Guohai Zhou

Mass General Brigham

13 active projects

D16_HTN_revision_after_code_review

We are using the All of Us Researcher Workbench interface to answer the question, "Is hypertension prevalence in the All of Us Research Program similar to hypertension prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES) ?". Clinical…

Scientific Questions Being Studied

We are using the All of Us Researcher Workbench interface to answer the question, "Is hypertension prevalence in the All of Us Research Program similar to hypertension prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES) ?". Clinical approaches to understanding and treating hypertension may benefit from the integration of a precision medicine approach that integrates data on environments, social determinants of health, behaviors, and genomic factors that contribute to hypertension risk. Hypertension is a major public health concern and remains a leading risk factor for stroke and cardiovascular disease.

Project Purpose(s)

  • Other Purpose (This work is an AoU demo project. Demo projects are efforts by the AoU Research Program designed to meet the program goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. As an approved demo project, this work was reviewed and overseen by the AoU Research Program Science Committee and the AoU Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use. )

Scientific Approaches

In this cross-sectional, population-based study, we used All of Us baseline data from patient (age>18) provided information (PPI) surveys and electronic health record (EHR) blood pressure measurements and retrospectively examined the prevalence of hypertension in the EHR cohort using Systemized Nomenclature of Medicine (SNOMED codes and blood pressure medications recorded in the EHR. We used the EHR data (SNOMED codes on 2 distinct dates and at least one hypertension medication) as the primary definition, and then add subjects with elevated systolic or elevated diastolic blood pressure on measurements 2 and 3 from PPI. We extracted each participant’s detailed dates of SNOMED code for essential hypertension from the Researcher Workbench table ‘cb_search_all_events’. We calculated an age-standardized HTN prevalence according to the age distribution of the U.S. Census, using 3 groups (18-39, 40-59, ≥ 60).

Anticipated Findings

The prevalence of hypertension in the All of Us cohort is similar to that of published literature. All of Us age-adjusted HTN prevalence was 27.9% compared to 29.6% in National Health and Nutrition Examination Survey. The All of Us cohort is a growing source of diverse longitudinal data that can be utilized to study hypertension nationwide. The prevalence of hypertension varies in the United States (U.S.) by age, sex, and socioeconomic status. Hypertension can often be treated successfully with medication, and prevented or delayed with lifestyle modifications. Even with these established hypertension intervention and prevention strategies, the prevalence of hypertension continues to be at levels of public health concern. The diversity within All of Us may provide insight into factors relevant to hypertension prevention and treatments in a variety of social and geographic contexts and population strata in the U.S.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Collaborators:

  • Roxana Loperena Cortes - Other, All of Us Program Operational Use
  • Elizabeth Karlson - Late Career Tenured Researcher, Mass General Brigham

obesity_mansucript_rerun

National obesity prevention and intervention strategies may benefit from precision medicine approaches that incorporate integrated data on environments, social determinants of health, and genomic factors. We examined the quality and utility of the All of Us Research Hub Workbench for…

Scientific Questions Being Studied

National obesity prevention and intervention strategies may benefit from precision medicine approaches that incorporate integrated data on environments, social determinants of health, and genomic factors. We examined the quality and utility of the All of Us Research Hub Workbench for accelerating precision medicine by replicating methods from existing studies that examine the prevalence of obesity at the population level. We evaluated the measurements of obesity in the participant measurement (PM) data set and the electronic health record (EHR) data set using methods similar to the Ward et al. NEJM December 2019 publication that assessed prevalence of obesity in the US by state using BRFSS data.

Project Purpose(s)

  • Disease Focused Research (obesity)
  • Educational
  • Methods Development
  • Other Purpose (This work is the result of an All of Us Research Program Demonstration Project. Demonstration Projects are efforts by the All of Us Research Program designed to meet the goal of ensuring the quality and utility of the Research Hub as a resource for accelerating precision medicine. This work has been approved, reviewed, and overseen by the All of Us Research Program Science Committee and Data and Research Center to ensure compliance with program policy.)

Scientific Approaches

For this population-based cross-sectional study of All of Us Research Workbench participants, we excluded individuals with measurements obtained during pregnancy or inpatient visits and individuals from states with fewer than 100 participants. Physical measurements (PM) of height and weight at the time of program enrollment of 142,116 participants and measured weight and height extracted from electronic health records (EHR) of 40,885 individuals were used to calculate body-mass index (BMI). We did a complete case analysis for All of Us participants with known sex (male or female), race, income and education levels and estimated state-specific and demographic subgroup-specific prevalence of categories of BMI [obesity (BMI ≥30) and extreme obesity (BMI ≥ 35)] nationwide and for each state: overall and by subgroups, male and female. We examined the difference between EHR and PM calculated BMI by state.

Anticipated Findings

Using states with at least 100 participants, PM data included 142,116 individuals (mean [SD] age, 51.2 [16.6] and EHR data on height and weight included 40,885 individuals (mean [SD] age, 52.5 [16.5]. The median BMI for PM participants was 28.4 [24.4 to 33.7]; the median BMI for EHR was 29.0 [24.8 to 34.5]. The PM national prevalence for obesity (includes BMI>30 and BMI >35) and extreme obesity (BMI >35) were 41.2 % (95% Confidence Interval [CI], 40.9 to 41.4) and 20.8% (95% CI, 20.6 to 21.0), respectively, with large variations across states. Women had higher prevalence of extreme obesity than men in all selected states. Subgroups with extreme obesity (BMI, >35) prevalence greater than 25% included subgroup, N, prevalence %, (95% CI): Black NH, 8913, 28.9 (25.8 to 32.0) , individuals with income less than $25,000, 13,244, 25.1 (22.1 to 28.1); education of high school to some college, 17, 272, 26.1 (23.1 to 29.1) and the region of the South, 6,639, 25.3 (22.3 to 28.3).

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Education Level
  • Income Level

Research Team

Owner:

Collaborators:

  • Francis Ratsimbazafy - Other, All of Us Program Operational Use
  • Karthik Natarajan - Other, All of Us Program Operational Use

DRC_Duplicate of for_obesity_code_review

National obesity prevention and intervention strategies may benefit from precision medicine approaches that incorporate integrated data on environments, social determinants of health, and genomic factors. We examined the quality and utility of the All of Us Research Hub Workbench for…

Scientific Questions Being Studied

National obesity prevention and intervention strategies may benefit from precision medicine approaches that incorporate integrated data on environments, social determinants of health, and genomic factors. We examined the quality and utility of the All of Us Research Hub Workbench for accelerating precision medicine by replicating methods from existing studies that examine the prevalence of obesity at the population level. We evaluated the measurements of obesity in the participant measurement (PM) data set and the electronic health record (EHR) data set using methods similar to the Ward et al. NEJM December 2019 publication that assessed prevalence of obesity in the US by state using BRFSS data.

Project Purpose(s)

  • Disease Focused Research (obesity)
  • Educational
  • Methods Development
  • Other Purpose (This work is the result of an All of Us Research Program Demonstration Project. Demonstration Projects are efforts by the All of Us Research Program designed to meet the goal of ensuring the quality and utility of the Research Hub as a resource for accelerating precision medicine. This work has been approved, reviewed, and overseen by the All of Us Research Program Science Committee and Data and Research Center to ensure compliance with program policy.)

Scientific Approaches

For this population-based cross-sectional study of All of Us Research Workbench participants, we excluded individuals with measurements obtained during pregnancy or inpatient visits and individuals from states with fewer than 100 participants. Physical measurements (PM) of height and weight at the time of program enrollment of 142,116 participants and measured weight and height extracted from electronic health records (EHR) of 40,885 individuals were used to calculate body-mass index (BMI). We did a complete case analysis for All of Us participants with known sex (male or female), race, income and education levels and estimated state-specific and demographic subgroup-specific prevalence of categories of BMI [obesity (BMI ≥30) and extreme obesity (BMI ≥ 35)] nationwide and for each state: overall and by subgroups, male and female. We examined the difference between EHR and PM calculated BMI by state.

Anticipated Findings

Using states with at least 100 participants, PM data included 142,116 individuals (mean [SD] age, 51.2 [16.6] and EHR data on height and weight included 40,885 individuals (mean [SD] age, 52.5 [16.5]. The median BMI for PM participants was 28.4 [24.4 to 33.7]; the median BMI for EHR was 29.0 [24.8 to 34.5]. The PM national prevalence for obesity (includes BMI>30 and BMI >35) and extreme obesity (BMI >35) were 41.2 % (95% Confidence Interval [CI], 40.9 to 41.4) and 20.8% (95% CI, 20.6 to 21.0), respectively, with large variations across states. Women had higher prevalence of extreme obesity than men in all selected states. Subgroups with extreme obesity (BMI, >35) prevalence greater than 25% included subgroup, N, prevalence %, (95% CI): Black NH, 8913, 28.9 (25.8 to 32.0) , individuals with income less than $25,000, 13,244, 25.1 (22.1 to 28.1); education of high school to some college, 17, 272, 26.1 (23.1 to 29.1) and the region of the South, 6,639, 25.3 (22.3 to 28.3).

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Education Level
  • Income Level

Research Team

Owner:

Collaborators:

  • Jun Qian - Other, All of Us Program Operational Use

For_DRC_obesity_code_review

National obesity prevention and intervention strategies may benefit from precision medicine approaches that incorporate integrated data on environments, social determinants of health, and genomic factors. We examined the quality and utility of the All of Us Research Hub Workbench for…

Scientific Questions Being Studied

National obesity prevention and intervention strategies may benefit from precision medicine approaches that incorporate integrated data on environments, social determinants of health, and genomic factors. We examined the quality and utility of the All of Us Research Hub Workbench for accelerating precision medicine by replicating methods from existing studies that examine the prevalence of obesity at the population level. We evaluated the measurements of obesity in the participant measurement (PM) data set and the electronic health record (EHR) data set using methods similar to the Ward et al. NEJM December 2019 publication that assessed prevalence of obesity in the US by state using BRFSS data.

Project Purpose(s)

  • Disease Focused Research (obesity)
  • Educational
  • Methods Development

Scientific Approaches

For this population-based cross-sectional study of All of Us Research Workbench participants, we excluded individuals with measurements obtained during pregnancy or inpatient visits and individuals from states with fewer than 100 participants. Physical measurements (PM) of height and weight at the time of program enrollment of 142,116 participants and measured weight and height extracted from electronic health records (EHR) of 40,885 individuals were used to calculate body-mass index (BMI). We did a complete case analysis for All of Us participants with known sex (male or female), race, income and education levels and estimated state-specific and demographic subgroup-specific prevalence of categories of BMI [obesity (BMI ≥30) and extreme obesity (BMI ≥ 35)] nationwide and for each state: overall and by subgroups, male and female. We examined the difference between EHR and PM calculated BMI by state.

Anticipated Findings

Using states with at least 100 participants, PM data included 142,116 individuals (mean [SD] age, 51.2 [16.6] and EHR data on height and weight included 40,885 individuals (mean [SD] age, 52.5 [16.5]. The median BMI for PM participants was 28.4 [24.4 to 33.7]; the median BMI for EHR was 29.0 [24.8 to 34.5]. The PM national prevalence for obesity (includes BMI>30 and BMI >35) and extreme obesity (BMI >35) were 41.2 % (95% Confidence Interval [CI], 40.9 to 41.4) and 20.8% (95% CI, 20.6 to 21.0), respectively, with large variations across states. Women had higher prevalence of extreme obesity than men in all selected states. Subgroups with extreme obesity (BMI, >35) prevalence greater than 25% included subgroup, N, prevalence %, (95% CI): Black NH, 8913, 28.9 (25.8 to 32.0) , individuals with income less than $25,000, 13,244, 25.1 (22.1 to 28.1); education of high school to some college, 17, 272, 26.1 (23.1 to 29.1) and the region of the South, 6,639, 25.3 (22.3 to 28.3).

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Education Level
  • Income Level

Research Team

Owner:

Duplicate_for_DRC_obesity_code_review

National obesity prevention and intervention strategies may benefit from precision medicine approaches that incorporate integrated data on environments, social determinants of health, and genomic factors. We examined the quality and utility of the All of Us Research Hub Workbench for…

Scientific Questions Being Studied

National obesity prevention and intervention strategies may benefit from precision medicine approaches that incorporate integrated data on environments, social determinants of health, and genomic factors. We examined the quality and utility of the All of Us Research Hub Workbench for accelerating precision medicine by replicating methods from existing studies that examine the prevalence of obesity at the population level. We evaluated the measurements of obesity in the participant measurement (PM) data set and the electronic health record (EHR) data set using methods similar to the Ward et al. NEJM December 2019 publication that assessed prevalence of obesity in the US by state using BRFSS data.

Project Purpose(s)

  • Disease Focused Research (obesity)
  • Educational
  • Methods Development

Scientific Approaches

For this population-based cross-sectional study of All of Us Research Workbench participants, we excluded individuals with measurements obtained during pregnancy or inpatient visits and individuals from states with fewer than 100 participants. Physical measurements (PM) of height and weight at the time of program enrollment of 142,116 participants and measured weight and height extracted from electronic health records (EHR) of 40,885 individuals were used to calculate body-mass index (BMI). We did a complete case analysis for All of Us participants with known sex (male or female), race, income and education levels and estimated state-specific and demographic subgroup-specific prevalence of categories of BMI [obesity (BMI ≥30) and extreme obesity (BMI ≥ 35)] nationwide and for each state: overall and by subgroups, male and female. We examined the difference between EHR and PM calculated BMI by state.

Anticipated Findings

Using states with at least 100 participants, PM data included 142,116 individuals (mean [SD] age, 51.2 [16.6] and EHR data on height and weight included 40,885 individuals (mean [SD] age, 52.5 [16.5]. The median BMI for PM participants was 28.4 [24.4 to 33.7]; the median BMI for EHR was 29.0 [24.8 to 34.5]. The PM national prevalence for obesity (includes BMI>30 and BMI >35) and extreme obesity (BMI >35) were 41.2 % (95% Confidence Interval [CI], 40.9 to 41.4) and 20.8% (95% CI, 20.6 to 21.0), respectively, with large variations across states. Women had higher prevalence of extreme obesity than men in all selected states. Subgroups with extreme obesity (BMI, >35) prevalence greater than 25% included subgroup, N, prevalence %, (95% CI): Black NH, 8913, 28.9 (25.8 to 32.0) , individuals with income less than $25,000, 13,244, 25.1 (22.1 to 28.1); education of high school to some college, 17, 272, 26.1 (23.1 to 29.1) and the region of the South, 6,639, 25.3 (22.3 to 28.3).

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Education Level
  • Income Level

Research Team

Owner:

Revision_after_HTN_code_review

We are using the All of Us Researcher Workbench interface to answer the question, "Is hypertension prevalence in the All of Us Research Program similar to hypertension prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES) ?". Clinical…

Scientific Questions Being Studied

We are using the All of Us Researcher Workbench interface to answer the question, "Is hypertension prevalence in the All of Us Research Program similar to hypertension prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES) ?". Clinical approaches to understanding and treating hypertension may benefit from the integration of a precision medicine approach that integrates data on environments, social determinants of health, behaviors, and genomic factors that contribute to hypertension risk. Hypertension is a major public health concern and remains a leading risk factor for stroke and cardiovascular disease.

Project Purpose(s)

  • Other Purpose (This work is an AoU demo project. Demo projects are efforts by the AoU Research Program designed to meet the program goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. As an approved demo project, this work was reviewed and overseen by the AoU Research Program Science Committee and the AoU Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use. )

Scientific Approaches

In this cross-sectional, population-based study, we used All of Us baseline data from patient (age>18) provided information (PPI) surveys and electronic health record (EHR) blood pressure measurements and retrospectively examined the prevalence of hypertension in the EHR cohort using Systemized Nomenclature of Medicine (SNOMED codes and blood pressure medications recorded in the EHR. We used the EHR data (SNOMED codes on 2 distinct dates and at least one hypertension medication) as the primary definition, and then add subjects with elevated systolic or elevated diastolic blood pressure on measurements 2 and 3 from PPI. We extracted each participant’s detailed dates of SNOMED code for essential hypertension from the Researcher Workbench table ‘cb_search_all_events’. We calculated an age-standardized HTN prevalence according to the age distribution of the U.S. Census, using 3 groups (18-39, 40-59, ≥ 60).

Anticipated Findings

The prevalence of hypertension in the All of Us cohort is similar to that of published literature. All of Us age-adjusted HTN prevalence was 27.9% compared to 29.6% in National Health and Nutrition Examination Survey. The All of Us cohort is a growing source of diverse longitudinal data that can be utilized to study hypertension nationwide. The prevalence of hypertension varies in the United States (U.S.) by age, sex, and socioeconomic status. Hypertension can often be treated successfully with medication, and prevented or delayed with lifestyle modifications. Even with these established hypertension intervention and prevention strategies, the prevalence of hypertension continues to be at levels of public health concern. The diversity within All of Us may provide insight into factors relevant to hypertension prevention and treatments in a variety of social and geographic contexts and population strata in the U.S.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Miscellaneous

Trouble-shooting, thanks for your help, Francis.

Scientific Questions Being Studied

Trouble-shooting, thanks for your help, Francis.

Project Purpose(s)

  • Other Purpose (Trouble-shooting, thanks for your help, Francis.)

Scientific Approaches

no approach is necessary for this workspace because this is for operational use only.

Anticipated Findings

Trouble-shooting, thanks for your help, Francis.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

For_HTN_code_review

We are using the All of Us Researcher Workbench interface to answer the question, "Is hypertension prevalence in the All of Us Research Program similar to hypertension prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES) ?". Clinical…

Scientific Questions Being Studied

We are using the All of Us Researcher Workbench interface to answer the question, "Is hypertension prevalence in the All of Us Research Program similar to hypertension prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES) ?". Clinical approaches to understanding and treating hypertension may benefit from the integration of a precision medicine approach that integrates data on environments, social determinants of health, behaviors, and genomic factors that contribute to hypertension risk. Hypertension is a major public health concern and remains a leading risk factor for stroke and cardiovascular disease.

Project Purpose(s)

  • Other Purpose (This work is an AoU demo project. Demo projects are efforts by the AoU Research Program designed to meet the program goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. As an approved demo project, this work was reviewed and overseen by the AoU Research Program Science Committee and the AoU Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use. )

Scientific Approaches

In this cross-sectional, population-based study, we used All of Us baseline data from patient (age>18) provided information (PPI) surveys and electronic health record (EHR) blood pressure measurements and retrospectively examined the prevalence of hypertension in the EHR cohort using Systemized Nomenclature of Medicine (SNOMED codes and blood pressure medications recorded in the EHR. We used the EHR data (SNOMED codes on 2 distinct dates and at least one hypertension medication) as the primary definition, and then add subjects with elevated systolic or elevated diastolic blood pressure on measurements 2 and 3 from PPI. We extracted each participant’s detailed dates of SNOMED code for essential hypertension from the Researcher Workbench table ‘cb_search_all_events’. We calculated an age-standardized HTN prevalence according to the age distribution of the U.S. Census, using 3 groups (18-39, 40-59, ≥ 60).

Anticipated Findings

The prevalence of hypertension in the All of Us cohort is similar to that of published literature. All of Us age-adjusted HTN prevalence was 27.9% compared to 29.6% in National Health and Nutrition Examination Survey. The All of Us cohort is a growing source of diverse longitudinal data that can be utilized to study hypertension nationwide. The prevalence of hypertension varies in the United States (U.S.) by age, sex, and socioeconomic status. Hypertension can often be treated successfully with medication, and prevented or delayed with lifestyle modifications. Even with these established hypertension intervention and prevention strategies, the prevalence of hypertension continues to be at levels of public health concern. The diversity within All of Us may provide insight into factors relevant to hypertension prevention and treatments in a variety of social and geographic contexts and population strata in the U.S.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Collaborators:

  • Elizabeth Karlson - Late Career Tenured Researcher, Mass General Brigham
  • Cheryl Clark

Obesity analysis

state level obesity

Scientific Questions Being Studied

state level obesity

Project Purpose(s)

  • Disease Focused Research (obesity)

Scientific Approaches

Not available.

Anticipated Findings

state level obesity disparities after adjusting for socioeconomic factors

Demographic Categories of Interest

  • Sex at Birth
  • Education Level
  • Income Level

Research Team

Owner:

Collaborators:

  • Francis Ratsimbazafy - Other, All of Us Program Operational Use
  • Paulette Chandler - Senior Researcher, Mass General Brigham
  • Andrea Ramirez - Other, All of Us Program Operational Use
  • Elizabeth Karlson - Late Career Tenured Researcher, Mass General Brigham
  • Cheryl Clark

HTN

What is the prevalence of hypertension (HTN) defined using an electronic health record definition from eMERGE among UBR groups defined by race/ethnicity, income and education? Do treatment patterns for HTN (using medication sequencing analysis) vary by UBR groups defined by…

Scientific Questions Being Studied

What is the prevalence of hypertension (HTN) defined using an electronic health record definition from eMERGE among UBR groups defined by race/ethnicity, income and education?

Do treatment patterns for HTN (using medication sequencing analysis) vary by UBR groups defined by race/ethnicity, income and education, and in geographic regions based on grouping states?

Project Purpose(s)

  • Disease Focused Research (hypertension)

Scientific Approaches

Not available.

Anticipated Findings

There may be disparities in HTN across racial and income groups of policy interest.

Demographic Categories of Interest

  • Income Level

Research Team

Owner:

Collaborators:

  • Francis Ratsimbazafy - Other, All of Us Program Operational Use
  • Andrea Ramirez - Other, All of Us Program Operational Use

Code_share

What is the prevalence of hypertension (HTN) defined using an electronic health record definition from eMERGE among UBR groups defined by race/ethnicity, income and education? Do treatment patterns for HTN (using medication sequencing analysis) vary by UBR groups defined by…

Scientific Questions Being Studied

What is the prevalence of hypertension (HTN) defined using an electronic health record definition from eMERGE among UBR groups defined by race/ethnicity, income and education?

Do treatment patterns for HTN (using medication sequencing analysis) vary by UBR groups defined by race/ethnicity, income and education, and in geographic regions based on grouping states?

Project Purpose(s)

  • Disease Focused Research (hypertension)

Scientific Approaches

Not available.

Anticipated Findings

There may be disparities in HTN across racial and income groups of policy interest.

Demographic Categories of Interest

  • Income Level

Research Team

Owner:

Collaborators:

  • Paulette Chandler - Senior Researcher, Mass General Brigham
  • Lizette Mendez - Project Personnel, Boston Medical Center
  • Confidence Achilike - Project Personnel, Boston Medical Center
  • Nyia Noel - Mid-career Tenured Researcher, Boston Medical Center

legacy_codes

What is the prevalence of hypertension (HTN) defined using an electronic health record definition from eMERGE among UBR groups defined by race/ethnicity, income and education? Do treatment patterns for HTN (using medication sequencing analysis) vary by UBR groups defined by…

Scientific Questions Being Studied

What is the prevalence of hypertension (HTN) defined using an electronic health record definition from eMERGE among UBR groups defined by race/ethnicity, income and education?

Do treatment patterns for HTN (using medication sequencing analysis) vary by UBR groups defined by race/ethnicity, income and education, and in geographic regions based on grouping states?

Project Purpose(s)

  • Disease Focused Research (hypertension)

Scientific Approaches

Not available.

Anticipated Findings

There may be disparities in HTN across racial and income groups of policy interest.

Demographic Categories of Interest

  • Income Level

Research Team

Owner:

BWH_HTN

What is the prevalence of hypertension (HTN) defined using an electronic health record definition from eMERGE among UBR groups defined by race/ethnicity, income and education? Do treatment patterns for HTN (using medication sequencing analysis) vary by UBR groups defined by…

Scientific Questions Being Studied

What is the prevalence of hypertension (HTN) defined using an electronic health record definition from eMERGE among UBR groups defined by race/ethnicity, income and education?

Do treatment patterns for HTN (using medication sequencing analysis) vary by UBR groups defined by race/ethnicity, income and education, and in geographic regions based on grouping states?

Project Purpose(s)

  • Disease Focused Research (hypertension)

Scientific Approaches

Not available.

Anticipated Findings

There may be disparities in HTN across racial and income groups of policy interest.

Demographic Categories of Interest

  • Income Level

Research Team

Owner:

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