Browsing by Subject "quality indicators"

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    Estimating and Reporting on the Quality of Inpatient Stroke Care by Veterans Health Administration Medical Centers
    (2012-01) Arling, Greg; Reeves, Mathew; Ross, Joseph S.; Williams, Linda S.; Keyhani, Salomeh; Chumbler, Neale R.; Phipps, Michael S.; Roumie, Christianne L; Myers, Laura J.; Salanitro, Amanda H; Ordin, Diana L.; Myers, Jennifer; Bravata, Dawn M.
    Background—Reporting of quality indicators (QIs) in Veterans Health Administration Medical Centers is complicated by estimation error caused by small numbers of eligible patients per facility. We applied multilevel modeling and empirical Bayes (EB) estimation in addressing this issue in performance reporting of stroke care quality in the Medical Centers. Methods and Results—We studied a retrospective cohort of 3812 veterans admitted to 106 Medical Centers with ischemic stroke during fiscal year 2007. The median number of study patients per facility was 34 (range, 12–105). Inpatient stroke care quality was measured with 13 evidence-based QIs. Eligible patients could either pass or fail each indicator. Multilevel modeling of a patient's pass/fail on individual QIs was used to produce facility-level EB-estimated QI pass rates and confidence intervals. The EB estimation reduced interfacility variation in QI rates. Small facilities and those with exceptionally high or low rates were most affected. We recommended 8 of the 13 QIs for performance reporting: dysphagia screening, National Institutes of Health Stroke Scale documentation, early ambulation, fall risk assessment, pressure ulcer risk assessment, Functional Independence Measure documentation, lipid management, and deep vein thrombosis prophylaxis. These QIs displayed sufficient variation across facilities, had room for improvement, and identified sites with performance that was significantly above or below the population average. The remaining 5 QIs were not recommended because of too few eligible patients or high pass rates with little variation. Conclusions—Considerations of statistical uncertainty should inform the choice of QIs and their application to performance reporting.
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    Hospital Length of Stay and Readmission Rate for Neurosurgical Patients
    (Oxford, 2018-02) Ansari, Shaheryar F.; Yan, Hong; Zou, Jian; Worth, Robert M.; Barbaro, Nicholas M.; Neurological Surgery, School of Medicine
    BACKGROUND Hospital readmission rate has become a major indicator of quality of care, with penalties given to hospitals with high rates of readmission. At the same time, insurers are increasing pressure for greater efficiency and reduced costs, including decreasing hospital lengths of stay (LOS). OBJECTIVE To analyze the authors’ service to determine if there is a relationship between LOS and readmission rates. METHODS Records of patients admitted to the authors’ institution from October 2007 through June 2014 were analyzed for several data points, including initial LOS, readmission occurrence, admitting and secondary diagnoses, and discharge disposition. RESULTS Out of 9409 patient encounters, there were 925 readmissions. Average LOS was 6 d. Univariate analysis indicated a higher readmission rate with more diagnoses upon admission (P < .001) and an association between insurance type and readmission (P < .001), as well as decreasing average yearly LOS (P = .0045). Multivariate analysis indicated statistically significant associations between longer LOS (P = .03) and government insurance (P < .01). CONCLUSION A decreasing LOS over time has been associated with an increasing readmission rate at the population level. However, at the individual level, a prolonged LOS was associated with a higher risk of readmission. This was attributed to patient comorbidities. However, this increasing readmission rate may represent many factors including patients’ overall health status. Thus, the rate of readmission may represent a burden of illness rather than a valid metric for quality of care.