Geographic Information Systems (GIS) can create, access, integrate, and display geographically relevant information. Moreover, GIS can be used to examine population-level effects of services as reflected in geographic and spatial distribution of populations and allows predictive modeling. It can also associate, for example, patients with the nearest medical facility or provider, locate under-served areas, measure access to care (distance) to medical facilities in a VISN, and many other analyses relevant to VA. GIS has been used in the health care industry for epidemiological studies, disease tracking, program evaluation, epidemic outbreak investigations, site location and patient distribution analysis, and community needs assessment.
The VA Health Care Atlas FY-2000 includes: (1) the number and location of the total veteran population by VISN, state and county; 2) the number and location of the VHA enrollee population, as well as the percentage of the veteran population enrolled in the VA health care system; 3) an overview and location of medical facilities in the VA health care system; (4) an examination of overall VA utilization; and(5) a depiction of patterns in health care use across the VA by the QUERI patient cohorts
The data that the research team used to compile the VA Health Care Atlas 2000 reside in VA’s 97 corporate data systems and/or at numerous field units throughout the VA. Veteran population data were obtained from the US Census Bureau. While no primary data collection was needed, identifying where the data reside and creating SAS programs or SQL queries to extract information from the databases entailed considerable time and effort. The investigators performed secondary data extractions, then displayed existing data in a new, more comprehensive and accessible format. The research team relied heavily on Geographic Information System (GIS) tools to create the VA Health Care Atlas, FY-2000.
For the QUERI cohorts, we used all the diagnostic codes in the inpatient and outpatient files to identify patients with each condition. For some conditions, one or two diagnostic codes were sufficient to classify a patient. For others, a number of diagnoses were required. All patients who had a means test classification other than "non-veteran" on the last episode of care (outpatient visit or inpatient admission) in the VA health care system in FY-2000 were included in the cohort. Demographic characteristics of the cohort were determined as follows. Means test status and marital status were based on the values recorded on the last episode of care in FY-2000.
The VA Health Care Atlas displays data on the veteran population, enrollee and patient populations in tabular and graphical form. The maps portray the amount and magnitude of geographic variation among VA’s patient population in terms of the number of veterans and the extent of the health care utilization. Drilling down to the county-level and graphically depicting the data raises questions as to why certain patterns occur and provides an impetus for further research investigations.
The overall research plan for this study was to organize information about the veteran population, enrollee population, and patient population in the form of a resource guide. To carry out this plan, we first had to identify what types of information would be useful to VA researchers. To this end, we compiled questions that were received by the VIReC Help Desk during its first two and a half years of operation. These inquiries were categorized and the research team developed the outline for the 14 chapters that are contained in the Atlas. The data sources to provide information were identified and data were extracted and reported in tabular and/or map format. Special attention was paid to providing sources where investigators or interested parties could find additional information on a particular topic.
External Links for this Project
HSR&D or QUERI Publications
- Cowper D, Yu W, Kuebeler M, Kubal JD, Manheim LM, Ripley BA. Using GIS in government: an overview of the VHA's Healthcare Atlas, FY-2000. Journal of medical systems. 2004 Jun 1; 28(3):257-69. [view]
- Yu W, Cowper D, Berger M, Kuebeler M, Kubal J, Manheim L. Using GIS to profile health-care costs of VA Quality-Enhancement Research Initiative diseases. Journal of medical systems. 2004 Jun 1; 28(3):271-85. [view]
- Cowper DC, Kubal JD, Kuebeler MK, Manheim LM, Ripley BA. VA Health Care Atlas FY 2000. 2005 May 6. [view]
- Cowper DC, Yu W, Kubal JD, Manheim LM. Creating a VA Health Care Atlas. Paper presented at: VA HSR&D National Meeting; 2003 Mar 13; Washington, DC. [view]
- Yu M, Cowper DC, Berger M, Kuebeler MK, Kubal JD, Manheim LM. Geographic Differences in VA QUERI Diseases. Paper presented at: VA HSR&D National Meeting; 2004 Mar 9; Washington, DC. [view]
- Cowper DC. GIS Tools for QUERI. Paper presented at: VA QUERI National Meeting; 2001 Dec 12; Orlando, FL. [view]
- Cowper DC, Yu W, Kubal JD, Manheim LM. Methods for Creating a VA Health Care Atlas. Paper presented at: VA HSR&D National Meeting; 2003 Feb 14; Washington, DC. [view]
- Cowper DC, Yu W, Kuebeler MK, Manheim LM, Kubal JD, Ripley BA. The VA Health Care Atlas FY-2000. Paper presented at: VA HSR&D National Meeting; 2004 Mar 11; Washington, DC. [view]
- Yu W, Cowper D, Berger M, Kuebeler M, Kubal J, Manheim L. Using GIS to Profile Healthcare Costs of VA Quality-Enhancement Research Initiative Diseases. Paper presented at: VA HSR&D National Meeting; 2004 Mar 1; Washington, DC. [view]
- Cowper DC, Ripley BA, Kuebeler MK, Yu W, Kubal JD, Manheim LM. VA Health Care Atlas, FY-2000. Presented at: VA Leadership Board Annual Meeting; 2003 Mar 13; Washington, DC. [view]
Treatment - Observational
Quality assessment, Quality assurance, improvement
Chronic Disease, Treatment Outcome, Geography, Utilization