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The Emerging Role of Data Science in the Health Plan Marketplace

Analysis  |  By Laura Beerman  
   November 01, 2021

"Payers have understood the value prop very quickly: the best fit for the customer is ideally the best fit for the plan," says one executive.

The data scientists will see you now. In fact, they're here to help not only healthcare consumers but payers through a growing number of insurtech platforms. Independent marketplace platforms are one example, offering payers increased customer retention potential through big data, artificial intelligence (AI), and their linkages to risk analysis, plan selection, and broader health and wealth planning. Such marketplace solutions could provide the missing ingredient for consumer-driven healthcare that complements payer efforts via scale, longevity, and positive customer experience.

How data science supports healthcare's "risk-takers"

A recent study from the Irish Journal of Medical Science defines data science as "an interdisciplinary field that extracts knowledge and insights from … big data." Specific to the health industry, the study further states: "Data science provides aid to process, manage, analyze, and assimilate the large quantities of fragmented, structured, and unstructured data created by healthcare systems. This data requires effective management and analysis to acquire factual results" including the "data cleansing, data mining, data preparation, and data analysis used in healthcare applications."

Technology's solutions often create new problems. The importance of data science and AI to fully utilize the big data generated by healthcare systems is but one example, with insurtech emerging as part of the solution subset. Insurtech includes new entrants (often startups) in health plan products, operations, benefits management, and the focus of this article, marketplaces.

Data and the data science that harnesses it have the power to aid payers and startups alike—and even unite them. PitchBook writes: "The growth and increased availability of traditional and nontraditional data sources enable startups to build patient management platforms that provide the risk-takers—including insurers, risk-taking providers, and self-insured employers—with a better understanding of individual healthcare needs."

"Building a better front door"

One such startup is Healthpilot, a new insurtech company using "data science at scale and proprietary decision-support technology to find and match consumers with Medicare plans that match their unique profile." Healthpilot also helps consumers enroll online by transferring their application information to the chosen payer for processing. Plan options include Medicare Advantage (MA), Medicare Supplement, and stand-alone Medicare Prescription Drug Plans (PDP).

Healthpilot's fully online customer engagement and enrollment model combines data collected from customers with diverse, third-party data from multiple sources to create individualized plan recommendations based on the Medicare plans available in the service area. "Our algorithm does two things," says CEO Dave Francis. "It cross-references personal information against larger data sets to create a risk profile and the customer's likely utilization of healthcare resources over the next year." Those larger data sets include aggregated medical claims data from millions of patients nationwide.

"With this information, says Francis, "we can get a pretty good match of who you are from a health utilization perspective, take that score, match it against plans in your ZIP code, and from there match your needs to the best plan for you." Customers indicate their preferences and see the top plan recommendation that fits them best, along with others for easy, transparent comparison. Think of it as Spotifying healthcare, although Francis cites another company, Amazon, as the inspiration for the company’s business model. "It's very forward-looking. This is rooted in data science's ability to bring in instant predictive analytics for the customer’s benefit."

How payers benefit

In addition to a better front door, Healthpilot seeks to offer a back door that stays comfortably shut—i.e., promotes customer retention through continued, personalized support that benefits payers as well. "Post enrollment, we continue to use data and data pathways that help us stay up to date with customers and create ongoing recommendations and targeted communications," says Francis. This data includes individual utilization data and marketplace changes (e.g., benefits, physician networks, pharmacy coverage). Healthpilot has plans to expand beyond Medicare to offer a comprehensive marketplace.

Francis notes that this kind of ongoing engagement "is not mutually exclusive with payer relationships. One of our biggest concerns was that we wouldn't get the time of day with big payers. We were humbled and surprised that they understood the value proposition quickly." That value proposition includes:

  • Improving risk analysis
  • Helping plans enroll the best-matched customers
  • Driving long-lasting relationships
  • Reducing customer complaints
  • Improving customer satisfaction

These benefits mirror those that insurtech startups in general can deliver to payers and other stakeholders. The more directly better plan choice can be correlated to better customer health and experience would be a boon to payers and insurtech providers alike. Francis continues: "The best fit for customers is ideally the best fit for the plan. Data science helps us put the customer in that place."

The broader impact could include improvements in how payers communicate and market to customers, including positioning coverage choices as a function of comprehensive health and wealth planning. In a 2021 research brief on value-based care models, The Geneva Association recommends that insurers "capture the opportunities afforded by the convergence of life and health products and solutions."

Data science implications for consumer-driven healthcare

So can data science, insurtech, and decision-support tools combine to deliver customers and carriers that are perfectly matched? A 2020 JAMA Health Forum article notes: "Some health insurance decision aids that incorporate consumer preferences have been experimentally shown to improve decision self-efficacy and confidence in health plan choice. However, …  [f]urther research is needed to determine the effect of decision support tools on access to and utilization of desired and high-quality health care services, health outcomes, and financial burden while covered under a plan."

This research and insurtech's rise comes at a time when the industry is wise to examine how technology can aid consumer-driven healthcare. Healthpilot's Francis notes that his company's model is to "service, not sell." That word—service—has become essential to intertwining technology's products with its value message (e.g., data-as-a-service, software-as-a-service, platform-as-a-service). Data-science-as-a service could very well be next in line.

Data science's impact on the value chain

The Irish Journal study cited previously states that data science and big data analytics help build "a comprehensive view of patients, consumers, and clinicians." The ideal solutions will create that view for these stakeholders as well. "Big data is a revolution in the world of health care. The attitude of patients, doctors, and healthcare providers to care delivery has only just begun to transform."

Francis agrees: "There is no reason stakeholders can't be aligned. Data science benefits customers, payers, and providers by delivering better individual capabilities at scale in a way that also addresses the need for personalized, localized solutions."

Laura Beerman is a contributing writer for HealthLeaders.


Data science has become essential in developing, supporting, and marketing healthcare technologies, including insurtech marketplaces.

A new generation of marketplace platforms uses these tools to leverage data in areas that include third-party claims, risk scoring, and plan recommendations.

Long-term payer advantages may include customer retention, satisfaction, and clinical management.

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