Enhanced care coordination is essential to improving access to and navigation between youth mental health services. By facilitating better communication and coordination within and between youth mental health services, the goal is to guide young people quickly to the level of care they need and reduce instances of those receiving inappropriate care (too much or too little), or no care at all. Yet, it is often unclear how this goal can be achieved in a scalable way in local regions. We recommend using technology-enabled care coordination to facilitate streamlined transitions for young people across primary, secondary, more specialised or hospital-based care. First, we describe how technology-enabled care coordination could be achieved through two fundamental shifts in current service provisions; a model of care which puts the person at the centre of their care; and a technology infrastructure that facilitates this model. Second, we detail how dynamic simulation modelling can be used to rapidly test the operational features of implementation and the likely impacts of technology-enabled care coordination in a local service environment. Combined with traditional implementation research, dynamic simulation modelling can facilitate the transformation of real-world services. This work demonstrates the benefits of creating a smart health service infrastructure with embedded dynamic simulation modelling to improve operational efficiency and clinical outcomes through participatory and data driven health service planning.
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http://dx.doi.org/10.3389/frhs.2021.745456 | DOI Listing |
Genet Med
January 2025
Division of Human Genetics, Children's Hospital of Philadelphia; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Purpose: Noonan syndrome and related disorders (NS) are multisystemic conditions affecting approximately 1:1000 individuals. Previous natural history studies were conducted prior to widespread comprehensive genetic testing. This study provides updated longitudinal natural history data in participants with molecularly confirmed NS.
View Article and Find Full Text PDFHealth Serv Res
January 2025
School of Nursing, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Objective: To estimate associations between Wisconsin Medicaid's Prenatal Care Coordination (PNCC) program and infant mortality.
Data Sources And Study Setting: We analyzed birth records, Medicaid claims, and infant death records for all resident and in-state Medicaid-paid live deliveries during 2010-2018.
Study Design: We measured PNCC exposure during pregnancy dichotomously (none; any) and categorically (none; assessment/care plan only; service receipt).
BMJ Open
December 2024
Africa University, Mutare, Manicaland, Zimbabwe.
Objective: Implementing evidence-based innovations often fails to translate into meaningful outcomes in practice due to dynamic real-world contextual factors. Identifying these influencing factors is pivotal to implementation success. This study aimed to determine the barriers and facilitators of implementing a community health worker (CHW)-delivered home management of hypertension (HoMHyper) intervention from a stakeholder's perspective using the Consolidated Framework for Implementation Research (CFIR).
View Article and Find Full Text PDFBMJ Open
December 2024
Department of Medicine, The University of Chicago, Chicago, Illinois, USA.
Objective: The COVID-19 pandemic required the rapid and often widespread implementation of medical practices without robust data. Many of these practices have since been tested in large, randomised trials and were found to be in error. We sought to identify incorrect recommendations, or reversals, among National Institute of Health COVID-19 guidelines and Food and Drug Administration (FDA) approvals and authorisations.
View Article and Find Full Text PDFBMJ Open
December 2024
Health Policy Research Center, Guangxi Medical University, Nanning, Guangxi, China
Objective: The purpose of this study is to analyse the changes in the equity of intensive care unit (ICU) bed allocation in 14 cities in China's Guangxi Zhuang Autonomous Region from 2018 to 2021, to identify the problems in the process of ICU bed allocation in China's ethnic minority regions.
Design: The Gini coefficient, Theil index, health resource density index, and spatial correlation analysis were used to analyse the current status of ICU bed resource allocation and allocation equity in Guangxi, China, on two dimensions: geography, and population.
Setting: The Guangxi Zhuang Autonomous Region.
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