Evolving availability and standardization of patient attributes for matching

Author:

Deng Yu1,Gleason Lacey P1ORCID,Culbertson Adam1,Chen Xiaotian2ORCID,Bernstam Elmer V34ORCID,Cullen Theresa5ORCID,Gouripeddi Ramkiran6ORCID,Harle Christopher78ORCID,Hesse David F9,Kean Jacob10ORCID,Lee John11ORCID,Magoc Tanja12ORCID,Meeker Daniella13ORCID,Ong Toan14,Pathak Jyotishman15,Rosenman Marc16ORCID,Rusie Laura K17ORCID,Shah Akash J18ORCID,Shi Lizheng19ORCID,Thomas Aaron20ORCID,Trick William E21ORCID,Grannis Shaun8,Kho Abel1ORCID

Affiliation:

1. Center for Health Information Partnerships, Feinberg School of Medicine, Northwestern University , Chicago, IL 60611 , United States

2. Statistical Innovation Group, Data and Statistical Sciences, AbbVie, Inc , North Chicago, IL 60064 , United States

3. School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, United States

4. Division of General Internal Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston , Houston, TX 77030 , United States

5. Pima County Health Department, Tucson, AZ 85714, United States

6. Clinical and Translational Science Institute and Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States

7. Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN 46202, United States

8. Regenstrief Institute Center for Biomedical Informatics, Indianapolis, IN 46202, United States

9. Hesse Foot and Ankle Clinic, SC, Eau Claire, WI 54751, United States

10. VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System and University of Utah, Salt Lake City, UT 84148, United States

11. Edward Hospital , Naperville, IL 60540 , United States

12. Integrated Data Repository Research Services, Clinical and Translational Science Institute, University of Florida, Gainesville, FL 32609, United States

13. Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT 06510, United States

14. Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, United States

15. Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, United States

16. Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL 60611, United States

17. Howard Brown Health, Chicago, IL 60640, United States

18. Nuvance Health, Danbury, CT 06810, United States

19. Department of Health Policy and Management, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, United States

20. North Carolina Translational and Clinical Sciences Institute, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States

21. Center for Health Equity & Innovation, Cook County Health, Chicago, IL 60612, United States

Abstract

Abstract Variation in availability, format, and standardization of patient attributes across health care organizations impacts patient-matching performance. We report on the changing nature of patient-matching features available from 2010–2020 across diverse care settings. We asked 38 health care provider organizations about their current patient attribute data-collection practices. All sites collected name, date of birth (DOB), address, and phone number. Name, DOB, current address, social security number (SSN), sex, and phone number were most commonly used for cross-provider patient matching. Electronic health record queries for a subset of 20 participating sites revealed that DOB, first name, last name, city, and postal codes were highly available (>90%) across health care organizations and time. SSN declined slightly in the last years of the study period. Birth sex, gender identity, language, country full name, country abbreviation, health insurance number, ethnicity, cell phone number, email address, and weight increased over 50% from 2010 to 2020. Understanding the wide variation in available patient attributes across care settings in the United States can guide selection and standardization efforts for improved patient matching in the United States.

Funder

National Center for Advancing Translational Sciences

Publisher

Oxford University Press (OUP)

Reference18 articles.

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