Facility Variation in Troponin Ordering Within the Veterans Health Administration.
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ABSTRACT: Background
Current United States guidelines recommend troponin as the preferred biomarker in assessing for acute coronary syndrome, but recommendations are limited about which patients to test. Variations in troponin ordering may influence downstream health care utilization.Methods
We performed a cross-sectional analysis of 3,308,131 emergency department (ED) visits in all 121 acute care facilities within the Veterans Health Administration from 2015 to 2017. We quantified the degree to which case mix and facility characteristics accounted for variations in facility rates in troponin ordering. We then assessed the association between facility quartiles of risk-adjusted troponin ordering and downstream resource utilization [inpatient admissions, noninvasive testing (stress tests, echocardiograms), and invasive procedures (coronary angiograms, percutaneous coronary interventions, and coronary artery bypass grafting surgeries)].Results
The proportion of ED visits with troponin orders ranged from 2.2% to 64.5%, with a median of 37.1%. Case mix accounted for 9.5% of the variation in troponin orders; case mix and differences in facility characteristics accounted for 34.6%. Facilities in the highest quartile of troponin ordering, as compared with those in the lowest quartile, had significantly higher rates of inpatient admissions, stress tests, echocardiograms, coronary angiograms, and percutaneous coronary intervention.Conclusions
Significant variation in troponin utilization exists across Veterans Health Administration facilities and that variation is not well explained by case mix alone. Facilities with higher rates of troponin ordering were associated with more downstream resource utilization.
SUBMITTER: Chui PW
PROVIDER: S-EPMC7666100 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:OBJECTIVE: To compare Veterans Health Administration (VA) patients, non-VA-using veterans, and nonveterans, separated by urban/rural residence and age group, on their use of major categories of medical care and payment sources. DATA SOURCE: Expenditures for health care-using men in Medical Expenditure Panel Surveys from 1996 through 2004. STUDY DESIGN: Retrospective, cross-sectional analysis. DATA COLLECTION/EXTRACTION METHODS: Controlling for demographics, health status, and insurance, we compared groups on population-weighted expenditures for inpatient, hospital-based outpatient, office-based, pharmacy, and other care, by major payers (self/family, private insurance, Medicare, other sources, and VA). RESULTS: VA users received most of their health care outside of the VA system, paid through private insurance or Medicare; self-payments were substantial. VA users under 65 reported worse health if they were rural residents but also lower expenditures overall and less care through private insurance. CONCLUSIONS: VA health care users get most of their medical care from non-VA providers. Working-age VA users have less insurance coverage and rely more on VA care if they live in rural areas.
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| S-EPMC7148193 | biostudies-literature
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| S-EPMC8103225 | biostudies-literature
Project description:ObjectiveTo characterize system-level barriers to bariatric surgery from the perspectives of Veterans with severe obesity and obesity care providers.Summary of background dataBariatric surgery is the most effective weight loss option for Veterans with severe obesity, but fewer than 0.1% of Veterans with severe obesity undergo it. Addressing low utilization of bariatric surgery and weight management services is a priority for the veterans health administration.MethodsWe conducted semi-structured interviews with Veterans with severe obesity who were referred for or underwent bariatric surgery, and providers who delivered care to veterans with severe obesity, including bariatric surgeons, primary care providers, registered dietitians, and health psychologists. We asked study participants to describe their experiences with the bariatric surgery delivery process in the VA system. All interviews were audio-recorded and transcribed. Four coders iteratively developed a codebook and used conventional content analysis to identify relevant systems or "contextual" barriers within Andersen Behavioral Model of Health Services Use.ResultsSeventy-three semi-structured interviews with veterans (n = 33) and providers (n = 40) throughout the veterans health administration system were completed. More than three-fourths of Veterans were male, whereas nearly three-fourths of the providers were female. Eight themes were mapped onto Andersen model as barriers to bariatric surgery: poor care coordination, lack of bariatric surgery guidelines, limited primary care providers and referring provider knowledge about bariatric surgery, long travel distances, delayed referrals, limited access to healthy foods, difficulties meetings preoperative requirements, and lack of provider availability and/or time.ConclusionsAddressing system-level barriers by improving coordination of care and standardizing some aspects of bariatric surgery care may improve access to evidence-based severe obesity care within VA.
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Project description:The purpose of this research was to explore and compare common health system factors for 5 Community Living Centers (ie Veterans Health Administration nursing homes) with high performance on both resident-centered care and clinical quality and for 5 Community Living Centers (CLC) with low performance on both resident-centered care and quality. In particular, we were interested in "how" and "why" some Community Living Centers were able to deliver high levels of resident-centered care and high quality of care, whereas others did not demonstrate this ability. Sites were identified based on their rankings on a composite quality measure calculated from 28 Minimum Data Set version 2.0 quality indicators and a resident-centered care summary score calculated from 6 domains of the Artifacts of Culture Change Tool. Data were from fiscal years 2009-2012. We selected high- and low-performing sites on quality and resident-centered care and conducted 12 in-person site visits in 2014-2015. We used systematic content analysis to code interview transcripts for a priori and emergent health system factor domains. We then assessed variations in these domains across high and low performers using cross-site summaries and matrixes. Our final sample included 108 staff members at 10 Veterans Health Administration CLCs. Staff members included senior leaders, middle managers, and frontline employees. Of the health system factors identified, high and low performers varied in 5 domains, including leadership support, organizational culture, teamwork and communication, resident-centered care recognition and awards, and resident-centered care training. Organizations must recognize that making improvements in the factors identified in this article will require dedicated resources from leaders and support from staff throughout the organization.
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Project description:We aimed to validate an algorithm using both primary discharge diagnosis (International Classification of Diseases Ninth Revision (ICD-9)) and diagnosis-related group (DRG) codes to identify hospitalisations due to decompensated heart failure (HF) in a population of patients with diabetes within the Veterans Health Administration (VHA) system.Validation study.Veterans Health Administration-Tennessee Valley Healthcare System PARTICIPANTS: We identified and reviewed a stratified, random sample of hospitalisations between 2001 and 2012 within a single VHA healthcare system of adults who received regular VHA care and were initiated on an antidiabetic medication between 2001 and 2008. We sampled 500 hospitalisations; 400 hospitalisations that fulfilled algorithm criteria, 100 that did not. Of these, 497 had adequate information for inclusion. The mean patient age was 66.1 years (SD 11.4). Majority of patients were male (98.8%); 75% were white and 20% were black.To determine if a hospitalisation was due to HF, we performed chart abstraction using Framingham criteria as the referent standard. We calculated the positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity for the overall algorithm and each component (primary diagnosis code (ICD-9), DRG code or both).The algorithm had a PPV of 89.7% (95% CI 86.8 to 92.7), NPV of 93.9% (89.1 to 98.6), sensitivity of 45.1% (25.1 to 65.1) and specificity of 99.4% (99.2 to 99.6). The PPV was highest for hospitalisations that fulfilled both the ICD-9 and DRG algorithm criteria (92.1% (89.1 to 95.1)) and lowest for hospitalisations that fulfilled only DRG algorithm criteria (62.5% (28.4 to 96.6)).Our algorithm, which included primary discharge diagnosis and DRG codes, demonstrated excellent PPV for identification of hospitalisations due to decompensated HF among patients with diabetes in the VHA system.
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Project description:BACKGROUND:Despite significant attention to resuscitation care by hospitals, national data on trends in the incidence and survival of patients with inhospital cardiac arrest (IHCA) are limited. OBJECTIVE:To determine trends and hospital-level variation in the incidence and outcomes associated with IHCA. In exploratory analyses, we evaluated the relationship between hospital-level IHCA incidence and outcomes with general hospital-wide quality improvement activities. DESIGN, SETTING, AND PARTICIPANTS:Retrospective cohort study of 2,205,123 hospitalizations at 101 Veterans Health Administration (VHA) hospitals between 2008 and 2012. MAIN OUTCOMES:Risk- and reliability-adjusted hospital-level IHCA incidence and survival to hospital discharge. RESULTS:A total of 8821 (0.40%) IHCA occurred between 2008 and 2012, with no significant change in risk-adjusted incidence over this time (P = .77). Hospital-level IHCA incidence varied substantially across facilities, with a median hospital incidence of 4.0 per 1000 hospitalizations and a range from 1.4 to 11.8 per 1000 hospitalizations. Overall, survival to discharge after IHCA was 31.2%. Risk-adjusted odds of survival increased over the study period (2012 vs 2008, OR: 1.49, 95% CI: 1.27, 1.75) but survival varied substantially across facilities from 20.3% to 45.4%. General hospital quality improvement activities were inconsistently associated with IHCA incidence and survival. CONCLUSIONS:Within the VHA, the incidence and outcomes of IHCA showed important trends over time but varied substantially across hospitals with no consistent link to general hospital quality improvement activities. Identification of specific resuscitation practices at hospitals with low incidence and high survival of IHCA may guide further improvements for inhospital resuscitation.
| S-EPMC6312852 | biostudies-literature