Kaela Acuff

Graduate Trainee, University of California, San Diego

4 active projects

SDHA in Eye Conditions - v6 Dataset

We are planning to explore disparities in healthcare access and utilization for patients with eye conditions across different demographic groups. We would like to evaluate risk of developing advanced/severe disease in different eye conditions, and understand how social determinants contribute…

Scientific Questions Being Studied

We are planning to explore disparities in healthcare access and utilization for patients with eye conditions across different demographic groups. We would like to evaluate risk of developing advanced/severe disease in different eye conditions, and understand how social determinants contribute to this risk while adjusting for other known risk factors. We are also interested in understanding the availability of social determinants of health data in this data repository compared to EHR clinical data warehouses alone.

Project Purpose(s)

  • Population Health

Scientific Approaches

We will build cohorts of patients with various eye diseases (i.e. diabetic retinopathy, retinal vein occlusions, glaucoma, etc.). Then we will develop concept sets and extract data on outcomes (i.e. development of complications), as well as predictors including clinical data and social data. We will draw on survey data and EHR data within All of Us. When genomic data and wearable data become available, we are interested in evaluating those data sources as well. We will use statistical modeling and machine learning to generate predictive models.

Anticipated Findings

We anticipate that there may be differential risk for developing complications based on disparities in healthcare access and utilization for patients with eye conditions.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Geography
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Registered Tier

Research Team

Owner:

Collaborators:

  • Joy Guo - Graduate Trainee, University of California, San Diego
  • Bonnie Huang - Graduate Trainee, Northwestern University
  • Kiana Tavakoli - Research Fellow, University of California, San Diego

POAG in OSA

The purpose of this study is to analyze the prevalence of primary open angle glaucoma in obstructive sleep apnea and compare overall rates with prevalence among minority groups. Previous studies have shown a higher prevalence in minority groups such as…

Scientific Questions Being Studied

The purpose of this study is to analyze the prevalence of primary open angle glaucoma in obstructive sleep apnea and compare overall rates with prevalence among minority groups. Previous studies have shown a higher prevalence in minority groups such as African Americans, Asians, and Latinos. However, studies have been limited by population size or have not controlled for related diseases.

Project Purpose(s)

  • Population Health
  • Social / Behavioral

Scientific Approaches

The base cohort will be defined as patients with obstructive sleep apnea, either by diagnosis code or PMH survey response reporting prior diagnosis. The primary open angle glaucoma group will include patients with a diagnosis code. A cross-sectional analysis of sleep apnea cohort for patients who have been diagnosed with POAG vs non-OSA patients. Further analysis will use logistic regression to obtain odds ratios for base cohort separated by race/ethnicity to see if there is a statistically significant increase of incidence among minority groups. Covariates will include demographic information including age, sex, gender, income level, insurance, BMI, and smoking status as well as associated conditions including hypertension, diabetes, coronary artery disease, peripheral artery disease, hyperlipidemia, lipid metabolism disorders, cataracts, and stroke. All analysis will be performed in All of Us database.

Anticipated Findings

Based on prior research, anticipated results include an increased incidence of POAG in patients with OSA. Further analysis is expected to reveal increased incidence among minority groups than in White population. This will help with targeting certain populations for intervention and clarifying risk factors for developing POAG among patients with OSA.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Kaela Acuff - Graduate Trainee, University of California, San Diego

Glaucoma Severity

This study intends to analyze various socioeconomic characteristics across glaucoma stages to assess if disease severity correlates with factors such as race/ethnicity, income, education level, or insurance status. The same cohort will then be used to see if certain barriers…

Scientific Questions Being Studied

This study intends to analyze various socioeconomic characteristics across glaucoma stages to assess if disease severity correlates with factors such as race/ethnicity, income, education level, or insurance status. The same cohort will then be used to see if certain barriers to care identified in the Health Care Access and Utilization Survey correlate with worsening glaucoma severity. This will help guide interventions to improve eye care utilization and eye care disparities.

Project Purpose(s)

  • Population Health

Scientific Approaches

Our cohort is made up of patients diagnosed with glaucoma and separated by stage to include mild, moderate, severe, and unspecified with limits to ensure patients are not counted multiple times. Patients with multiple glaucoma diagnoses are excluded. The desired characteristics such as age, age at first diagnosis, income, education, insurance status, and race/ethnicity have been added to the concept set as well as questions relating to eye care and barriers to care chosen from the HCAUS. Variables will be compared across glaucoma stages using chi square analysis and odds ratios. Findings will guide us towards potential interventions to improve healthcare disparities. Analysis will be conducted within the NIH All of Us Workspace.

Anticipated Findings

Anticipated findings include disparities based on socioeconomic factors leading to increased severity of disease among patients from disadvantaged backgrounds. It is anticipated that answers to the HCAUS will highlight barriers to care which may be contributing to these disparities and lead to the development of action plans which will help alleviate these disparities.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Geography
  • Access to Care
  • Education Level

Data Set Used

Registered Tier

Research Team

Owner:

SDHA in Eye Conditions - v5 Dataset

We are planning to explore disparities in healthcare access and utilization for patients with eye conditions across different demographic groups. We would like to evaluate risk of developing advanced/severe disease in different eye conditions, and understand how social determinants contribute…

Scientific Questions Being Studied

We are planning to explore disparities in healthcare access and utilization for patients with eye conditions across different demographic groups. We would like to evaluate risk of developing advanced/severe disease in different eye conditions, and understand how social determinants contribute to this risk while adjusting for other known risk factors. We are also interested in understanding the availability of social determinants of health data in this data repository compared to EHR clinical data warehouses alone.

Project Purpose(s)

  • Population Health

Scientific Approaches

We will build cohorts of patients with various eye diseases (i.e. diabetic retinopathy, retinal vein occlusions, glaucoma, etc.). Then we will develop concept sets and extract data on outcomes (i.e. development of complications), as well as predictors including clinical data and social data. We will draw on survey data and EHR data within All of Us. When genomic data and wearable data become available, we are interested in evaluating those data sources as well. We will use statistical modeling and machine learning to generate predictive models.

Anticipated Findings

We anticipate that there may be differential risk for developing complications based on disparities in healthcare access and utilization for patients with eye conditions.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Geography
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Registered Tier

Research Team

Owner:

  • Terrence Lee - Graduate Trainee, University of California, San Diego
  • Tonya Lee - Graduate Trainee, University of California, San Diego
  • Sophia Sidhu - Graduate Trainee, University of California, San Diego
  • Sally Baxter - Research Fellow, University of California, San Diego
  • Kaela Acuff - Graduate Trainee, University of California, San Diego
  • John McDermott - Graduate Trainee, University of California, San Diego
  • Grace Ahn - Graduate Trainee, University of California, San Diego
  • Gordon Ye - Undergraduate Student, University of California, San Diego
  • Alison Chan - Graduate Trainee, University of California, San Diego
  • Bita Shahrvini - Graduate Trainee, University of California, San Diego
  • Bharanidharan Radha Saseendrakumar - Project Personnel, University of California, San Diego
  • Arash Delavar - Graduate Trainee, University of California, San Diego

Collaborators:

  • Francis Ratsimbazafy - Other, All of Us Program Operational Use
  • Jun Qian - Other, All of Us Program Operational Use
  • Joy Guo - Graduate Trainee, University of California, San Diego
  • Bonnie Huang - Graduate Trainee, Northwestern University
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