Implementing Predictive Models Within an Electronic Health Record System: Lessons from an External Validation of a Suicide Risk Model.
Stud Health Technol Inform
; 290: 562-566, 2022 Jun 06.
Article
en En
| MEDLINE
| ID: mdl-35673079
ABSTRACT
Over the past 5 years, there has been an increase in the development of EHR-based models for predicting suicidal behaviour. Using the McGinn (2000) framework for creating clinical prediction rules, this study discusses the broad validation of one such predictive model in a context external to its derivation. Along with reporting performance metrics, our paper high-lights five practical challenges that arise when trying to undertake such a project including (i) validation sample sizes, (ii) availability and timeliness of data, (iii) limited or incomplete documentation for predictor variables, (iv) reliance on structured data and (v) differences in the source context of algorithms. We also discuss our study in the context of the current literature.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Registros Electrónicos de Salud
/
Ideación Suicida
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Stud Health Technol Inform
Asunto de la revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Año:
2022
Tipo del documento:
Article
País de afiliación:
Canadá