Hospital Use and Survival among Veterans Affairs Beneficiaries
ABSTRACT Initiatives to reduce hospital care were part of the reorganization of the Department of Veterans Affairs (VA) medical care system undertaken in the mid-1990s. We examined changes in the use of VA health services and survival from 1994 through 1998 among VA beneficiaries with serious chronic diseases. We postulated that if access to hospital care was reduced too much, or if decreased hospital use was not offset by improvements in ambulatory care, urgent care visits would increase or survival rates would fall.
We tracked changes in risk-adjusted VA bed-day rates, rates of medical visits, rates of visits for testing and consultation, and rates of urgent care visits per patient-year among VA beneficiaries in nine disease cohorts (a total of 342,300 beneficiaries). Trends in non-VA hospital use by VA beneficiaries 65 years of age or older who were enrolled in fee-for-service Medicare were also studied. VA and Medicare vital-status data were used to calculate one-year survival rates.
From 1994 through 1998, VA bed-day rates fell by 50 percent, rates of medical-clinic visits and visits for testing and consultation increased moderately, and rates of urgent care visits fell by 35 percent. The sharp decline in the use of VA hospitals was not compensated for by increases in the use of Medicare-reimbursed non-VA hospital care by veterans eligible for both VA care and Medicare, and the use of non-VA hospitals actually declined in four cohorts. The survival rates were essentially unchanged over the study period.
The marked decline in VA hospital use from 1994 through 1998 did not curtail access to needed services and was not associated with serious consequences for chronically ill VA beneficiaries.
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- "OEF/OIF Roster data through 9/30/09 were linked to VA clinical data contained in the VA National Patient Care Database (NPCD) through 1/1/10. The VA electronic medical record has been used extensively for research (Ashton et al., 2003; Boyko et al., 2000) and includes the date of the clinic visit and associated diagnosis(es) designated using International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) codes. 2.3. "
ABSTRACT: The prevalence and correlates of alcohol use disorder (AUD) and drug use disorder (DUD) diagnoses in Iraq and Afghanistan veterans who are new users of Department of Veterans Affairs (VA) healthcare nationwide has not been evaluated. VA administrative data were used in retrospective cross-sectional descriptive and multivariable analyses to determine the prevalence and independent correlates of AUD and DUD in 456,502 Iraq and Afghanistan veterans who were first-time users of VA healthcare between October 15, 2001 and September 30, 2009 and followed through January 1, 2010. Over 11% received substance use disorder diagnoses: AUD, DUD or both; 10% received AUD diagnoses, 5% received DUD diagnoses and 3% received both. Male sex, age < 25 years, being never married or divorced, and proxies for greater combat exposure were independently associated with AUD and DUD diagnoses. Of those with AUD, DUD or both diagnoses, 55-75% also received PTSD or depression diagnoses. AUD, DUD or both diagnoses were 3-4.5 times more likely in veterans with PTSD and depression (p < 0.001). Post-deployment AUD and DUD diagnoses were more prevalent in subgroups of Iraq and Afghanistan veterans and were highly comorbid with PTSD and depression. Stigma and lack of universal screening may have reduced the number of DUD diagnoses reported. There is a need for improved screening and diagnosis of substance use disorders and increased availability of integrated treatments that simultaneously address AUD and DUD in the context of PTSD and other deployment-related mental health disorders.Drug and alcohol dependence 07/2011; 116(1-3):93-101. DOI:10.1016/j.drugalcdep.2010.11.027 · 3.28 Impact Factor
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- "Length of stay can also measure the ability of physicians to process administrative tasks such as scheduling a series of treatments. The VA strove to decrease length of stays in the mid-1990s by decentralizing power to geographic regions, changing ambulatory care benefits and creating incentives that reward medical center directors for shorter lengths of stay (Ashton et al., 2003). These policy changes would have been uniformly applicable to both Programs A and B, although we can test for differences in the response to these initiatives. "
ABSTRACT: Physicians play a major role in determining the cost and quality of healthcare, yet estimates of these effects can be confounded by patient sorting. This paper considers a natural experiment where nearly 30,000 patients were randomly assigned to clinical teams from one of two academic institutions. One institution is among the top medical schools in the U.S., while the other institution is ranked lower in the distribution. Patients treated by the two programs have similar observable characteristics and have access to a single set of facilities and ancillary staff. Those treated by physicians from the higher ranked institution have 10-25% less expensive stays than patients assigned to the lower ranked institution. Health outcomes are not related to the physician team assignment. Cost differences are most pronounced for serious conditions, and they largely stem from diagnostic-testing rates: the lower ranked program tends to order more tests and takes longer to order them.Journal of Health Economics 12/2010; 29(6):866-82. DOI:10.1016/j.jhealeco.2010.08.004 · 2.25 Impact Factor
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- "Longer stays represent greater time for supervision and additional care. The VA strove to decrease length of stays in the mid-1990's by decentralizing power to geographic regions, changing ambulatory care benefits and creating incentives that reward medical center directors for shorter lengths of stay (Ashton et al., 2003). These policy changes would have been uniformly applicable to both Programs A and B, although we can test for differences in the response to these initiatives. "
ABSTRACT: Patient sorting can confound estimates of the returns to physician human capital. This paper compares nearly 30,000 patients who were randomly assigned to clinical teams from one of two academic institutions. One institution is among the top medical schools in the country, while the other institution is ranked lower in the quality distribution. Patients treated by the two teams have identical observable characteristics and have access to a single set of facilities and ancillary staff. Those treated by physicians from the higher-ranked institution have 10-25% shorter and less expensive stays than patients assigned to the lower-ranked institution. Health outcomes are not related to the physician team assignment, and the estimates are precise. Procedure differences across the teams are consistent with the ability of physicians in the lower-ranked institution to substitute time and diagnostic tests for the faster judgments of physicians from the top-ranked institution.