Kubey, Alan

Objectives: To evaluate the association of a templated interhospital transfer (IHT) note on transfer appropriateness and clinical outcomes. Methods: We conducted a retrospective, single-center study of 100 IHTs to the Department of Medicine services between May and June 2023. The exposure was the type of documentation at the time of transfer, categorized as templated note, nontemplated note, or no note. The primary outcome was appropriateness of transfer, determined by 2 independent adjudicators using a standardized framework developed as part of the POINT Study. Documentation type by clinical specialty and reason for transfer were assessed, with statistical analyses of clinical outcomes limited to those with an incidence >5% (ie, escalation/downgrade in level of care within 24 h of transfer and 30 d mortality). Results: Among 100 transfers, 81 (81%) were deemed appropriate and 19 (19%) were deemed inappropriate. Documentation was present in 59%, including templated (35%) and nontemplated notes (24%). IHTs without documentation had the highest appropriateness rate (87.8%, 36/41), compared with templated notes (29/35, 82.9%; P =0.15) and nontemplated notes (66.7%, 16/24; P =0.042). Downgrades were more common in inappropriate transfers with nontemplated notes (50.0%, 4/8) than in appropriate transfers with templated notes (10.3%, 3/29; P =0.012). Conclusions: Structured IHT documentation was inconsistently used and did not predict the appropriateness of transfer. Transfers without documentation were most often appropriate, suggesting straightforward cases may not require formal notes. In contrast, nontemplated notes in inappropriate transfers showed high downgrade rates, implying that unstructured documentation may inflate perceived acuity. Further evaluation of documentation strategies is needed to support appropriate transfer decision-making.

AbstractSecure messaging platforms were designed to optimize healthcare communication by providing asynchronous, bidirectional, Health Insurance Portability and Accountability Act‐compliant text messaging options. Proponents argue that these platforms streamline workflows, foster coordination across multidisciplinary teams, and improve patient safety. However, critics highlight their potential to disrupt workflows through overwhelming message volumes and task interruptions, increased risk for miscommunication, and possible detrimental impacts on patient care. While secure messaging shows promise for modernizing hospital communication, it requires institutional guidelines and thoughtful use to mitigate inefficiencies and risks.

Abstract Background Time spent awaiting discharge after the acute need for hospitalization has resolved is an important potential contributor to hospital length of stay (LOS). Objective To measure the prevalence, impact, and context of patients who remain hospitalized for prolonged periods after completion of acute care needs. Design, Setting, and Participants We conducted a cross‐sectional “point‐in‐time” survey at each of 15 academic US hospitals using a structured data collection tool with on‐service acute care medicine attending physicians in fall 2022. Main Outcomes and Measures Primary outcomes were number and percentage of patients considered “medically ready for discharge” with emphasis on those who had experienced a “major barrier to discharge” (medically ready for discharge for ≥1 week). Estimated LOS attributable to major discharge barriers, contributory discharge needs, and associated hospital characteristics were measured. Results Of 1928 patients sampled, 35.0% ( n = 674) were medically ready for discharge including 9.8% ( n = 189) with major discharge barriers. Many patients with major discharge barriers (44.4%; 84/189) had spent a month or longer medically ready for discharge and commonly (84.1%; 159/189) required some form of skilled therapy or daily living support services for discharge. Higher proportions of patients experiencing major discharge barriers were found in public versus private, nonprofit hospitals (12.0% vs. 7.2%; p = .001) and county versus noncounty hospitals (14.5% vs. 8.8%; p = .002). Conclusions Patients experience major discharge barriers in many US hospitals and spend prolonged time awaiting discharge, often for support needs that may be outside of clinician control.

AbstractInternational Statistical Classification of Disease and Related Health Problems, 10th Revision codes (ICD‐10) are used to characterize cohort comorbidities. Recent literature does not demonstrate standardized extraction methods. Objective: Compare COVID‐19 cohort manual‐chart‐review and ICD‐10‐based comorbidity data; characterize the accuracy of different methods of extracting ICD‐10‐code‐based comorbidity, including the temporal accuracy with respect to critical time points such as day of admission. Design: Retrospective cross‐sectional study. Measurements: ICD‐10‐based‐data performance characteristics relative to manual‐chart‐review. Results: Discharge billing diagnoses had a sensitivity of 0.82 (95% confidence interval [CI]: 0.79–0.85; comorbidity range: 0.35–0.96). The past medical history table had a sensitivity of 0.72 (95% CI: 0.69–0.76; range: 0.44–0.87). The active problem list had a sensitivity of 0.67 (95% CI: 0.63–0.71; range: 0.47–0.71). On day of admission, the active problem list had a sensitivity of 0.58 (95% CI: 0.54–0.63; range: 0.30–0.68)and past medical history table had a sensitivity of 0.48 (95% CI: 0.43–0.53; range: 0.30–0.56). Conclusions and Relevance: ICD‐10‐based comorbidity data performance varies depending on comorbidity, data source, and time of retrieval; there are notable opportunities for improvement. Future researchers should clearly outline comorbidity data source and validate against manual‐chart‐review.

AbstractCOVID‐19 has disproportionately affected low‐income communities and people of color. Previous studies demonstrated that race/ethnicity and socioeconomic status (SES) are not independently correlated with COVID‐19 mortality. The purpose of our study is to determine the effect of race/ethnicity and SES on COVID‐19 30‐day mortality in a diverse, Philadelphian population. This is a retrospective cohort study in a single‐center tertiary care hospital in Philadelphia, PA. The study includes adult patients hospitalized with polymerase‐chain‐reaction‐confirmed COVID‐19 between March 1, 2020 and June 6, 2020. The primary outcome was a composite of COVID‐19 death or hospice discharge within 30 days of discharge. The secondary outcome was intensive care unit (ICU) admission. The study included 426 patients: 16.7% died, 3.3% were discharged to hospice, and 20.0% were admitted to the ICU. Using multivariable analysis, race/ethnicity was not associated with the primary nor secondary outcome. In Model 4, age greater than 75 (odds ratio [OR]: 11.01; 95% confidence interval [CI]: 1.96–61.97) and renal disease (OR: 2.78; 95% CI: 1.31–5.90) were associated with higher odds of the composite primary outcome. Living in a “very‐low‐income area” (OR: 0.29; 95% CI: 0.12–0.71) and body mass index (BMI) 30–35 (OR: 0.24; 95% CI: 0.08–0.69) were associated with lower odds of the primary outcome. When controlling for demographics, SES, and comorbidities, race/ethnicity was not independently associated with the composite primary outcome. Very‐low SES, as extrapolated from census‐tract‐level income data, was associated with lower odds of the composite primary outcome.