Challenges and best practices for big data-driven healthcare innovations conducted by profit–non-profit partnerships–a quantitative prioritization

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Abstract

Big data-driven innovations are key in improving healthcare system sustainability. Given the complexity, these are frequently conducted by public-private-partnerships (PPPs) between profit and non-profit parties. However, information on how to manage big data-driven healthcare innovations by PPPs is limited. This study elucidates challenges and best practices in managing big data-driven healthcare innovations by PPPs in the Netherlands. Fifteen technical, organizational, competence and ethical/legal challenges and best practices to overcome these challenges were identified in expert interviews with key opinion leaders (KOLs) and through literature review. They were prioritized by a second KOL-panel in an online questionnaire and results were interpreted by a focus-group. ‘Data variety’ was the main challenge, followed by ‘lack of data sharing’ and ‘insufficient data quality’. PPP-respondents ranked appropriate big data skills significantly lower (P = 0.049) and conservatism towards health care decisions significantly (P = 0.026) than non-PPP respondents. The profit sub-group ranked data access higher compared to the non-profit sub-group (P = 0.022). Continuous dialogue between stakeholders, cost-benefit analyses and pilot experiments might overcome conservatism. In conclusion, PPPs should blend skills and resources to maximize benefits of big data-driven healthcare innovations. Mitigating actions could overcome technical issues, whilst a better common support base might prevent conservatism and lack of data sharing.

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Witjas-Paalberends, E. R., van Laarhoven, L. P. M., van de Burgwal, L. H. M., Feilzer, J., de Swart, J., Claassen, E., & Jansen, W. T. M. (2018). Challenges and best practices for big data-driven healthcare innovations conducted by profit–non-profit partnerships–a quantitative prioritization. International Journal of Healthcare Management, 11(3), 171–181. https://doi.org/10.1080/20479700.2017.1371367

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