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There’s a seemingly never-ending flood of healthcare data and analytics in the industry. From medical claims, to predictive modeling, to artificial intelligence, the pool of data has never been bigger. But what are the major limitations that businesses are facing when it comes to leveraging this data? If you are among the ones with the problem of finding the right data sources and technologies to get your analytics going, this article is for you. We’ve got the names of three technologies that will help you solve the problem of data integration.

HIPAA Compliance for Data

One of the major factors which delay the pace of healthcare analytics is the complexity of HIPAA compliance. The healthcare sector is governed by an act of Congress known as HIPAA. This act is the reason why the majority of data is closely guarded. However, for your analytics to be truly successful, the data must be available. The process of data availability is known as data integration. The healthcare industry is coming up with ways to make data available while still following the rules of HIPAA.

Data Integration Process

The data integration process in the healthcare industry is similar to other industries. It starts with an intake process, which includes preparing data to be sent to analytics tools. The next step involves gathering the data from several sources. After that, data is normalized, cleaned, formatted, and loaded. Finally, a data model is constructed and the analytics are performed.

Since the data is at the heart of any kind of analytics, it is important to make sure that the integrity of the data is maintained. Various techniques are used to address issues with data quality, including statistical and visual audits, real-time tests, and more.

Source Data

For data integration to be successful, there are three major data sources that must be used. Here’s a brief overview of them:

Clinical trials. This data is used to determine the effectiveness of medical treatments. It includes information on trial participants, medical procedures, and the results obtained by the trial.

Biometric data. This includes information about patients’ facial features, body shape, height, weight, and the gender. This










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