Relationship between clinical conditions and use of Veterans Affairs health care among Medicare-enrolled veterans.

OBJECTIVE: To determine how reliance on Veterans Affairs (VA) for medical care among veterans enrolled in Medicare is affected by medical conditions, access, and patient characteristics. DATA SOURCES/STUDY SETTING: Department of Veterans Affairs. STUDY DESIGN: We examined reliance on the VA for inpatient, outpatient, and overall medical care among all VA users in fiscal years 2003 and 2004 who were also enrolled in Medicare. We calculated the marginal effects of patient factors on VA reliance using fractional logistic regression; we also analyzed overall VA reliance separately for under-65 and age-65+ groups. The primary focus of this analysis was the relationship between aggregated condition categories (ACCs), which represent medical conditions, and reliance on the VA. PRINCIPAL FINDINGS: Mean VA reliance was significantly higher in the under-65 population than in the age-65+ group (0.800 versus 0.531). Lower differential distance to the VA, and higher VA-determined priority for health care, predicted higher VA reliance. Most individual ACCs were negatively associated with VA reliance, though substance abuse and mental health disorders were significantly associated with increased reliance on VA care. Conditions of the eyes and ears/nose/throat had positive marginal effect on VA reliance for the under 65, while diabetes was positive for age 65+. Among inpatients, veterans with ACCs for mental health conditions, eye conditions, amputations, or infectious and parasitic conditions had higher likelihood of a VA hospitalization than inpatients without these conditions. CONCLUSIONS: Many dually enrolled Veterans use both Medicare and VA health care. Age, accessibility, and priority level for VA services have a clear relationship with VA reliance. Because dual use is common, coordination of care among health care settings for such patients should be a policy priority.

Method to develop health care peer groups for quality and financial comparisons across hospitals.

OBJECTIVE: To develop and explore the characteristics of a novel "nearest neighbor" methodology for creating peer groups for health care facilities. DATA SOURCES: Data were obtained from the Department of Veterans Affairs (VA) databases. STATISTICAL METHODS AND FINDINGS: Peer groups are developed by first calculating the multidimensional Euclidean distance between each of 133 VA medical centers based on 16 facility characteristics. Each medical center then serves as the center for its own peer group, and the nearest neighbor facilities in terms of Euclidean distance comprise the peer facilities. We explore the attributes and characteristics of the nearest neighbor peer groupings. In addition, we construct standard cluster analysis-derived peer groups and compare the characteristics of groupings from the two methodologies. CONCLUSIONS: The novel peer group methodology presented here results in groups where each medical center is at the center of its own peer group. Possible advantages over other peer group methodologies are that facilities are never on the "edge" of a group and group size-and thus group dispersion-is determined by the researcher. Peer groups with these characteristics may be more appealing to some researchers and administrators than standard cluster analysis and may thus strengthen organizational buy-in for financial and quality comparisons.