Identifying persistent high-cost patients in the hospital for care management: development and validation of prediction models
Ursula W de Ruijter, Z L Rana Kaplan, Frank Eijkenaar, Carolien C H M Maas, Agnes van der Heide, Willem A Bax, Hester F Lingsma · 2024
Read Identifying persistent high-cost patients in the hospital for care management: development and validation of prediction models by Ursula W de Ruijter, Z L Rana Kaplan, Frank Eijkenaar, Carolien C H M Maas, Agnes van der Heide, Willem A Bax, Hester F Lingsma (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11590622.txt.
Description
Ursula de Ruijter and co-authors build models to spot lasting high-cost patients in a 2024 study. A small group of patients drives a large share of hospital spending, and better care coordination might bend that cost. Clinics need a way to flag, early, whose high costs will persist.
Dutch insurer claims fed two models, one at first outpatient visit and one at admission. The target was staying in the top cost tenth for three straight years. Predictors came from the prior year's records, guided by an earlier review. Split-year cohorts tested how the models held up. The aim is a flag care teams can act on.
Catalog record
| CREATOR | Ursula W de Ruijter, Z L Rana Kaplan, Frank Eijkenaar, Carolien C H M Maas, Agnes van der Heide, Willem A Bax, Hester F Lingsma |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 38 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |