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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Main Authors: Boback Ziaeian, Haolin Xu, Roland A. Matsouaka, Ying Xian, Yosef Khan, Lee S. Schwamm, Eric E. Smith, Gregg C. Fonarow
Format: Article
Language:English
Published: BMC 2021-02-01
Series:BMC Medical Research Methodology
Subjects:
Online Access:https://doi.org/10.1186/s12874-021-01214-z
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spelling 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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