Healthcare payer analytics and data strategies in 2026

Transforming payer healthcare data into actionable insights

The solutions to many of the problems payers are facing in 2026 start with implementing a clear data strategy that has a quality foundation in data infrastructure, analytics, and clinical evidence.

“We have data, but we're not doing the right thing with it,” Soot asserted.

Even as important as population health data is to informing payer outreach strategies, it is mostly used as a “retrospective kind of review,” looking at past years’ results to inform future strategies, she said. “Let's get ahead of that, and let's do the intervention” when it can still prevent suboptimal outcomes.

“I think that's the really exciting thing with where we are,” Soot continued. “If governed appropriately with the right clinical oversight and new processes, rather than just putting it into old processes, [payer data could] identify those members that are prospectively rising-risk, that are going to have a care gap, that are going to be nonadherent with their medication.”

Soot added, “I think there is a lot of power in data, but we absolutely have to look at it differently than we have before.”

Collier recommended “tying a lot of that data with member feedback loops in action.” By analyzing member engagement with health plan-provided outreach and determining if they actually made changes to their health practices after those interactions, payers could tailor future outreach or target certain populations with recommendations and education that are more likely to “really resonate with them.”

Part of that process is also analyzing the data of not just what members interact with, but when and how they consume the information. It optimizes resources and promotes affordability if payers can “leverage that data to be able to provide [members] with insights at that right time,” Collier said.

Pasko added that data-driven outreach can also target members prior to healthcare visits to help prepare them with thoughtful, useful questions for their providers, potentially counteracting misinformation from Internet sources and AI and saving members the time and costs of follow-up visits.

While the rise of open-sourced AI has been problematic, at times, for misleading members seeking health information, evidence-based healthcare AI solutions can offer an advantage to payers for internal use, Pasko noted. AI can create efficiencies in analyzing data, she said, “but it's making sure that you're pulling the data from the right data source… high-veracity data or high-quality data, and using it in the right way.”

Personalized member care: Driven by data to manage costs and risks

There is a misperception for insurance companies, Soot said, that prioritizing financial stewardship means saying no to everything, while prioritizing member-centered care means saying yes to everything. “And I would like to say that that those two [assumptions] are not true. There really is a way that we can balance those and make high-value, medically appropriate care more affordable.”

Payers should focus on “reducing waste,” she said, which could include duplication of therapies, avoidable admissions, ineffective treatments, and inappropriate dosage and frequency of medications. The latter, she noted, “dramatically increases the cost of the drug.”

Additionally, she reiterated the need for a proactive data strategy to personalize member care and better engage members, potentially improving care and avoiding wasteful spending. “We do a really good job of taking care of sick people. We don't do a very good job of keeping people from getting sick.”

Strengthening care management is vital to more proactive care, although Soot said, it can be difficult to justify to organizational leadership from an ROI perspective.

Her business has compiled “data that shows there is an ROI to integrated care management,” demonstrating that having care management teams embedded with benefits and health services teams has resulted in increased engagement with members at highest risk, leading to actions that decreased the cost of care and improved their outcomes.

A benefit of having care management teams embedded with other functions is that it reduced internal fragmentation in her organization, Soot said.

Drug decisions – whether surrounding intended uses or formulary exclusion-inclusion criteria – must be informed by real-world evidence and clinical practice, Pasko explained. Because some drug therapies are actually covered by medical benefits rather than prescription (for example, infusion medications), payer data systems need to be able to navigate between internal teams.

Collier added that it was similarly important to fight external fragmentation across the healthcare ecosystem by prioritizing interoperability.

Seemingly effective point solutions can ultimately prove “cumbersome” if they don’t “make it easy to share information or make it easier for clinicians to find the information they're looking for,” he said.

Care management solutions also have to provide flexibility to effectively engage with members, Collier said. “Having solutions that are really flexible [supports] actionable, timely information.” These could include offering content through various media such as videos, materials that depict diverse member populations, or a variety of language options for those more comfortable learning in a language other than English.

“If you have solutions that are able to support those personalized needs, that's really important,” Collier said.

“How do you take care of somebody at the right time: Know the right patient, the right time, the right place, the right thing that they need?” Soot asked. “That is all based on evidence, using the evidence that is in good clinical research and has been [built to help guide] the workflow plan.”

She explained that evidence-based treatment pathways and recommendations can help standardize care and promote better member outcomes. But they also help indicate when a treatment or procedure is not recommended or is not a first-line approach to appropriate care, helping contain costs and reduce unnecessary care.

AI could be useful here, she noted. “We could design systems that understand [those evidence-based] clinical workflows and ‘click the boxes’ so that the doctors can really work at the top of their license and scope, which is understanding who falls into a very standard algorithm and who is falling out and why.”

Whether AI is being used to automate prior authorization, automate drug coding processes, or expedite clinical reviews, payers will need a “working therapeutical intelligence layer on top of [AI-driven processes], to have guardrails around AI, and have new solutions that work within those guardrails,” Pasko emphasized.

Watch the webinar

To dive deeper on some of these topics and learn more about how payers can leverage advanced analytics and evidence-based workflows to curb rising costs while improving member outcomes, watch the full webinar replay, “Thriving in 2026 with Data, Evidence-Based Practices, and Affordable, Member-Centered Care.”