Data and knowledge standards for learning health: A population management example using chronic kidney disease

Abstract

The widespread creation of learning health care systems (LHSs) will depend upon the use of standards for data and knowledge representation. Standards can facilitate the reuse of approaches for the identification of patient cohorts and the implementation of interventions. Standards also support rapid evaluation and dissemination across organizations. Building upon widely-used models for process improvement, we identify specific LHS activities that will require data and knowledge standards. Using chronic kidney disease (CKD) as an example, we highlight the specific data and knowledge requirements for a disease-specific LHS cycle, and subsequently identify areas where standards specifications, clarification, and tools are needed. The current data standards for CKD population management recommendations were found to be partially ambiguous, leading to barriers in phenotyping, risk identification, patient-centered clinical decision support, patient education needs, and care planning.Robust tools are needed to effectively identify patient health care needs and preferences and to measure outcomes that accurately depict the multiple facets of CKD. This example presents an approach for defining the specific data and knowledge representation standards required to implement condition-specific population health management programs. These standards specifications can be promoted by disease advocacy and professional societies to enable the widespread design, implementation, and evaluation of evidence-based health interventions, and the subsequent dissemination of experience in different settings and populations. arising from overwhelming system complexity, suboptimal data quality and analytical tools, and misaligned health care policies. [2][3][4][5][6] In particular, health care organizations struggle to leverage data stored within proprietary electronic health record (EHR) systems to gainThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. In this paper, we use existing models for evidence-based medicine (EBM), learning health, and process improvement to identify datadependent activities, which by definition will benefit from the use of standards. We identify relevant data domains for each datadependent activity, and look at national standards to evaluate the clarity and specificity of those current data standards in the context of a population management program for CKD. | DATA-DEPENDENT ACTIVITIES AND STANDARDS FOR LEARNING HEALTH SYSTEMSIn an early roundtable on learning health, the Institute of Medicine set a goal that "by the year 2020, ninety percent of clinical decisions will be supported by accurate, timely, and up-to-date information, and will reflect the best available evidence. The data-dependent LHS activities (design, implement, evaluate, and adjust) are presented above with a n...

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