Advancing Standards for Precision Medicine

Data sharing is critical to realizing the future of precision medicine. Launched in 2018, the Advancing Standards for Precision Medicine (ASPM) project furthered the development and testing of standards for new and diverse types of health data. This ONC project is part of the Precision Medicine Initiative (PMI), and conducted in partnership with the National Institutes of Health’s All of Us Research Program. The ultimate goal is to make health data easier to share, curate, aggregate, and synthesize.

The ASPM project focused on standards in two areas:

  • Mobile health, sensor, and wearable data; and
  • Social determinants of health (SDOH) data

To advance mobile health, sensors, and wearables, two demonstration projects tested the implementation of the HL7® FHIR® Mobile Health Application Data Exchange Assessment Framework and Functional Requirements Implementation Guide (mHealth ADE FHIR IG) that was developed by the ASPM project team to capture mobile health, sensor, and wearable data.

Another demonstration project tested the Integrating the Healthcare Enterprise Assessment Curation and Data Collection (IHE ACDC) profile, which was developed by the ASPM project team to capture SDOH data through assessments and questionnaires.

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Final Report

To learn more about the Advancing Standards for Precision Medicine project, read the Final Report [PDF- 2.5 MB], which details new findings and recommendations for advancing standards for mobile health, sensor, and wearable data, and SDOH data.

Health IT Buzz Blog

Standards Beyond the Clinic: Capturing Patient Health Data to Advance Precision Medicine shares results from the Advancing Standards for Precision Medicine project and its effort to advance standardized sharing of mobile health, sensor, and wearable; and social determinant of health data.

Implementation Guide

Access the HL7 FHIR mHealth App Data Exchange Functional Requirements Implementation Guide developed to enable standardized sharing of mobile health, sensor, and wearable data.

Implementation Guide