An overview of electronic personal health records

© 2018 Fellowship of Postgraduate Medicine Electronic Personal Health Record systems are providing health consumers with greater access and control to their health records by shifting these records from being a health provider-centred Electronic Health Record, to a patient-centred, Electronic Personal Health Record (ePHR). Based on the delivery system, ePHR systems are classified into standalone, tethered, and integrated or unified ePHRs. While national approaches of implementing integrated ePHR vary, the middle out method has been recognised as the ideal approach. It is worth considering the adoption of ePHRs has been slow due to several factors, including technical, individual, environmental, social, and legal factors. This paper provides a representative overview of an ePHR system, outlining its definition, types, architectures, and nationwide approaches of its implementation. Additionally, the drivers and hindrances to health consumer adoption are discussed

Patient Consent for Health Information Exchange: Blockchain-driven Innovation

Health information exchange (HIE) is vital to improving care delivery and outcomes, and patient consent is an important component of HIE. Existing consent processes that involve completing forms at a provider, along with poor interoperability between HIEs, give patients limited control of their consent management. We developed and deployed a survey to assess how people perceive the value of HIE, the importance of controlling access to their protected health information (PHI), and how they would prefer to manage consent for the exchange of their PHI. Given the option, 70% of the participants would prefer to use a consent application (app) to manage their consent. Based on the current U.S. HIE environment, we argue that the most viable architecture for implementing an HIE consent app would be a permissioned blockchain. We describe and illustrate a consent management app prototype that is blockchain-based as an effective alternative to current HIE consent practices

An experiment on data sharing options designs for eHealth interventions

Background: With eHealth technology interventions, users' personal health data can be easily shared among different stakeholders. Users should decide with whom they want to share their data. As support, most eHealth technology has data sharing options functionalities. However, there is little research on how to design these visually. In this paper, we took two possible data sharing options designs - data and party perspective – for an existing eHealth technology intervention, and we explored them. Objective: The aim was to find which of the two designs is the best in terms of trust, privacy concerns, ease of use, and information control. Additionally, to investigate how these factors influence each other with also the goal of giving practical advice on designing for privacy. Method: We conducted a between-subjects online design experiment (N = 123). After having visualised one of the two data sharing options designs, participants filled in an online questionnaire. To analyse the data, t-test analyses, correlation analyses, and backward regression analyses were conducted. Results: Information control scored higher in the data perspective condition (t (97) = 2.25, p = .03). From the different regression analyses, we found that trust and ease of use play a role in all sharing-related factors. Conclusions: We concluded that the design of data-sharing options in eHealth technology affects the experience of the user, mostly for trust and ease of use. In the end, we provided several actionable design advices on how to design for privacy.</p

Gathering data for decisions: best practice use of primary care electronic records for research

In Australia, there is limited use of primary health care data for research and for data linkage between health care settings. This puts Australia behind many developed countries. In addition, without use of primary health care data for research, knowledge about patients' journeys through the health care system is limited. There is growing momentum to establish "big data" repositories of primary care clinical data to enable data linkage, primary care and population health research, and quality assurance activities. However, little research has been conducted on the general public's and practitioners' concerns about secondary use of electronic health records in Australia. International studies have identified barriers to use of general practice patient records for research. These include legal, technical, ethical, social and resource-related issues. Examples include concerns about privacy protection, data security, data custodians and the motives for collecting data, as well as a lack of incentives for general practitioners to share data. Addressing barriers may help define good practices for appropriate use of health data for research. Any model for general practice data sharing for research should be underpinned by transparency and a strong legal, ethical, governance and data security framework. Mechanisms to collect electronic medical records in ethical, secure and privacy-controlled ways are available. Before the potential benefits of health-related data research can be realised, Australians should be well informed of the risks and benefits so that the necessary social licence can be generated to support such endeavours.Rachel Canaway, Douglas IR Boyle, Jo‐Anne E Manski‐Nankervis, Jessica Bell, Jane S Hocking, Ken Clarke, Malcolm Clark, Jane M Gunn, Jon D Emer

Stakeholder’s Perceptions of Value and Risks in Data Governance for the Secondary Use of Health Data

The study is a literature study assessing the value expectations and risks perceived by the different stakeholders related to the governance of secondary use of health data. A key value expectation for all stakeholders was found to be that data provides public benefits and “common good”, especially through academic research. Especially for the researchers improvement of health equity in the society was also an important value expectation. For patients and also for decisionmakers security and privacy related risks were often mentioned. For all stakeholders the risk of stigma for different groups in the society and for the patient herself was seen to be important. Constant and clear communication towards all stakeholders about what data is collected, how it is used, what the expected benefits are and how the risks are managed needs to be a key element of health data governance solutions. All stakeholders see the importance of involving also the patient representatives to the governance of health data. Data governance should be developed towards a continuous and transparent collaborative process, where all stakeholders voice is heard, and they can affect the decisions.publishedVersionPeer reviewe

What can data trusts for health research learn from participatory governance in biobanks?

New models of data governance for health data are a focus of growing interest in an era of challenge to the social licence. In this article, we reflect on what the data trust model, which is founded on principles of participatory governance, can learn from experiences of involving and engagement of members of the public and participants in the governance of large-scale biobanks. We distinguish between upstream and ongoing governance models, showing how they require careful design and operation if they are to deliver on aspirations for deliberation and participation. Drawing on this learning, we identify a set of considerations important to future design for data trusts as they seek to ensure just, proportionate and fair governance. These considerations relate to the timing of involvement of participants, patterns of inclusion and exclusion, and responsiveness to stakeholder involvement and engagement. We emphasise that the evolution of governance models for data should be matched by a commitment to evaluation.This work was supported by funding from the National Institute for Health Research [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust]. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Richard Milne is funded by Wellcome grant 206194 to Society and Ethics Research, Connecting Science, Wellcome Genome Campus. Mary Dixon-Woods is funded by the Health Foundation’s grant to the University of Cambridge for The Healthcare Improvement Studies (THIS) Institute. THIS Institute is supported by the Health Foundation—an independent charity committed to bringing about better health and health care for people in the UK. MDW is a National Institute for Health Research (NIHR) Senior Investigator (NF-SI-0617-10026

Innovative Verfahren für die standortübergreifende Datennutzung in der medizinischen Forschung

Implementing modern data-driven medical research approaches ("Artificial intelligence", "Data Science") requires access to large amounts of data ("Big Data"). Typically, this can only be achieved through cross-institutional data use and exchange ("Data Sharing"). In this process, the protection of the privacy of patients and probands affected is a central challenge. Various methods can be used to meet this challenge, such as anonymization or federation. However, data sharing is currently put into practice only to a limited extent, although it is demanded and promoted from many sides. One reason for this is the lack of clarity about the advantages and disadvantages of different data sharing approaches. The first goal of this thesis was to develop an instrument that makes these advantages and disadvantages more transparent. The instrument systematizes approaches based on two dimensions - utility and protection - where each dimension is further differentiated with three axes describing different aspects of the dimensions, such as the degree of privacy protection provided by the results of performed analyses or the flexibility of a platform regarding the types of analyses that can be performed. The instrument was used for evaluation purposes to analyze the status quo and to identify gaps and potentials for innovative approaches. Next, and as a second goal, an innovative tool for the practical use of cryptographic data sharing methods has been designed and implemented. So far, such approaches are only rarely used in practice due to two main obstacles: (1) the technical complexity of setting up a cryptography-based data sharing infrastructure and (2) a lack of user-friendliness of cryptographic data sharing methods, especially for medical researchers. The tool EasySMPC, which was developed as part of this work, is characterized by the fact that it allows cryptographically secure computation of sums (e.g., frequencies of diagnoses) across institutional boundaries based on an easy-to-use graphical user interface. Neither technical expertise nor the deployment of specific infrastructure components is necessary for its practical use. The practicability of EasySMPC was analyzed experimentally in a detailed performance evaluation.Moderne datengetriebene medizinische Forschungsansätze („Künstliche Intelligenz“, „Data Science“) benötigen große Datenmengen („Big Data“). Dies kann im Regelfall nur durch eine institutionsübergreifende Datennutzung erreicht werden („Data Sharing“). Datenschutz und der Schutz der Privatsphäre der Betroffenen ist dabei eine zentrale Herausforderung. Um dieser zu begegnen, können verschiedene Methoden, wie etwa Anonymisierungsverfahren oder föderierte Auswertungen, eingesetzt werden. Allerdings findet Data Sharing in der Praxis nur selten statt, obwohl es von vielen Seiten gefordert und gefördert wird. Ein Grund hierfür ist die Unklarheit ¸über Vor- und Nachteile verschiedener Data Sharing-Ansätze. Erstes Ziel dieser Arbeit war es, ein Instrument zu entwickeln, welches diese Vor- und Nachteile transparent macht. Das Instrument bewertet Ansätze anhand von zwei Dimensionen - Nutzen und Schutz - wobei jede Dimension mit drei Achsen weiter differenziert ist. Die Achsen bestehen etwa aus dem Grad des Schutzes der Privatsphäre, der durch die Ergebnisse der durchgeführten Analysen gewährleistet wird oder der Flexibilität einer Plattform hinsichtlich der Arten von Analysen, die durchgeführt werden können. Das Instrument wurde zu Evaluationszwecken für die Analyse des Status Quo sowie zur Identifikation von Lücken und Potenzialen für innovative Verfahren eingesetzt. Als zweites Ziel wurde anschließend ein innovatives Werkzeug für den praktischen Einsatz von kryptographischen Data Sharing-Verfahren entwickelt. Der Einsatz entsprechender Ansätze scheitert bisher vor allem an zwei Barrieren: (1) der technischen Komplexität beim Aufbau einer Kryptographie-basierten Data Sharing-Infrastruktur und (2) der Benutzerfreundlichkeit kryptographischer Data Sharing-Verfahren, insbesondere für medizinische Forschende. Das neue Werkzeug EasySMPC zeichnet sich dadurch aus, dass es eine kryptographisch sichere Berechnung von Summen (beispielsweise Häufigkeiten von Diagnosen) über Institutionsgrenzen hinweg auf Basis einer einfach zu bedienenden graphischen Benutzeroberfläche ermöglicht. Zur Anwendung ist weder technische Expertise noch der Aufbau spezieller Infrastrukturkomponenten notwendig. Die Praxistauglichkeit von EasySMPC wurde in einer ausführlichen Performance-Evaluation experimentell analysiert

A latent class approach:characterizing the willingness to share personal health information in Finland

Abstract. BACKGROUND: With the fast advances in technology, the aging populations, and the climate change, the amount of data in our hands has become enormous, and the ways of handling it has become better. There has been large amount of privacy concerns as well due to the fast-growing data that are spread everywhere. This study focuses on health data to find out whether personal characteristics can be associated with the willingness to consent it for secondary purposes. METHODS: A sample data (n=2338) concerning the Finnish populations attitudes towards secondary uses of health data was acquired and analyzed. The questionnaire included 14 questions regarding the willingness to consent data for different purposes. The dimensionality of this issue was reduced with a latent class analysis, and the information was condensed into one latent variable with 5 classes. After that a latent class regression was performed to find out whether the willingness could be explained with the help of other background information. RESULTS: A statistically significant association between the willingness to consent health data and the following characteristics; Gender, Age, Education, Perception of health, Number of visits to health or social care, and Financial situation. Political orientation had a high value of estimate, but no significance. CONCLUSIONS: Secondary uses of health data can achieve improvements in public health and welfare and health equality. Therefore, it is important that we make sure that the privacy concerns of using and sharing health data are taken care of. Methods for increasing the citizens willingness to consent their health data could be done through education and by building mutual trust between the health care system and the patients

Measuring the willingness to share personal health information: a systematic review

BackgroundIn the age of digitalization and big data, personal health information is a key resource for health care and clinical research. This study aimed to analyze the determinants and describe the measurement of the willingness to disclose personal health information.MethodsThe study conducted a systematic review of articles assessing willingness to share personal health information as a primary or secondary outcome. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocol. English and Italian peer-reviewed research articles were included with no restrictions for publication years. Findings were narratively synthesized.ResultsThe search strategy found 1,087 papers, 89 of which passed the screening for title and abstract and the full-text assessment.ConclusionNo validated measurement tool has been developed for willingness to share personal health information. The reviewed papers measured it through surveys, interviews, and questionnaires, which were mutually incomparable. The secondary use of data was the most important determinant of willingness to share, whereas clinical and socioeconomic variables had a slight effect. The main concern discouraging data sharing was privacy, although good data anonymization and the high perceived benefits of sharing may overcome this issue