TY  - JOUR
PY  - 2023//
TI  - A case-control study on predicting population risk of suicide using health administrative data: a research protocol
JO  - BMJ open
A1  - Wang, JianLi
A1  - Gholi Zadeh Kharrat, Fatemeh
A1  - Pelletier, Jean-François
A1  - Rochette, Louis
A1  - Pelletier, Éric
A1  - Levesque, Pascale
A1  - Massamba, Victoria
A1  - Brousseau-Paradis, Camille
A1  - Mohammed, Mada
A1  - Gariepy, Geneviève
A1  - Gagné, Christian
A1  - Lesage, Alain
SP  - e066423
EP  - e066423
VL  - 13
IS  - 2
N2  - INTRODUCTION: Suicide has a complex aetiology and is a result of the interaction among the risk and protective factors at the individual, healthcare system and population levels. Therefore, policy and decision makers and mental health service planners can play an important role in suicide prevention. Although a number of suicide risk predictive tools have been developed, these tools were designed to be used by clinicians for assessing individual risk of suicide. There have been no risk predictive models to be used by policy and decision makers for predicting population risk of suicide at the national, provincial and regional levels. This paper aimed to describe the rationale and methodology for developing risk predictive models for population risk of suicide. <br><br>METHODS AND ANALYSIS: A case-control study design will be used to develop sex-specific risk predictive models for population risk of suicide, using statistical regression and machine learning techniques. Routinely collected health administrative data in Quebec, Canada, and community-level social deprivation and marginalisation data will be used. The developed models will be transformed into the models that can be readily used by policy and decision makers. Two rounds of qualitative interviews with end-users and other stakeholders were proposed to understand their views about the developed models and potential systematic, social and ethical issues for implementation; the first round of qualitative interviews has been completed. We included 9440 suicide cases (7234 males and 2206 females) and 661 780 controls for model development. Three hundred and forty-seven variables at individual, healthcare system and community levels have been identified and will be included in least absolute shrinkage and selection operator regression for feature selection. ETHICS AND DISSEMINATION: This study is approved by the Health Research Ethnics Committee of Dalhousie University, Canada. This study takes an integrated knowledge translation approach, involving knowledge users from the beginning of the process.<p />  <p>Language: en</p>
LA  - en
SN  - 2044-6055
UR  - http://dx.doi.org/10.1136/bmjopen-2022-066423
ID  - ref1
ER  -