Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making

Cleland, Brian; Wallace, Jonathan; Bond, Raymond; Muuraiskangas, Salla; Pajula, Juha; Epelde, Gorka; Arrue, Monica; Álvarez, Roberto; Black, Michaela; Mulvenna, Maurice; Rankin, Debbie; Carlin, Paul

doi:10.1007/978-3-030-22660-2_13

Cited by 12 publications

(11 citation statements)

References 16 publications

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“…A substantial part of technology adoption in public health and healthcare is the utility of the tools and the meaningfulness of their outcomes. As a result of being co-created with stakeholders [8], undergoing regular impact evaluations [10], and having usability formally evaluated by policy-makers [6], the MIDAS platform has proved its usefulness and has led to the development of components driven by stakeholder requests. Significant interest was established in the MIDAS platform in what it can offer to new regions, cities and organizations.…”

Section: Resultsmentioning

confidence: 99%

Meaningful Big Data Integration for a Global COVID-19 Strategy

Costa

Grobelnik

Fuart

et al. 2020

IEEE Comput. Intell. Mag.

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With the rapid spread of the COVID-19 pandemic, the novel Meaningful Integration of Data Analytics and Services (MIDAS) platform quickly demonstrates its value, relevance and transferability to this new global crisis. The MIDAS platform enables the connection of a large number of isolated heterogeneous data sources, and combines rich datasets including open and social data, ingesting and preparing these for the application of analytics, monitoring and research tools. These platforms will assist public health authorities in: (i) better understanding the disease and its impact; (ii) monitoring the different aspects of the evolution of the pandemic across a diverse range of groups; (iii) contributing to improved resilience against the impacts of this global crisis; and (iv) enhancing preparedness for future public health emergencies. The model of governance and ethical review, incorporated and defined within MIDAS, also addresses the complex privacy and ethical issues that the developing pandemic has highlighted, allowing oversight and scrutiny of more and richer data sources by users of the system.

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Section: Resultsmentioning

confidence: 99%

Meaningful Big Data Integration for a Global COVID-19 Strategy

Costa

Grobelnik

Fuart

et al. 2020

IEEE Comput. Intell. Mag.

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“…The user evaluation session involved a variety of users from different backgrounds carrying out tasks associated with the obesity self-management approach developed during the OBINTER project. User evaluation was carefully defined to evaluate both the OBINTER approach and the developed solution’s usability, by departing from a well-tested usability protocol [ 44 ], and defining representative tasks tackling the OBINTER approach’s different dimensions (see Table 2 ) and extending the usability questionnaires with approach-specific questions.…”

Section: Discussionmentioning

confidence: 99%

“…A detailed test protocol was developed, inspired by the protocol detailed in [ 44 ]. The protocol is depicted graphically in Figure 10 .…”

Section: Methodsmentioning

confidence: 99%

OBINTER: A Holistic Approach to Catalyse the Self-Management of Chronic Obesity

Álvarez

Torres

Artola

et al. 2020

Sensors

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Obesity is a preventable chronic condition that, in 2016, affected more than 1.9 billion people globally. Several factors have been identified that have a positive impact on long-term weight loss programs such as personalized recommendations, adherence strategies, weight and diet follow-up or physical activity tracking. Recently, various applications have been developed which help patients to self-manage their condition. These apps implement either one or some of these identified factors; however, there is not a single application that combines all of them following a holistic approach. In this context, we developed the OBINTER platform, which assists patients during the weight loss process by targeting user engagement during the longer term. The solution includes a mobile application which allows users to fill out dietetic questionnaires, receive dietetic and nutraceutical plans, track the evolution of their weight and adherence to the diet, as well as track their physical activity via a wearable device. Furthermore, an adherence strategy has been developed as a tool to foster the app usage during the whole weight loss process. In this paper, we present how the OBINTER approach gathers all of these features as well as the positive results of a usability testing study performed to assess the performance and usability of the OBINTER platform.

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“…We conducted three rounds of user experience testing to help improve the intermediate prototypes, methodology and results of the initial round are reported in ( 27 ). A combination of heuristic and formative user-centered evaluation methods was employed, providing feedback from both usability experts and evaluating prototypes with real users.…”

Section: Methodsmentioning

confidence: 99%

System Architecture of a European Platform for Health Policy Decision Making: MIDAS

Shi

Nikolić

Fischaber

et al. 2022

Front. Public Health

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BackgroundHealthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the monumental challenge policy-makers face in safely accessing all relevant data to assist in managing the health and wellbeing of all. The goal of this study was to develop a novel health data platform within the MIDAS (Meaningful Integration of Data Analytics and Services) project, that harnesses the potential of latent healthcare data in combination with open and social data to support evidence-based health policy decision-making in a privacy-preserving manner.MethodsThe MIDAS platform was developed in an iterative and collaborative way with close involvement of academia, industry, healthcare staff and policy-makers, to solve tasks including data storage, data harmonization, data analytics and visualizations, and open and social data analytics. The platform has been piloted and tested by health departments in four European countries, each focusing on different region-specific health challenges and related data sources.ResultsA novel health data platform solving the needs of Public Health decision-makers was successfully implemented within the four pilot regions connecting heterogeneous healthcare datasets and open datasets and turning large amounts of previously isolated data into actionable information allowing for evidence-based health policy-making and risk stratification through the application and visualization of advanced analytics.ConclusionsThe MIDAS platform delivers a secure, effective and integrated solution to deal with health data, providing support for health policy decision-making, planning of public health activities and the implementation of the Health in All Policies approach. The platform has proven transferable, sustainable and scalable across policies, data and regions.

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Usability Evaluation of a Co-created Big Data Analytics Platform for Health Policy-Making

Cited by 12 publications

References 16 publications

Meaningful Big Data Integration for a Global COVID-19 Strategy

Meaningful Big Data Integration for a Global COVID-19 Strategy

OBINTER: A Holistic Approach to Catalyse the Self-Management of Chronic Obesity

System Architecture of a European Platform for Health Policy Decision Making: MIDAS

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