conveyed neutrality, we found extensive evidence of adversarial relationships with patients with unnecessary details and language that could stigmatize patients and bias future readers.

Conclusions: Many notes documenting AMA discharges contain stigmatizing language, with writers frequently taking a defensive or paternalistic stance toward their interactions with patients. Our findings reflect a lack of clarity about what should be documented in the medical record regarding the events surrounding this type of contentious discharge.