Prenatal Care in Georgia Counties
Capstone Project for the Google Data Analytics Certification
Scenario
I am a junior data analyst working on the marketing analyst team at a fictional nonprofit, FAMily!, whose mission is improving maternal and fetal health outcomes in the state of Georgia.
Business Task
Eva Faulkner, the Programs Director at FAMily!, believes that low prenatal care rates are contributing to poor birth outcomes such as low birth weight. She wants to launch a program offering free transportation to prenatal visits. Mariah Ferry, the Marketing Director, will be running the campaign to bring awareness to the program.
Before a statewide program is implemented, the Board of Directors would like to do a pilot campaign in one county to see if it is effective, and which marketing avenues reach the target audience.
I have been tasked with answering three questions
Are low prenatal care rates and poor birth outcomes correlated?
What county in Georgia has the highest percentage of people giving birth who received little or no prenatal care?
What age groups have the highest percentage of people giving birth who received little or no prenatal care?
The final deliverable will be recommending a county for the pilot program, and what age range to target for advertising the program.
Data Source
I used data from the Online Analytical Statistical Information System (OASIS) Web Query Tool, Georgia Department of Public Health, Office of Health Indicators for Planning (OHIP).
The standardized health data repository used by OASIS is currently populated with Vital Statistics (births, deaths, fetal deaths, induced terminations, pregnancies), Hospital Discharge, Emergency Room Visit, Youth Risk Behavior Survey (YRBS), Behavioral Risk Factor Surveillance Survey (BRFSS), STD, Motor Vehicle Crash, and Population data.
I used data for the years 2019-2021 containing data on county of birth, total number of births, low birthweight births, births with little or no prenatal care, and age range of birthing persons
Processing the Data
As this dataset was relatively small, I chose to use Google Sheets to clean my data and prepare it for analysis.
Cleaning
Cleaned column names
Removed rows not containing data
Checked column types
Preparing
Created new column to combine “very low birthweight” with “low birthweight” columns in “all_lbw” column
Created new column to combine “<5 prenatal visits” with “late or no care” columns into “all_lpc” column
Created new columns to calculate percentages of births within each category
Confirmed that all of my subcategories added up to the total number of births
Saved file as .csv to proceed to analysis
Analysis and Visualization
I used Tableau to analyze and visualize my data.
First, I created a scatter plot clearly illustrating that percent of low prenatal care and low birthweight are correlated.
My next step was to identify the counties in the state that had the highest rates of low prenatal care. I first created a map view:
The metro Atlanta area clearly stands out as having the highest rates. (This was interesting to me as I had assumed that rural counties would have higher rates. I made a mental note to look into this later, and got back to the task at hand).
I then created a bar graph with the 10 counties that had the highest rates:
Fulton County has the highest percentage of low prenatal care in the state of Georgia.
My third task was identifying which age group had the highest rates of low prenatal care.
The 25-29 age group is the highest.
Recommendations
I presented my results to Eva, Mariah, and members of the BOD. (Slide presentation below)
My recommendations are:
Perform the pilot program in Fulton County
Advertise to the 25-29 year age group
For further analysis:
Follow up after a year and compare the rates of prenatal care and low birthweight babies to see if the program has been effective
Design a survey for participants to gain insight on satisfaction with the program and suggestions for improvement