An Electronic Clinical Decision Support System for the Assessment and Management of Suicidality in Primary Care: Protocol for a Mixed-Methods Study

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An Electronic Clinical Decision Support System for the Assessment and Management of Suicidality in Primary Care : Protocol for a Mixed-Methods Study. / Horrocks, Matthew; Michail, Maria; Aubeeluck, Aimee; Wright, Nicola; Morriss, Richard.

In: JMIR Research Protocols, Vol. 7, No. 12, e11135, 07.12.2018.

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@article{e7ea3ad9952044b0937c95c16394e31d,
title = "An Electronic Clinical Decision Support System for the Assessment and Management of Suicidality in Primary Care: Protocol for a Mixed-Methods Study",
abstract = "BACKGROUND: Suicide is a global public health concern, but it is preventable. Increased contact with primary care before the suicide or attempted suicide raises opportunities for intervention and prevention. However, suicide assessment and management are areas that many general practitioners (GPs) find particularly challenging. Previous research has indicated significant variability in how GPs understand, operationalize, and assess suicide risk, which subsequently has an impact on clinical decision making. Clinical decision support systems (CDSS) have been widely implemented across different health care settings, including primary care to support practitioners in clinical decision making. A CDSS may reduce inconsistencies in the identification, assessment, and management of suicide risk by GPs by guiding them through the consultation and generating a risk assessment plan that can be shared with a service user or with specialized mental health services.OBJECTIVE: Our aim is to co-develop and test with end users (eg, GPs, primary care attendees, mental health professionals) an electronic clinical decision support system (e-CDSS) to support GPs in the identification, assessment, and management of suicidality in primary care.METHODS: Ours is an ongoing embedded mixed-methods study with four phases: (1) qualitative interviews with GPs to explore their views on the content, format, and use of the e-CDSS, as well as consultation with two service-user advisory groups (people aged ≤25 and people aged ≥25) to inform the content of the e-CDSS including phrasing of items and clarity; (2) participatory co-production workshops with GPs, service users, and clinical experts in suicidality to determine the content and format of the e-CDDS; gain consensus of the relevance of items; establish content validity and identify pathways to implementation, using the Consolidated Framework for Implementation Research; (3) building the e-CDSS so that it guides the GP through a consultation; and (4) usability testing of the e-CDSS with GPs and service users in one primary care practice involving a nonlive and a live stage.RESULTS: The study was funded for four years, to take place between 2015 and 2019, and is currently completing phase 4 data collection. The first results are expected to be submitted for publication in June 2019. The findings will enable us to evaluate the feasibility, acceptability, and usability of a suicide-specific, electronic, guided decision support system in primary care.CONCLUSIONS: This study will be the first to explore the feasibility, acceptability, and usability of an electronic, guided decision support system for use in primary care consultations for the improved assessment and management of suicidality.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/11135.",
keywords = "clinical decision support system, general practitioner, primary care, suicide",
author = "Matthew Horrocks and Maria Michail and Aimee Aubeeluck and Nicola Wright and Richard Morriss",
note = "{\textcopyright}Matthew Horrocks, Maria Michail, Aimee Aubeeluck, Nicola Wright, Richard Morriss. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 07.12.2018.",
year = "2018",
month = dec
day = "7",
doi = "10.2196/11135",
language = "English",
volume = "7",
journal = "JMIR Research Protocols",
issn = "1929-0748",
publisher = "JMIR Publications",
number = "12",

}

RIS

TY - JOUR

T1 - An Electronic Clinical Decision Support System for the Assessment and Management of Suicidality in Primary Care

T2 - Protocol for a Mixed-Methods Study

AU - Horrocks, Matthew

AU - Michail, Maria

AU - Aubeeluck, Aimee

AU - Wright, Nicola

AU - Morriss, Richard

N1 - ©Matthew Horrocks, Maria Michail, Aimee Aubeeluck, Nicola Wright, Richard Morriss. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 07.12.2018.

PY - 2018/12/7

Y1 - 2018/12/7

N2 - BACKGROUND: Suicide is a global public health concern, but it is preventable. Increased contact with primary care before the suicide or attempted suicide raises opportunities for intervention and prevention. However, suicide assessment and management are areas that many general practitioners (GPs) find particularly challenging. Previous research has indicated significant variability in how GPs understand, operationalize, and assess suicide risk, which subsequently has an impact on clinical decision making. Clinical decision support systems (CDSS) have been widely implemented across different health care settings, including primary care to support practitioners in clinical decision making. A CDSS may reduce inconsistencies in the identification, assessment, and management of suicide risk by GPs by guiding them through the consultation and generating a risk assessment plan that can be shared with a service user or with specialized mental health services.OBJECTIVE: Our aim is to co-develop and test with end users (eg, GPs, primary care attendees, mental health professionals) an electronic clinical decision support system (e-CDSS) to support GPs in the identification, assessment, and management of suicidality in primary care.METHODS: Ours is an ongoing embedded mixed-methods study with four phases: (1) qualitative interviews with GPs to explore their views on the content, format, and use of the e-CDSS, as well as consultation with two service-user advisory groups (people aged ≤25 and people aged ≥25) to inform the content of the e-CDSS including phrasing of items and clarity; (2) participatory co-production workshops with GPs, service users, and clinical experts in suicidality to determine the content and format of the e-CDDS; gain consensus of the relevance of items; establish content validity and identify pathways to implementation, using the Consolidated Framework for Implementation Research; (3) building the e-CDSS so that it guides the GP through a consultation; and (4) usability testing of the e-CDSS with GPs and service users in one primary care practice involving a nonlive and a live stage.RESULTS: The study was funded for four years, to take place between 2015 and 2019, and is currently completing phase 4 data collection. The first results are expected to be submitted for publication in June 2019. The findings will enable us to evaluate the feasibility, acceptability, and usability of a suicide-specific, electronic, guided decision support system in primary care.CONCLUSIONS: This study will be the first to explore the feasibility, acceptability, and usability of an electronic, guided decision support system for use in primary care consultations for the improved assessment and management of suicidality.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/11135.

AB - BACKGROUND: Suicide is a global public health concern, but it is preventable. Increased contact with primary care before the suicide or attempted suicide raises opportunities for intervention and prevention. However, suicide assessment and management are areas that many general practitioners (GPs) find particularly challenging. Previous research has indicated significant variability in how GPs understand, operationalize, and assess suicide risk, which subsequently has an impact on clinical decision making. Clinical decision support systems (CDSS) have been widely implemented across different health care settings, including primary care to support practitioners in clinical decision making. A CDSS may reduce inconsistencies in the identification, assessment, and management of suicide risk by GPs by guiding them through the consultation and generating a risk assessment plan that can be shared with a service user or with specialized mental health services.OBJECTIVE: Our aim is to co-develop and test with end users (eg, GPs, primary care attendees, mental health professionals) an electronic clinical decision support system (e-CDSS) to support GPs in the identification, assessment, and management of suicidality in primary care.METHODS: Ours is an ongoing embedded mixed-methods study with four phases: (1) qualitative interviews with GPs to explore their views on the content, format, and use of the e-CDSS, as well as consultation with two service-user advisory groups (people aged ≤25 and people aged ≥25) to inform the content of the e-CDSS including phrasing of items and clarity; (2) participatory co-production workshops with GPs, service users, and clinical experts in suicidality to determine the content and format of the e-CDDS; gain consensus of the relevance of items; establish content validity and identify pathways to implementation, using the Consolidated Framework for Implementation Research; (3) building the e-CDSS so that it guides the GP through a consultation; and (4) usability testing of the e-CDSS with GPs and service users in one primary care practice involving a nonlive and a live stage.RESULTS: The study was funded for four years, to take place between 2015 and 2019, and is currently completing phase 4 data collection. The first results are expected to be submitted for publication in June 2019. The findings will enable us to evaluate the feasibility, acceptability, and usability of a suicide-specific, electronic, guided decision support system in primary care.CONCLUSIONS: This study will be the first to explore the feasibility, acceptability, and usability of an electronic, guided decision support system for use in primary care consultations for the improved assessment and management of suicidality.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/11135.

KW - clinical decision support system

KW - general practitioner

KW - primary care

KW - suicide

U2 - 10.2196/11135

DO - 10.2196/11135

M3 - Article

C2 - 30530459

VL - 7

JO - JMIR Research Protocols

JF - JMIR Research Protocols

SN - 1929-0748

IS - 12

M1 - e11135

ER -