| Autor: |
Ben-Assuli O; 61282Ono Academic College, Kiryat Ono, Israel., Vest JR; Richard M. Fairbanks School of Public Health, 1772Indiana University, Indianapolis, IN, USA. |
| Jazyk: |
angličtina |
| Zdroj: |
Health informatics journal [Health Informatics J] 2022 Apr-Jun; Vol. 28 (2), pp. 14604582221105444. |
| DOI: |
10.1177/14604582221105444 |
| Abstrakt: |
Stratification modeling in health services is useful to identify differential patient risk groups, or latent classes. Given the frequency and costs, repeated emergency department (ED) may be an appropriate candidate for risk stratification modeling. We applied a method called group-based trajectory modeling (GBTM) to a sample of 37,416 patients who visited an urban, safety-net ED between 2006 and 2016. Patients had up to 10 ED visits during the study period. Data sources included the hospital's electronic health record (EHR), the state-wide health information exchange system, and area-level social determinants of health factors. Results revealed three distinct trajectory groups. Trajectories with a higher risk of revisit were marked by more patients with behavioral diagnoses, injuries, alcohol & substance abuse, stroke, diabetes, and other factors. The application of advanced computational techniques, like GBTM, provides opportunities for health care organizations to better understand the underlying risks of their large patient populations. Identifying those patients who are likely to be members of high-risk trajectories allows healthcare organizations to stratify patients by level of risk and develop early targeted interventions. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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