OMOP Common Data Model (CDM)

In a fast result oriented and customer satisfaction oriented medical industry ANIRA CDM is designed for accommodating both administrative claims and HER. Here CDM is a Data Model which integrates multiple Databases.

“Electronic Medical Records (EMR) are aimed at supporting clinical practice at the point of care, while administrative claims data are built for the insurance reimbursement processes “is one of the basic advantages of CDM

ANIRA OMOP Creates Standardized structure where different types and attributes of Data can be allocated in same tables, same fields, same datatypes and same conventions across disparate sources.

Different Programming languages are also not a constraint as Source codes mapped into each domain standard so that now you can talk across different languages

Objectives of ANIRA OMOP development

  • One model to accommodate both administrative claims and electronic health records
  • Claims from private and public payers, and captured at point
  • EHRs from both inpatient and outpatient settings
  • Also used to support registries and longitudinal surveys
  • One model to support collaborative research across data
  • Sources both within and outside of US
  • One model that can be manageable for data owners and useful for data users (efficient to put data IN and get data OUT)
  • Enable standardization of structure, content, and analytics
  • Focused on specific use cases

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 ANIRA framework is the most advanced platform for developing solutions and applications in this area, and is getting more and more traction around the globe. ANIRA 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?

ANIRA 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. ANIRA supports the ANIRA platform (www.ANIRA.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.