4.4 Article

Comparison of Two VA Laboratory Data Repositories Indicates That Missing Data Vary Despite Originating From the Same Source

期刊

MEDICAL CARE
卷 47, 期 1, 页码 121-124

出版社

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/MLR.0b013e31817d69c2

关键词

laboratory; DSS; ICR; VA

资金

  1. NIAAA [U01-13566]
  2. Veterans Affairs Public Health Strategic Healthcare Group
  3. NATIONAL INSTITUTE ON ALCOHOL ABUSE AND ALCOHOLISM [U01AA013566, U10AA013566] Funding Source: NIH RePORTER

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Background: Assessing accuracy and completeness of data is an important component of conducting research. VA Healthcare System benefits from a highly developed electronic medical information system. The Immunology Case Registry was designed to monitor costs and quality of HIV care. The Decision Support System was developed to monitor utilization and costs of veterans in care. Because these systems extract data from the same source using independent methods, they provide an opportunity to compare the accuracy and completeness of each. Objective: To compare overlapping laboratory data from the Veterans Affairs Health Information System between 2 data repositories. Research Design: For hemoglobin, CD4(+) lymphocyte counts (CD4), HIV RNA viral load, aspartate aminotransferase, alanine aminotransferase, glycosylated hemoglobin, creatinine, and white blood count, we calculated the percent of individuals with a value from each Source. For results in both repositories, we calculated Pearson's correlation coefficients. Subjects: A total of 22,647 HIV+ veterans in the Virtual Cohort with a visit in fiscal year 2002. Results: For 6 out of 9 tests, 68% to 72% of the observations overlapped. For CD4, viral load, and glycosylated hemoglobin less than 31% of observations overlapped. Overlapping results were nearly perfectly correlated except for CD4. Conclusions: Six of the laboratory tests demonstrated remarkably similar amounts of overlap, though Immunology Case Registry and Decision Support System both have missing data. Findings indicate that validation of laboratory data should be conducted before its use in quality and efficiency projects. When 2 databases arc not available for comparison, other methods of validation should be implemented.

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