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Associations With Gaps in Standardized Methods for Measuring Social Determinants of Health When Compared With State and County Level 2019, 2020, and 2023 Methods for Measuring Health Outcomes in Five Southeast States.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Associations With Gaps in Standardized Methods for Measuring Social Determinants of Health When Compared With State and County Level 2019, 2020, and 2023 Methods for Measuring Health Outcomes in Five Southeast States./
作者:	Mullen, Barry Kenneth.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2024,
面頁冊數:	120 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-07, Section: B.
Contained By:	Dissertations Abstracts International85-07B.
標題:	Health sciences. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30990564
ISBN:	9798381428988

Associations With Gaps in Standardized Methods for Measuring Social Determinants of Health When Compared With State and County Level 2019, 2020, and 2023 Methods for Measuring Health Outcomes in Five Southeast States.
Mullen, Barry Kenneth.

Associations With Gaps in Standardized Methods for Measuring Social Determinants of Health When Compared With State and County Level 2019, 2020, and 2023 Methods for Measuring Health Outcomes in Five Southeast States. - Ann Arbor : ProQuest Dissertations & Theses, 2024 - 120 p.

Source: Dissertations Abstracts International, Volume: 85-07, Section: B.

Thesis (Ph.D.)--Trident University International, 2024.

Background: The study addressed how Social Determinants of Health factors get measured in the United States and how they can be used to help determine and measure health outcomes. In the healthcare industry, over 95 percent of hospitals collect medical information using a form of electronic data input. Over the last few years, Social Determinants of Health has identified potential upstream drivers of poor health outcomes that resulted in higher healthcare costs. Even though Social Determinants of Health data is collected, there needed to be more variability and standardization in integrating information into a patient's health record, linking Social Determinants of Health factor's impact to a health outcome. Purpose: This study used three methods applied in the U.S. for measuring Social Determinants of Health influence on three healthcare industry approaches to measure quality and performance for ascertaining health outcomes. The dependent variables came from three national datasets (2019, 2020, and 2023). Dependent variable one was the 2023 National Hospital Star ratings for quality of patient experiences from the Centers for Medicare and Medicaid Services. Dependent variable two was the 2020 National Hospital Safety and Quality Ratings, called LeapFrog from the Centers for Medicare and Medicaid Services. Dependent variable three was the 2019 Hospital Consumer Assessment of Healthcare Providers and Systems overall quality and performance Star ratings. The independent variables came from national datasets (2019, 2020, and 2023). Independent variable one was the 2023 U.S. County Health Rankings from the University of Wisconsin Population Health Institute. Independent variable two was the 2020 Social Vulnerability Index from the Centers for Disease Control and Prevention. Independent variable three was from the 2019 Social Deprivation Index from the Robert Graham Center. Methods: The method was a quantitative correlational comparison that investigated whether there were any statistically significant associations between three independent variables and three dependent variables. The independent variables were deidentified as secondary population data from five states by counties for 2019, 2020, and 2023. The data sources were from the 2023 University of Wisconsin Population Health Institute County Health rankings based on their County Health Rankings Model; the 2020 Centers for Disease Prevention and Control's Agency for Toxic Substances and Disease Registry and the 2019 Social Deprivation Index from the Robert Graham Center. The dependent variables were deidentified secondary data from the Centers for Medicare and Medicaid Services. The statistical analysis tests used were descriptive, bivariate, and multivariate analyses. The descriptive analyses included the mean, standard deviation, and range. The bivariate analyses consisted of the Related-Samples Wilcoxon Signed Rank test and Friedman's Two-Way Analysis of Variance since the data was determined to be from a non-normal distribution. The multivariate analyses included conducting the Kruskal-Wallis test of the dependent and independent variables with multiple levels between five Southeast states. Results: The null hypothesis for research question one was rejected and showed that there was a statistically significant association between the 2023 U.S. County health rankings when compared with the state-level 2023 Centers for Medicare and Medicaid Services Hospital Consumer Assessment of Healthcare Providers and Systems hospital star ratings for patient experience satisfaction. The null hypothesis for research question two was rejected and showed that there was a statistically significant association between how Social Determinants of Health were measured at the state level using the 2020 Social Vulnerability Index when compared with the state-level 2020 Centers for Medicare and Medicaid Services hospital LeapFrog rating scores for safety and quality. The null hypothesis for research question three was rejected and showed that there was a statistically significant association between how Social Determinants of Health were measured at the state level using the 2019 Social Deprivation Index when compared with the state-level 2019 Centers for Medicare and Medicaid Services Hospital Consumer Assessment of Healthcare Providers and Systems hospital star ratings for overall quality and performance. Conclusions: The results showed statistically significant associations that could be used to develop further insight as to how the United States measures Social Determinants of Health elements combined with the approaches that the United States healthcare system uses to measure quality, safety, and performance, for opening pathways to the development of a nationally standardized way of measuring health outcomes.Keywords: Social Determinants of Health (SDOH), Health Outcomes, Centers for Medicare and Medicaid Services (CMS), Centers for Disease Control and Prevention (CDC), and Agency for Toxic Substances and Disease Registry (ATSDR).

ISBN: 9798381428988Subjects--Topical Terms:

3168359
Health sciences.
Subjects--Index Terms:

Agency for Toxic Substances and Disease Registry

Associations With Gaps in Standardized Methods for Measuring Social Determinants of Health When Compared With State and County Level 2019, 2020, and 2023 Methods for Measuring Health Outcomes in Five Southeast States.
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520 $a Background: The study addressed how Social Determinants of Health factors get measured in the United States and how they can be used to help determine and measure health outcomes. In the healthcare industry, over 95 percent of hospitals collect medical information using a form of electronic data input. Over the last few years, Social Determinants of Health has identified potential upstream drivers of poor health outcomes that resulted in higher healthcare costs. Even though Social Determinants of Health data is collected, there needed to be more variability and standardization in integrating information into a patient's health record, linking Social Determinants of Health factor's impact to a health outcome. Purpose: This study used three methods applied in the U.S. for measuring Social Determinants of Health influence on three healthcare industry approaches to measure quality and performance for ascertaining health outcomes. The dependent variables came from three national datasets (2019, 2020, and 2023). Dependent variable one was the 2023 National Hospital Star ratings for quality of patient experiences from the Centers for Medicare and Medicaid Services. Dependent variable two was the 2020 National Hospital Safety and Quality Ratings, called LeapFrog from the Centers for Medicare and Medicaid Services. Dependent variable three was the 2019 Hospital Consumer Assessment of Healthcare Providers and Systems overall quality and performance Star ratings. The independent variables came from national datasets (2019, 2020, and 2023). Independent variable one was the 2023 U.S. County Health Rankings from the University of Wisconsin Population Health Institute. Independent variable two was the 2020 Social Vulnerability Index from the Centers for Disease Control and Prevention. Independent variable three was from the 2019 Social Deprivation Index from the Robert Graham Center. Methods: The method was a quantitative correlational comparison that investigated whether there were any statistically significant associations between three independent variables and three dependent variables. The independent variables were deidentified as secondary population data from five states by counties for 2019, 2020, and 2023. The data sources were from the 2023 University of Wisconsin Population Health Institute County Health rankings based on their County Health Rankings Model; the 2020 Centers for Disease Prevention and Control's Agency for Toxic Substances and Disease Registry and the 2019 Social Deprivation Index from the Robert Graham Center. The dependent variables were deidentified secondary data from the Centers for Medicare and Medicaid Services. The statistical analysis tests used were descriptive, bivariate, and multivariate analyses. The descriptive analyses included the mean, standard deviation, and range. The bivariate analyses consisted of the Related-Samples Wilcoxon Signed Rank test and Friedman's Two-Way Analysis of Variance since the data was determined to be from a non-normal distribution. The multivariate analyses included conducting the Kruskal-Wallis test of the dependent and independent variables with multiple levels between five Southeast states. Results: The null hypothesis for research question one was rejected and showed that there was a statistically significant association between the 2023 U.S. County health rankings when compared with the state-level 2023 Centers for Medicare and Medicaid Services Hospital Consumer Assessment of Healthcare Providers and Systems hospital star ratings for patient experience satisfaction. The null hypothesis for research question two was rejected and showed that there was a statistically significant association between how Social Determinants of Health were measured at the state level using the 2020 Social Vulnerability Index when compared with the state-level 2020 Centers for Medicare and Medicaid Services hospital LeapFrog rating scores for safety and quality. The null hypothesis for research question three was rejected and showed that there was a statistically significant association between how Social Determinants of Health were measured at the state level using the 2019 Social Deprivation Index when compared with the state-level 2019 Centers for Medicare and Medicaid Services Hospital Consumer Assessment of Healthcare Providers and Systems hospital star ratings for overall quality and performance. Conclusions: The results showed statistically significant associations that could be used to develop further insight as to how the United States measures Social Determinants of Health elements combined with the approaches that the United States healthcare system uses to measure quality, safety, and performance, for opening pathways to the development of a nationally standardized way of measuring health outcomes.Keywords: Social Determinants of Health (SDOH), Health Outcomes, Centers for Medicare and Medicaid Services (CMS), Centers for Disease Control and Prevention (CDC), and Agency for Toxic Substances and Disease Registry (ATSDR).
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