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Evolving availability and standardization of patient attributes for matching.
Deng, Yu; Gleason, Lacey P; Culbertson, Adam; Chen, Xiaotian; Bernstam, Elmer V; Cullen, Theresa; Gouripeddi, Ramkiran; Harle, Christopher; Hesse, David F; Kean, Jacob; Lee, John; Magoc, Tanja; Meeker, Daniella; Ong, Toan; Pathak, Jyotishman; Rosenman, Marc; Rusie, Laura K; Shah, Akash J; Shi, Lizheng; Thomas, Aaron; Trick, William E; Grannis, Shaun; Kho, Abel.
Affiliation
  • Deng Y; Center for Health Information Partnerships, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States.
  • Gleason LP; Center for Health Information Partnerships, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States.
  • Culbertson A; Center for Health Information Partnerships, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States.
  • Chen X; Statistical Innovation Group, Data and Statistical Sciences, AbbVie, Inc, North Chicago, IL 60064, United States.
  • Bernstam EV; School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, United States.
  • Cullen T; Division of General Internal Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, United States.
  • Gouripeddi R; Pima County Health Department, Tucson, AZ 85714, United States.
  • Harle C; Clinical and Translational Science Institute and Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States.
  • Hesse DF; Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN 46202, United States.
  • Kean J; Regenstrief Institute Center for Biomedical Informatics, Indianapolis, IN 46202, United States.
  • Lee J; Hesse Foot and Ankle Clinic, SC, Eau Claire, WI 54751, United States.
  • Magoc T; VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System and University of Utah, Salt Lake City, UT 84148, United States.
  • Meeker D; Edward Hospital, Naperville, IL 60540, United States.
  • Ong T; Integrated Data Repository Research Services, Clinical and Translational Science Institute, University of Florida, Gainesville, FL 32609, United States.
  • Pathak J; Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT 06510, United States.
  • Rosenman M; Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, United States.
  • Rusie LK; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, United States.
  • Shah AJ; Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL 60611, United States.
  • Shi L; Howard Brown Health, Chicago, IL 60640, United States.
  • Thomas A; Nuvance Health, Danbury, CT 06810, United States.
  • Trick WE; Department of Health Policy and Management, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, United States.
  • Grannis S; North Carolina Translational and Clinical Sciences Institute, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
  • Kho A; Center for Health Equity & Innovation, Cook County Health, Chicago, IL 60612, United States.
Health Aff Sch ; 1(4): qxad047, 2023 Oct.
Article in En | MEDLINE | ID: mdl-38756741
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Health Aff Sch Year: 2023 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Health Aff Sch Year: 2023 Document type: Article Affiliation country: Country of publication: