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Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study

Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study

As a study to confirm the EHR data from the time of admission to the time of discharge of the patient, the information collected until January 31, 2021, was used to track readmission within 30 days. Data were requested from S University Hospital via the SOBIG data portal using subject inclusion criteria.

Eui Geum Oh, Sunyoung Oh, Seunghyeon Cho, Mir Moon

JMIR Med Inform 2025;13:e56671

Hospital Length of Stay Prediction for Planned Admissions Using Observational Medical Outcomes Partnership Common Data Model: Retrospective Study

Hospital Length of Stay Prediction for Planned Admissions Using Observational Medical Outcomes Partnership Common Data Model: Retrospective Study

Out of a total of 961,672 admission episodes, 137,437 (14.3%) indexed hospitalizations with Lo S ranging from 2 to 30 days between January 2016 and December 2020 were included in the study. The prediction timing was set within 30 days, aligning with standard practices in most studies [25].

Haeun Lee, Seok Kim, Hui-Woun Moon, Ho-Young Lee, Kwangsoo Kim, Se Young Jung, Sooyoung Yoo

J Med Internet Res 2024;26:e59260

Older Adults, the “Social Admission,” and Nonspecific Complaints in the Emergency Department: Protocol for a Scoping Review

Older Adults, the “Social Admission,” and Nonspecific Complaints in the Emergency Department: Protocol for a Scoping Review

If older adults present with poorly controlled or multiple geriatric syndromes, then a “social admission” may occur if no specific diagnosis can be identified [21]. Not infrequently, these patients cannot return to their prior place of residence without additional support, which may require extensive discharge liaison and planning.

Kayla Rose Furlong, Kathleen O'Donnell, Alison Farrell, Susan Mercer, Paul Norman, Michael Parsons, Christopher Patey

JMIR Res Protoc 2023;12:e38246