If health insurers want to garner new members and keep them well, it may be worth looking internally, at how employees are faring and how managers make decisions.
Doug Rauch, the former president of Trader Joe's, offered advice to insurers in times of industry upheaval: "Why do you exist? What is your purpose?
"This may seem obvious," he said, but if insurers -- who haven't always had a positive relationships with their members -- want to innovate and get to the point where consumers heed and respect their health advice and continue enrolling, it's worth going back to basics to articulate values.
"They won't miss you if you cease to exist," he said, at AHIP Institute 2014 in Seattle.
To innovate with customers -- to design new plans; to offer employers and individuals wellness programs that are both popular and effective; to succeed in a new, regulated and scrutinized market -- it is going to take an internal culture that values and unites employees, and constantly learns from data, Rauch said.
"Start looking at your culture," including everything from how decisions are made to how people are promoted, Rauch said. "Don't be afraid to fail, but fail on purpose, meaning around your purpose. All innovation is about taking risk," he said.
At Trader Joe's, which grew from a local California outlet in 1969 to a 400-store chain with an uber-loyal following, products are sampled and rated by employees and are also tested with consumers through limited releases that can be tweaked or yanked, depending on sales and feedback.
Data-driven decisions
"If an item doesn't pull its weight in our stores, it goes away for something else," the company, owned by the privately-held German conglomerate Aldi, says on its website.
That type of iterative strategy of constant-learning is possible for health insurers if they have the right data and technology in place.
"It used to be that experts in different situations who were in charge of decisions used their experience and inference," said Dan Wagner, the founder and CEO of Civis Analytics, a one-year-old startup that grew out of President Obama's campaign team and is now trying to tackle problems in education and healthcare.
"But humans are weird, socially-driven animals who we can't actually measure very well," said Wagner. "The new paradigm is that experts help define the questions and data helps answer them."
How's that going in healthcare?
Suffice it to say, everyone -- hospitals, medical practices, insurers -- is coming along, first by moving digital and gradually integrating data sources to get something close to a real-time view of patients and populations as they move through the healthcare system.
Long-term, health systems and health plans should be able to collaborate on much-needed comparative effectiveness studies. But for many, it's still early in data integration and initiatives to convince individuals to get preventive care or change their habits.
Health insurers also face the challenge -- shared with other industries but amplified in healthcare -- of learning to engage on an individual basis that accounts for member individuality.
"To look for trends," said Keith Dunleavy, MD, the CEO of analytics company Inovalon, "the trend is all people are unique."
Early risk adjustment was done on a population level, he noted. "We were forced to use simpler models when we had to, when we couldn't look at members on a member to member level."
Now, with medical loss ratio rules, data can "be properly understood and used at the individual level," Dunleavy said.
And now that insurers can examine claims and clinical data at a member level and a population level, it's becoming more possible to craft personalized engagement strategies -- for example, with some members notified of preventive needs via mail, phone call or email based on past communications they've initiated, or reminders for diabetic screenings based on members' latest control numbers.
As insurers learn of utilization sooner and sooner, those types of outreach strategies can be expanded into member support and home visit programs, especially for high-risk populations like Medicare-Medicaid dual eligibles.
"We are a pebble's throw away from real time analysis" of both populations and patients, as Dunleavy said.