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Home / Healthcare & Medicine / AI & Robotics / AI and Big Data in Global Health Improvement / Services And Possibilities OHDSI Offered

Services And Possibilities OHDSI Offered

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14.2
Many researchers want data for their research. However, the data owners think differently and there are many many problems sharing out data. Because of the technical issues, data quality, technical limitation and heterogeneity of the data structure and data meaning. And also there are legal issues. Especially for the private protection law and permission from the data owner. They don’t want share the data and work. It’s kind of depends on human nature. Can you share your diary? Except removing your name. Can you share your data for me? I want to use that your diary for very important things. Can you share? How many of you can share your data?
64.4
So basically we do not want to share “my data” because I’m afraid something can happens to that. So there are a lot of problems sharing the data. So this is how the distributed research network works. As you see the A hospital has this structure and meaning of their data, and B hospitals they have - all of them have different structure and meaning. In the OHDSI community we use common data model, that means we convert the different Hospital data into the same structure and same meaning. And here, let’s suppose every hospital have the same structure and same meaning in their Hospital. And rather than getting that data and navigating in my lab.
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Just we can send the analytic code into each Hospital. So we can make analytic code using it ourselves and send them into the hospital. And in the hospital we can administrate of the hospital, can learn this analogy code against the data. Then we can get the results such as hazard ratio, OHDSI ratio or summary statistics and then, the summary statistics can be used to the researchers. And the researchers only gathering, navigating the data, he can get the same result. With that, he pooled the data. So this is how the the disrelated distributed in such Network works. The researchers cannot see the individual patient data. Only he make an analatic code and send it to the hospital and get the results.
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That is how it works. So there is no issues on the project has information leakage. And you can use multiple databases for this purpose, and the analytic code can be used again and again. This is the OHDSI observation data sets and informatics, OHDSI and it was established 2013. It has six objectives, was included. Including innovation, reproducibility, community, collaboration, openness, and beneficence. And OHDSI now more than 200 institution around the world joined it to the community. and it has most CDM, it also has a standardized vocabulary. And now more than 99 databases from the world stater are converted into OMOP CDM. That means now 1.5 billion patient data are already converted into OMOP CDM. So it’s available to the world.
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And now there are more than 110 opens of tools utilizing the OMOPCDM data. So it is also open to anyone. So in the Github, type OHDSI, you can see all the source code of this open wares. And now more than 1,500 researchers and developers joined this community and all of them developed this OHDSI ecosystem for the research. As you see there are more than 110 open source tools in the github. Flash OHDSI, you can see. Even with your cell phone.

This video, Dr. Rae Woong Park introduces the organization, OHDSI, Observational Health Data Sciences and Informatics.

OHDSI is established to improve global health by empowering a community to collaboratively generate the clinical evidence and then to promotes better health decisions and better care. This community welcomes everyone to join. Whether you are a patient, a health professional, a researcher, or anyone interested.

We know that using Big Data required a communication platform and protocol for each user. OHDSI has established an international network of researchers and observational health databases with a central coordinating center housed at Columbia University.

Dr. Rae Woong Park will introduce its open-source tool in the next steps.

How do you feel about sharing your health data? If possible, your data can be “Anonymised,” would you willing to share for a certain purpose? Given what kind of situation was given would you willing to share? You are welcome to share your opinion on comments.

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This content is taken from Taipei Medical University online course
AI and Big Data in Global Health Improvement
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AI and Big Data in Global Health Improvement

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