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Browsing by Author "Li, Xinli"
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Item Does Inclusion of Stroke Severity in a 30-day Mortality Model Change Standardized Mortality Rates at VA Hospitals?(2012-07) Keyhani, Salomeh; Cheng, Eric M.; Arling, Greg; Li, Xinli; Myers, Laura J.; Ofner, Susan; Williams, Linda S.; Phipps, Michael S.; Ordin, Diana L.; Bravata, Dawn M.Background—The Centers for Medicare and Medicaid Services is considering developing a 30-day ischemic stroke hospital-level mortality model using administrative data. We examined whether inclusion of the National Institutes of Health Stroke Scale (NIHSS), a measure of stroke severity not included in administrative data, would alter 30-day mortality rates in the Veterans Health Administration. Methods and Results—A total of 2562 veterans admitted with ischemic stroke to 64 Veterans Health Administration Hospitals in the fiscal year 2007 were included. First, we examined the distribution of unadjusted mortality rates across the Veterans Health Administration. Second, we estimated 30-day all-cause, risk standardized mortality rates (RSMRs) for each hospital by adjusting for age, sex, and comorbid conditions using hierarchical models with and without the inclusion of the NIHSS. Finally, we examined whether adjustment for the NIHSS significantly changed RSMRs for each hospital compared with other hospitals. The median unadjusted mortality rate was 3.6%. The RSMR interquartile range without the NIHSS ranged from 5.1% to 5.6%. Adjustment with the NIHSS did not change the RSMR interquartile range (5.1%–5.6%). Among veterans ≥65 years, the RSMR interquartile range without the NIHSS ranged from 9.2% to 10.3%. With adjustment for the NIHSS, the RSMR interquartile range changed from 9.4% to 10.0%. The plot of 30-day RSMRs estimated with and without the inclusion of the NIHSS in the model demonstrated overlapping 95% confidence intervals across all hospitals, with no hospital significantly below or above the mean-unadjusted 30-day mortality rate. The 30-day mortality measure did not discriminate well among hospitals. Conclusions—The impact of the NIHSS on RSMRs was limited. The small number of stroke admissions and the narrow range of 30-day stroke mortality rates at the facility level in the Veterans Health Administration cast doubt on the value of using 30-day RSMRs as a means of identifying outlier hospitals based on their stroke care quality.Item Inpatient stroke care quality for Veterans: Are there differences between VA medical centers in the stroke belt and other areas?(Wiley, 2015-01) Jia, Huanguang; Phipps, Michael S.; Bravata, Dawn M.; Castro, Jaime; Li, Xinli; Ordin, Diana L.; Myers, Jennifer; Vogel, W. Bruce; Williams, Linda S.; Chumbler, Neale R.; Department of Medicine, IU School of MedicineBackground Stroke mortality has been found to be much higher among residents in the stroke belt region than in the rest of United States, but it is not known whether differences exist in the quality of stroke care provided in Department of Veterans Affairs medical centers in states inside and outside this region. Objective We compared mortality and inpatient stroke care quality between Veterans Affairs medical centers inside and outside the stroke belt region. Methods Study patients were veterans hospitalized for ischemic stroke at 129 Veterans Affairs medical centers. Inpatient stroke care quality was assessed by 14 quality indicators. Multivariable logistic regression models were fit to examine differences in quality between facilities inside and outside the stroke belt, adjusting for patient characteristics and Veterans Affairs medical centers clustering effect. Results Among the 3909 patients, 28·1% received inpatient ischemic stroke care in 28 stroke belt Veterans Affairs medical centers, and 71·9% obtained care in 101 non-stroke belt Veterans Affairs medical centers. Patients cared for in stroke belt Veterans Affairs medical centers were more likely to be younger, Black, married, have a higher stroke severity, and less likely to be ambulatory pre-stroke. We found no statistically significant differences in short- and long-term post-admission mortality and inpatient care quality indicators between the patients cared for in stroke belt and non-stroke belt Veterans Affairs medical centers after risk adjustment. Conclusions These data suggest that a stroke belt does not exist within the Veterans Affairs health care system in terms of either post-admission mortality or inpatient care quality.Item Postdischarge quality of care: Do age disparities exist among Department of Veterans Affairs ischemic stroke patients?(2013) Chumbler, Neale R.; Jia, Huanguang; Phipps, Michael S.; Li, Xinli; Ordin, Diana L.; Williams, Linda S.; Myers, Laura J.This study examined whether age disparities existed across postdischarge quality indicators (QIs) for veterans with ischemic stroke who received care at Department of Veterans Affairs medical centers (VAMCs). This retrospective cohort included a national sample of 3,196 veterans who were diagnosed with ischemic stroke and received acute and postdischarge stroke care at 127 VAMCs in fiscal year 2007 (10/1/06 through 9/30/07). Data included an assessment of postdischarge stroke QIs in the outpatient setting during the 6 mo postdischarge. The QIs included measurement of and goal achievement for (1) blood pressure, (2) serum international normalized ratio (INR) for all patients discharged on warfarin, (3) cholesterol (low-density lipoprotein [LDL]) levels, (4) serum glycosylated hemoglobin, and (5) depression treatment. The mean age for the 3,196 veterans included in this study was 67.2 +/– 11.3 yr. Before risk adjustment, there were age differences in (1) depression screening/treatment, (2) blood pressure goals, and (3) LDL levels. After we adjusted for patient sociodemographic, clinical, and facility-level characteristics by using hierarchical linear mixed modeling, none of these differences remained significant but INR goals for patients discharged on warfarin differed significantly by age. After we adjusted for patient and facility characteristics, fewer age differences were found in the postdischarge stroke QIs. Clinical trial registration was not required.Item Rural-Urban Differences in Inpatient Quality of Care in US Veterans With Ischemic Stroke(2014-06) Phipps, Michael S.; Jia, Huanguang; Chumbler, Neale R.; Li, Xinli; Castro, Jaime G; Myers, Jennifer; Williams, Linda S.; Bravata, Dawn M.Purpose Differences in stroke care quality for patients in rural and urban locations have been suggested, but whether differences exist across Veteran Administration Medical Centers (VAMCs) is unknown. This study examines whether rural-urban disparities exist in inpatient quality among veterans with acute ischemic stroke. Methods In this retrospective study, inpatient stroke care quality was assessed in a national sample of veterans with acute ischemic stroke using 14 quality indicators (QIs). Rural-Urban Commuting Areas codes defined each VAMC's rural-urban status. A hierarchical linear model assessed the rural-urban differences across the 14 QIs, adjusting for patient and facility characteristics, and clustering within VAMCs. Findings Among 128 VAMCs, 18 (14.1%) were classified as rural VAMCs and admitted 284 (7.3%) of the 3,889 ischemic stroke patients. Rural VAMCs had statistically significantly lower unadjusted rates on 6 QIs: Deep vein thrombosis (DVT) prophylaxis, antithrombotic at discharge, antithrombotic at day 2, lipid management, smoking cessation counseling, and National Institutes of Health Stroke Scale completion, but they had higher rates of stroke education, functional assessment, and fall risk assessment. After adjustment, differences in 2 QIs remained significant—patients treated in rural VAMCs were less likely to receive DVT prophylaxis, but more likely to have documented functional assessment. Conclusions After adjustment for key demographic, clinical, and facility-level characteristics, there does not appear to be a systematic difference in inpatient stroke quality between rural and urban VAMCs. Future research should seek to understand the few differences in care found that could serve as targets for future quality improvement interventions.