Predicting high-cost care in a mental health setting

BACKGROUND: The density of information in digital health records offers new potential opportunities for automated prediction of cost-relevant outcomes. AIMS: We investigated the extent to which routinely recorded data held in the electronic health record (EHR) predict priority service outcomes and w...

Descripción completa

Detalles Bibliográficos
Autores principales: Colling, Craig, Khondoker, Mizanur, Patel, Rashmi, Fok, Marcella, Harland, Robert, Broadbent, Matthew, McCrone, Paul, Stewart, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2020
Materias:
Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7001466/
https://www.ncbi.nlm.nih.gov/pubmed/31950891
http://dx.doi.org/10.1192/bjo.2019.96

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7001466/
https://www.ncbi.nlm.nih.gov/pubmed/31950891
http://dx.doi.org/10.1192/bjo.2019.96

Ejemplares similares