A Conceptual Framework of Data Readiness: The Contextual Intersection of Quality, Availability, Interoperability, and Provenance

• Published in: Applied clinical informatics Vol. 12; no. 3; pp. 675 - 685
• Main Authors: Douthit, Brian J., Del Fiol, Guilherme, Staes, Catherine J., Docherty, Sharron L., Richesson, Rachel L.
• Format: Journal Article
• Language: English
• Published: Rüdigerstraße 14, 70469 Stuttgart, Germany Georg Thieme Verlag KG 01.05.2021
• Subjects: Review; Review Article; data quality; interoperability; data management; electronic health record; governance
• ISSN: 1869-0327; 1869-0327
• DOI: 10.1055/s-0041-1732423

Abstract Background  Data readiness is a concept often used when referring to health information technology applications in the informatics disciplines, but it is not clearly defined in the literature. To avoid misinterpretations in research and implementation, a formal definition should be developed. Objectives  The objective of this research is to provide a conceptual definition and framework for the term data readiness that can be used to guide research and development related to data-based applications in health care. Methods  PubMed, the National Institutes of Health RePORTER, Scopus, the Cochrane Library, and Duke University Library databases for business and information sciences were queried for formal mentions of the term “data readiness.” Manuscripts found in the search were reviewed, and relevant information was extracted, evaluated, and assimilated into a framework for data readiness. Results  Of the 264 manuscripts found in the database searches, 20 were included in the final synthesis to define data readiness. In these 20 manuscripts, the term data readiness was revealed to encompass the constructs of data quality, data availability, interoperability, and data provenance. Discussion  Based upon our review of the literature, we define data readiness as the application-specific intersection of data quality, data availability, interoperability, and data provenance. While these concepts are not new, the combination of these factors in a novel data readiness model may help guide future informatics research and implementation science. Conclusion  This analysis provides a definition to guide research and development related to data-based applications in health care. Future work should be done to validate this definition, and to apply the components of data readiness to real-world applications so that specific metrics may be developed and disseminated.