Digital Public Health – Hebel für Capacity Building in der kommunalen Gesundheitsförderung

Zens, Maria; Zarneh, Yvette Shajanian; Dolle, Jürgen; Bock, Freia De

doi:10.1007/s00103-020-03148-1

Cited by 8 publications

(2 citation statements)

References 44 publications

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“…Most interventions were health care applications (ie, 100/179, 55.9% for primary, 89/179, 49.7% for secondary, and 55/179, 30.7% for tertiary health care). Out of the 179 interventions, while 16 (8.9%) interventions included a research component [ 57 , 84 , 93 , 104 , 128 , 139 , 154 , 163 , 180 , 220 , 221 , 225 ], only 3 (1.7%) focused exclusively on research: the Lone Star Stroke Consortium Telestroke Registry, the SAI Databank for electronic health research and evaluation, and the German COVID-19 data donation app (ie, Corona Datenspende) [ 57 , 93 , 128 ]. For prevention, of the 179 interventions, 13 (7%) exclusively targeted primary prevention (ie, through vaccination registries, behavior change programs, or health education in healthy individuals) [ 55 , 62 , 96 , 98 , 101 , 106 , 126 , 140 , 143 , 188 , 208 , 223 , 226 ].…”

Section: Resultsmentioning

confidence: 99%

Mapping Digital Public Health Interventions Among Existing Digital Technologies and Internet-Based Interventions to Maintain and Improve Population Health in Practice: Scoping Review

Maaß,

Angoumis,

Freye

et al. 2024

J Med Internet Res

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Background:The rapid progression and integration of digital technologies into public health have reshaped the global landscape of healthcare delivery and disease prevention. In pursuit of better population health and healthcare accessibility, many countries have integrated digital interventions into their healthcare systems, such as online consultations, electronic health records, and telemedicine. Despite the increasing prevalence and relevance of digital technologies in public health and their varying definitions, there has been a shortage of studies examining whether these technologies align with the established definition and core characteristics of digital public health (DiPH) interventions. Hence, the imperative need for a scoping review emerges to explore the breadth of literature dedicated to this subject.Objective: This scoping review aims to outline DiPH interventions from different implementation stages for health promotion, primary to tertiary prevention, including healthcare and disease surveillance and monitoring. Additionally, we aim to map the reported intervention characteristics, including their technical features and non-technical elements.Methods: Original studies or reports of DiPH intervention focused on population health were eligible for this review. PubMed, Web of Science, the Cochrane Central Register of Controlled Trials, IEEE Xplore, and the ACM Full-text collection were searched for relevant literature (last updated October 5, 2022). Intervention characteristics of each identified DiPH intervention, such as target groups, level of prevention or healthcare, digital health functions, intervention types, and public health functions, were extracted and used to map DiPH interventions. MAXQDA 2022.7 was used for qualitative data analysis of such interventions' technical functions and non-technical characteristics. Results:In total, we identified and screened 15,701 records. Of these, 1,562 full-texts were considered relevant and were assessed for eligibility. Finally, we included 185 references, which reported 179 different DiPH interventions. Our analysis revealed a diverse landscape of interventions, with telemedical services, health apps, and electronic health records as dominant types. These interventions target a wide range of populations and settings, demonstrating their adaptability. The analysis highlighted the multifaceted nature of digital interventions, necessitating precise definitions and standardized terminologies for effective collaboration and evaluation.

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Section: Resultsmentioning

confidence: 99%

Mapping Digital Public Health Interventions Among Existing Digital Technologies and Internet-Based Interventions to Maintain and Improve Population Health in Practice: Scoping Review

Maaß,

Angoumis,

Freye

et al. 2024

J Med Internet Res

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“…Previous studies have reported the health management model, including Community health management models in the United States (Chronic Care Model, CCM) framework, Finland (Vartiainen, 2018 ), the United Kingdom, Germany, and Japan. The models described earlier clarify the management targets, subjects, processes, specific practices, and safeguards, but lack digitally driven CDM and do not maximize the benefits of digital technology (Zens et al, 2020 ). Digital technology is a key enabler for integrated models of community-based primary health care, but little is known about how existing technologies can be utilized to support the delivery of integrated care.…”

Section: Introductionmentioning

confidence: 99%

The digitized chronic disease management model: scalable strategies for implementing standardized healthcare and big data analytics in Shanghai

Sui,

Cheng,

Zhang

et al. 2023

Front. Big Data

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BackgroundChronic disease management (CDM) falls under production relations, and digital technology belongs to the realm of productivity. Production relations must adapt to the development of productivity. Simultaneously, the prevalence and burden of chronic diseases are becoming increasingly severe, leveraging digital technology to innovate chronic disease management model is essential.MethodsThe model was built to cover experts in a number of fields, including administrative officials, public health experts, information technology staff, clinical experts, general practitioners, nurses, metrologists. Integration of multiple big data platforms such as General Practitioner Contract Platform, Integrated Community Multimorbidity Management System and Municipal and District-Level Health Information Comprehensive Platform. This study fully analyzes the organizational structure, participants, service objects, facilities and equipment, digital technology, operation process, etc., required for new model in the era of big data.ResultsBased on information technology, we build Integrated Community Multimorbidity Care Model (ICMCM). This model is based on big data, is driven by “technology + mechanism,” and uses digital technology as a tool to achieve the integration of services, technology integration, and data integration, thereby providing patients with comprehensive people-centered services. In order to promote the implementation of the ICMCM, Shanghai has established an integrated chronic disease management information system, clarified the role of each module and institution, and achieved horizontal and vertical integration of data and services. Moreover, we adopt standardized service processes and accurate blood pressure and blood glucose measurement equipment to provide services for patients and upload data in real time. On the basis of Integrated Community Multimorbidity Care Model, a platform and index system have been established, and the platform's multidimensional cross-evaluation and indicators are used for management and visual display.ConclusionsThe Integrated Community Multimorbidity Care Model guides chronic disease management in other countries and regions. We have utilized models to achieve a combination of services and management that provide a grip on chronic disease management.

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Digital Health: Bürgerinnen und Bürger als Subjekte und Objekte ihrer Gesundheit

Strünck

2022

Handbuch Digitalisierung Und Politische Beteiligung

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Digital Public Health – Hebel für Capacity Building in der kommunalen Gesundheitsförderung

Cited by 8 publications

References 44 publications

Mapping Digital Public Health Interventions Among Existing Digital Technologies and Internet-Based Interventions to Maintain and Improve Population Health in Practice: Scoping Review

Mapping Digital Public Health Interventions Among Existing Digital Technologies and Internet-Based Interventions to Maintain and Improve Population Health in Practice: Scoping Review

The digitized chronic disease management model: scalable strategies for implementing standardized healthcare and big data analytics in Shanghai

Digital Health: Bürgerinnen und Bürger als Subjekte und Objekte ihrer Gesundheit

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