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Data is the currency of innovation in medicine these days and being able to collect, sort, and interpret clinical data can't be a little cumbersome, time-consuming, and exceedingly difficult. CDISC in healthcare is here to help transform clinical data. The Clinical Data Interchange Standards Consortium (CDISC) is the official organization to develop global standards in data structure to improve the interoperability of clinical trial data for patients, and regulators. The standards set global measures through application, removing transfers in murky webs and clouds, while improving transparency and efficacy in data interoperability, and ensuring safety for patients.

This blog draft will talk about the importance of CDISC in healthcare, its uses and benefits, and its future direction toward new reimbursements and value-based care to make healthcare data-driven. 

What is CDISC? 

The Clinical Data Interchange Standards Consortium, Inc. (CDISC) is a non-profit consortium that has developed and pioneered clinical research data standards. These standards allow any organization to collect, share, submit and store clinical research data in a recognized format. CDISC standards are utilized by regulatory authorities such as the U.S. Food and Drug Administration (FDA) or Japan's Pharmaceuticals and Medical Devices Agency (PMDA) for the review and discussion of clinical trial submissions. Organizations are also utilizing CDISC standards to develop workflows from their real world healthcare data initiatives which are critical to establishing standards for clinical decision making, research use, and public health decision making. 

CDISC Standards in Healthcare 

Historically, CDISC has been utilized in clinical trials, primarily in the pharmaceutical and biotechnology industries. As the healthcare industry is transitioning to interoperable and integrated data systems, the applicability of CDISC in healthcare has evolved to encompass additional areas.

Common Data Standards from CDISC (clinical data interoperability standards consortium) help standardize healthcare data from:

Electronic Health Records (EHRs)

Republicies

Claim databases

Real-world evidence (RWE) platforms

Public health surveillance systems

Utilizing CDISC standards promotes consistency, reliability and data re-usability which all contribute to clarification of research, comparative outcomes, and adherence to recommendations that are based on complex and voluminous datasets.

CDISC Core Standards

CDISC has a number of core standards that are based on foundations in healthcare and clinical research:

1. SDTM (Study Data Tabulation Model)

The SDTM is a standards framework used to organize and format the data gathered during a clinical trial, for submission to regulators.

2. ADaM (Analysis Data Model)

The ADaM standards framework ensures the ability to trace from raw data to a statistical result. This allows for the supporting analysis of the data being studied.

3. CDASH (Clinical Data Acquisition Standards Harmonization)

CDASH is a standards framework that harmonizes the data collection and data entry process, which helps reduce data entry errors and helps ensure that data are collected consistently.

4. SEND (Standard for Exchange of Nonclinical Data)

SEND is related to any data that has been analysed in non-clinical (mostly pre-human) environment, most importantly data analysed from a toxicology study.

5. ODM (Operational Data Model)

ODM establishes appropriate route of data exchange across a variety of system and platform constructs.

Why CDISC in Healthcare Matters

The application of CDISC in healthcare can provide many desired outcomes for stakeholders. 

✅ Greater Data Quality and Interoperability

CDISC builds standards for the structure and format of clinical research data which facilitates clinical research data integration into health care records while limiting inconsistencies and data silos.

✅ Speedy Research and Innovation

When clinical research data is transformed into CDISC data standards, the resulting structured data can be accessed much quicker with less time on data cleaning and more time focused on new insights and discoveries.

✅ Compliance with Regulatory Authorities

Health authorities (such as the FDA) require the use of CDISC standards when submitting data. These standards minimize the ambiguous and variably established definition of data submitted to the health authorities which can reduce the review time. 

✅ Improved Patient Safety and Quality of Care

CDISC provides valuable healthcare data integration; therefore health care provider can use the data together to make informed evidence-based decision making about patients that have better overall patient outcome. 

✅ Save Costs and Time

Standardized data helps eliminates redundancies, fosters stakeholder collaboration, and reduces the cost associated with managing data. 

Applications of CDISC in Real-World Healthcare

With the lines between clinical trials and real-world evidence having blurred, CDISC in healthcare is having a tremendous influence on:

1. Post-Market Surveillance

CDISC standard can monitor the safety and efficacy of medications outside of a controlled setting, identifying long-term outcomes as well as adverse events.

2. Clinical Registries

Establishing standards and aligning registry data, ensures consistency in the tracking of chronic illnesses, rare diseases, and their responses.The standardized data could be gathered from diverse subsets and populations and that demonstrates safety and efficacy.

3. Global Pandemic Response

The COVID-19 Pandemic created opportunities for CDISC to collaborate with other organizations to standardize data collection from public and private sources in order to track disease transmission and vaccine effectiveness and to understand the impact on public health broadly.

4. Health Data Exchange

When hospitals and clinics are using CDISC-compatible formats, they are able to easily integrate with those clinical research systems that allow clinicians to flow seamlessly from electronic health records (EHR) to clinical research database.

Barriers to Adoption of CDISC in Healthcare

While CDISC in healthcare offers tremendous opportunities, implementing CDISC standards in healthcare comes with its challenges:

Training and Awareness: Given that CDISC was designed for a clinical trial and research environment many clinicians are unfamiliar with CDISC standards and data and they will need training to make full utilization of CDISC data.

Legacy Systems: Many healthcare IT systems are older and, more commonly, either will not accept CDISC-compliant data or there is no incentive to change to accept CDISC-compliant data.

Resource Constraints: Smaller organizations may have limited expertise and funding for a transition to CDISC.

That said, regulatory pressures are increasing and the urgency for standardization of data and sharing of data across the clinical research enterprise is leading to greater investment in CDISC adoption across healthcare.

The Future of CDISC in Healthcare

As interest in real-world data (RWD) and real-world evidence (RWE) grows, CDISC will become a powerful resource for those interested in: 

- Personalized Medicine: Harmonized data is important for better patient stratification and will support precision therapies. 

- Artificial Intelligence and Machine Learning: Standardized data is crucial as the vast volumes of data needed to train reproducible and unbiased AI models won’t be achieved through free-text conversations in healthcare. 

- Global Collaboration: CDISC is a contributor to the ability to collaborate around the world, because your standardized data could be transferred across states and countries and organizations.

Furthermore, technological advances such as CDISC 360 will enable easier implementations based on metadata-driven automation. This will promote better use of CDISC and CDASH in the clinical care and clinical research environments. 

Conclusion

Integrating CDISC into the health care system is a significant step toward "smarter" data driven medicine. CDISC standards will help solve the needs of those who share data, those who analyze data, and the regulation of medicine as it further evolves and moves forward to support every patients' quality of life around the world.