Journal
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
Volume 19, Issue E1, Pages E54-E59Publisher
OXFORD UNIV PRESS
DOI: 10.1136/amiajnl-2011-000335
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Funding
- National Library of Medicine [LM007124-11]
- Robert Wood Johnson Foundation
- Huntsman Intermountain Cancer Control Program
- Huntsman Cancer Institute Cancer Center Support grant, from National Cancer Institute [P30 CA42014]
- National Cancer Institute [HHSN 261201000026C]
- Utah Department of Health
- University of Utah
- Division of Genetic Epidemiology in the Department of Biomedical Informatics University of Utah
- VA Informatics and Computing Infrastructure (VINCI), VA HSR HIR [08-204]
- Consortium for Healthcare Informatics Research (CHIR), VA HSR HIR [08-374]
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Objective Electronically linked datasets have become an important part of clinical research. Information from multiple sources can be used to identify comorbid conditions and patient outcomes, measure use of healthcare services, and enrich demographic and clinical variables of interest. Innovative approaches for creating research infrastructure beyond a traditional data system are necessary. Materials and methods Records from a large healthcare system's enterprise data warehouse (EDW) were linked to a statewide population database, and a master subject index was created. The authors evaluate the linkage, along with the impact of missing information in EDW records and the coverage of the population database. The makeup of the EDW and population database provides a subset of cancer records that exist in both resources, which allows a cancer-specific evaluation of the linkage. Results About 3.4 million records (60.8%) in the EDW were linked to the population database with a minimum accuracy of 96.3%. It was estimated that approximately 24.8% of target records were absent from the population database, which enabled the effect of the amount and type of information missing from a record on the linkage to be estimated. However, 99% of the records from the oncology data mart linked; they had fewer missing fields and this correlated positively with the number of patient visits. Discussion and conclusion A general-purpose research infrastructure was created which allows disease-specific cohorts to be identified. The usefulness of creating an index between institutions is that it allows each institution to maintain control and confidentiality of their own information.
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