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Prospects for Care Coordination Measurement Using Electronic Data Sources


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Prospects for Care Coordination Measurement Using Electronic Data Sources



Prospects for Care Coordination Measurement Using Electronic Data Sources


Care coordination has been recognized as a priority area for improving health care delivery in the U.S. Robust measures of care coordination processes will be essential tools to evaluate, guide, and support efforts to understand and improve deficits in care coordination.
This report presents an assessment of the potential for measuring care coordination processes using data from electronic data sources, in particular from existing and emerging health information technology (IT) systems such as electronic health records (EHR), health information exchanges (HIE), and all-payer claims databases (APCD).
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Prepared by: Stanford University Center for Primary Care and Outcomes Research.
Authors:
Kathryn M. McDonald, M.M.
Ellen Schultz, M.S.
Tamara Chapman, M.A.
Sheryl Davies, M.A.
Noelle Pineda, B.A.
Julia Lonhart, B.S., B.A.
Eric Schmidt, B.A
Suzanne Wilson, A.B., M.P.H.
Contract Number:
290-04-0020 (AHRQ SQI-II)

Contents

Executive Summary
Introduction
Challenges of Measuring Care Coordination Using Electronic Data and Recommendations to Address Those Challenges
Key Challenge Area 1: Underutilization of Health IT System Capabilities and Clinical Workflow Barriers
Key Challenge Area 2: Lack of Data Standardization and Limited Health IT System Interoperability
Key Challenge Area 3: Unknown Clinical Data Quality in Electronic Data Sources
Key Challenge Area 4: Limitations in Linking Data
Key Challenge Area 5: Technical Hurdles to Accessing Data
Key Challenge Area 6: Business Models That Facilitate Competition Rather Than Cooperation
Opportunities for Future Measurement of Care Coordination with Electronic Data
Near-term Opportunities
Long-term Opportunities
Summary of Measurement Opportunities
Conclusion
Appendix A: Methods of Seeking Input About the Potential for Measuring Care Coordination Using Electronic Data
Panelist Selection
Conference Calls
Limitations
Appendix B: Group Panel Call Agenda
Appendix C. Glossary and Abbreviations
Appendix D: Additional Sources

Acknowledgements

We thank Jan Genevro, David Meyers and Mamatha Pancholi of the Agency for Healthcare Research and Quality for their support of this work. We wish to thank Sarah Knoop, Bill Cody, John Timm and Daniel Gruhl for providing background into the health IT field and standards and Ben Wilson and Oanh Nguyen for their insight and review of draft materials. Finally, we gratefully acknowledge all those who participated in our expert panel: Hunt Blair, Carmella Bocchino, Keri Christensen, Joanne Cuny, Aaron Cutshall, Floyd Eisenberg, J. Michael Fitzmaurice, Valerie Fong, Craig Jones, Melanie Mastanduno, Patrick Miller, Jon Morrow, Wilson Pace, L. Greg Pawlson, Fred Rachman, Elizabeth Schofield, Claudia Steiner, Paul Tang and Charlene Underwood. While our panelists and reviewers are not responsible for the contents of this report, their knowledge and insight has helped inform and strengthen our work.
AHRQ Publication No. 12-0014-EF
Current as of March 2012

Internet Citation:
McDonald KM, Schultz E, Chapman T, Davies S, Pineda N, Lonhart J, Schmidt E, Wilson AB. Prospects for Care Coordination Measurement Using Electronic Data Sources. AHRQ Publication No. 12-0014-EF, March 2012. Prepared by Stanford University under subcontract to Battelle on Contract No. 290-04-0020 (AHRQ SQI-II). Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/qual/prospectscare/index.html


Prospects for Care Coordination Measurement Using Electronic Data Sources

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