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Original Question
purpose of this assignment is to provide learners with hands-on experience in designing, creating, and managing a relational database while analyzing real-world data related to prenatal care disparities. By completing this assignment, learners will: Understand Database Design Principles: Learners will apply foundational concepts of database design, including entity-relationship diagrams (ERD), normalization, and relationships between tables, to create an efficient and well-structured database. Practice SQL Skills: Learners will gain practical experience in creating tables, defining data types, inserting data, and writing SQL queries to retrieve meaningful insights from the database. Analyze Data to Address Prenatal Care Disparities: Through SQL queries and data visualizations, learners will analyze critical factors that contribute to disparities in prenatal care, such as socioeconomic factors, healthcare access, and health outcomes. Develop Data Visualization Skills: Learners will create data visualizations that highlight trends and patterns within the dataset, making the insights more accessible and actionable for stakeholders. Connect Database Insights to Real-World Issues: By working with prenatal care data, learners will gain a deeper understanding of how databases and data analysis can be used to address public health challenges and inform healthcare decision-making. Topic 4 Case Study: Prenatal Disparities Directions: For this case study, read the “Background” and “Objective”, then complete Parts 1-6. Background: Dr. West, a local public health department director, has recognized significant disparities in prenatal care among different population groups in its service area. He has brought this to the attention of the informatics department of which you are a part. These disparities manifest in lower access to care, delayed initiation of prenatal visits, and poorer birth outcomes among low-income, minority, and uninsured populations. The health department aims to address these disparities by gathering comprehensive data to inform targeted interventions, policy changes, and resource allocation. To achieve this, the health department has commissioned the development of a database to track and analyze prenatal care disparities, aiming to identify specific barriers and tailor solutions to improve maternal and infant health outcomes. Objective: The objective of the database is to collect and analyze data on prenatal care access, utilization, and outcomes among diverse patient populations to identify disparities and inform targeted public health interventions. The database will be used by healthcare providers, policymakers, and researchers to develop strategies that improve care for at-risk groups. Part 1: Entity Relationship Diagram (ERD) – Create an ERD using one of the tools below and the data elements below. Use the example of an ERD below for assistance. Example ERD: Use one of the following tools to create the ERD: Canva.com Conceptdraw.com Lucidchart.com Include the following Data Elements in the ERD: Patient Table: Patient ID (Primary Key) (4 numbers) Last Name Date of Birth Gender Race/Ethnicity Socioeconomic Status (Income Level, Education Level) Insurance Status (Insured/Uninsured) Geographic Location (ZIP Code, Urban/Rural) Prenatal Care Table: Care Episode ID (Primary Key) (first, second, etc. care visit) Patient ID (Foreign Key) (4 numbers) Date of First Prenatal Visit Number of Prenatal Visits (8,10, 14,16.20) Gestational Age at First Visit Healthcare Provider (Name) Type (MFM (maternal fetal medicine), obstetrics, infertility, midwife) Facility Name Type of Facility (Public/Private, Hospital/Clinic) Healthcare Provider Table: Provider ID (Primary Key) Name Specialty (MFM (maternal fetal medicine), obstetrics, infertility) Years of Experience Facility ID (Primary Key) (5 numbers) Facility Name Location (Address, ZIP Code) Type of Facility (Public/Private, Hospital/Clinic) Outcomes Table: Outcome ID (Primary Key) (3 numbers) Care Episode ID (Foreign Key) (first, second, etc. care visit) Birth Outcome (Full-term, Preterm, Low Birth Weight, Stillbirth) Complications (Yes/No) Postnatal Follow-up (Yes/No) Infant Health Status at Birth (preterm or full term) Disparity Indicator Table: Patient ID (Foreign Key) Access to Care (Distance to Facility) Language Barrier (Yes/No) Cultural Competency of Provider (Assessed by Patient Feedback) Yes, No Socioeconomic Barriers (Transportation, Childcare, Work Leave) Facility Table (Facility ID, Facility Name, Type of Facility) Part 2: Data Dictionary – generate five data dictionaries for all six tables below. Use the example a data dictionary below for assistance. Part 3: generate and Populate Tables in SQL File Format – Use DB Fiddle or SQL Fiddle and follow the instructions below to create and populate tables with data using the SQL queries. Use the list of “Data Elements” from Part 1 to incorporate into the tables. Use the following instructions to generate the tables: Insert at least 7 rows of data. Perform the following queries: Patient and Prenatal Care Tables: this table combines both the Patient and Prenatal Care tables from Deliverable 1. Identify Average Number of Prenatal Visits by Race/Ethnicity. Patient and Outcomes Table: This table combines both the Patient and Outcomes tables from Deliverable 1. Analyze Birth Outcomes by Income Level. Language Barriers Disparity Table – This table only identifies the Language Barriers from the Disparity Table from Deliverable 1. Parts 4-6: Data Visualizations – Use the three query tables generated in Part 3 to create the three data visualizations below in Word Excel. Then, reflect and explain the results. Using Word Excel to generate the following data visualizations: Part 4: Data Visualization 1 – generate a meaningful data visualization that highlights trends in prenatal care disparities using the database you generated. Part 5: Data Visualization 2 – Provide a second visualization focused on socioeconomic factors and prenatal disparities. Part 6: Data Visualization 3 – generate a third visualization showcasing the impact of language barriers on prenatal care disparities.
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