include not just taxonomy and inventory of data sources, but assessment of how high-priority questions and issues map to existing sources and methods, including annotation of sources used in research studies.


As emphasized in Crossing the Quality Chasm in 2001, patient-centered care has been highlighted as a central component of quality health care (IOM, 2001). Extending this notion to digital health information was a frequent theme in workshop discussions.

Information patients care about. Several participants and speakers emphasized collecting information that patients care about, and including information on wellness and productivity, as a first step toward this goal. Similarly, increasing the inclusion of patient-reported information in the digital health data utility was highlighted as a priority. Development, validation, and encouragement of the use of patient-reported preferences, symptoms, care-process measures, and outcomes were called out as potential important components of this strategy.

Usability. Improving the usability of health and biomedical information technology and prioritizing information collection were strategies suggested to minimize the burden imposed on data collectors. Identifying and eliminating the collection of low-value data, as well as automating data collection, whenever appropriate, were suggested as potential approaches.

Contextual tagging. Maintenance of the provenance and context of the data was also highlighted as an important issue, particularly when data is used for a purpose other than that for which it was collected. The use of metadata tagging and strategies to enable access to full original context (e.g., on place, time, person/SES) were called out as potential approaches.

Core elements. In order to make progress on the goal of improving data quality, the development of more standardized digital health data definitions and representations was highlighted for attention. In particular, several participants emphasized the need for development of a set of core minimum standardized data elements to provide timely essential information on cost, quality, and health status and trends, available across institutions and geographic areas and designed to harmonize funder data set requirements. Some participants felt that inclusion of these core elements as part of the certification process was an effective way to further progress.

The National Academies of Sciences, Engineering, and Medicine
500 Fifth St. N.W. | Washington, D.C. 20001

Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement