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Organizational Health Literacy: Quality Improvement Measures with Expert Consensus
BACKGROUND: Organizational health literacy (OHL) is the degree to which health care organizations implement strategies to make it easier for patients to understand health information, navigate the health care system, engage in the health care process, and manage their health. Although resources exis...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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SLACK Incorporated
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610031/ https://www.ncbi.nlm.nih.gov/pubmed/31294314 http://dx.doi.org/10.3928/24748307-20190503-01 |
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author | Brega, Angela G. Hamer, Mika K. Albright, Karen Brach, Cindy Saliba, Debra Abbey, Dana Gritz, R. Mark |
author_facet | Brega, Angela G. Hamer, Mika K. Albright, Karen Brach, Cindy Saliba, Debra Abbey, Dana Gritz, R. Mark |
author_sort | Brega, Angela G. |
collection | PubMed |
description | BACKGROUND: Organizational health literacy (OHL) is the degree to which health care organizations implement strategies to make it easier for patients to understand health information, navigate the health care system, engage in the health care process, and manage their health. Although resources exist to guide OHL-related quality improvement (QI) initiatives, little work has been done to establish measures that organizations can use to monitor their improvement efforts. OBJECTIVE: We sought to identify and evaluate existing OHL-related QI measures. To complement prior efforts to develop measures based on patient-reported data, we sought to identify measures computed from clinical, administrative, QI, or staff-reported data. Our goal was to develop a set of measures that experts agree are valuable for informing OHL-related QI activities. METHODS: We used four methods to identify relevant measures computed from clinical, administrative, QI, or staff-reported data. We convened a Technical Expert Panel, published a request for measures, conducted a literature review, and interviewed 20 organizations working to improve OHL. From the comprehensive list of measures identified, we selected a set of high-priority measures for review by a second expert panel. Using a modified Delphi review process, panelists rated measures on four evaluation criteria, participated in a teleconference to discuss areas of disagreement among panelists, and rerated all measures. KEY RESULTS: Across all methods, we identified 233 measures. Seventy measures underwent Delphi Panel review. For 22 measures, there was consensus among panelists that the measures were useful, meaningful, feasible, and had face validity. Five additional measures received strong ratings for usefulness, meaningfulness, and face validity, but failed to show consensus among panelists regarding feasibility. CONCLUSIONS: We identified OHL-related QI measures that have the support of experts in the field. Although additional measure development and testing is recommended, the Consensus OHL QI Measures are appropriate for immediate use. [HLRP: Health Literacy Research and Practice. 2019;3(2):e127–e146.] PLAIN LANGUAGE SUMMARY: The health care system is complex. Health care organizations can make things easier for patients by making changes to improve communication and to help patients find their way around, become engaged in the health care process, and manage their health. We identify 22 measures that organizations can use to monitor their efforts to improve communication with and support for patients. |
format | Online Article Text |
id | pubmed-6610031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | SLACK Incorporated |
record_format | MEDLINE/PubMed |
spelling | pubmed-66100312019-07-10 Organizational Health Literacy: Quality Improvement Measures with Expert Consensus Brega, Angela G. Hamer, Mika K. Albright, Karen Brach, Cindy Saliba, Debra Abbey, Dana Gritz, R. Mark Health Lit Res Pract Original Research BACKGROUND: Organizational health literacy (OHL) is the degree to which health care organizations implement strategies to make it easier for patients to understand health information, navigate the health care system, engage in the health care process, and manage their health. Although resources exist to guide OHL-related quality improvement (QI) initiatives, little work has been done to establish measures that organizations can use to monitor their improvement efforts. OBJECTIVE: We sought to identify and evaluate existing OHL-related QI measures. To complement prior efforts to develop measures based on patient-reported data, we sought to identify measures computed from clinical, administrative, QI, or staff-reported data. Our goal was to develop a set of measures that experts agree are valuable for informing OHL-related QI activities. METHODS: We used four methods to identify relevant measures computed from clinical, administrative, QI, or staff-reported data. We convened a Technical Expert Panel, published a request for measures, conducted a literature review, and interviewed 20 organizations working to improve OHL. From the comprehensive list of measures identified, we selected a set of high-priority measures for review by a second expert panel. Using a modified Delphi review process, panelists rated measures on four evaluation criteria, participated in a teleconference to discuss areas of disagreement among panelists, and rerated all measures. KEY RESULTS: Across all methods, we identified 233 measures. Seventy measures underwent Delphi Panel review. For 22 measures, there was consensus among panelists that the measures were useful, meaningful, feasible, and had face validity. Five additional measures received strong ratings for usefulness, meaningfulness, and face validity, but failed to show consensus among panelists regarding feasibility. CONCLUSIONS: We identified OHL-related QI measures that have the support of experts in the field. Although additional measure development and testing is recommended, the Consensus OHL QI Measures are appropriate for immediate use. [HLRP: Health Literacy Research and Practice. 2019;3(2):e127–e146.] PLAIN LANGUAGE SUMMARY: The health care system is complex. Health care organizations can make things easier for patients by making changes to improve communication and to help patients find their way around, become engaged in the health care process, and manage their health. We identify 22 measures that organizations can use to monitor their efforts to improve communication with and support for patients. SLACK Incorporated 2019-07-01 /pmc/articles/PMC6610031/ /pubmed/31294314 http://dx.doi.org/10.3928/24748307-20190503-01 Text en © 2019 Brega, Hamer, Albright, et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0). This license allows users to copy and distribute, to remix, transform, and build upon the article, for any purpose, even commercially, provided the author is attributed and is not represented as endorsing the use made of the work. |
spellingShingle | Original Research Brega, Angela G. Hamer, Mika K. Albright, Karen Brach, Cindy Saliba, Debra Abbey, Dana Gritz, R. Mark Organizational Health Literacy: Quality Improvement Measures with Expert Consensus |
title | Organizational Health Literacy: Quality Improvement Measures with Expert Consensus |
title_full | Organizational Health Literacy: Quality Improvement Measures with Expert Consensus |
title_fullStr | Organizational Health Literacy: Quality Improvement Measures with Expert Consensus |
title_full_unstemmed | Organizational Health Literacy: Quality Improvement Measures with Expert Consensus |
title_short | Organizational Health Literacy: Quality Improvement Measures with Expert Consensus |
title_sort | organizational health literacy: quality improvement measures with expert consensus |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610031/ https://www.ncbi.nlm.nih.gov/pubmed/31294314 http://dx.doi.org/10.3928/24748307-20190503-01 |
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