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      Practices and Attitudes of Bavarian Stakeholders Regarding the Secondary Use of Health Data for Research Purposes During the COVID-19 Pandemic: Qualitative Interview Study

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          Abstract

          Background

          The COVID-19 pandemic is a threat to global health and requires collaborative health research efforts across organizations and countries to address it. Although routinely collected digital health data are a valuable source of information for researchers, benefiting from these data requires accessing and sharing the data. Health care organizations focusing on individual risk minimization threaten to undermine COVID-19 research efforts, and it has been argued that there is an ethical obligation to use the European Union’s General Data Protection Regulation (GDPR) scientific research exemption during the COVID-19 pandemic to support collaborative health research.

          Objective

          This study aims to explore the practices and attitudes of stakeholders in the German federal state of Bavaria regarding the secondary use of health data for research purposes during the COVID-19 pandemic, with a specific focus on the GDPR scientific research exemption.

          Methods

          Individual semistructured qualitative interviews were conducted between December 2020 and January 2021 with a purposive sample of 17 stakeholders from 3 different groups in Bavaria: researchers involved in COVID-19 research (n=5, 29%), data protection officers (n=6, 35%), and research ethics committee representatives (n=6, 35%). The transcripts were analyzed using conventional content analysis.

          Results

          Participants identified systemic challenges in conducting collaborative secondary-use health data research in Bavaria; secondary health data research generally only happens when patient consent has been obtained, or the data have been fully anonymized. The GDPR research exemption has not played a significant role during the pandemic and is currently seldom and restrictively used. Participants identified 3 key groups of barriers that led to difficulties: the wider ecosystem at many Bavarian health care organizations, legal uncertainty that leads to risk-adverse approaches, and ethical positions that patient consent ought to be obtained whenever possible to respect patient autonomy. To improve health data research in Bavaria and across Germany, participants wanted greater legal certainty regarding the use of pseudonymized data for research purposes without the patient’s consent.

          Conclusions

          The current balance between enabling the positive goals of health data research and avoiding associated data protection risks is heavily skewed toward avoiding risks; so much so that it makes reaching the goals of health data research extremely difficult. This is important, as it is widely recognized that there is an ethical imperative to use health data to improve care. The current approach also creates a problematic conflict with the ambitions of Germany, and the federal state of Bavaria, to be a leader in artificial intelligence. A recent development in the field of German public administration known as norm screening ( Normenscreening) could potentially provide a systematic approach to minimize legal barriers. This approach would likely be beneficial to other countries.

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          Most cited references74

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          Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups.

          Qualitative research explores complex phenomena encountered by clinicians, health care providers, policy makers and consumers. Although partial checklists are available, no consolidated reporting framework exists for any type of qualitative design. To develop a checklist for explicit and comprehensive reporting of qualitative studies (in depth interviews and focus groups). We performed a comprehensive search in Cochrane and Campbell Protocols, Medline, CINAHL, systematic reviews of qualitative studies, author or reviewer guidelines of major medical journals and reference lists of relevant publications for existing checklists used to assess qualitative studies. Seventy-six items from 22 checklists were compiled into a comprehensive list. All items were grouped into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. Duplicate items and those that were ambiguous, too broadly defined and impractical to assess were removed. Items most frequently included in the checklists related to sampling method, setting for data collection, method of data collection, respondent validation of findings, method of recording data, description of the derivation of themes and inclusion of supporting quotations. We grouped all items into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. The criteria included in COREQ, a 32-item checklist, can help researchers to report important aspects of the research team, study methods, context of the study, findings, analysis and interpretations.
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            • Record: found
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            • Article: not found

            Three approaches to qualitative content analysis.

            Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research.

              Purposeful sampling is widely used in qualitative research for the identification and selection of information-rich cases related to the phenomenon of interest. Although there are several different purposeful sampling strategies, criterion sampling appears to be used most commonly in implementation research. However, combining sampling strategies may be more appropriate to the aims of implementation research and more consistent with recent developments in quantitative methods. This paper reviews the principles and practice of purposeful sampling in implementation research, summarizes types and categories of purposeful sampling strategies and provides a set of recommendations for use of single strategy or multistage strategy designs, particularly for state implementation research.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J Med Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                June 2022
                27 June 2022
                27 June 2022
                : 24
                : 6
                : e38754
                Affiliations
                [1 ] Institute of History and Ethics in Medicine TUM School of Medicine Technical University of Munich Munich Germany
                [2 ] TUM Center for Digital Public Services Department Governance, TUM School of Social Sciences and Technology Technical University of Munich Munich Germany
                Author notes
                Corresponding Author: Stuart McLennan stuart.mclennan@ 123456tum.de
                Author information
                https://orcid.org/0000-0002-2019-6253
                https://orcid.org/0000-0003-2003-0074
                https://orcid.org/0000-0001-9643-7407
                https://orcid.org/0000-0001-7207-6897
                https://orcid.org/0000-0002-3640-1645
                https://orcid.org/0000-0002-5726-7633
                Article
                v24i6e38754
                10.2196/38754
                9239567
                35696598
                c4aaa6fc-c56d-4832-929f-0a64ad64fdb2
                ©Stuart McLennan, Sarah Rachut, Johannes Lange, Amelia Fiske, Dirk Heckmann, Alena Buyx. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.06.2022.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 14 April 2022
                : 9 May 2022
                : 28 May 2022
                : 29 May 2022
                Categories
                Original Paper
                Original Paper

                Medicine
                covid-19,data sharing,general data protection regulation,gdpr,research exemption,public health,research,digital health,electronic health records

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