Linking Individual Records from Multiple Large Databases; a short History and Practical Solution

1. Linking Individual Records from Multiple Large Databases;a short History and Practical Solution Marlene M. Lugg, DrPH Research Scientist Southern California Kaiser Permanenete Pasadena California

2. Medical Record Linkage; What is it? The process of bringing together two or more records relating to the same entity - person, family, event, hospital. Deterministic – agreement on 1 or more variables; rules based decision tables Probabilistic – mathematical theory developed by Fellegi and Sunter; utilizes software using different weights on each field.

3. Medical Records Evolution- Stone Age - Patient Charts & Manual Logs Industrial Revolution - Simple EDP Electronic Age - Computers

4. Stone Age –Some Early History Paintings and writings on stone (Paleolithic period) no name or ID. Western Australia’s first hospital was a merchant ship grounded off Fremantle. Medical records consisted of one line on admission and one on discharge. Later, more detailed charts kept in doctor’s office, usually filed by patient name.

5. Industrial Revolution I: included simple ADP Separate charts for each hospital admission. Each person had as many charts as he/she had admissions. Terminal digit filing system, along with Patient Index, lead to combining all of a patient’s admissions into one chart. Ambulatory Care data was most often separate unless clinic was part of the hospital.

6. Industrial Revolution II: included mainframe computers 1946 - H. L. Dunn (USA), initial ideas for linking life data. 1950’s - H B Newcombe (Canada) laid probabilistic foundations of modern linkage theory into family groups. 1962 - Oxford Record Linkage Study –Sir Donald Acheson linked birth, morbidity and mortality data for Oxford area.

7. Electronic Age – computerized systems Made probabilistic linkage possible for large databases. (in house, between facilities, local, state-wide, national). Provides advantages of quality control, speed, consistency and reproducibility. Electronic Medical Records can make data available over wide geographic areas.

8. Criteria for Medical Record Linkage for large scale or national linkage I Universality Availability Ease of implementation and maintenance Minimal inconvenience patient and provider Unique Economic Permanent

9. Criteria for Medical Record Linkage for large scale or national linkage II Linkage should be created from personal data readily available and provided by the patient, and No Identity Card or number should be required. “Patient always has the correct linkage number with him/her!”

10. Linkage Problems False linkages Release of confidential information Special populations Immigrants Indigenous populations Character-based languages.

11. Find the Error David L. James, born March 16, 2003 @ West Hospital Ambulatory care visit on May 29, 2004 for 1-year old immunizations. Physician found Medical Record entry that this child had the immunizations 3 weeks previously. Parent denied this. Error? Twins? David L. James, born March 16, 2003 @ West Hospital Born at the same hospital, same day, same name, same gender, but different parents, and was found to be a different child. Different MRN assigned; records divided accordingly

12. Australian National Hospital and Allied Services Advisory Council -1973 Studied ways to create a uniform personal identifier using personal data readily available to the patient and health care provider without recalling a medical record number, or finding a membership card. (HASAC Identifier)

13. HASAC Recommendations 1st 4 digits of last name 1st 2 digits of first name Middle initial Gender Date of Birth

14. HASAC Results 696,000 persons 17 duplicate identifiers Duplicates eliminated with a tie-breaker: Place of Birth

15. Further Use of HASAC Identifier In 1983-4, Australia implemented national health insurance. A statistical algorithm was applied to the HASAC Identifier for privacy, and the new number became the National Health Insurance number.

16. California Child Health Data 2003 CA Health Information for Policy Project’s Interagency Working Party wanted to link children from ten different state and local databases in order to provide continuity of care, and eliminate duplicative care.

17. California Child Health Data 2003 Data sources Birth Certificates Death Certificates State disability files State Welfare Records Public Health Centers Medicaid Programs for uninsured children Hospitals School Records

18. California Child Health Data 2003 Matrix of data from all sources showed all contained Name Date of Birth Gender Modified HASAC number selected Project failed……. Why?

19. California Child Health Data 2003 Politics intervened One of the committee members insisted on using mother’s maiden name as a tie-breaker, instead of place of birth. Committee agreed. Most large heath care organizations did not have mother’s maiden name in their records, and it was too expensive to collect it retrospectively.

20. Immunization Registries Immunization registries play a vital role in Vaccine Safety Monitoring and Studies. State –wide Immunization registries keep a person’s record in one place, regardless of how many provider sites administered the vaccines. Linkage necessary for de-duplication of immunizations and making sure no patient has more than one MRN, nor shares an MRN with another patient.

21. Immunization Registries Data sources

22. In California, The Kaiser Immunization Tracking System (KITS), covers 33% of all California children. The Southern California KITS contains 48 million inoculations from Kaiser facilities and immunization records provided from other sources.

23. Kaiser Permanente -Non-profit group model HMOComprehensive Health Care Southern California For 3.0 million members and 40,000 births/year At 12 hospital/medical centers and 90+ outpatient clinics By over 3,000 providers, including 800+ in pediatric primary care

24. KITS linkage Linkage results: Twenty-six algorithms developed to be run automatically 85% linked with Medical Record Number alone 90.0% linked with MRN, last name, first name, gender, DOB 97.1% linked after first 5 algorithms 99.1% linked after 16 algorithms 99.7% linked after 26 algorithms

25. KITS Linkage Problems Day of birth proved to be more accurate than month 1st name often misspelled Gender listed incorrectly Twins had same first and last names, with only differing middle names etc., etc., etc.

26. Kaiser Permanente Southern California Data Consolidation Current data consolidation method used by Southern California Kaiser Permanente utilizes algorithm using personal data from the membership file, hospital discharges, and ambulatory care clinic data, with a 99% linkage rate. Lists all MRN’s assigned to an individual, rather than correcting them.

27. Uses of Linked Data I Care Examine the health of the public Avoid duplicate treatments Reveal who needs preventive care Continuity of care Generate immunization and disease registers Management Examine the health of the health care system Create health indicators Research

28. Uses of Linked Data II Scottish Health Information System Study of unscheduled care patient pathways. Impact of road safety cameras –linkage of police records to hospital inpatient data. Risk of skin cancer after phototherapy for neonatal jaundice. Can link with census data, which is not possible in some countries.

29. Summary and Advice Probabilistic linkage is excellent but involves more time, money and staff, which may not available. A less involved linkage such as the HASAC method, modified for local needs will often yield excellent results in a cost-effective manner.

30. Acknowledgements: A sincere thank you to all my former staff at the Statistics Branch, Health Department of Western Australia, students and staff at UCLA, and colleagues at Kaiser Permanente, who have spent innumerable hours working together on Medical Record Linkage.