Francis Ratsimbazafy

All of Us Program Operational Use

5 active projects

Demo - Hypertension Prevalence

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:

Duplicate of Cancer

We intend to explore the difference in the prevalence of cancer between the AoU population. In particular, we will be looking at the difference between the entire population, the subset with medical records, and the subset with self-reported data.

Scientific Questions Being Studied

We intend to explore the difference in the prevalence of cancer between the AoU population. In particular, we will be looking at the difference between the entire population, the subset with medical records, and the subset with self-reported data.

Project Purpose(s)

  • Population Health

Scientific Approaches

We intend to select a list of SNOMED codes corresponding to primary cancers to get the subset with cancer in the medical record

We intend to select the survey question asking about self-reported cancer to get the subset with self-reported cancer

Anticipated Findings

We expect the difference of cancer to vary between self-report and medical record, which could have implications for how cancer is measured on a population-level.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Collaborators:

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

Systemic Disease and Glaucoma (Cloned)

We have previously published a predictive model of glaucoma progression using electronic health record (EHR) data pertaining to systemic attributes from a single institution. We aim to use the All of Us dataset to 1) serve as external validation for…

Scientific Questions Being Studied

We have previously published a predictive model of glaucoma progression using electronic health record (EHR) data pertaining to systemic attributes from a single institution. We aim to use the All of Us dataset to 1) serve as external validation for this single-center model and 2) to train new models focused on predicting glaucoma progression using systemic predictors. This is important to understand whether the original findings are generalizable and provide additional knowledge about the utility of systemic predictors on a national-level dataset.

Project Purpose(s)

  • Disease Focused Research (Primary open angle glaucoma)
  • 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

We plan to primarily work with EHR data contained in All of Us for a cohort of adult participants diagnosed with primary open-angle glaucoma. We will extract data on systemic conditions and medications for this cohort, as well as physical measurements and vital signs. We will clean the data such that the format is consistent with the data from our previously published model. Then, we will use this data as an external validation of a logistic regression model derived from our prior study that was based at a single academic center. Next, we will use All of Us data to train a new set of models, using techniques such as logistic regression, random forests, and artificial neural networks. We will optimize these models using feature selection methods and class balancing procedures. By evaluating performance metrics such as area under the curve (AUC), precision, recall, and accuracy, we will assess whether we can achieve superior predictive performance when training models using All of Us.

Anticipated Findings

We anticipate that the All of Us data will validate the findings from the model, which demonstrated that blood pressure-related metrics and certain medication classes had predictive value for glaucoma progression. In addition, we anticipate that the models trained with All of Us data will outperform the model trained with single institution data due to larger sample size and greater diversity. These findings will support further investigation in understanding the relationship between systemic conditions like blood pressure with glaucoma progression.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

How to Backup Notebooks and Intermediate Results

Not applicable - these utility notebooks do not perform any analyses.

Scientific Questions Being Studied

Not applicable - these utility notebooks do not perform any analyses.

Project Purpose(s)

  • Other Purpose (Demonstrate to workbench users how to create snapshots of notebooks and backups of intermediate results stored in other files such as plot images and derived data.)

Scientific Approaches

Not available.

Anticipated Findings

Not applicable - these utility notebooks do not perform any analyses.

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:

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