Journal of rehabilitation research and development
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The Medicare Current Beneficiary Survey (MCBS) is a longitudinal, multipurpose panel survey of a nationally representative sample of Medicare beneficiaries sponsored by the Centers for Medicare and Medicaid Services (CMS). The MCBS serves as a comprehensive data source on self-reported health and socioeconomic status, health insurance, healthcare utilization and costs, and patient satisfaction. CMS uses Medicare claims data to validate self-reported Medicare Fee-For-Service (FFS) utilization. ⋯ Since reliable VHA utilization and cost data existed in either FY1998 or FY1999 onward, study goals include estimating the relative share and/or cost of care provided by Medicare and the VHA. Researchers with access to VHA datasets should consider merging them into the MCBS and replacing self-reported utilization and CMS's imputed costs with VHA administrative data. This replacement would significantly improve the accuracy, quality, and usefulness of the MCBS dataset for policy research.
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Comparative Study
Brief report: Comparison of methods to identify Iraq and Afghanistan war veterans using Department of Veterans Affairs administrative data.
The Department of Veterans Affairs (VA) has made treatment and care of Operation Iraqi Freedom/Operation Enduring Freedom (OIF/OEF) veterans a priority. Researchers face challenges identifying the OIF/OEF population because until fiscal year 2008, no indicator of OIF/OEF service was present in the Veterans Health Administration (VHA) administrative databases typically used for research. In this article, we compare an algorithm we developed to identify OIF/OEF veterans using the Austin Information Technology Center administrative data with the VHA Support Service Center OIF/OEF Roster and veterans' self-report of military service. ⋯ However, this method of identifying OIF/OEF veterans failed to identify a large proportion of OIF/OEF veterans listed in the VHA Support Service Center OIF/OEF Roster. Demographic, diagnostic, and VA service use differences were found between veterans identified using our method and those we failed to identify but who were in the VHA Support Service Center OIF/OEF Roster. Therefore, depending on the research objective, this method may not be a viable alternative to the VHA Support Service Center OIF/OEF Roster for identifying OIF/OEF veterans.
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Within the Veterans Health Administration (VHA), anthropometric measurements entered into the electronic medical record are stored in local information systems, the national Corporate Data Warehouse (CDW), and in some regional data warehouses. This article describes efforts to examine the quality of weight and height data within the CDW and to compare CDW data with data from warehouses maintained by several of VHA's regional groupings of healthcare facilities (Veterans Integrated Service Networks [VISNs]). We found significantly fewer recorded heights than weights in both the CDW and VISN data sources. ⋯ Implausible variation in same-day and same-year heights and weights was noted, suggesting measurement or data-entry errors. Our work suggests that the CDW, over time and through validation, has become a generally reliable source of anthropometric data. Researchers should assess the reliability of data contained within any source and apply strategies to minimize the impact of data errors appropriate to their study population.
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The Department of Veterans Affairs (VA) provides integrated services to more than 25,000 veterans with spinal cord injuries and disorders (SCI/D). VA data offer great potential for providing insights into healthcare utilization and morbidity, and these capabilities are central to efforts to improve healthcare for veterans with SCI/D. The objective of this article is to introduce researchers to the use of VA data to examine questions related to SCI/D using examples from Spinal Cord Injury (SCI) Quality Enhancement Research Initiative studies. ⋯ Methods used to identify veterans with SCI/D include the Allocation Resource Center cohort, the Spinal Cord Dysfunction (SCD) Registry, and the VA inpatient SCI flag; only 33% of veterans were included in all three groups (n = 12,306). While neurological level of SCI was unknown for approximately a third of veterans (from SCD Registry data alone), the percent decreased to 13% when augmented with diagnostic codes. Primary data can be used to augment other missing SCI data and to provide more detailed information about complications commonly associated with SCI/D.
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We evaluated the improvement in Department of Veterans Affairs (VA) race data completeness that could be achieved by linking VA data with data from Medicare and the Department of Defense (DOD) and examined agreement in values across the data sources. After linking VA with Medicare and DOD records for a 10% sample of VA patients, we calculated the percentage for which race could be identified in those sources. To evaluate race agreement, we calculated sensitivities, specificities, positive predictive values (PPVs), negative predictive values, and kappa statistics. ⋯ Kappa statistics reflected these patterns. Supplementing VA with Medicare and DOD data improves VA race data completeness substantially. More study is needed to understand poor rates of agreement between VA and external sources in identifying non-African-American minority individuals.