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Resource Big Data Analytics in Healthcare Jon Duke, George Ripsaw, Patrick Ryan www.ohdsi.org/medinfo2015tutorialIntroductionIntroducing OH DSI The Observational Health Data Sciences and Informatics

How to fill out ohdsi cdm

How to fill out OHDSI CDM:

1. Understand the purpose of OHDSI CDM: OHDSI CDM (Observational Health Data Sciences and Informatics Common Data Model) is a standardized data model designed to integrate and analyze healthcare data from different sources. Before filling it out, it is essential to understand the specific goals and requirements of the OHDSI project or study you are working on.
2. Gather the necessary data: Identify the data sources that will contribute to the OHDSI CDM. These sources may include electronic health records, claims data, registries, or other healthcare databases. Ensure that the data is relevant, reliable, and comprehensive.
3. Map the data to the CDM structure: The OHDSI CDM provides a predefined schema that helps organize and standardize data elements. One of the crucial steps in filling out the CDM is mapping the data from the source databases to the appropriate CDM tables and fields. Use the OHDSI documentation and mapping tools to facilitate this process.
4. Transform and load the data: After mapping the data, transform it into the appropriate format required by the CDM. This may involve converting data types, normalizing values, or aggregating information. Implement an ETL (Extract, Transform, Load) process or leverage existing tools like Achilles or Atlas for data transformation and loading.
5. Validate the data: Perform thorough data validation to ensure accuracy and consistency. Use validation scripts or tools provided by OHDSI to check for any missing or erroneous data. Address any issues or inconsistencies found during this process.
6. Document the data mapping and transformation: Maintain clear documentation throughout the entire process. Document the data sources, mapping decisions, transformations applied, and any assumptions made during the CDM filling process. This documentation will be valuable for future reference and reproducibility.
7. Ensure data privacy and security: As you fill out OHDSI CDM, it is crucial to prioritize data privacy and security. Adhere to the necessary privacy regulations, de-identify sensitive information, and implement appropriate access controls to protect patient confidentiality.
8. Continuously monitor and update the CDM: Data in the CDM may evolve and require updates over time. Regularly monitor the data quality, apply necessary updates, and track any changes made to the CDM structure.

Who needs OHDSI CDM:

1. Researchers: OHDSI CDM is primarily targeted towards researchers in the field of healthcare data analytics. Researchers can leverage the standardized data model to integrate and analyze data from multiple sources, facilitating comparative effectiveness studies, safety surveillance, and other observational research.
2. Healthcare institutions: Healthcare institutions, such as hospitals, clinics, or health systems, may implement OHDSI CDM to organize and standardize their internal data for research and analysis purposes. By adopting the CDM, these institutions can contribute to collaborative studies and evidence generation in the broader OHDSI community.
3. Data scientists and analysts: Data scientists and analysts specializing in healthcare data can benefit from OHDSI CDM by having a consistent and harmonized data structure to work with. It allows them to focus more on analyzing data rather than dealing with data harmonization and integration challenges.
4. Public health agencies and policymakers: OHDSI CDM enables public health agencies and policymakers to leverage real-world data for population health assessments, policy evaluations, and healthcare decision-making. By using a standardized data model, they can gain insights into the effectiveness, safety, and comparative outcomes of healthcare interventions.
5. Software developers: OHDSI CDM serves as a foundation for the development of various software applications and tools within the OHDSI ecosystem. Software developers can build applications that facilitate data analysis, data visualization, or predictive modeling using the standardized CDM structure.

Overall, OHDSI CDM caters to a wide range of stakeholders involved in healthcare research and analysis, aiming to democratize access to high-quality healthcare data and promote collaborative discoveries.

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What is ohdsi cdm?

OHDSI CDM stands for Observational Health Data Sciences and Informatics Common Data Model. It is a standardized database schema used for organizing and storing healthcare data for research purposes.

Who is required to file ohdsi cdm?

Researchers, healthcare professionals, and organizations involved in healthcare data analysis and research are required to implement and use OHDSI CDM in their projects.

How to fill out ohdsi cdm?

OHDSI CDM can be filled out by mapping and transforming data from various healthcare sources into the standard schema defined by OHDSI. Tools and guidelines are provided by OHDSI for this purpose.

What is the purpose of ohdsi cdm?

The purpose of OHDSI CDM is to enable standardized analysis and comparison of healthcare data across different sources and studies. It facilitates collaborative research and allows for more efficient data analysis.

What information must be reported on ohdsi cdm?

OHDSI CDM requires information such as patient demographics, medical diagnoses, procedures, medications, laboratory results, and healthcare encounters to be reported in a standardized format.