Opportunities and challenges in the use of personal health data for health research

Objective: Understand barriers to the use of personal health data (PHD) in research from the perspective of three stakeholder groups: early adopter individuals who track data about their health, researchers who may use PHD as part of their research, and companies that market self-tracking devices, apps or services, and aggregate and manage the data that are generated. Materials and Methods: A targeted convenience sample of 465 individuals and 134 researchers completed an extensive online survey. Thirty-five hourlong semi-structured qualitative interviews were conducted with a subset of 11 individuals and 9 researchers, as well as 15 company/key informants. Results: Challenges to the use of PHD for research were identified in six areas: data ownership; data access for research; privacy; informed consent and ethics; research methods and data quality; and the unpredictable nature of the rapidly evolving ecosystem of devices, apps, and other services that leave “digital footprints.” Individuals reported willingness to anonymously share PHD if it would be used to advance research for the good of the public. Researchers were enthusiastic about using PHD for research, but noted barriers related to intellectual property, licensing, and the need for legal agreements with companies. Companies were interested in research but stressed that their first priority was maintaining customer relationships. Conclusion: Although challenges exist in leveraging PHD for research, there are many opportunities for stakeholder engagement, and experimentation with these data is already taking place. These early examples foreshadow a much larger set of activities with the potential to positively transform how health research is conducted

Building the case for actionable ethics in digital health research supported by artificial intelligence

The digital revolution is disrupting the ways in which health research is conducted, and subsequently, changing healthcare. Direct-to-consumer wellness products and mobile apps, pervasive sensor technologies and access to social network data offer exciting opportunities for researchers to passively observe and/or track patients ‘in the wild’ and 24/7. The volume of granular personal health data gathered using these technologies is unprecedented, and is increasingly leveraged to inform personalized health promotion and disease treatment interventions. The use of artificial intelligence in the health sector is also increasing. Although rich with potential, the digital health ecosystem presents new ethical challenges for those making decisions about the selection, testing, implementation and evaluation of technologies for use in healthcare. As the ‘Wild West’ of digital health research unfolds, it is important to recognize who is involved, and identify how each party can and should take responsibility to advance the ethical practices of this work. While not a comprehensive review, we describe the landscape, identify gaps to be addressed, and offer recommendations as to how stakeholders can and should take responsibility to advance socially responsible digital health research

Data Donation as a Model for Citizen Science Health Research

New computational and sensing innovations, coupled with increasingly affordable access to consumer health technologies, allow individuals to generate personal health information that they are then able to submit to a shared archive or repository. This paper presents data donation as a model for health-focused citizen science, with special attention to the ethical challenges and opportunities that this model presents. We also highlight some existing data donation projects curated by citizen scientists. After describing data donation in more detail, including its relationship to movements like the Quantified Self and research in personalized medicine, we report findings from the Health Data Exploration (HDE) Project’s second annual Network Meeting, which was focused on data donation. These findings include identification of four challenges for the ethical conduct of health-focused data donation research: Participant protection, representativeness, incentives to participate, and governance. We use these insights as a springboard for further discussion of specific issues, pointing both to the current state of the field and our suggestions about potential pathways for addressing some of the challenges

A framework to facilitate interprovincial sharing of secondary health data in Canada

Introduction The use of administrative health data can generate knowledge to improve the delivery and outcomes of health care. Yet, the sharing and use of secondary health data presents concerns given these data were not collected for health research purposes. The sharing of patient-level health data across Canadian provinces is uncommon. Objectives and Approach The Maritime SPOR SUPPORT Unit (a patient-oriented research unit serving the three Canadian Maritime Provinces of New Brunswick, Nova Scotia, and Prince Edward Island) struck a Working Group to develop a conceptual framework for the interprovincial sharing of secondary health data for research purposes. Membership comprised a researcher, two privacy managers/officers, and a manager of research ethics. The framework sought to: (1) facilitate researchers’ understanding of the foundational elements (legal/ethical) of interprovincial data sharing for health research; and (2) identify challenges and opportunities for improving sharing of data across the Maritime Provinces to support patient-oriented research. Results In all three Maritime provinces, de-identified personal health information may be used for approved health research purposes, with each province having its own data holdings and repositories. Applying the applicable governance principles and regulations (i.e., the ethical governance of research involving human subjects and the legal governance of health information) and drawing on best practices nationally and internationally, a framework was developed to incorporate and address the various aspects of sharing and using health data across provinces for the purposes of health research. The resultant framework discusses when and how the legal and ethical frameworks apply, the de-identification of data, degrees of data sharing, and information governance. It also identifies challenges and opportunities to moving forward with interprovincial data sharing. Conclusion/Implications Development of this framework was the first phase of a multi-phase approach to move towards improved interprovincial data sharing for patient-oriented research. Cross-provincial sharing and linkage of data can lead to comprehensive, cost-effective, and multi-disciplinary research that benefits patients, the health system, and the public at large

The funhouse mirror: the I in personalised healthcare

Precision Medicine is driven by the idea that the rapidly increasing range of relatively cheap and efficient self-tracking devices make it feasible to collect multiple kinds of phenotypic data. Advocates of N = 1 research emphasize the countless opportunities personal data provide for optimizing individual health. At the same time, using biomarker data for lifestyle interventions has shown to entail complex challenges. In this paper, we argue that researchers in the field of precision medicine need to address the performative dimension of collecting data. We propose the fun-house mirror as a metaphor for the use of personal health data; each health data source yields a particular type of image that can be regarded as a ‘data mirror’ that is by definition specific and skewed. This requires competence on the part of individuals to adequately interpret the images thus provided

Picturing Life: Using Photo Journals to Explore Challenges and Supports for Women Living with HIV (WL-HIV)

Human immunodeficiency virus (HIV) is a health-related stigmatizing condition that progresses to acquired immune deficiency syndrome (AIDS), characterized by a weakened immune system and opportunistic diseases. South Carolina ranks eighth for AIDS prevalence in the United States, and for socioeconomic reasons, women, specifically minority women, in the southern region of the country experience the worst clinical outcomes after receiving an HIV diagnosis. Research that focuses on strategies to improve clinical outcomes for women living with HIV (WL-HIV) has great value in promoting empowerment and health equity especially among minority women. The current study used a participatory research design to collaborate with WL-H IV to create photo journals to identify personal challenges and supports. Data source included (discussions, photographs, and one-on-one interviews). The investigator used a grounded theory approach to analyze the data and identified major themes and subthemes. Major themes for supports included spirituality and empowerment; and subthemes were, reinventing self and positive relationships. The investigator identified stigma as the major theme for challenges, and public silence on HIV and missed opportunities were subthemes. The author provided specific recommendations for future research and clinical practice. Manuscript 1: Defining Hope among HIV-Positive African American Females. This article was a concept analysis of hope among African American females living with HIV and was accepted for publication by The Journal of Christian Nurses, (Kennedy, 2015). Manuscript 2: Ethical Considerations Regarding Barriers and Facilitators to Research Participation for Patients Affected by Health-related Stigmatizing Conditions. This integrative review focused on the ethical implications of omitting persons living with health-related stigmatizing conditions, such as human immunodeficiency virus, substance use disorders, and intimate partner violence. The author formatted this manuscript for The American Journal of Nursing. Manuscript 3: Picturing Life: Using Photo Journals to Explore Challenges and Supports for Women Living with HIV. This manuscript explored the challenges and supports experienced by women with HIV in South Carolina. This qualitative study employed a participatory research design with Photovoice as the method of data collection

Translating Bioinformatics Back To Healthcare: Facilitating the use of Artificial Intelligence at UW Medicine

It is an opportune time to be engaged in the research and application of informatics in biomedicine. The increased use of electronic and personal health records and personal mobile devices is creating many opportunities at research academic medical centers. At the University of Washington, I believe we are laying the groundwork to build the informatics and information technology infrastructure to support research on personalized approaches and the use of data science to enable them. We are beginning to see the early successes of these efforts and I will describe some of them. But there are many challenges, for example, we continue to generate massive amounts of data that is largely uncurated. This includes images, genomes and other -omics datasets, personal monitors, electronic health records, etc. In this presentation, I will discuss our support of data for research use within UW Medicine, our efforts to build new machine learning and data science approaches using clinical datasets, and our efforts to develop new machine learning methods and to implement them so that we can study the impacts of their use.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

The Second International Conference on Health Information Technology Advancement

TABLE OF CONTENTS I. Message from the Conference Co-Chairs B. Han and S. Falan …………………………....….……………. 5 II. Message from the Transactions Editor H. Lee …...………..………….......………….……….………….... 7 III. Referred Papers A. Emerging Health Information Technology and Applications The Role of Mobile Technology in Enhancing the Use of Personal Health Records Mohamed Abouzahra and Joseph Tan………………….……………. 9 Mobile Health Information Technology and Patient Care: Methods, Themes, and Research Gaps Bahae Samhan, Majid Dadgar, and K. D. Joshi…………..…. 18 A Balanced Perspective to Perioperative Process Management Jim Ryan, Barbara Doster, Sandra Daily, and Carmen Lewis…..….…………… 30 The Impact of Big Data on the Healthcare Information Systems Kuo Lane Chen and Huei Lee………….…………… 43 B. Health Care Communication, Literacy, and Patient Care Quality Digital Illness Narratives: A New Form of Health Communication Jofen Han and Jo Wiley…..….……..…. 47 Relationships, Caring, and Near Misses: Michael’s Story Sharie Falan and Bernard Han……………….…..…. 53 What is Your Informatics Skills Level? -- The Reliability of an Informatics Competency Measurement Tool Xiaomeng Sun and Sharie Falan.….….….….….….…. 61 C. Health Information Standardization and Interoperability Standardization Needs for Effective Interoperability Marilyn Skrocki…………………….…….………….… 76 Data Interoperability and Information Security in Healthcare Reid Berryman, Nathan Yost, Nicholas Dunn, and Christopher Edwards.…. 84 Michigan Health Information Network (MiHIN) Shared Services vs. the HIE Shared Services in Other States Devon O’Toole, Sean O’Toole, and Logan Steely…..……….…… 94 D. Health information Security and Regulation A Threat Table Based Approach to Telemedicine Security John C. Pendergrass, Karen Heart, C. Ranganathan, and V.N. Venkatakrishnan …. 104 Managing Government Regulatory Requirements for Security and Privacy Using Existing Standard Models Gregory Schymik and Dan Shoemaker…….…….….….… 112 Challenges of Mobile Healthcare Application Security Alan Rea………………………….……………. 118 E. Healthcare Management and Administration Analytical Methods for Planning and Scheduling Daily Work in Inpatient Care Settings: Opportunities for Research and Practice Laila Cure….….……………..….….….….… 121 Predictive Modeling in Post-reform Marketplace Wu-Chyuan Gau, Andrew France, Maria E. Moutinho, Carl D. Smith, and Morgan C. Wang…………...…. 131 A Study on Generic Prescription Substitution Policy as a Cost Containment Approach for Michigan’s Medicaid System Khandaker Nayeemul Islam…….…...……...………………….… 140 F. Health Information Technology Quality Assessment and Medical Service Delivery Theoretical, Methodological and Practical Challenges in Designing Formative Evaluations of Personal eHealth Tools Michael S. Dohan and Joseph Tan……………….……. 150 The Principles of Good Health Care in the U.S. in the 2010s Andrew Targowski…………………….……. 161 Health Information Technology in American Medicine: A Historical Perspective Kenneth A. Fisher………………….……. 171 G. Health Information Technology and Medical Practice Monitoring and Assisting Maternity-Infant Care in Rural Areas (MAMICare) Juan C. Lavariega, Gustavo Córdova, Lorena G Gómez, Alfonso Avila….… 175 An Empirical Study of Home Healthcare Robots Adoption Using the UTUAT Model Ahmad Alaiad, Lina Zhou, and Gunes Koru.…………………….….………. 185 HDQM2: Healthcare Data Quality Maturity Model Javier Mauricio Pinto-Valverde, Miguel Ángel Pérez-Guardado, Lorena Gomez-Martinez, Martha Corrales-Estrada, and Juan Carlos Lavariega-Jarquín.… 199 IV. A List of Reviewers …………………………..…….………………………208 V. WMU – IT Forum 2014 Call for Papers …..…….…………………20

Research data management in Education, Psychology and Sport Sciences at the Faculty of Human Sciences, University of Bern, Switzerland

1. Introduction The Faculty of Human Sciences at the University of Bern includes three institutes: the Institute of Educational Science, the Institute of Psychology and the Institute of Sport Science. Research management (FOMA) at the Faculty of Human Sciences aims to support researchers by strengthening excellent research and managing research data ethically in line with the Swiss federal laws and ordinances. We advise researchers where and how, and under which conditions and formats to store their research data, and provide consulting on requirements and best practices for metadata and documentation description, data monitoring and coding of variables. We support with the data management processes, continuous monitoring and updates related to data management plans (DMP), which are required by the Swiss National Science Foundation and EU-Commission. We inform researchers on the legal ordinance of the Swiss Federal Act on Data Protection (FADP) for the ethical management of sensitive data, on the Findable, Accessible, Interoperable, and Reusable (FAIR) data principles and on available IT-solutions in accordance to the General Data Protection Regulations (GDPR). 2. Research Data Data collection and sharing is part of the research projects conducted at the Faculty and therefore need to meet ethical and legal requirements. Collected are either related to clinical studies, which fall under the Federal Act on Research involving Human Beings (HRA, Art. 118b § 1) and require approvals from an ethics committee (e.g., Cantonal Ethic Commission (CEC) or Swissmedic), or studies that do not fall under the HRA and can be reviewed and evaluated by the Ethical Committee experts at the Faculty. Yet, most of the data are personal and health-related personal data, therefore, informed consent, case report forms and homogenized protocols should be taken into consideration in agreement with legislation in Switzerland. Here we give some examples of the ethical data treatment according to good research practices. We face challenges, leverage strengths and create opportunities by providing data management within the human science disciplines in relation to: Personal and health-personal data: Sociodemographic (date of birth, place of birth, civil status, nationality, old-age and survivor's insurance (OASI); Personality- and ability-related data (workplace-related problems); psychophysiological data such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings; mental health-related behaviors and attitudes; anthropometric data: Body Mass Index (BMI), waist circumference, bioimpedance data; cardiovascular data (blood pressure, pulse wave velocity, heart rate variability). Clinical data: Symptom severity and changes during therapy; online-assessments; randomized online studies and surveys; confidentiality agreements; inform consent forms; study protocols; case report forms; monitoring reports. IT- and software applications: Computer games; applications for kids; educational applications; self-help applications; phone applications; survey & interviews (Qualtrics, Atlas.ti); clinical trials and surveys (RedCap, Qualtrics); statistical software (R, Stata, SAS, SPSS). Data format and storage: Anonymised scans (.tiff, .png); tables (.csv encoded in UTF-8); text documents (txt, A/PDF) coded as ASCII; audio (.wav, .mp4); video (.mov, .avi, .mj2, .mkv, FFV1 codec); graphics (HDF5, .svg). Password-protected access for the project principal investigators (PI) and project members. Traceable anonymized data transfer and password-protected access to the encoded data within the project partners. All tablet computers are password-protected, with the experimenters being the only persons to have password-protected access to the data. Information about data collection and documentation, ethical, legal and security issues, data storage and preservation, as well as data sharing and reuse is provided in the data management plans, supporting researchers to design and conduct their projects according to the FAIR principles, legal ordinances and requirements of the national and international funding agencies. 3. Challenges • Where and how to store the identifying data or personal participants’ data additionally to separate database with anonymised encoded data? • Possible delays in the study due to amendments to the ethics commissions. • Where is the right place to store encrypted and password-protected video/audio interviews? • Which is the most appropriate Software to use for surveys? • Is it necessary to use licensing under continuous games integration? • Where is the right place to store neurophysiological (EEG- and fMRI) data? • What is the right criteria to use pseudonymisation vs. anonymisation? Encrypted and anonymised interviews are often needed to be pseudonymised (e.g. Olympic champions). • How can video/audio images of interviews be anonymised? If not at all, then what are the possible solutions? 4. Strengths & Opportunities • Use professional software that correspond to the GDPR and store the data within national Swiss data repositories or within European Union. • Follow the Good Clinical Practice (GCP) and International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) rules and prepare applications for the ethics committees earlier enough by leverage better study planning. • Use collaborative approach at the institutional level and with other research centers to strengthen network. • Follow Open Science strategy by “open data as possible, as close as necessary” under legal ordinance of the FADP for the management of sensitive data ethically based on the FAIR data principles and on available IT-solutions in accordance to the GDPR. • Identify the overall strategy for data management processes before the project starts. Apply for licenses for presentations, talks, developed games, phone applications etc. 5. Collaboration The FOMA data management support at the Faculty is offered in collaboration with the Clinical Trial Unit (CTU, University of Bern); IT-persons of the three research institutes at the Faculty and Ethics Committee at the Faculty; and the Open Science Team at the University of Bern, Switzerland

GDPR and Biobanking

This open access book focuses on the discrepancies in biobank research regulations that are among the most significant hurdles to effective research collaboration. The General Data Protection Regulation (GDPR) has established stringent requirements for the processing of health and genetic data, while simultaneously allowing considerable multi-level exceptions for the purposes of scientific research. In addition to directly applicable exceptions, the GDPR places the regulatory responsibility for further defining how the Member States strike a balance between the individuals' rights and the public interest in research within their national legal orders. Since Member States' approaches to the trade-off between data subjects' rights on the one hand, and appropriate safeguards on the other, differ according to their ethical and legal traditions, their data protection requirements for research also differ considerably. This study takes a comprehensive approach to determine how the GDPR affects regulatory regimes on the use of personal data in biobanking research, with a particular focus on the balance between individuals' rights, public interest and scientific research. In this regard, it has two main goals: first, to scrutinize the GDPR research regime, its objective and constitutive elements, the impact it has on biobanking, and its role in a changing EU landscape post-Brexit; and second, to examine how various exceptions have been operationalized nationally, and what challenges and opportunities this diversification entails. The book not only captures the complexity GDPR creates for biobanking, but also sheds light on various approaches to tackling the corresponding challenges. It offers the first comprehensive analysis of GDPR for biobanking, and the most up-to-date overview of the national biobank regulatory frameworks in Europe