The Impact of Technology-Enabled Care Coordination in a Complex Mental Health System: A Local System Dynamics Model.


Journal

Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882

Informations de publication

Date de publication:
30 06 2021
Historique:
received: 28 10 2020
accepted: 15 04 2021
revised: 20 12 2020
pubmed: 3 6 2021
medline: 21 7 2021
entrez: 2 6 2021
Statut: epublish

Résumé

Prior to the COVID-19 pandemic, major shortcomings in the way mental health care systems were organized were impairing the delivery of effective care. The mental health impacts of the pandemic, the recession, and the resulting social dislocation will depend on the extent to which care systems will become overwhelmed and on the strategic investments made across the system to effectively respond. This study aimed to explore the impact of strengthening the mental health system through technology-enabled care coordination on mental health and suicide outcomes. A system dynamics model for the regional population catchment of North Coast New South Wales, Australia, was developed that incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and suicidal behavior. The model reproduced historic time series data across a range of outcomes and was used to evaluate the relative impact of a set of scenarios on attempted suicide (ie, self-harm hospitalizations), suicide deaths, mental health-related emergency department (ED) presentations, and psychological distress over the period from 2021 to 2030. These scenarios include (1) business as usual, (2) increase in service capacity growth rate by 20%, (3) standard telehealth, and (4) technology-enabled care coordination. Each scenario was tested using both pre- and post-COVID-19 social and economic conditions. Technology-enabled care coordination was forecast to deliver a reduction in self-harm hospitalizations and suicide deaths by 6.71% (95% interval 5.63%-7.87%), mental health-related ED presentations by 10.33% (95% interval 8.58%-12.19%), and the prevalence of high psychological distress by 1.76 percentage points (95% interval 1.35-2.32 percentage points). Scenario testing demonstrated that increasing service capacity growth rate by 20% or standard telehealth had substantially lower impacts. This pattern of results was replicated under post-COVID-19 conditions with technology-enabled care coordination being the only tested scenario, which was forecast to reduce the negative impact of the pandemic on mental health and suicide. The use of technology-enabled care coordination is likely to improve mental health and suicide outcomes. The substantially lower effectiveness of targeting individual components of the mental health system (ie, increasing service capacity growth rate by 20% or standard telehealth) reiterates that strengthening the whole system has the greatest impact on patient outcomes. Investments into more of the same types of programs and services alone will not be enough to improve outcomes; instead, new models of care and the digital infrastructure to support them and their integration are needed.

Sections du résumé

BACKGROUND
Prior to the COVID-19 pandemic, major shortcomings in the way mental health care systems were organized were impairing the delivery of effective care. The mental health impacts of the pandemic, the recession, and the resulting social dislocation will depend on the extent to which care systems will become overwhelmed and on the strategic investments made across the system to effectively respond.
OBJECTIVE
This study aimed to explore the impact of strengthening the mental health system through technology-enabled care coordination on mental health and suicide outcomes.
METHODS
A system dynamics model for the regional population catchment of North Coast New South Wales, Australia, was developed that incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and suicidal behavior. The model reproduced historic time series data across a range of outcomes and was used to evaluate the relative impact of a set of scenarios on attempted suicide (ie, self-harm hospitalizations), suicide deaths, mental health-related emergency department (ED) presentations, and psychological distress over the period from 2021 to 2030. These scenarios include (1) business as usual, (2) increase in service capacity growth rate by 20%, (3) standard telehealth, and (4) technology-enabled care coordination. Each scenario was tested using both pre- and post-COVID-19 social and economic conditions.
RESULTS
Technology-enabled care coordination was forecast to deliver a reduction in self-harm hospitalizations and suicide deaths by 6.71% (95% interval 5.63%-7.87%), mental health-related ED presentations by 10.33% (95% interval 8.58%-12.19%), and the prevalence of high psychological distress by 1.76 percentage points (95% interval 1.35-2.32 percentage points). Scenario testing demonstrated that increasing service capacity growth rate by 20% or standard telehealth had substantially lower impacts. This pattern of results was replicated under post-COVID-19 conditions with technology-enabled care coordination being the only tested scenario, which was forecast to reduce the negative impact of the pandemic on mental health and suicide.
CONCLUSIONS
The use of technology-enabled care coordination is likely to improve mental health and suicide outcomes. The substantially lower effectiveness of targeting individual components of the mental health system (ie, increasing service capacity growth rate by 20% or standard telehealth) reiterates that strengthening the whole system has the greatest impact on patient outcomes. Investments into more of the same types of programs and services alone will not be enough to improve outcomes; instead, new models of care and the digital infrastructure to support them and their integration are needed.

Identifiants

pubmed: 34077384
pii: v23i6e25331
doi: 10.2196/25331
pmc: PMC8274674
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e25331

Informations de copyright

©Frank Iorfino, Jo-An Occhipinti, Adam Skinner, Tracey Davenport, Shelley Rowe, Ante Prodan, Julie Sturgess, Ian B Hickie. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.06.2021.

Références

JAMA Psychiatry. 2015 Sep;72(9):892-9
pubmed: 26176785
World Psychiatry. 2019 Feb;18(1):88-96
pubmed: 30600612
Early Interv Psychiatry. 2011 Feb;5 Suppl 1:63-9
pubmed: 21208394
J Med Internet Res. 2017 Jul 12;19(7):e247
pubmed: 28701290
JAMA Psychiatry. 2020 Nov 1;77(11):1093-1094
pubmed: 32275300
World Psychiatry. 2018 Feb;17(1):30-38
pubmed: 29352529
Public Health Res Pract. 2017 Apr 27;27(2):
pubmed: 28474048
Med J Aust. 2019 Oct;211 Suppl 7:S3-S39
pubmed: 31587276
Epidemiol Psychiatr Sci. 2017 Aug;26(4):383-394
pubmed: 27780495
World Psychiatry. 2020 Feb;19(1):38-39
pubmed: 31922686
BMJ Open. 2015 Apr 08;5(4):e007848
pubmed: 25854979
J Rural Health. 2018 Dec;34(1):48-62
pubmed: 28084667
J Affect Disord. 2011 Jun;131(1-3):84-91
pubmed: 21112640
Qual Saf Health Care. 2010 Apr;19(2):113-6
pubmed: 20142404
J Gen Intern Med. 2017 Apr;32(4):398-403
pubmed: 28243871
Am J Psychiatry. 2003 Dec;160(12):2080-90
pubmed: 14638573
Dialogues Clin Neurosci. 2009;11(1):7-20
pubmed: 19432384
BMC Health Serv Res. 2011 Dec 14;11:336
pubmed: 22168915
Pharmacoeconomics. 2016 Apr;34(4):349-61
pubmed: 26660529
J Subst Abuse Treat. 2018 Dec;95:35-42
pubmed: 30352668
Adm Policy Ment Health. 2016 Nov;43(6):861-878
pubmed: 27000148
J Med Internet Res. 2017 Aug 24;19(8):e295
pubmed: 28838887
BMC Psychiatry. 2012 Dec 26;12:234
pubmed: 23268688
JAMA Psychiatry. 2019 Nov 1;76(11):1167-1175
pubmed: 31461129
BMJ Open. 2014 Dec 23;4(12):e006378
pubmed: 25537785
Med J Aust. 2014 Feb 3;200(2):108-11
pubmed: 24484115
Br J Psychiatry. 2014 Nov;205(5):362-8
pubmed: 25213156
Aust J Rural Health. 2020 Apr;28(2):190-194
pubmed: 32281183
BMC Med. 2021 Mar 12;19(1):61
pubmed: 33706764
Psychother Res. 2015;25(1):6-19
pubmed: 23885809
Am J Psychiatry. 2012 Aug;169(8):790-804
pubmed: 22772364
Early Interv Psychiatry. 2021 Aug;15(4):828-836
pubmed: 32748501
JAMA. 2002 Oct 9;288(14):1775-9
pubmed: 12365965
Lancet. 2011 Jun 18;377(9783):2093-102
pubmed: 21652063
Med J Aust. 2019 Nov;211 Suppl 9:S3-S46
pubmed: 31679171
Neuropsychiatr Dis Treat. 2018 Sep 13;14:2337-2349
pubmed: 30254446
Lancet Psychiatry. 2016 Feb;3(2):171-8
pubmed: 26851330
J Med Syst. 2016 Feb;40(2):39
pubmed: 26590977
N Engl J Med. 2020 Aug 6;383(6):510-512
pubmed: 32283003

Auteurs

Frank Iorfino (F)

Brain and Mind Centre, University of Sydney, Sydney, Australia.

Jo-An Occhipinti (JA)

Brain and Mind Centre, University of Sydney, Sydney, Australia.

Adam Skinner (A)

Brain and Mind Centre, University of Sydney, Sydney, Australia.

Tracey Davenport (T)

Brain and Mind Centre, University of Sydney, Sydney, Australia.

Shelley Rowe (S)

Brain and Mind Centre, University of Sydney, Sydney, Australia.

Ante Prodan (A)

Translational Health Research Institute, Western Sydney University, Sydney, Australia.

Julie Sturgess (J)

North Coast Primary Health Network, Coffs Harbour, Australia.

Ian B Hickie (IB)

Brain and Mind Centre, University of Sydney, Sydney, Australia.

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