Lirio designed and launched a digital health solution for a state’s health systems to move their employees and patients toward vaccination.
Case Study: Bon Secours Mercy Health Moves 84% of Unengaged Patients with Diabetes Toward PCP Visits
Bon Secours Mercy Health (BSMH) partnered with Lirio to co-develop a Precision Nudging™ solution utilizing hyper-personalized patient communications for people with diabetes.
Bon Secours Mercy Health (BSMH) partnered with Lirio to create a Precision Nudging™ solution to deliver hyper-personalized messages specifically designed to move patients to schedule and attend their mammograms.
True digital transformation is finally at hand in healthcare, and it has ushered in a new standard of patient experience. With the dramatic shift to consumer-friendly and virtual care options, patients are looking for more personalized care.
How to Connect with Patients as Individuals: 10 Behavioral Biases Healthcare Systems Should Know [eBook]
Understanding how cognitive bias influences healthcare behaviors can enable those charged with improving population health to drive positive healthcare behavior change. This ebook provides a quick overview on how cognitive biases hold a key to encouraging healthy behaviors, followed by briefs on ten thoughtfully selected biases. Think of it as a valuable resource for your population health toolkit, designed to help you step even closer to the idea of patients as individuals who want, need, and deserve a more personalized care experience.
With COVID-19 variants proliferating despite widespread availability of the vaccine, understanding and overcoming vaccine resistance is healthcare’s ongoing pandemic challenge. Learn more about how Lirio can address vaccine hesitancy for your community.
While AI is still relatively new to the industry, the global healthcare AI market is growing fast. Understanding its application is critical to determining which solutions can actually make a difference in care delivery and business operations…
COVID-19 has been a catalyst for the rapid adoption of digital healthcare tools, and creates a window of opportunity to reshape healthcare. Learn about healthcare shifts in a COVID-19 landscape, and the critical role person-centered communication plays in getting your community to adjust to the “new normal” of healthcare.
Behavioral Science Solutions Briefs
Lirio’s Precision Nudging™ tailors hyper-personalized communications to individuals through a rich set of Behavioral Science Solutions (BSS). Our BSS Brief series walks through some of these to illustrate the active behavioral science ingredients in our intervention messages designed to influence decision-making and overcome barriers to action.
It’s New Year’s Day, 2022, and you just woke up. You pour yourself a cup of coffee and settle into your favorite spot on the couch. As you gaze out the window, you feel a sense of calm and hope. There’s a brand-new year ahead of you. As you think about what lies...
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Lirio delivers results by drawing insights from hundreds of behavioral biases and theories. Our Bias Brief series walks through some of the biases that inform our Behavioral Science Solutions (BSS), each thoughtfully selected from our long list of insights.
Lirio delivers results by drawing insights from hundreds of behavioral biases and theories. Our Bias Brief series walks through specific biases one by one, each thoughtfully selected from our long list of insights. Read on for a brief rundown on the chosen bias,...
Availability Bias is a mental shortcut that leads people to assume that things they can more easily recall are more likely to occur. As a result, people tend to weigh their judgments toward more recent information.
Dates that stand out as being more meaningful—such as the start of a new week or financial quarter, a birthday, or a holiday— signal the start of a new, distinct time period. These “temporal landmarks” make people more motivated to pursue their goals because specific dates make it easier for them to mentally separate their past imperfections and failures from their future self.
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