The Executive Suite: The benefits of acquiring new real world data for medical special societies and patient advocacy organizations

Not-for-profit healthcare organizations such as medical special societies (MSSs) and patient advocacy organizations manage vital data registries about patients and providers for specific research, quality, and educational purposes. However, given the limited scope of their registries, they often fail to fully address broader organizational and research needs.

Shifting market conditions, particularly a changing regulatory environment and a movement towards patient centric data ownership, are driving an increased supply and demand for health data that can provide more comprehensive views of complex patient pathways. Increased access to patient-centric data sources such as electronic health records, patient reported outcomes, claims data, and genomic data is driving a renewed interest in patient registries as a potential nexus for a more holistic view of the patient experience.

MSSs and patient advocacy organizations are ideally positioned to take advantage of these market shifts and become the go-to data resource for their specialty area. Embracing new data sources and acting as a trusted data steward can bolster these organization’s convening powers, strengthen their collaborations with other health care stakeholders, and drive collective insights that will benefit patients and providers alike.

What is the value of acquiring new types of real world data

Augmenting registries with additional types of data can provide a more comprehensive understanding of patient journeys across the continuum of care. Additionally, acquiring new data sources can support an organization’s mission and long-term financial sustainability by addressing critical research questions and by enabling new use cases and market offerings. While the research questions supported will vary widely based on current scientific and care paradigms, market offerings generally include: real word research, trial recruitment and support, QI and implementation science programs, development of new digital quality measures, patient preference and satisfaction research, utilization management, and/or provider and patient-centric benchmarking.

What are the challenges to identifying, evaluating, and integrating real world data sources

Data landscapes are growing progressively more crowded as the supply and demand for data continues to expand. However, despite this growing availability of data, there is huge variation in the quality, coverage, and value of each data source. The process of selecting the most appropriate data source(s) can be an overwhelming task. Organizations need a systematic way of identifying, assessing, prioritizing, and partnering with relevant data source owners best suited to address current and future organizational and research needs.

How to set up a data landscaping and sourcing process

Successful organizations follow a methodical process to identify and prioritize third-party data sources. This three-step process includes:

Step 1: Data needs prioritization and qualitative data source assessment: To start organizations need to define and prioritize their unmet needs and existing data gaps. Once these are identified, a thorough review of the existing data landscape should be conducted through literature reviews and internal knowledge gathering. This list is then further refined through interviews with data source owners to better understand the data variables, quality, access requirements, and permitted data uses.

Step 2: Quantitatively evaluate datasets: Based on the qualitative assessment, a small number of highly promising datasets are then selected for a more intensive quantitative pilot. The goal of this stage is to work directly with the database owners to understand the presence, completeness, and quality of key variables required to address your organizational needs, in addition to the feasibility of linking the new data to an existing registry.
Step 3: Partner with the best data sources for your organization: Following the quantitative evaluation, you will be ready to select the most promising dataset(s) to formally partner with.

No “one-size fits all” approach to assessing value of new data sources

It is important to note that the most appropriate data sources to assess and partner with will also vary significantly based on current data and capabilities. For example, an MSS may find less value in EHR data if they already obtain this data from providers in their quality registries. Instead, they may prefer to link claims data to help them obtain a more complete view of the patient pathway, enabling the capture and characterizing of the outcomes and risk factors that occur along each patient’s journey more accurately. On the flipside, patient advocacy organizations may find EHR data particularly valuable for gaining a fuller understanding of the patient journey for their unique populations.

The need to transform data into insights will continue to grow

As the amount of real world data continues to grow, so too will the need to turn that data into meaningful insights that can advance knowledge, support providers, and improve patient care. Patient advocacy organizations and MSSs who can successfully leverage and augment their existing registries with new sources of data will be well positioned to fulfill their missions and support their members now and well into the future.