Statistical methods to harmonize electronic health record data across healthcare systems: case study and lessons learned.
Saved in:
| Title: | Statistical methods to harmonize electronic health record data across healthcare systems: case study and lessons learned. |
|---|---|
| Authors: | Shi X; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, United States., Zhai Y; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, United States., Yu X; Department of Computer Sciences, University of Wisconsin, Madison 53706, United States., Li X; School of Statistics, University of Minnesota, Minneapolis, MN 55455, United States., Hazlehurst BL; Kaiser Permanente Northwest, Center for Health Research, Portland, OR 97227, United States., Nyongesa DB; Kaiser Permanente Northwest, Center for Health Research, Portland, OR 97227, United States., Sapp DS; Kaiser Permanente Northwest, Center for Health Research, Portland, OR 97227, United States., Williamson BD; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, United States., Carrell DS; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, United States.; Division of Biomedical Health Informatics, Department of Biomedical Informatics and Medical Education, University of Washington School of Medicine, Seattle, WA 98195, United States., Healy L; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, United States., Cushing-Haugen KL; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, United States., Wong J; Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, United States., Wang SV; Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Boston, MA 02115, United States., Floyd JS; Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, United States.; Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA 98195, United States.; Cardiovascular Health Research Unit, University of Washington, Seattle, WA 98195, United States., Shattuck K; Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, United States., McGown S; Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, United States., Alam S; Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, United States., Hernández-Muñoz JJ; Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD 20993, United States., Li J; Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD 20993, United States., Ma Y; Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD 20993, United States., Stojanovic D; Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD 20993, United States., Raman SR; Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27710, United States., Davis SE; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, United States., Cai T; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States., Nelson JC; Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, United States., Heagerty PJ; Department of Biostatistics, University of Washington, Seattle, WA 1415 Washington Heights, Ann Arbor, MI 48109, United States. |
| Source: | Bioinformatics (Oxford, England) [Bioinformatics] 2026 Feb 28; Vol. 42 (3). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1367-4811 |
|---|---|
| DOI: | 10.1093/bioinformatics/btag107 |
