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Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research

INTRODUCTION: To address the electronic health data fragmentation that is a methodological limitation of comparative effectiveness research (CER), the Washington Heights Inwood Informatics Infrastructure for Comparative Effectiveness Research (WICER) project is creating a patient-centered research d...

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Autores principales: Yoon, Sunmoo, Wilcox, Adam B., Bakken, Suzanne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AcademyHealth 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4371426/
https://www.ncbi.nlm.nih.gov/pubmed/25848564
http://dx.doi.org/10.13063/2327-9214.1021
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author Yoon, Sunmoo
Wilcox, Adam B.
Bakken, Suzanne
author_facet Yoon, Sunmoo
Wilcox, Adam B.
Bakken, Suzanne
author_sort Yoon, Sunmoo
collection PubMed
description INTRODUCTION: To address the electronic health data fragmentation that is a methodological limitation of comparative effectiveness research (CER), the Washington Heights Inwood Informatics Infrastructure for Comparative Effectiveness Research (WICER) project is creating a patient-centered research data warehouse (RDW) by linking electronic clinical data (ECD) from New York Presbyterian Hospital’s clinical data warehouse with ECD from ambulatory care, long-term care, and home health settings and the WICER community health survey (CHS). The purposes of the research were to identify areas of overlap between the WICER CHS and two other surveys that include health behavior data (the Behavioral Risk Factor Surveillance System (BRFSS) Survey and the New York City Community Health Survey (NYC CHS)) and to identify gaps in the current WICER RDW that have the potential to affect patient-centered CER. METHODS: We compared items across the three surveys at the item and conceptual levels. We also compared WICER RDW (ECD and WICER CHS), BRFSS, and NYC CHS to the County Health Ranking framework. RESULTS: We found that 22 percent of WICER items were exact matches with BRFSS and that there were no exact matches between WICER CHS and NYC CHS items not also contained in BRFSS. CONCLUSIONS: The results suggest that BRFSS and, to a lesser extent, NYC CHS have the potential to serve as population comparisons for WICER CHS for some health behavior-related data and thus may be particularly useful for considering the generalizability of CER study findings. Except for one measure related to health behavior (motor vehicle crash deaths), the WICER RDW’s comprehensive coverage supports the mortality, morbidity, and clinical care measures specified in the County Health Ranking framework but is deficient in terms of some socioeconomic factors and descriptions of the physical environment as captured in BRFSS. Linkage of these data in the WICER RDW through geocoding can potentially facilitate patient-centered CER that integrates important socioeconomic and physical environment influences on health outcomes. The research methods and findings may be relevant to others interested in either integrating health behavior data into RDWs to support patient-centered CER or conducting population-level comparisons.
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spelling pubmed-43714262015-04-06 Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research Yoon, Sunmoo Wilcox, Adam B. Bakken, Suzanne EGEMS (Wash DC) Methods INTRODUCTION: To address the electronic health data fragmentation that is a methodological limitation of comparative effectiveness research (CER), the Washington Heights Inwood Informatics Infrastructure for Comparative Effectiveness Research (WICER) project is creating a patient-centered research data warehouse (RDW) by linking electronic clinical data (ECD) from New York Presbyterian Hospital’s clinical data warehouse with ECD from ambulatory care, long-term care, and home health settings and the WICER community health survey (CHS). The purposes of the research were to identify areas of overlap between the WICER CHS and two other surveys that include health behavior data (the Behavioral Risk Factor Surveillance System (BRFSS) Survey and the New York City Community Health Survey (NYC CHS)) and to identify gaps in the current WICER RDW that have the potential to affect patient-centered CER. METHODS: We compared items across the three surveys at the item and conceptual levels. We also compared WICER RDW (ECD and WICER CHS), BRFSS, and NYC CHS to the County Health Ranking framework. RESULTS: We found that 22 percent of WICER items were exact matches with BRFSS and that there were no exact matches between WICER CHS and NYC CHS items not also contained in BRFSS. CONCLUSIONS: The results suggest that BRFSS and, to a lesser extent, NYC CHS have the potential to serve as population comparisons for WICER CHS for some health behavior-related data and thus may be particularly useful for considering the generalizability of CER study findings. Except for one measure related to health behavior (motor vehicle crash deaths), the WICER RDW’s comprehensive coverage supports the mortality, morbidity, and clinical care measures specified in the County Health Ranking framework but is deficient in terms of some socioeconomic factors and descriptions of the physical environment as captured in BRFSS. Linkage of these data in the WICER RDW through geocoding can potentially facilitate patient-centered CER that integrates important socioeconomic and physical environment influences on health outcomes. The research methods and findings may be relevant to others interested in either integrating health behavior data into RDWs to support patient-centered CER or conducting population-level comparisons. AcademyHealth 2013-05-31 /pmc/articles/PMC4371426/ /pubmed/25848564 http://dx.doi.org/10.13063/2327-9214.1021 Text en All eGEMs publications are licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Methods
Yoon, Sunmoo
Wilcox, Adam B.
Bakken, Suzanne
Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research
title Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research
title_full Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research
title_fullStr Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research
title_full_unstemmed Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research
title_short Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research
title_sort comparisons among health behavior surveys: implications for the design of informatics infrastructures that support comparative effectiveness research
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4371426/
https://www.ncbi.nlm.nih.gov/pubmed/25848564
http://dx.doi.org/10.13063/2327-9214.1021
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