Learning accountable governance: Challenges and perspectives for data-intensive health research networks
Current challenges to sustaining public support for health data research have directed attention to the governance of data-intensive health research networks. Accountability is hailed as an important element of trustworthy governance frameworks for data-intensive health research networks. Yet the ex...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2022-07-01
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| Series: | Big Data & Society |
| Online Access: | https://doi.org/10.1177/20539517221136078 |
| _version_ | 1811230924526845952 |
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| author | Sam HA Muller Menno Mostert Johannes JM van Delden Thomas Schillemans Ghislaine JMW van Thiel |
| author_facet | Sam HA Muller Menno Mostert Johannes JM van Delden Thomas Schillemans Ghislaine JMW van Thiel |
| author_sort | Sam HA Muller |
| collection | DOAJ |
| description | Current challenges to sustaining public support for health data research have directed attention to the governance of data-intensive health research networks. Accountability is hailed as an important element of trustworthy governance frameworks for data-intensive health research networks. Yet the extent to which adequate accountability regimes in data-intensive health research networks are currently realized is questionable. Current governance of data-intensive health research networks is dominated by the limitations of a drawing board approach. As a way forward, we propose a stronger focus on accountability as learning to achieve accountable governance. As an important step in that direction, we provide two pathways: (1) developing an integrated structure for decision-making and (2) establishing a dialogue in ongoing deliberative processes. Suitable places for learning accountability to thrive are dedicated governing bodies as well as specialized committees, panels or boards which bear and guide the development of governance in data-intensive health research networks. A continuous accountability process which comprises learning and interaction accommodates the diversity of expectations, responsibilities and tasks in data-intensive health research networks to achieve responsible and effective governance. |
| first_indexed | 2024-04-12T10:36:17Z |
| format | Article |
| id | doaj.art-d4d0c09f84174e0ab5c0fea933d79390 |
| institution | Directory Open Access Journal |
| issn | 2053-9517 |
| language | English |
| last_indexed | 2024-04-12T10:36:17Z |
| publishDate | 2022-07-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Big Data & Society |
| spelling | doaj.art-d4d0c09f84174e0ab5c0fea933d793902022-12-22T03:36:42ZengSAGE PublishingBig Data & Society2053-95172022-07-01910.1177/20539517221136078Learning accountable governance: Challenges and perspectives for data-intensive health research networksSam HA Muller0Menno Mostert1Johannes JM van Delden2Thomas Schillemans3Ghislaine JMW van Thiel4 Department of Medical Humanities, , University Medical Center Utrecht, Utrecht, The Netherlands Department of Medical Humanities, , University Medical Center Utrecht, Utrecht, The Netherlands Department of Medical Humanities, , University Medical Center Utrecht, Utrecht, The Netherlands Utrecht School of Governance, , Utrecht, The Netherlands Department of Medical Humanities, , University Medical Center Utrecht, Utrecht, The NetherlandsCurrent challenges to sustaining public support for health data research have directed attention to the governance of data-intensive health research networks. Accountability is hailed as an important element of trustworthy governance frameworks for data-intensive health research networks. Yet the extent to which adequate accountability regimes in data-intensive health research networks are currently realized is questionable. Current governance of data-intensive health research networks is dominated by the limitations of a drawing board approach. As a way forward, we propose a stronger focus on accountability as learning to achieve accountable governance. As an important step in that direction, we provide two pathways: (1) developing an integrated structure for decision-making and (2) establishing a dialogue in ongoing deliberative processes. Suitable places for learning accountability to thrive are dedicated governing bodies as well as specialized committees, panels or boards which bear and guide the development of governance in data-intensive health research networks. A continuous accountability process which comprises learning and interaction accommodates the diversity of expectations, responsibilities and tasks in data-intensive health research networks to achieve responsible and effective governance.https://doi.org/10.1177/20539517221136078 |
| spellingShingle | Sam HA Muller Menno Mostert Johannes JM van Delden Thomas Schillemans Ghislaine JMW van Thiel Learning accountable governance: Challenges and perspectives for data-intensive health research networks Big Data & Society |
| title | Learning accountable governance: Challenges and perspectives for data-intensive health research networks |
| title_full | Learning accountable governance: Challenges and perspectives for data-intensive health research networks |
| title_fullStr | Learning accountable governance: Challenges and perspectives for data-intensive health research networks |
| title_full_unstemmed | Learning accountable governance: Challenges and perspectives for data-intensive health research networks |
| title_short | Learning accountable governance: Challenges and perspectives for data-intensive health research networks |
| title_sort | learning accountable governance challenges and perspectives for data intensive health research networks |
| url | https://doi.org/10.1177/20539517221136078 |
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