scholarly journals eHealth platforms as user–data communication: Examining patients’ struggles with digital health data

2021 ◽  
Vol 42 (s4) ◽  
pp. 45-58
Author(s):  
Martina Skrubbeltrang Mahnke ◽  
Mikka Nielsen
Keyword(s):  
Digital Health ◽  
Qualitative Interviews ◽  
Patient Empowerment ◽  
Data Communication ◽  
Health Data ◽  
Domestic Space ◽  
Starting Point ◽  
User Data ◽  
Access To Data ◽  
Communicative Space

Abstract Sundhed.dk is Denmark's national eHealth platform allowing citizens to access their personal health data. Based on 16 qualitative interviews with patients, our aim in this article is to examine how patients engage with their health data. First, we illustrate how patients struggle in different ways to make sense of numerical measurements and written notes. Second, we examine the platform as a communicative space and suggest that a new “medical-domestic” space arises in which medical data is interpreted and negotiated at home. Third, we investigate how health data affects patients’ experiences of being involved as equal partners and how access to data potentially enhances patient empowerment, but also how expectations are sometimes unfulfilled. In conclusion, we argue for a broader public dialogue in order to make sure that the data provided actually creates an optimal starting point and does not foster insecurity or self-doubt on the patient's side.

scholarly journals MAPPING HEALTH: HOW DANES EXPERIENCE THEIR DIGITAL HEALTH DATA

2021 ◽  
Author(s):  
Martina Skrubbeltrang Mahnke ◽  
Mikka Nielsen
Keyword(s):  
Empirical Analysis ◽  
Digital Health ◽  
Health Data ◽  
Medical Data ◽  
Emotional Experiences ◽  
Structural Effects ◽  
Primary Analysis ◽  
Personal Experiences ◽  
User Data ◽  
The Empirical Analysis

This paper explores how Danish citizens experience digital health data and how these in turn affect their understanding of digital health data and their self-understanding as a patient. Previous research on digital health data examines primarily opportunities and challenges as well as structural effects concluding that having access to one's medical data is generally beneficial for patients but also comes with literacy challenges. The aim of this research is to look deeper into personal experiences with digital health data in order to understand what is at stake when people become digitally mapped patients and how experiences of empowerment, independence, perplexity, and doubt intermingle when reading one’s own health data. Taking a user’s view, the paper draws theoretically on the concept of ‘assemblage’ understanding digital health data as a complex nexus of user-data relationships. The empirical analysis draws on 16 in-depth purposefully sampled interviews that have been coded thematically. The primary analysis shows that digital health data creates unique, deeply emotional experiences that lead towards a variety of existential questions. Combining the theoretical lens with the empirical analysis this paper contributes with what we call ‘health assemblages’ that highlight the emerging relationships and personal emotional attachments users make with their digital health data. In conclusion, it can be stated that seeing oneself mapped in data creates unique experiences, often challenging the self-understanding of the patient.

scholarly journals Assessing and piloting interoperability for population health research

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
F Estupiñán-Romero ◽  
J Gonzalez-García ◽  
E Bernal-Delgado
Keyword(s):  
Case Studies ◽  
Population Health ◽  
Health Research ◽  
Network Architecture ◽  
Digital Health ◽  
Data Extraction ◽  
Health Data ◽  
Research Network ◽  
Technical Solution ◽  
Privacy And Security

Abstract Issue/problem Interoperability is paramount when reusing health data from multiple data sources and becomes vital when the scope is cross-national. We aimed at piloting interoperability solutions building on three case studies relevant to population health research. Interoperability lies on four pillars; so: a) Legal frame (i.e., compliance with the GDPR, privacy- and security-by-design, and ethical standards); b) Organizational structure (e.g., availability and access to digital health data and governance of health information systems); c) Semantic developments (e.g., existence of metadata, availability of standards, data quality issues, coherence between data models and research purposes); and, d) Technical environment (e.g., how well documented are data processes, which are the dependencies linked to software components or alignment to standards). Results We have developed a federated research network architecture with 10 hubs each from a different country. This architecture has implied: a) the design of the data model that address the research questions; b) developing, distributing and deploying scripts for data extraction, transformation and analysis; and, c) retrieving the shared results for comparison or pooled meta-analysis. Lessons The development of a federated architecture for population health research is a technical solution that allows full compliance with interoperability pillars. The deployment of this type of solution where data remain in house under the governance and legal requirements of the data owners, and scripts for data extraction and analysis are shared across hubs, requires the implementation of capacity building measures. Key messages Population health research will benefit from the development of federated architectures that provide solutions to interoperability challenges. Case studies conducted within InfAct are providing valuable lessons to advance the design of a future pan-European research infrastructure.

scholarly journals The role of collaborative, multistakeholder partnerships in reshaping the health management of patients with noncommunicable diseases during and after the COVID-19 pandemic

2021 ◽  
Author(s):  
Alessandro Monaco ◽  
Amaia Casteig Blanco ◽  
Mark Cobain ◽  
Elisio Costa ◽  
Nick Guldemond ◽  
...  
Keyword(s):  
Health Management ◽  
Digital Health ◽  
Patient Empowerment ◽  
Advisory Board ◽  
Noncommunicable Diseases ◽  
Informal Carer ◽  
Economic Support ◽  
Health And Social Care ◽  
Care Models ◽  
Multistakeholder Partnerships

Abstract Background Policies to combat the COVID-19 pandemic have disrupted the screening, diagnosis, treatment, and monitoring of noncommunicable (NCD) patients while affecting NCD prevention and risk factor control. Aims To discuss how the first wave of the COVID-19 pandemic affected the health management of NCD patients, identify which aspects should be carried forward into future NCD management, and propose collaborative efforts among public–private institutions to effectively shape NCD care models. Methods The NCD Partnership, a collaboration between Upjohn and the European Innovation Partnership on Active and Healthy Ageing, held a virtual Advisory Board in July 2020 with multiple stakeholders; healthcare professionals (HCPs), policymakers, researchers, patient and informal carer advocacy groups, patient empowerment organizations, and industry experts. Results The Advisory Board identified barriers to NCD care during the COVID-19 pandemic in four areas: lack of NCD management guidelines; disruption to integrated care and shift from hospital-based NCD care to more community and primary level care; infodemics and a lack of reliable health information for patients and HCPs on how to manage NCDs; lack of availability, training, standardization, and regulation of digital health tools. Conclusions Multistakeholder partnerships can promote swift changes to NCD prevention and patient care. Intra- and inter-communication between all stakeholders should be facilitated involving all players in the development of clinical guidelines and digital health tools, health and social care restructuring, and patient support in the short-, medium- and long-term future. A comprehensive response to NCDs should be delivered to improve patient outcomes by providing strategic, scientific, and economic support.

Implementation of the Vinehealth application, a digital health tool, into the care of patients living with brain cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13582-e13582
Author(s):  
Andrew Gvozdanovic ◽  
Riccardo Mangiapelo ◽  
Rayna Patel ◽  
Georgina Kirby ◽  
Neil Kitchen ◽  
...  
Keyword(s):  
Real World ◽  
Brain Cancer ◽  
Care Delivery ◽  
Digital Health ◽  
Patient Empowerment ◽  
Initial Step ◽  
Mixed Methodology ◽  
Structured Interviews ◽  
Strong Basis ◽  
Eortc Qlq

e13582 Background: Cancers of the brain lead to significant neurocognitive, physical and psychological morbidities. Digital technologies provide a novel platform to capture and evaluate these needs. Mobile health (mHealth) applications typically focus on one aspect of care rather than addressing the multimodal needs of the demographic of these patients. The Vinehealth application aims to address this by tracking symptoms, delivering machine learning-based personalised educational content, and facilitating reminders for medications and appointments. Where mHealth interventions traditionally lack the evidence-based approach of pharmaceuticals, this study acts as an initial step in the rigorous assessment of a new digital health tool. Methods: A mixed methodology approach was applied to evaluate the Vinehealth application as a care delivery adjunct. Patients with brain cancer were recruited from the day of their procedure ± 7 days. Over a 12-week period, we collected real-world and ePRO data via the application. We assessed qualitative feedback from mixed-methodology surveys and semi-structured interviews at onboarding and after two weeks of application use. Results: Six participants enrolled of whom four downloaded the application; four completed all interviews. One patient set up their device incorrectly and so couldn't receive the questionnaires; excluding this patient, the EQ-5D-5L and EORTC QLQ-BN20 completion rates were 100% and 83% respectively. Average scores (±SD) at onboarding and offboarding were EQ-5D-5L: 2.07±1.28 and 1.73±1.22, and QLQ-BN20: 13.33 and 22.5. In total: 212 symptoms, 174 activity, and 47 medication data points were captured, and 113 educational articles were read. Participants were generally optimistic about application use. All users stated they would recommend Vinehealth and expressed subjective improvements in care. Accessibility issues in the ePRO delivery system which impacted completion rate were identified and have subsequently been fully addressed. Conclusions: This feasibility study showed acceptable patient use, led to a subjective improvement in care, and demonstrated effective collection of real-world and validated ePRO data. This provides a strong basis to further explore the integration of the Vinehealth application into brain cancer care. This study will inform the design of a larger, more comprehensive trial continuing to evaluate improvements in care delivery through data collection, educational support and patient empowerment.

Selected ‘Starter Kit’ energy system modelling data for Paraguay (#CCG)

2021 ◽  
Author(s):  
Carla Cannone ◽  
Lucy Allington ◽  
Ioannis Pappis ◽  
Karla Cervantes Barron ◽  
Will Usher ◽  
...  
Keyword(s):  
Model Development ◽  
Energy System ◽  
Simple Zero ◽  
System Model ◽  
System Modelling ◽  
Local Data ◽  
Energy System Model ◽  
Starting Point ◽  
Modelling Studies ◽  
Access To Data

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to energy system modelling, causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Paraguay, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.

scholarly journals Selected ‘Starter Kit’ energy system modelling data for Morocco (#CCG)

2021 ◽  
Author(s):  
Carla Cannone ◽  
Lucy Allington ◽  
Ioannis Pappis ◽  
Karla Cervantes Barron ◽  
Will Usher ◽  
...  
Keyword(s):  
Model Development ◽  
Energy System ◽  
Simple Zero ◽  
System Model ◽  
System Modelling ◽  
Local Data ◽  
Energy System Model ◽  
Starting Point ◽  
Modelling Studies ◽  
Access To Data

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Morocco, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.

scholarly journals Selected ‘Starter Kit’ energy system modelling data for Ecuador (#CCG)

2021 ◽  
Author(s):  
Carla Cannone ◽  
Lucy Allington ◽  
Ioannis Pappis ◽  
Karla Cervantes Barron ◽  
Will Usher ◽  
...  
Keyword(s):  
Model Development ◽  
Energy System ◽  
Simple Zero ◽  
System Model ◽  
System Modelling ◽  
Local Data ◽  
Energy System Model ◽  
Starting Point ◽  
Modelling Studies ◽  
Access To Data

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to energy system modelling, causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Ecuador, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.

scholarly journals Selected ‘Starter Kit’ energy system modelling data for Laos (#CCG)

2021 ◽  
Author(s):  
Lucy Allington ◽  
Carla Cannone ◽  
Ioannis Pappis ◽  
Karla Cervantes Barron ◽  
Will Usher ◽  
...  
Keyword(s):  
Model Development ◽  
Energy System ◽  
Simple Zero ◽  
System Model ◽  
System Modelling ◽  
Local Data ◽  
Energy System Model ◽  
Starting Point ◽  
Modelling Studies ◽  
Access To Data

Abstract Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to energy system modelling, causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Laos, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and three stylized scenarios (Fossil Future, Least Cost and Net Zero by 2050) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.

scholarly journals Use of Existing Health Data in Epidemiologic Research–Issues of Informed Consent Under Normal Circumstances and at a Time of Health Crises

2020 ◽  
pp. 1-4
Author(s):  
Carsten Obel ◽  
Carsten Obel ◽  
Jørn Olsen ◽  
Uffe Juul Jensen
Keyword(s):  
Informed Consent ◽  
Personal Data ◽  
Health Data ◽  
Epidemiologic Research ◽  
Health Crisis ◽  
Research Issues ◽  
Data Analyses ◽  
Computer Scientists ◽  
Patient Groups ◽  
Access To Data

In epidemiologic research we study why we get sick and how we get better. To do this we frequently need large datasets on exposure, diagnoses, treatment and more. We need data often classified as sensitive and regulated by law stating a need for informed consent. We argue that modern epidemiologic research often can be done on existing data without having informed consent and without violating basic ethic principles. We also argue for a timely and fair access to data in approved project. Modern encryption technics and methods of data analyses can reduce the risk of disclosure of personal data to a level close to what we have for anonymous data. If we allow open use of administrative health data and existing research data, we will be able to produce much more information to advance disease prevention, health promotion and treatment. Epidemiologists should collaborate more with computer scientists and patient groups in developing/implementing principles for ‘modern methods of data analyses’. Under a severe health crisis data are in high demand to provide the information needed to prevent deaths and diseases and often time does not permit requiring ‘informed consent’. Such a situation in now plying out worldwide under the Covid-19 pandemic.

scholarly journals British Columbia’s Health Data Platform: Unleashing the Power of a Data Environment Commons for Health and Health System Improvement

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Shirley Wong ◽  
Victoria Schuckel ◽  
Simon Thompson ◽  
David Ford ◽  
Ronan Lyons ◽  
...  
Keyword(s):  
Health Sector ◽  
Data Access ◽  
Health Data ◽  
Decision Makers ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Data Accessibility ◽  
Data Platform ◽  
Access To Data ◽  
Data Consumer

IntroductionThere is no power for change greater than a community discovering what it cares about.1 The Health Data Platform (HDP) will democratize British Columbia’s (population of approximately 4.6 million) health sector data by creating common enabling infrastructure that supports cross-organization analytics and research used by both decision makers and cademics. HDP will provide streamlined, proportionate processes that provide timelier access to data with increased transparency for the data consumer and provide shared data related services that elevate best practices by enabling consistency across data contributors, while maintaining continued stewardship of their data. HDP will be built in collaboration with Swansea University following an agile pragmatic approach starting with a minimum viable product. Objectives and ApproachBuild a data sharing environment that harnesses the data and the understanding and expertise about health data across academe, decision makers, and clinicians in the province by: Enabling a common harmonized approach across the sector on: Data stewardship Data access Data security and privacy Data management Data standards To: Enhance data consumer data access experience Increase process consistency and transparency Reduce burden of liberating data from a data source Build trust in the data and what it is telling us and therefore the decisions made Increase data accessibility safely and responsibly Working within the jurisdiction’s existing legislation, the Five Safes Privacy and Security Framework will be implemented, tailored to address the requirements of data contributors. ResultsThe minimum viable product will provide the necessary enabling infrastructure including governance to enable timelier access, safely to administrative data to a limited set of data consumers. The MVP will be expanded with another release planned for early 2021. Conclusion / ImplicationsCollaboration with Swansea University has enabled BC to accelerate its journey to increasing timelier access to data, safely and increasing the maturity of analytics by creating the enabling infrastructure that promotes collaboration and sharing of data and data approaches. 1 Margaret Wheatley

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