Evidence Based Public Health Policy Making: Tool Support

Basdekis, Ioannis; Pozdniakov, Konstantin; Prasinos, Marios; Koloutsou, Konstantina

doi:10.1109/services.2019.00080

Cited by 5 publications

(7 citation statements)

References 12 publications

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“…The EVOTION platform demonstration (item 3) included the user interface of the dashboard, how to perform queries in the EDR, use of analytic tools (including the creation of tasks, workflows and policies) and results visualisation [ 38 ]. The demonstration focused on how the end-user can run analytics in three steps – (1) the creation of a policy specifying which PHPDM model it should be linked to, (2) the creation of a workflow within that policy specifying the statistical techniques to be used and (3) the creation of a data analytics task within the workflow by specifying the types of data from the EDR to be used (Fig.…”

Section: Methodsmentioning

confidence: 99%

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Public health policy-making for hearing loss: stakeholders’ evaluation of a novel eHealth tool

Dritsakis

Trenkova²,

Śliwińska-Kowalska³

et al. 2020

Health Res Policy Sys

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Background Hearing loss (HL) affects 466 million people of all ages worldwide, with a rapidly increasing prevalence, and therefore requires appropriate public health policies. Multi-disciplinary approaches that make use of eHealth services can build the evidence to influence public policy. The European Union-funded project EVOTION developed a platform that is fed with real-time data from hearing aids, a smartphone, and additional clinical data and makes public health policy recommendations based on hypothetical public health policy-making models, a big data engine and decision support system. The present study aimed to evaluate this platform as a new tool to support policy-making for HL. Methods A total of 23 key stakeholders in the United Kingdom, Croatia, Bulgaria and Poland evaluated the platform according to the Strengths, Weaknesses, Opportunities and Threats methodology. Results There was consensus that the platform, with its advanced technology as well as the amount and variety of data that it can collect, has huge potential to inform commissioning decisions, public health regulations and affect healthcare as a whole. To achieve this, several limitations and external risks need to be addressed and mitigated. Differences between countries highlighted that the EVOTION tool should be used and managed according to local constraints to maximise success. Conclusion Overall, the EVOTION platform can equip HL policy-makers with a novel data-driven tool that can support public health policy-making for HL in the future.

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Section: Methodsmentioning

confidence: 99%

“…Bottom: Creation of a data analytics task within the workflow by specifying the types of data from the EVOTION Data Repository to be used. Source: Basdekis et al [ 37 ]. Used with permission …”

Section: Methodsmentioning

confidence: 99%

Public health policy-making for hearing loss: stakeholders’ evaluation of a novel eHealth tool

Dritsakis

Trenkova²,

Śliwińska-Kowalska³

et al. 2020

Health Res Policy Sys

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“…Pseudonymised data: personal health records, devices/sensors big data, questionnaires, interventions, usage data from synergies projects, stored in the Data Repository are subjected to different types of analysis, including statistical analysis techniques and data mining techniques, to obtain the evidence needed in order to offer personalised interventions promoting their healthy and independent living. PIIs removal techniques used were introduced in [10] and properly enhanced to meet SMART BEAR needs. By design, data kept in the SC will no longer be needed to conduct the research (e.g., analytics, interventions), and consequently will be erased and not further used for any data processing.…”

Section: Security Componentmentioning

confidence: 99%

“…Finally, all the components need to be integrated into the SMART BEAR cloud platform. The complexity of the project and the necessity of delivering new releases of the components at high velocity require a DevOps-like integration culture 10 . That is specially important when the pilots are running and the initial requirements are evolving and functionalities need to be improved, testing and released in a very short period of time.…”

Section: Introductionmentioning

confidence: 99%

A Big Data Infrastructure in Support of Healthy and Independent Living: A Real Case Application

Bellandi

2022

Intelligent Systems Reference Library

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This chapter illustrates how the SMART BEAR project aims to integrate heterogeneous smart devices, including wearables and environmental sensors, to enable the continuous data collection from the everyday life of the elderly, which will be processed by an affordable, accountably secure, and privacy-preserving eHealth platform applying Machine Learning algorithms to deliver interventions such as personalized notifications and alerts to each patient, thus promoting their healthy and independent living.

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“…The EVOTION platform, by virtue of its design, sup-ports privacy. For stored data, personally identifiable information (PII) for the subject of the data is masked or removed from it altogether (GDPR compliance presented in [60]).…”

Section: Ethical Issues Using the Platform To Collect Hl Data And Pri...mentioning

confidence: 99%

A Modelling Framework for Evidence-Based Public Health Policy Making

Prasinos

Basdekis

Anisetti

et al. 2022

IEEE J. Biomed. Health Inform.

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Evidence Based Public Health Policy Making: Tool Support

Cited by 5 publications

References 12 publications

Public health policy-making for hearing loss: stakeholders’ evaluation of a novel eHealth tool

Public health policy-making for hearing loss: stakeholders’ evaluation of a novel eHealth tool

A Big Data Infrastructure in Support of Healthy and Independent Living: A Real Case Application

A Modelling Framework for Evidence-Based Public Health Policy Making

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