This page provides you with instructions on how to extract data from HIPAA and analyze it in Amazon QuickSight. (If the mechanics of extracting data from HIPAA seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What is HIPAA?
The Health Insurance Portability and Accountability Act (HIPAA) defines rules that American organizations must follow to securely handle and maintain Protected Health Information (PHI). To remain in compliance, organizations are required to have a signed Business Associate Agreement (BAA) from any partner organization that creates, receives, maintains, or transmits PHI. The partner must ensure that it will safeguard the PHI that passes through its systems. Businesses also have to meet a long checklist of compliance rules and practices.
What is QuickSight?
Amazon QuickSight is the AWS business intelligence tool for creating dashboards and visualizations. Users are charged per session only for the time when they access dashboards or reports. QuickSight supports a variety of data sources, such as individual databases (Amazon Aurora, MariaDB, and Microsoft SQL Server), data warehouses (Amazon Redshift and Snowflake), and SaaS sources (Adobe Analytics, GitHub, and Salesforce), along with several common standard file formats.
Getting HIPAA data
You migrate PHI just as you would any other data, but you must stay cognizant of HIPAA regulations. No one but you and the data source can handle the data unless you have a BAA in place with them.
You can use any methods your data provider offers to extract data from their service. Many cloud-based data sources provide APIs that expose data to programmatic retrieval. Others allow you to set up webhooks to push event data to requesters. For data that lives in a database, you can use SELECT statements or a utility that does a mass dump of the data you specify.
Loading data into QuickSight
You must replicate data from your SaaS applications to a data warehouse (such as Redshift) before you can report on it using QuickSight. Once you specify a data source you want to connect to, you must specify a host name and port, database name, and username and password to get access to the data. You then choose the schema you want to work with, and a table within that schema. You can add additional tables by specifying them as new datasets from the main QuickSight page.
Using data in QuickSight
QuickSights provides both a visual report builder and the ability to use SQL to select, join, and sort data. QuickSight lets you combine visualizations into dashboards that you can share with others, and automatically generate and send reports via email.
Keeping HIPAA data up to date
Once you've set up your data pipeline to your HIPAA data source, you can relax – as long as nothing changes. You have to keep an eye on any modifications that your sources make to the data they deliver. You should also watch out for cases where your script doesn't recognize a new data type. And since you'll be responsible for maintaining your script, every time your users want slightly different information, you'll have to modify the script. Keep in mind that HIPAA is all about rules and compliance, so you'll also have to know what HIPAA permits and proscribes, as will anyone else who works on the script.
From HIPAA to your data warehouse: An easier solution
As mentioned earlier, the best practice for analyzing HIPAA data in Amazon QuickSight is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites HIPAA to Redshift, HIPAA to BigQuery, HIPAA to Azure Synapse Analytics, HIPAA to PostgreSQL, HIPAA to Panoply, and HIPAA to Snowflake.
Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate HIPAA with Amazon QuickSight. With just a few clicks, Stitch starts extracting your HIPAA data, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Amazon QuickSight.