What Is De-identified Real-World Data and How Is it Used?

Blog Posts  |  23 June 2023

Written by: Cheryl Reifsnyder, PhD

In today’s healthcare environment, real-world data (RWD) is being generated at an unprecedented rate. Patients generate data from wearable devices, mobile health technologies, and at-home diagnostic tools. Healthcare providers contribute real-world patient data with the near ubiquitous use of electronic health records (EHRs). Health plans and payers generate claims data as their members seek care and treatment.

When these data are de-identified, they become a powerful resource from which life science researchers and other healthcare stakeholders can derive key insights. This article explores what “de-identified data” are and how it is changing healthcare.

What are de-identified data?

The Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule protects most health information that could be individually identified. The Privacy Rule names this information “protected health information” (PHI), and it cannot be shared with other entities or organizations without patients’ express knowledge and consent.

De-identified data are data from which direct identifiers have been removed. “Direct identifiers” include details that might be used to identify the individual(s) and where the information was derived from—for instance, patients’ names, addresses, birth dates, email addresses, Social Security numbers, etc.

Data can be de-identified in a HIPAA-compliant fashion using one of two methods:

  • “Expert Determination” method: This requires enlistment of a qualified statistical expert to identify the risk of re-identification as very small.
  • “Safe Harbor” method: This method removes all the “specific identifiers” listed for the patient, which should include all identifiable data.

Neither method can completely remove all risk that patients might be re-identified, but both reduce that risk to a very low—and thus acceptable—level. After application of one of these methods, the patient information is no longer considered PHI and is no longer covered by HIPAA Privacy Rule restrictions. Covered organizations can share it with other entities while remaining compliant with the HIPAA Privacy Rule.

The Department of Health and Human Services states: “The process of de-identification, by which identifiers are removed from the health information, mitigates privacy risks to individuals and thereby supports the secondary use of data for comparative effectiveness studies, policy assessment, life sciences research, and other endeavors.”

How are de-identified data used?

RWD are collected nearly every day—every time you visit your healthcare provider, file an insurance claim, or open a health app on your cell phone. The entity collecting the RWD (e.g., the healthcare provider, health plan, or technology platform) may have rights to use that data for research—but unless they obtain the patient’s consent, the data must be de-identified.

Often, data curators take additional steps to link data in different sources or to map data to standard data models. These linkages can help optimize the data’s utility for analytics and research. For instance, claims data might be linked to EHR data. This connects the clinical information documented in a patient’s medical record with detailed information about services provided and their costs.

Life science research

De-identified RWD can be a powerful tool for life science researchers because it enables researchers to answer questions about patient populations without launching full-scale randomized clinical trials (RCTs). This can reduce time to market for new therapies; improve diversity in clinical research; and reduce costs of medical research. RWD can also help researchers:

  • Gain insights into therapies’ real-world performance
  • Provide evidence for expanding a medication’s approved indications for use in new types of patients, for new conditions, or for patients whose needs are not currently being met

As a result, many life science organizations are beginning to fully embrace using RWD. A survey of life science organizations found over 90% of respondents currently use RWD in clinical development and decision-making.

Data-driven treatment

The findings generated through analysis of de-identified RWD benefit healthcare providers as well. Although physicians have traditionally relied on evidence from RCTs to help guide their decisions regarding which drugs or devices to use in treatment, RWD can also help guide data-driven treatment decisions. RWD and the real-world evidence (RWE) derived from it are increasingly used to enhance RCT evidence to help physicians improve patient care.

Since RWD so dramatically benefits the healthcare system, there is growing clinical support for collecting RWD and using it to generate RWE. The American Medical Association has adopted a policy supporting the generation and use of RWD and RWE for purposes such as:

  • Evaluating the safety and effectiveness of medical products
  • Helping with regulatory decision-making
  • Enhancing research efficiency
  • Improving clinical care and outcomes for patients

Health plan and payer analytics

Researchers found that payers also recognize the value of RWD and RWE. Most of those surveyed believe that organizations should be open to using RWD as well as data from RCTs when making healthcare decisions.

Health plans and payers have found that evidence generated from de-identified RWD can promote informed safety monitoring, utilization management, and cost/value analysis. RWD can also help payers determine coverage for specific procedures; assess the health of their beneficiaries; or track and report quality of care. Some payers even see benefit in using de-identified RWD and its associated evidence to inform pharmacy and therapeutic (P & T) committee decisions.

Veradigm Real-World Data

Veradigm Real-World Data provides comprehensive, linkable RWD for use in generating RWE. Its data sets include:

  • Veradigm Network EHR Data: An easy-to-use data set that provides streamlined access to over 174 million patient records* by combining multiple EHR data sources within the Veradigm EHR network. It offers geographic, demographic, and social diversity via an extensive, nationally distributed patient population.
  • Veradigm Linked Claims: This data set links claims and EHR data to provide access to the clinical detail documented in the patient record linked to claims information covering costs and services. Linked claims are not limited by payer type or payment and provide both off-the-shelf and custom-linked data sets to fit your specific research needs.
  • Veradigm Clinical Data Registries: These include the Veradigm Cardiology Registry (formerly PINNACLE Registry) and Veradigm Metabolic Registry (formerly Diabetes Collaborative Registry), both operated in partnership with the American College of Cardiology. These registries provide access to curated data collected from a cross-sectional, geographically dispersed patient population.

Contact us to learn more about Veradigm’s Real-World Data and Real-World Evidence and how we can help you meet your research needs.

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