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      Short-Term Medical Costs of a VHA Health Information Exchange: A CHEERS-Compliant Article

      research-article
      , PhD, , PhD, , PhD, , PhD, , MD, , PharmD, , MD, MAS
      Medicine
      Wolters Kluwer Health

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          Abstract

          The Virtual Lifetime Electronic Record (VLER) Health program provides the Veterans Health Administration (VHA) a framework whereby VHA providers can access the veterans’ electronic health record information to coordinate healthcare across multiple sites of care. As an early adopter of VLER, the Indianapolis VHA and Regenstrief Institute implemented a regional demonstration program involving bi-directional health information exchange (HIE) between VHA and non-VHA providers.

          The aim of the study is to determine whether implementation of VLER HIE reduces 1 year VHA medical costs.

          A cohort evaluation with a concurrent control group compared VHA healthcare costs using propensity score adjustment. A CHEERs compliant checklist was used to conduct the cost evaluation.

          Patients were enrolled in the VLER program onsite at the Indianapolis VHA in outpatient clinics or through the release-of-information office.

          VHA cost data (in 2014 dollars) were obtained for both enrolled and nonenrolled (control) patients for 1 year prior to, and 1 year after, the index date of patient enrollment.

          There were 6104 patients enrolled in VLER and 45,700 patients in the control group. The annual adjusted total cost difference per patient was associated with a higher cost for VLER enrollees $1152 (95% CI: $807–1433) ( P < 0.01) (in 2014 dollars) than VLER nonenrollees.

          Short-term evaluation of this demonstration project did not show immediate reductions in healthcare cost as might be expected if HIE decreased redundant medical tests and treatments. Cost reductions from shared health information may be realized with longer time horizons.

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          Most cited references14

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          Too much ado about two-part models and transformation? Comparing methods of modeling Medicare expenditures.

          Many methods for modeling skewed health care cost and use data have been suggested in the literature. This paper compares the performance of eight alternative estimators, including OLS and GLM estimators and one- and two-part models, in predicting Medicare costs. It finds that four of the alternatives produce very similar results in practice. It then suggests an efficient method for researchers to use when selecting estimators of health care costs. Copyright 2004 Elsevier B.V.
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            The risks of risk adjustment.

            Risk adjustment is essential before comparing patient outcomes across hospitals. Hospital report cards around the country use different risk adjustment methods. To examine the history and current practices of risk adjusting hospital death rates and consider the implications for using risk-adjusted mortality comparisons to assess quality. This article examines severity measures used in states and regions to produce comparisons of risk-adjusted hospital death rates. Detailed results are presented from a study comparing current commercial severity measures using a single database. It included adults admitted for acute myocardial infarction (n=11880), coronary artery bypass graft surgery (n=7765), pneumonia (n=18016), and stroke (n=9407). Logistic regressions within each condition predicted in-hospital death using severity scores. Odds ratios for in-hospital death were compared across pairs of severity measures. For each hospital, z scores compared actual and expected death rates. The severity measure called Disease Staging had the highest c statistic (which measures how well a severity measure discriminates between patients who lived and those who died) for acute myocardial infarction, 0.86; the measure called All Patient Refined Diagnosis Related Groups had the highest for coronary artery bypass graft surgery, 0.83; and the measure, MedisGroups, had the highest for pneumonia, 0.85 and stroke, 0.87. Different severity measures predicted different probabilities of death for many patients. Severity measures frequently disagreed about which hospitals had particularly low or high z scores. Agreement in identifying low- and high-mortality hospitals between severity-adjusted and unadjusted death rates was often better than agreement between severity measures. Severity does not explain differences in death rates across hospitals. Different severity measures frequently produce different impressions about relative hospital performance. Severity-adjusted mortality rates alone are unlikely to isolate quality differences across hospitals.
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              Improving the management of chronic disease at community health centers.

              The Health Disparities Collaboratives of the Health Resources and Services Administration (HRSA) were designed to improve care in community health centers, where many patients from ethnic and racial minority groups and uninsured patients receive treatment. We performed a controlled preintervention and postintervention study of community health centers participating in quality-improvement collaboratives (the Health Disparities Collaboratives sponsored by the HRSA) for the care of patients with diabetes, asthma, or hypertension. We enrolled 9658 patients at 44 intervention centers that had participated in the collaboratives and 20 centers that had not participated (external control centers). Each intervention center also served as an internal control for another condition. Quality measures were abstracted from medical records at each health center. We created overall quality scores by standardizing and averaging the scores from all of the applicable measures. Changes in quality were evaluated with the use of hierarchical regression models that controlled for patient characteristics. Overall, the intervention centers had considerably greater improvement than the external and internal control centers in the composite measures of quality for the care of patients with asthma and diabetes, but not for those with hypertension. As compared with the external control centers, the intervention centers had significant improvements in the measures of prevention and screening, including a 21% increase in foot examinations for patients with diabetes, and in disease treatment and monitoring, including a 14% increase in the use of antiinflammatory medication for asthma and a 16% increase in the assessment of glycated hemoglobin. There was no improvement, however, in any of the intermediate outcomes assessed (urgent care or hospitalization for asthma, control of glycated hemoglobin levels for diabetes, and control of blood pressure for hypertension). The Health Disparities Collaboratives significantly improved the processes of care for two of the three conditions studied. There was no improvement in the clinical outcomes studied. Copyright 2007 Massachusetts Medical Society.
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                Author and article information

                Journal
                Medicine (Baltimore)
                Medicine (Baltimore)
                MEDI
                Medicine
                Wolters Kluwer Health
                0025-7974
                1536-5964
                January 2016
                15 January 2016
                : 95
                : 2
                : e2481
                Affiliations
                From the Department of Ophthalmology and the Center for Healthcare Studies, Feinberg School of Medicine, Northwestern University, and the Veterans Affairs Health Services Research and Development Service, in Chicago, IL (DDF); Department of BioHealth Informatics, Indiana University School of Informatics and Computing, VHA Health Services Research and Development Center for Health Information and Communication, and Regenstrief Institute, Inc., (BED); Department of Biostatistics, Indiana University School of Medicine, (SMP); Center for Health Information and Communication, Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service; Division of General Internal Medicine, Department of Medicine, Indiana University School of Medicine, and Regenstrief Institute, Inc. (LJM, MW, DAH); and Center for Health Information and Communication, Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service,; Regenstrief Institute, Inc.; Indiana University Center for Health Services and Outcomes Research, Indianapolis, IN; College of Pharmacy, Purdue University, West Lafayette, IN (AJZ).
                Author notes
                Correspondence: Dustin D. French, Department of Ophthalmology, 645 N. Michigan Ave, Suite 440, Chicago (e-mail: Dustin.Frenchnorthwestern.edu; drddfrenchyahoo.com; Dustin.French2@ 123456va.gov ).
                Article
                02481
                10.1097/MD.0000000000002481
                4718279
                26765453
                9d19b21a-51c8-449c-aa73-33e5b4217b51
                Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.

                This is an open access article distributed under the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0

                History
                : 28 September 2015
                : 2 December 2015
                : 14 December 2015
                Categories
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                Research Article
                Economic Evaluation Study
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