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Standardized and systematic analysis of Healthcare Data is the foundation for better understanding the inner workings of interventions in healthcare: drug treatment, provider settings, quality measurements and cost reduction.

The OHDSI framework is the most advanced platform for developing solutions and applications in this area, and is getting more and more traction around the globe. The Odysseus Data Services, Inc. is intimately involved in this Open Source community through participation in research and development of the platform. We are therefore uniquely positioned to provide professional services for clients who do not wish or are not able to utilize the tools, artifacts and methods out of the box.

Observational data has tremendous potential to answer a myriad of important questions in healthcare:

- How can we identify new therapeutic targets quickly and effectively?
- Can we measure the relative impact of different treatment interventions?
- How can we predict patients with a high risk profile for certain diseases before they present with symptoms?
- How can we better prevent chronic conditions?
- What are the best care patterns to manage patients, especially with different combinations of comorbidities?
- How can we improve clinical trial design by focusing on patients with the best recruitment to effect size profile?
- How can we optimize adherence to treatment guidelines, and which factors influence patients' behavior?

Odysseus aims to provide data and tools for standardized systematic analytics of observational data at scale to answer these and other questions. The basis for these is the generation of standardized data. Odysseus supports the OHDSI platform (www.ohdsi.org). We provide services for standardization of the data, both in format as well as content (coding). We also build custom tools to make use of these standardized data.

Keywords

healthcare data analytics, life sciences, advanced data analytics, omop data standards, conversion, real world evidence, real world data, real world research, omop cdm, ohdsi, omop, rwe, rwd, observational research, software engineering, prometheus, arachne, ohdsi atlas, omop etl

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41
2015
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