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Hephestus: Health data warehousing tool for public health and clinical research

Originally published by Bell Eapen at nuchange.ca on November 3, 2018. If you have some feedback, reach out to the author on TwitterLinkedIn or Github.

Health data warehousing is becoming an important requirement for deriving knowledge from the vast amount of health data that healthcare organizations collect. A data warehouse is vital for collaborative and predictive analytics. The first step in designing a data warehouse is to decide on a suitable data model. This is followed by the extract-transform-load (ETL) process that converts source data to the new data model amenable for analytics.

The OHDSI – OMOP Common Data Model is one such data model that allows for the systematic analysis of disparate observational databases and EMRs. The data from diverse systems needs to be extracted, transformed and loaded on to a CDM database. Once a database has been converted to the OMOP CDM, evidence can be generated using standardized analytics tools that are already available.

Each data source requires customized ETL tools for this conversion from the source data to CDM. The OHDSI ecosystem has made some tools available for helping the ETL process such as the White Rabbit and the Rabbit In a Hat. However, health data warehousing process is still challenging because of the variability of source databases in terms of structure and implementations.

Hephestus is an open-source python tool for this ETL process organized into modules to allow code reuse between various ETL tools for open-source EMR systems and data sources. Hephestus uses SqlAlchemy for database connection and automapping tables to classes and bonobo for managing ETL. The ultimate aim is to develop a tool that can translate the report from the OHDSI tools into an ETL script with minimal intervention. This is a good python starter project for eHealth geeks.

Anyone anywhere in the world can build their own environment that can store patient-level observational health data, convert their data to OHDSI’s open community data standards (including the OMOP Common Data Model), run open-source analytics using the OHDSI toolkit, and collaborate in OHDSI research studies that advance our shared mission toward reliable evidence generation. Join the journey! here

Disclaimer: Hephestus is just my experiment and is not a part of the official OHDSI toolset.

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OpenSource

Are you ready to ‘Git’ into Open Source

Open Source health information systems provide cost-effective tools for healthcare. Even if you are not a coder, you may be able to contribute to open source projects. As a matter of fact, some open-source projects find it difficult to get volunteers to document and test the code. E-Health enthusiasts from the clinical and management fields often want to contribute to popular open source projects, but do not know how. 

Open source projects involve a collaboration of people with various skills, often with no way of physically meeting each other. In a complex software product, even a misplaced comma can break the system. How do open source projects effectively collaborate avoiding such code-breaking mistakes? Well, they use some specialized tools and workflows to manage code, many of which are not familiar to non-programmers. In the next few posts, I will introduce you to the most important tool that coders use; the versioning system. We shall discuss Git (the most popular versioning system), from a non-programmers perspective.

This is not for those who are familiar with Git and we will not be discussing advanced Git usage. Hence, let me state the assumptions that I am making about you as the reader. You have not heard of Git before. You are as scared of code as you are scared of python. When you hear Java, the first thing that comes to your mind is the island in Indonesia. You don’t know what ‘typing on the command line’ means. But you own a computer, know how to download and install programs, know how to navigate the web, wants to learn more about contributing to open-source projects and above all want to help save lives especially in resource-deprived areas. Watch the video below for inspiration.

At the end of this journey, you will know how to follow open-source projects and make minor code contributions. This might initiate you into learning computer programming, but that is not my intention. You might even win a free T-Shirt from DigitalOcean. If you are ready to jump right in, follow the steps herehttp://wiki.canehealth.com/index.php/GIT:_First_Steps_(Creating_GitHub_Account_and_Downloading_SourceTree)