Tuesday 15 November 2022

Learning accountable governance: Challenges and perspectives for data-intensive health research networks

by Sam Muller

Muller, S. H. A., Mostert, M., van Delden, J. J. M., Schillemans, T., & van Thiel, G. J. M. W.(2022). Learning accountable governance: Challenges and perspectives for data-intensive health research networks. Big Data & Society, 9(2). https://doi.org/10.1177/20539517221136078

In our article, we address the accountability of large-scale health data research. Accountability is crucial to ensure democratic control and to steer health data research to contribute public value. Yet whereas previous research about health data paid much attention to accountability as a norm for doing and organising health data research, it did not specify what accountability processes should look like in practice. Specifically, previous research did not take into account that much health data research takes place in international networks, in which public and private organisations collaborate internationally and in a relatively horizontal way.
In our analysis of the current state of accountability, we found that governing such networks to foster accountability faces several challenges. The fact that health data research takes place in complex networks puts a lot of pressure on realizing clear and stable accountability relationships. Moreover, smooth cooperation is difficult due to unclarity of norms and principles which could guide accountability processes. Lastly, effective design of information provision and debate is lacking.
To complement the shortcomings of current accountability in health data research networks, we propose focusing on accountability as a means of learning from insights and feedback about how good governance can be achieved. We suggest two pathways for pursuing learning accountability. First, an integrated governance structure for learning to occur needs to be developed. Provisional goals need to be established by building on overlapping consensus. This is crucial to develop mutual understanding, shared motivation and common commitment between organisations engaged in health data research. Second, ongoing deliberation and open communication about collaboration are required for reflexive dialogue. Stakeholders (publics and communities affected by health data research) should be represented and enabled to participate. Empowering them in the form of a collective forum enables learning from their experiences and holding health data research to account.