The purpose of this paper is to describe the application of soft systems methodology (SSM) to address the problematic situation of low opt-in rates for Precision Health-Care (PHC).

Design/methodology/approach:
The design logic is that when trust is enhanced and compliance is better assured, participants such as patients and their doctors would be more likely to share their medical data and diagnosis for the purpose of precision modeling.

Findings:
The authors present the findings of an empirical study that confronts the design challenge of increasing participant opt-in to a PHC repository of Electronic Medical Records and genetic sequencing. Guided by SSM, the authors formulate design rules for the establishment of a trust-less platform for PHC which incorporates key principles of transparency, traceability and immutability.

Research limitations/implications:
The SSM approach has been criticized for its lack of “rigour” and “replicability”. This is a fallacy in understanding its purpose – theory exploration rather than theory confirmation. Moreover, it is unlikely that quantitative modeling yields any clearer an understanding of complex, socio-technical systems.

Practical implications:
The application of Blockchain, a platform for distributed ledgers and associated technologies present a feasible approach for resolving the problematic situation of low opt-in rates.

Social implications:
A consequence of low participation is the weak recall and precision of descriptive, predictive and prescriptive analytic models. Factors such as cyber-crime, data violation and the potential for misuse of genetic and medical records have led to a lack of trust from key stakeholders – accessors, participants, miners and regulators – to varying degrees.

Originality/value:
The application of Blockchain as a trust-enabling platform in the domain of an emerging eco-system such as precision health is novel and pioneering.