TY  - JOUR
PY  - 2022//
TI  - Implementing predictive models within an electronic health record system: lessons from an external validation of a suicide risk model
JO  - Studies in health technology and informatics
A1  - Sequeira, Lydia
A1  - McNair, Douglas
A1  - Wiljer, David
A1  - Strudwick, Gillian
A1  - Deluca, Vincenzo
A1  - Kailasam, Kanakasaba
A1  - Thompson, Michael
A1  - Chou, Brian
A1  - Strauss, John
SP  - 562
EP  - 566
VL  - 290
IS  - 
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 0926-9630
UR  - http://dx.doi.org/10.3233/SHTI220140
ID  - ref1
ER  -