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Blurred Lines: An RWD/RWE Snapshot

by Elizabeth Kneeland | December 01, 2022

Executive Summary

New vendors continue to flood the real-world data and real-world evidence markets with analytics solutions that are powered by increasingly massive health datasets. Data cleaning and normalization solutions have been rolled into larger analytics and data vendors and no longer constitute their own sub-sector.

Post-market surveillance by the life sciences remains the most widespread activity using RWD/RWE, though marketing and sales uses are catching up quickly.

Clinical data is a rich source of information for all stakeholders, but only generated by a few of them, leading to novel models for partnerships and risk sharing.

Clinical research trial (CRT) optimization and management solutions are rapidly becoming their own market with increasingly specialized platforms and a dizzying array of new entrants.

Platforms targeting providers and healthcare organizations are stronger on integrations capabilities than they are on their ability to generate deep clinical insights for providers that can currently help them care for patients.


Key Takeaways:

  • The perceived highest value services are those that handle implementation and provide training and end-user support on behalf of the organization
  • Movement upstream remains focused on data entry accuracy and completeness; development within clinical decision support tools is moving much more slowly
  • Healthcare organizations need systems with strong integrations capabilities, which require more upfront investment, which most do not have right now absent future bailout legislation
  • The CRT process may be fundamentally transformed by the entry of retail pharmacy giants for recruitment and management

RWD/RWE Market Overview

Life sciences, payers, health care providers (HCPs), and healthcare organizations (HCOs), are the stakeholders who currently dominate the real-world data and real-world evidence market.

Payers and life sciences companies were the earliest entrants and remain the largest buyers.

Payers have been using claims data for nearly a decade to compare drug and treatment plans for safety and efficacy and to identify high utilization members; in turn, they use these insights to inform decisions on plan coverage and reimbursements and develop targeted strategies to better manage sicker patients.  This is helping to align payer and provider incentives in the ongoing transition from volume to value in medicine.

Life sciences companies have also been using these data for many years, in a growing number of applications in the drug R&D life cycle. The dominant use cases for life sciences are: post-market surveillance to fulfill pre-market commitments, improving clinical trials design, and marketing/sales.

Healthcare providers (HCPs) and healthcare organizations (HCOs) represent a much smaller but still growing market. While these participants have less capital for investing in comprehensive analytics platforms, they generate the lion’s share of clinical data, which is a rich and valued source of information, but one that also requires substantial cleaning and normalization prior to use.

Once normalized, these data can be used to support providers in identifying patient cohorts and optimal treatment pathways within the context of real-world populations. Hospitals and health systems seek platforms with strong integrations capabilities to aggregate clinical, operational, and financial data. From this single source of truth, insights can be gleaned to support operational and financial decisions, which are becoming increasingly complex as new payer risk models are becoming more prevalent, while labor costs are far higher than pre-pandemic levels.

Some datasets available now include multiple years of data, with records linked from disparate sources of clinical, claims, PROs, registries, social determinants of health (SDoH), consumer behavior, and even credit bureau datasets.  Chilmark’s upcoming Market Trends Report on RWD/RWE markets will compare dataset attributes of participating vendors in greater detail.

Powerful analytics software can link and perform analytics on these data to uncover deep insights of value to market stakeholders. We are just scratching the surface of what can be learned from these data – the RWD/RWE market will continue to grow at an aggressive pace. Sub-sectors of the market are emerging, all of which seem to promote convergence with provider incentives, with the notable exception of retail pharmacy giant entry into CRTs.

Forces that continue to encourage adoption of these solutions include:

  • A wave of bi-partisan legislation promoting development of RWD/RWE for health research
  • The shift from volume to value in healthcare[1]
  • The COVID-19 pandemic and jump in adoption rates of remote care technologies and clinical data exchange
  • Growing focus on the cost of care and need to demonstrate value to payers, providers, and regulatory bodies


Steady Demand for Clinical Data Cleaning & Normalizing Processes

The messiness of clinical datasets has generated strong demand for vendors specializing in efficient, secure, and transparent solutions to aggregate, clean, and normalize unstructured health records data.

The earliest startups leveraged natural language processing (NLP) and optical character recognition (OCR) technologies. Machine learning algorithms were trained on massive datasets of clinical records within  healthcare coding and medical ontologies. These start-ups were acquired by the established analytics vendors very quickly.

The underlying technologies for the automation components remain surprisingly underdeveloped. Such processes are still powered by substantial manual review, which, while relatively far more streamlined when augmented by ML, are not yet able to be fully replaced by these technologies.   

Nevertheless, they hold tremendous promise for a wide range of applications within the healthcare sector. As they continue to mature, they will transform the sector on a fundamental level, because they serve as lower risk inroads for ML/AI applications than within clinical decision-making support tools, many of which have been found to demonstrate racial bias post-deployment. Providers must be continually engaged in order for solutions to move further up the process chain. Some vendors offer platforms that can integrate into EHRs and generate real time nudges and alerts for users of the system. These are more commonly found in analytics solutions being developed by EHRs themselves and will likely prove a powerful differentiator for moving the needle on provider engagement.

Post-Market Surveillance Solutions Increasingly Used for Marketing

Fulfillment of post-market surveillance commitments was one of the first uses of RWE by the life sciences; payers, too, have been using these same data for years to determine product and procedure valuations, among other uses.

Marketing and sales strategy for life sciences is increasingly leveraging these same mechanisms, using the platforms to:

  • Monitor competing products
  • Demonstrate product safety and value
  • Identify trends in off-label usage and target populations
  • Develop strategies to target messaging for both patients and clinicians

Ease of integration is a key differentiator of the available solutions. Vendor services to support implementation and training are also increasingly recognized as critical to secure clients, regardless of size.

The most sophisticated platforms are developing mechanisms that work further upstream in the care process and ensure clean and complete data capture from the moment of entry, reducing the need for data cleaning and normalization services in the longest-term. However, most of these originally built for post-surveillance targeting solutions are not able to transmit data and perform analytics in near real time; as such, their value right now to providers, and to a lesser degree payers, remains limited.

The industry-wide movement into the cloud is supporting increased elasticity for both data storage and data processing. This will be important to render systems capable of supporting multiple stakeholders in the ways that will facilitate a smoother transition from volume to value.

CRT Optimization Solutions Market is Becoming Crowded

Substantial investment dollars are flowing into the clinical research trials (CRTs) component of the R&D pipeline for life sciences. Vendors have built software solutions that are highly specific to not only how CRTs are managed, but also how they are designed in the first place, with a patient-centric focus.

Nearly every clinical research organization (CRO) has established one or more partnerships with vendors to win contracts with life sciences to run their CRTs. These vendors have designed tools that aim to reduce participation burden for research subjects, sites, clinical staff, and principal investigators. When used for conducting CRTs, these integrated technologies are commonly referred to as distributed clinical trials (DCTs), or virtual/hybrid trials solutions or tools. These include telemedicine, ePROs, role-based portal access, and workflow support in the form of dashboards for simplified management of study activity, and fulfillment of regulatory requirements.

These higher value vendors in this space offer platforms capable of EHR integration, machine learning algorithms, and connections to datasets of competing trials information and referring provider activity. Again, we notice the importance of provider usability as a differentiator among vendors gaining the greatest market share.  

Retail Pharmacy Giants Entering CRT Optimization Solutions Market

Retail pharmacy giants are entering the CRTs space at a rapid clip and forming their own relationships with CROs and technology vendors. They are targeting ‘last mile’ activities with promises of greater diversity, faster recruitment, and reduced rates of subject attrition for life sciences. Retail pharmacies are familiar with the RWD/RWE market and its vast potential, as most of them have been selling their pharmacy datasets for many years already.

CVS, Walgreens, and recently Walmart have all announced their entrance into the CRTs realm within the past year. CVS and Walgreens have expressed intent to grow their respective scopes of involvement further upstream into protocol development and study design. Walmart recently announced a partnership with a generic drug maker in an unusual new vertical that does not involve a provider group partner in the mix.

There is a notable absence of provider influence in this corner of the market. Most of the clinical services being offered by retail pharmacy giants are not provided by physicians, but overwhelmingly by nurses, medical assistants, and pharmacists.

Healthcare Organizations Have RWD, Need RWE

Clinical data have greater dimensionality than claims data, but these data are overwhelmingly unstructured, and require substantial cleaning and normalization before use. This is regardless of the quality, size, type, and reputation of the HCO generating these RWD as a byproduct of providing care. Clinical data are continuously generated from a diverse array of specialized hardware and software sources, with the electronic health record (EHR) being only one of many.

Several vendors are offering HCOs clean, normalized, and curated versions of their clinical data, in exchange for the rights to use that data for other purposes. Vendors performing this service for their data providers include IQVIA, TriNetX, Cerner, and Epic.

But with HCOs, hospitals, and practices throughout the US closing their doors due to insolvency, there are few buyers with sufficient capital to invest in technology right now. The handful that do have cash remaining are skittish about spending it all in one place. Vendors that can offer modular solutions and are willing to explore non-traditional models for compensation are outperforming others.

[1] https://pharmanewsintel.com/news/fundamentals-of-the-pharmaceutical-supply-chain

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