Measuring Stroke Quality: Methodological Considerations in Selecting, Defining, and Analyzing Quality Measures

Amy Y.X. Yu; Dawn M. Bravata; Bo Norrving; Mathew J. Reeves; Liping Liu; Monique F. Kilkenny

doi:10.1161/STROKEAHA.122.036485

Measuring Stroke Quality: Methodological Considerations in Selecting, Defining, and Analyzing Quality Measures

Amy Y.X. Yu, Dawn M. Bravata, Bo Norrving, Mathew J. Reeves, Liping Liu, Monique F. Kilkenny

Medicine Monash Health

Research output: Contribution to journal › Review Article › Other › peer-review

19 Citations (Scopus)

Abstract

Knowledge about stroke and its management is growing rapidly and stroke systems of care must adapt to deliver evidence-based care. Quality improvement initiatives are essential for translating knowledge from clinical trials and recommendations in guidelines into routine clinical practice. This review focuses on issues central to the measurement of the quality of stroke care, including selection and definition of quality measures, identification of the eligible patient cohorts, optimization of data quality, and considerations for data analysis and interpretation.

Original language	English
Pages (from-to)	3214-3221
Number of pages	8
Journal	Stroke
Volume	53
Issue number	10
DOIs	https://doi.org/10.1161/STROKEAHA.122.036485
Publication status	Published - 1 Oct 2022

Keywords

data analysis
evidence-based care
health services
ischemic stroke
quality improvement

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10.1161/STROKEAHA.122.036485

Cite this

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title = "Measuring Stroke Quality: Methodological Considerations in Selecting, Defining, and Analyzing Quality Measures",

abstract = "Knowledge about stroke and its management is growing rapidly and stroke systems of care must adapt to deliver evidence-based care. Quality improvement initiatives are essential for translating knowledge from clinical trials and recommendations in guidelines into routine clinical practice. This review focuses on issues central to the measurement of the quality of stroke care, including selection and definition of quality measures, identification of the eligible patient cohorts, optimization of data quality, and considerations for data analysis and interpretation.",

keywords = "data analysis, evidence-based care, health services, ischemic stroke, quality improvement",

author = "Yu, \{Amy Y.X.\} and Bravata, \{Dawn M.\} and Bo Norrving and Reeves, \{Mathew J.\} and Liping Liu and Kilkenny, \{Monique F.\}",

note = "Funding Information: A.Y.X. Yu holds a National New Investigator Award from the Heart and Stroke Foundation of Canada. M. Kilkenny is supported by a Future Leader Fellowship (Award Reference No. 105737) from the National Heart Foundation of Australia. Funding Information: A.Y.X. Yu holds a National New Investigator Award from the Heart \& Stroke Foundation of Canada. M. Kilkenny is supported by a Future Leader Fellowship (Award Reference No. 105737) from the National Heart Foundation of Australia. Publisher Copyright: {\textcopyright} 2022 Lippincott Williams and Wilkins. All rights reserved.",

year = "2022",

month = oct,

day = "1",

doi = "10.1161/STROKEAHA.122.036485",

language = "English",

volume = "53",

pages = "3214--3221",

journal = "Stroke",

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publisher = "American Heart Association",

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T1 - Measuring Stroke Quality

T2 - Methodological Considerations in Selecting, Defining, and Analyzing Quality Measures

AU - Yu, Amy Y.X.

AU - Bravata, Dawn M.

AU - Norrving, Bo

AU - Reeves, Mathew J.

AU - Liu, Liping

AU - Kilkenny, Monique F.

N1 - Funding Information: A.Y.X. Yu holds a National New Investigator Award from the Heart and Stroke Foundation of Canada. M. Kilkenny is supported by a Future Leader Fellowship (Award Reference No. 105737) from the National Heart Foundation of Australia. Funding Information: A.Y.X. Yu holds a National New Investigator Award from the Heart & Stroke Foundation of Canada. M. Kilkenny is supported by a Future Leader Fellowship (Award Reference No. 105737) from the National Heart Foundation of Australia. Publisher Copyright: © 2022 Lippincott Williams and Wilkins. All rights reserved.

PY - 2022/10/1

Y1 - 2022/10/1

N2 - Knowledge about stroke and its management is growing rapidly and stroke systems of care must adapt to deliver evidence-based care. Quality improvement initiatives are essential for translating knowledge from clinical trials and recommendations in guidelines into routine clinical practice. This review focuses on issues central to the measurement of the quality of stroke care, including selection and definition of quality measures, identification of the eligible patient cohorts, optimization of data quality, and considerations for data analysis and interpretation.

AB - Knowledge about stroke and its management is growing rapidly and stroke systems of care must adapt to deliver evidence-based care. Quality improvement initiatives are essential for translating knowledge from clinical trials and recommendations in guidelines into routine clinical practice. This review focuses on issues central to the measurement of the quality of stroke care, including selection and definition of quality measures, identification of the eligible patient cohorts, optimization of data quality, and considerations for data analysis and interpretation.

KW - data analysis

KW - evidence-based care

KW - health services

KW - ischemic stroke

KW - quality improvement

UR - https://www.scopus.com/pages/publications/85139276743

U2 - 10.1161/STROKEAHA.122.036485

DO - 10.1161/STROKEAHA.122.036485

M3 - Review Article

C2 - 35876016

AN - SCOPUS:85139276743

SN - 0039-2499

VL - 53

SP - 3214

EP - 3221

JO - Stroke

JF - Stroke

IS - 10

ER -

Measuring Stroke Quality: Methodological Considerations in Selecting, Defining, and Analyzing Quality Measures

Abstract

Keywords

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Other files and links

National Stroke Data Linkage Program: Using big data to improve diagnostic coding, clinical management and long-term outcomes after stroke

Cite this

Measuring Stroke Quality: Methodological Considerations in Selecting, Defining, and Analyzing Quality Measures

Abstract

Keywords

Access to Document

Other files and links

Projects

National Stroke Data Linkage Program: Using big data to improve diagnostic coding, clinical management and long-term outcomes after stroke

Cite this