Ensure MLHC is equitable by design | Develop pipelines for the promotion of diverse teams in all aspects of MLHC Ensure the inclusion of data from a broad range of groups, in a broad range of contexts Incorporate global partners to ensure health data science promotes global health equity.
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Encourage public and open MLHC research | |
Ensure adequate access to health information technology (IT) infrastructure | Ensure all are included in the datasets by funding health data gathering infrastructure in underserved communities Develop MLHC products with an awareness of the broad range of health IT contexts for deployment
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Ensure MLHC is clinically effective and impactful | Ensure the presence of multidisciplinary teams that represent both clinical and data science perspectives Promote pathways for interdisciplinary training Hold MLHC innovations to the same standards as other healthcare interventions, including requirements for prospective validation and clear demonstration of impact
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Audit MLHC on ethical metrics | |
Mandate transparency in data collection, analysis and usage | |
Promote inclusive and interoperable data policy | Ensure the existence of clear and ethical methods for ensuring the sharing of data between different sources while protecting patient rights and privacy Improve the standardisation of medical data generation and labelling across contexts Ensure that global partners are included, so that interoperability barriers do not hinder inclusive global collaboration
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