National surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registry
Abstract Background The U.S. lacks a stroke surveillance system. This study develops a method to transform an existing registry into a nationally representative database to evaluate acute ischemic stroke care quality. Methods Two statistical approaches are used to develop post-stratification weights...
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doaj-ca3eb67b643c423b9a181bb4ddff019a2021-02-07T12:03:07ZengBMCBMC Medical Research Methodology1471-22882021-02-0121111510.1186/s12874-021-01214-zNational surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registryBoback Ziaeian0Haolin Xu1Roland A. Matsouaka2Ying Xian3Yosef Khan4Lee S. Schwamm5Eric E. Smith6Gregg C. Fonarow7Division of Cardiology, David Geffen School of Medicine at University of CaliforniaDuke Clinical Research InstituteDuke Clinical Research InstituteDuke Clinical Research InstituteHealthcare Quality Research and Bioinformatics, American Heart AssociationDepartment of Neurology, Comprehensive Stroke Center Massachusetts General Hospital and Harvard Medical SchoolDepartment of Clinical Neurosciences and Hotchkiss Brain Institute, University of CalgaryDivision of Cardiology, David Geffen School of Medicine at University of CaliforniaAbstract Background The U.S. lacks a stroke surveillance system. This study develops a method to transform an existing registry into a nationally representative database to evaluate acute ischemic stroke care quality. Methods Two statistical approaches are used to develop post-stratification weights for the Get With The Guidelines-Stroke registry by anchoring population estimates to the National Inpatient Sample. Post-stratification survey weights are estimated using a raking procedure and Bayesian interpolation methods. Weighting methods are adjusted to limit the dispersion of weights and make reasonable epidemiologic estimates of patient characteristics, quality of hospital care, and clinical outcomes. Standardized differences in national estimates are reported between the two post-stratification methods for anchored and non-anchored patient characteristics to evaluate estimation quality. Primary measures evaluated are patient and hospital characteristics, stroke severity, vital and laboratory measures, disposition, and clinical outcomes at discharge. Results A total of 1,388,296 acute ischemic strokes occurred between 2012 and 2014. Raking and Bayesian estimates of clinical data not available in administrative data are estimated within 5 to 10% of margin for expected values. Median weight for the raking method is 1.386 and the weights at the 99th percentile is 6.881 with a maximum weight of 30.775. Median Bayesian weight is 1.329 and the 99th percentile weights is 11.201 with a maximum weight of 515.689. Conclusions Leveraging existing databases with patient registries to develop post-stratification weights is a reliable approach to estimate acute ischemic stroke epidemiology and monitoring for stroke quality of care nationally. These methods may be applied to other diseases or settings to better monitor population health.https://doi.org/10.1186/s12874-021-01214-zEpidemiologyIschemic strokeQuality and outcomesHealth servicesBayesian analysisPopulation surveillance |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Boback Ziaeian Haolin Xu Roland A. Matsouaka Ying Xian Yosef Khan Lee S. Schwamm Eric E. Smith Gregg C. Fonarow |
spellingShingle |
Boback Ziaeian Haolin Xu Roland A. Matsouaka Ying Xian Yosef Khan Lee S. Schwamm Eric E. Smith Gregg C. Fonarow National surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registry BMC Medical Research Methodology Epidemiology Ischemic stroke Quality and outcomes Health services Bayesian analysis Population surveillance |
author_facet |
Boback Ziaeian Haolin Xu Roland A. Matsouaka Ying Xian Yosef Khan Lee S. Schwamm Eric E. Smith Gregg C. Fonarow |
author_sort |
Boback Ziaeian |
title |
National surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registry |
title_short |
National surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registry |
title_full |
National surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registry |
title_fullStr |
National surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registry |
title_full_unstemmed |
National surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registry |
title_sort |
national surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the get with the guidelines-stroke patient registry |
publisher |
BMC |
series |
BMC Medical Research Methodology |
issn |
1471-2288 |
publishDate |
2021-02-01 |
description |
Abstract Background The U.S. lacks a stroke surveillance system. This study develops a method to transform an existing registry into a nationally representative database to evaluate acute ischemic stroke care quality. Methods Two statistical approaches are used to develop post-stratification weights for the Get With The Guidelines-Stroke registry by anchoring population estimates to the National Inpatient Sample. Post-stratification survey weights are estimated using a raking procedure and Bayesian interpolation methods. Weighting methods are adjusted to limit the dispersion of weights and make reasonable epidemiologic estimates of patient characteristics, quality of hospital care, and clinical outcomes. Standardized differences in national estimates are reported between the two post-stratification methods for anchored and non-anchored patient characteristics to evaluate estimation quality. Primary measures evaluated are patient and hospital characteristics, stroke severity, vital and laboratory measures, disposition, and clinical outcomes at discharge. Results A total of 1,388,296 acute ischemic strokes occurred between 2012 and 2014. Raking and Bayesian estimates of clinical data not available in administrative data are estimated within 5 to 10% of margin for expected values. Median weight for the raking method is 1.386 and the weights at the 99th percentile is 6.881 with a maximum weight of 30.775. Median Bayesian weight is 1.329 and the 99th percentile weights is 11.201 with a maximum weight of 515.689. Conclusions Leveraging existing databases with patient registries to develop post-stratification weights is a reliable approach to estimate acute ischemic stroke epidemiology and monitoring for stroke quality of care nationally. These methods may be applied to other diseases or settings to better monitor population health. |
topic |
Epidemiology Ischemic stroke Quality and outcomes Health services Bayesian analysis Population surveillance |
url |
https://doi.org/10.1186/s12874-021-01214-z |
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