Literature DB >> 34077384

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

Frank Iorfino1, Jo-An Occhipinti1, Adam Skinner1, Tracey Davenport1, Shelley Rowe1, Ante Prodan2, Julie Sturgess3, Ian B Hickie1.   

Abstract

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. ©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.

Entities:  

Keywords:  care coordination; complex systems; health systems; internet; medical informatics; mental health; policy; simulation

Year:  2021        PMID: 34077384     DOI: 10.2196/25331

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   5.428


  6 in total

1.  Integrated Health and Social Services for People With Chronic Mental Health Problems: People Are More Important Than Processes. Insights From a Multiple Case Study in Swedish Psychiatry.

Authors:  Karin Solberg Carlsson; Mats Brommels
Journal:  Front Public Health       Date:  2022-06-22

2.  Informing the Future of Integrated Digital and Clinical Mental Health Care: Synthesis of the Outcomes From Project Synergy.

Authors:  Haley M LaMonica; Frank Iorfino; Grace Yeeun Lee; Sarah Piper; Jo-An Occhipinti; Tracey A Davenport; Shane Cross; Alyssa Milton; Laura Ospina-Pinillos; Lisa Whittle; Shelley C Rowe; Mitchell Dowling; Elizabeth Stewart; Antonia Ottavio; Samuel Hockey; Vanessa Wan Sze Cheng; Jane Burns; Elizabeth M Scott; Ian B Hickie
Journal:  JMIR Ment Health       Date:  2022-03-09

Review 3.  AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients.

Authors:  Krešimir Ćosić; Siniša Popović; Marko Šarlija; Ivan Kesedžić; Mate Gambiraža; Branimir Dropuljić; Igor Mijić; Neven Henigsberg; Tanja Jovanovic
Journal:  Front Psychol       Date:  2021-12-28

4.  iHealth: The ethics of artificial intelligence and big data in mental healthcare.

Authors:  Giovanni Rubeis
Journal:  Internet Interv       Date:  2022-03-02

5.  An e-Mental Health Resource for COVID-19-Associated Stress Reduction: Mixed Methods Study of Reach, Usability, and User Perceptions.

Authors:  Nadia Minian; Allison Gayapersad; Anika Saiva; Rosa Dragonetti; Sean A Kidd; Gillian Strudwick; Peter Selby
Journal:  JMIR Ment Health       Date:  2022-08-26

Review 6.  The Potential Impact of Adjunct Digital Tools and Technology to Help Distressed and Suicidal Men: An Integrative Review.

Authors:  Luke Balcombe; Diego De Leo
Journal:  Front Psychol       Date:  2022-01-04
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.