The emerging role of data science in the health plan market

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“Payers quickly understood the added value: the best solution for the customer is ideally the best solution for the plan,” says an executive.

Data scientists will see you now. In fact, they are there to help not only healthcare consumers, but payers as well through a growing number of insurance platforms. Independent market platforms are one example, offering payers increased potential for customer loyalty through big data, artificial intelligence (AI) and their links to risk analysis, plan selection and broader health and wealth planning. Such market-based solutions could provide the missing ingredient for consumer-centric healthcare that complements payers’ efforts through scale, longevity, and a positive customer experience.

How data science supports health ‘risk takers’

A recent study of Irish Journal of Medical Sciences defines data science as “an interdisciplinary field that extracts knowledge and ideas from… big data”. Specific to the healthcare sector, the study further states: “Data science provides assistance in processing, managing, analyzing and assimilating the large amounts of fragmented, structured and unstructured data created by healthcare systems. require effective management and analysis to acquire factual results, “including” data cleansing, data mining, data preparation, and analysis of data used in healthcare applications “.

Technological solutions often create new problems. The importance of data science and AI to fully utilize big data generated by healthcare systems is just one example, with insurtech emerging as a subset of the solution. Insurtech includes new entrants (often startups) in health plan products, operations, benefit management, and the topic of this article, markets.

Data and the data science behind it has the power to help payers and startups, and even unite them. PitchBook written: “The growth and increased availability of traditional and non-traditional data sources are enabling startups to create patient management platforms that empower risk takers, including insurers, risky service providers and self-employed employers. insured, a better understanding of individual health care needs. “

“Building a better front door”

One of these startups is Health pilot, a new insurance company using “large-scale data science and proprietary decision-support technology to find and match consumers with health insurance plans that match their unique profile.” Healthpilot also helps consumers register online by forwarding their claim 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 client engagement and enrollment model combines data collected from clients with various third-party data from multiple sources to create personalized plan recommendations based on Medicare plans available in the service area. “Our algorithm does two things,” says CEO David Francois. “It intersects personal information with larger data sets to create a profile of risk and the likely use of healthcare resources by the client over the next year.” These larger datasets include aggregated data on medical claims for millions of patients nationwide.

“With that information,” Francis says, “we can get a pretty good match of who you are in terms of health usage, take that score, compare it to your zip code plans, and go from there. , match your needs to the best plan for you. ”Customers indicate their preferences and see the plan recommendation that works best for them and others for easy and seamless comparison. Think of it as Spotifying Healthcare, though Francis cites another company, Amazon, as the inspiration for the company’s business model “It’s very forward-looking. This is rooted in the ability of data science to bring instant predictive analytics to the benefit of the customer.” “

Benefits for payers

In addition to a better front door, Healthpilot seeks to offer a back door that stays comfortably closed – that is, that promotes customer loyalty through ongoing, personalized support that also benefits payers. “After signing up, we continue to use data and data paths that help us stay up to date with customers and create ongoing recommendations and targeted communications,” explains Francis. This data includes individual usage data and market changes (e.g. employee benefits, physician networks, pharmacy coverage). Healthpilot intends to expand beyond Medicare to provide a full market.

Francis notes that this type of ongoing engagement “is not mutually exclusive with payor relationships. One of our biggest concerns was that we wouldn’t have the time of day with the big payers. We did. been humiliated and surprised that they quickly understood the value proposition. ”This value proposition includes:

  • Improve risk analysis
  • Help plans enroll the most suitable clients
  • Drive lasting relationships
  • Reduce customer complaints
  • Improve customer satisfaction

These benefits reflect those who Insurtech startups in general can deliver to payers and other stakeholders. The better choice of plan most directly can correlate with better health and customer experience would be a boon to payers and insurance providers. Francis continues: “The best solution for customers is ideally the best solution for the plan. Data science helps us put the customer there. “

The broader impact could include improvements in the way payors communicate and market to clients, including positioning coverage choices based on comprehensive health and wealth planning. In a Research thesis 2021 on value-based care models, the Geneva Association recommends that insurers “seize the opportunities offered by the convergence of life and health products and solutions”.

Implications of data science for consumer-centric healthcare

So, can data science, insurance, and decision support tools combine to deliver the right customers and carriers? A 2020 JAMA Health Forum item Note: “Certain health insurance decision aids that incorporate consumer preferences have been shown experimentally to improve decision-making self-efficacy and confidence in health plan choice. However, … [f]More research is needed to determine the effect of decision support tools on access and use of desired and high quality health services, health outcomes and financial burden while covered. by diet.

This rise in research and insurtech comes at a time when the industry is wise to examine how technology can help consumer-centric healthcare. Francis of Healthpilot notes that his business model is to “serve, not sell”. This word — service — has become essential for associating technology products with their value message (eg, data as a service, software as a service, platform as a service). Data science as a service could very well be next in line.

The impact of data science on the value chain

The Irish newspaper previously cited study States that data science and big data analytics help create “a comprehensive view of patients, consumers and clinicians”. Ideal solutions will create this view for these stakeholders too. “Big data is a revolution in the world of healthcare. The attitudes of patients, physicians and health care providers towards the delivery of care are only beginning to change.

Francis agrees: “There is no reason that stakeholders cannot 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 customized and localized solutions. “

Laura Beerman is a contributing writer for HealthLeaders.


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