Formative evaluation of an emergency department clinical decision support system for agitation symptoms: a study protocol

IntroductionThe burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice guidance from experts recommends early assessment of at-risk populations and pre-emptive intervention using de-escalation techniques...

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Veröffentlicht in:BMJ open Jg. 14; H. 2; S. e082834
Hauptverfasser: Wong, Ambrose H, Nath, Bidisha, Shah, Dhruvil, Kumar, Anusha, Brinker, Morgan, Faustino, Isaac V, Boyce, Michael, Dziura, James D, Heckmann, Rebekah, Yonkers, Kimberly A, Bernstein, Steven L, Adapa, Karthik, Taylor, Richard Andrew, Ovchinnikova, Polina, McCall, Terika, Melnick, Edward R
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England British Medical Journal Publishing Group 19.02.2024
BMJ Publishing Group LTD
BMJ Publishing Group
Schriftenreihe:Protocol
Schlagworte:
ACCIDENT & EMERGENCY MEDICINE
Adult
Best practice
Clinical decision making
Clinical Trial
Community
Decision Support Systems, Clinical
Electronic health records
Emergency medical care
Emergency Medicine
Emergency Service, Hospital
Health informatics
Humans
Informatics
Information technology
Informed Consent
Intervention
MENTAL HEALTH
Patients
Peer tutoring
Physical restraints
PSYCHIATRY
Randomized Controlled Trials as Topic
Research Design
Risk assessment
Usability
United States > US
MENTAL HEALTH
Clinical Trial
PSYCHIATRY
Information technology
ACCIDENT & EMERGENCY MEDICINE
Health informatics
ISSN:2044-6055, 2044-6055
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Abstract IntroductionThe burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice guidance from experts recommends early assessment of at-risk populations and pre-emptive intervention using de-escalation techniques to prevent agitation. Time pressure, fluctuating work demands, and other systems-related factors pose challenges to efficient decision-making and adoption of best practice recommendations during an unfolding behavioural crisis. As such, we propose to design, develop and evaluate a computerised clinical decision support (CDS) system, Early Detection and Treatment to Reduce Events with Agitation Tool (ED-TREAT). We aim to identify patients at risk of agitation and guide ED clinicians through appropriate risk assessment and timely interventions to prevent agitation with a goal of minimising restraint use and improving patient experience and outcomes.Methods and analysisThis study describes the formative evaluation of the health record embedded CDS tool. Under aim 1, the study will collect qualitative data to design and develop ED-TREAT using a contextual design approach and an iterative user-centred design process. Participants will include potential CDS users, that is, ED physicians, nurses, technicians, as well as patients with lived experience of restraint use for behavioural crisis management during an ED visit. We will use purposive sampling to ensure the full spectrum of perspectives until we reach thematic saturation. Next, under aim 2, the study will conduct a pilot, randomised controlled trial of ED-TREAT at two adult ED sites in a regional health system in the Northeast USA to evaluate the feasibility, fidelity and bedside acceptability of ED-TREAT. We aim to recruit a total of at least 26 eligible subjects under the pilot trial.Ethics and disseminationEthical approval by the Yale University Human Investigation Committee was obtained in 2021 (HIC# 2000030893 and 2000030906). All participants will provide informed verbal consent prior to being enrolled in the study. Results will be disseminated through publications in open-access, peer-reviewed journals, via scientific presentations or through direct email notifications.Trial registration numberNCT04959279; Pre-results.
AbstractList Introduction The burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice guidance from experts recommends early assessment of at-risk populations and pre-emptive intervention using de-escalation techniques to prevent agitation. Time pressure, fluctuating work demands, and other systems-related factors pose challenges to efficient decision-making and adoption of best practice recommendations during an unfolding behavioural crisis. As such, we propose to design, develop and evaluate a computerised clinical decision support (CDS) system, Early Detection and Treatment to Reduce Events with Agitation Tool (ED-TREAT). We aim to identify patients at risk of agitation and guide ED clinicians through appropriate risk assessment and timely interventions to prevent agitation with a goal of minimising restraint use and improving patient experience and outcomes.Methods and analysis This study describes the formative evaluation of the health record embedded CDS tool. Under aim 1, the study will collect qualitative data to design and develop ED-TREAT using a contextual design approach and an iterative user-centred design process. Participants will include potential CDS users, that is, ED physicians, nurses, technicians, as well as patients with lived experience of restraint use for behavioural crisis management during an ED visit. We will use purposive sampling to ensure the full spectrum of perspectives until we reach thematic saturation. Next, under aim 2, the study will conduct a pilot, randomised controlled trial of ED-TREAT at two adult ED sites in a regional health system in the Northeast USA to evaluate the feasibility, fidelity and bedside acceptability of ED-TREAT. We aim to recruit a total of at least 26 eligible subjects under the pilot trial.Ethics and dissemination Ethical approval by the Yale University Human Investigation Committee was obtained in 2021 (HIC# 2000030893 and 2000030906). All participants will provide informed verbal consent prior to being enrolled in the study. Results will be disseminated through publications in open-access, peer-reviewed journals, via scientific presentations or through direct email notifications.Trial registration number NCT04959279; Pre-results.
IntroductionThe burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice guidance from experts recommends early assessment of at-risk populations and pre-emptive intervention using de-escalation techniques to prevent agitation. Time pressure, fluctuating work demands, and other systems-related factors pose challenges to efficient decision-making and adoption of best practice recommendations during an unfolding behavioural crisis. As such, we propose to design, develop and evaluate a computerised clinical decision support (CDS) system, Early Detection and Treatment to Reduce Events with Agitation Tool (ED-TREAT). We aim to identify patients at risk of agitation and guide ED clinicians through appropriate risk assessment and timely interventions to prevent agitation with a goal of minimising restraint use and improving patient experience and outcomes.Methods and analysisThis study describes the formative evaluation of the health record embedded CDS tool. Under aim 1, the study will collect qualitative data to design and develop ED-TREAT using a contextual design approach and an iterative user-centred design process. Participants will include potential CDS users, that is, ED physicians, nurses, technicians, as well as patients with lived experience of restraint use for behavioural crisis management during an ED visit. We will use purposive sampling to ensure the full spectrum of perspectives until we reach thematic saturation. Next, under aim 2, the study will conduct a pilot, randomised controlled trial of ED-TREAT at two adult ED sites in a regional health system in the Northeast USA to evaluate the feasibility, fidelity and bedside acceptability of ED-TREAT. We aim to recruit a total of at least 26 eligible subjects under the pilot trial.Ethics and disseminationEthical approval by the Yale University Human Investigation Committee was obtained in 2021 (HIC# 2000030893 and 2000030906). All participants will provide informed verbal consent prior to being enrolled in the study. Results will be disseminated through publications in open-access, peer-reviewed journals, via scientific presentations or through direct email notifications.Trial registration numberNCT04959279; Pre-results.
The burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice guidance from experts recommends early assessment of at-risk populations and pre-emptive intervention using de-escalation techniques to prevent agitation. Time pressure, fluctuating work demands, and other systems-related factors pose challenges to efficient decision-making and adoption of best practice recommendations during an unfolding behavioural crisis. As such, we propose to design, develop and evaluate a computerised clinical decision support (CDS) system, Early Detection and Treatment to Reduce Events with Agitation Tool (ED-TREAT). We aim to identify patients at risk of agitation and guide ED clinicians through appropriate risk assessment and timely interventions to prevent agitation with a goal of minimising restraint use and improving patient experience and outcomes. This study describes the formative evaluation of the health record embedded CDS tool. Under aim 1, the study will collect qualitative data to design and develop ED-TREAT using a contextual design approach and an iterative user-centred design process. Participants will include potential CDS users, that is, ED physicians, nurses, technicians, as well as patients with lived experience of restraint use for behavioural crisis management during an ED visit. We will use purposive sampling to ensure the full spectrum of perspectives until we reach thematic saturation. Next, under aim 2, the study will conduct a pilot, randomised controlled trial of ED-TREAT at two adult ED sites in a regional health system in the Northeast USA to evaluate the feasibility, fidelity and bedside acceptability of ED-TREAT. We aim to recruit a total of at least 26 eligible subjects under the pilot trial. Ethical approval by the Yale University Human Investigation Committee was obtained in 2021 (HIC# 2000030893 and 2000030906). All participants will provide informed verbal consent prior to being enrolled in the study. Results will be disseminated through publications in open-access, peer-reviewed journals, via scientific presentations or through direct email notifications. NCT04959279; Pre-results.
The burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice guidance from experts recommends early assessment of at-risk populations and pre-emptive intervention using de-escalation techniques to prevent agitation. Time pressure, fluctuating work demands, and other systems-related factors pose challenges to efficient decision-making and adoption of best practice recommendations during an unfolding behavioural crisis. As such, we propose to design, develop and evaluate a computerised clinical decision support (CDS) system, Early Detection and Treatment to Reduce Events with Agitation Tool (ED-TREAT). We aim to identify patients at risk of agitation and guide ED clinicians through appropriate risk assessment and timely interventions to prevent agitation with a goal of minimising restraint use and improving patient experience and outcomes.INTRODUCTIONThe burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice guidance from experts recommends early assessment of at-risk populations and pre-emptive intervention using de-escalation techniques to prevent agitation. Time pressure, fluctuating work demands, and other systems-related factors pose challenges to efficient decision-making and adoption of best practice recommendations during an unfolding behavioural crisis. As such, we propose to design, develop and evaluate a computerised clinical decision support (CDS) system, Early Detection and Treatment to Reduce Events with Agitation Tool (ED-TREAT). We aim to identify patients at risk of agitation and guide ED clinicians through appropriate risk assessment and timely interventions to prevent agitation with a goal of minimising restraint use and improving patient experience and outcomes.This study describes the formative evaluation of the health record embedded CDS tool. Under aim 1, the study will collect qualitative data to design and develop ED-TREAT using a contextual design approach and an iterative user-centred design process. Participants will include potential CDS users, that is, ED physicians, nurses, technicians, as well as patients with lived experience of restraint use for behavioural crisis management during an ED visit. We will use purposive sampling to ensure the full spectrum of perspectives until we reach thematic saturation. Next, under aim 2, the study will conduct a pilot, randomised controlled trial of ED-TREAT at two adult ED sites in a regional health system in the Northeast USA to evaluate the feasibility, fidelity and bedside acceptability of ED-TREAT. We aim to recruit a total of at least 26 eligible subjects under the pilot trial.METHODS AND ANALYSISThis study describes the formative evaluation of the health record embedded CDS tool. Under aim 1, the study will collect qualitative data to design and develop ED-TREAT using a contextual design approach and an iterative user-centred design process. Participants will include potential CDS users, that is, ED physicians, nurses, technicians, as well as patients with lived experience of restraint use for behavioural crisis management during an ED visit. We will use purposive sampling to ensure the full spectrum of perspectives until we reach thematic saturation. Next, under aim 2, the study will conduct a pilot, randomised controlled trial of ED-TREAT at two adult ED sites in a regional health system in the Northeast USA to evaluate the feasibility, fidelity and bedside acceptability of ED-TREAT. We aim to recruit a total of at least 26 eligible subjects under the pilot trial.Ethical approval by the Yale University Human Investigation Committee was obtained in 2021 (HIC# 2000030893 and 2000030906). All participants will provide informed verbal consent prior to being enrolled in the study. Results will be disseminated through publications in open-access, peer-reviewed journals, via scientific presentations or through direct email notifications.ETHICS AND DISSEMINATIONEthical approval by the Yale University Human Investigation Committee was obtained in 2021 (HIC# 2000030893 and 2000030906). All participants will provide informed verbal consent prior to being enrolled in the study. Results will be disseminated through publications in open-access, peer-reviewed journals, via scientific presentations or through direct email notifications.NCT04959279; Pre-results.TRIAL REGISTRATION NUMBERNCT04959279; Pre-results.
Author Kumar, Anusha
Adapa, Karthik
Faustino, Isaac V
Shah, Dhruvil
Melnick, Edward R
Heckmann, Rebekah
Ovchinnikova, Polina
Nath, Bidisha
Wong, Ambrose H
Brinker, Morgan
Yonkers, Kimberly A
Dziura, James D
Taylor, Richard Andrew
Boyce, Michael
McCall, Terika
Bernstein, Steven L
AuthorAffiliation 6 Carolina Health Informatics Program , University of North Carolina System , Chapel Hill , North Carolina , USA
4 Department of Psychiatry , University of Massachusetts System , Worchester , Massachusetts , USA
5 Department of Emergency Medicine , Geisel School of Medicine at Dartmouth , Lebanon , New Hampshire , USA
2 Department of Emergency Medicine , Yale School of Medicine , New Haven , Connecticut , USA
7 Section of Biomedical Informatics and Data Science , Yale School of Medicine , New Haven , Connecticut , USA
3 Department of Biostatistics , Yale School of Public Health , New Haven , Connecticut , USA
1 Yale New Haven Health System , New Haven , Connecticut , USA
AuthorAffiliation_xml – name: 3 Department of Biostatistics , Yale School of Public Health , New Haven , Connecticut , USA
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– name: 5 Department of Emergency Medicine , Geisel School of Medicine at Dartmouth , Lebanon , New Hampshire , USA
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/38373857$$D View this record in MEDLINE/PubMed
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CitedBy_id crossref_primary_10_3390_diagnostics15172276
crossref_primary_10_3390_ijerph22040479
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Issue 2
Keywords MENTAL HEALTH
Clinical Trial
PSYCHIATRY
Information technology
ACCIDENT & EMERGENCY MEDICINE
Health informatics
Language English
License This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
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Snippet IntroductionThe burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best...
The burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice...
Introduction The burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best...
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StartPage e082834
SubjectTerms ACCIDENT & EMERGENCY MEDICINE
Adult
Best practice
Clinical decision making
Clinical Trial
Community
Decision Support Systems, Clinical
Electronic health records
Emergency medical care
Emergency Medicine
Emergency Service, Hospital
Health informatics
Humans
Informatics
Information technology
Informed Consent
Intervention
MENTAL HEALTH
Patients
Peer tutoring
Physical restraints
PSYCHIATRY
Randomized Controlled Trials as Topic
Research Design
Risk assessment
Usability
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Title Formative evaluation of an emergency department clinical decision support system for agitation symptoms: a study protocol
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