Minding The Population Health’s “Psâ€
The saying “there’s an app for that” has never been truer. That’s both good and bad for healthcare leaders interested in improving member and population health.
An unprecedented number of digital health applications, tools, and platforms are transforming the way consumers can engage in managing their own health.
While volume means more choices, it also makes it more difficult to separate the great and effective from the not-so-good. When selecting which of these innovative solutions to pilot and commercialize for member populations, healthcare leaders can benefit from evaluating the myriad options along five key criterion: Prediction, Proof Points, Personalization, Participation and Practicality, (“The Five Ps” framework).
Prediction
Predictive modeling is used just about everywhere. Mining insights from historical data sets enables more effective and less costly choices.
Take Jane, a 70 year old overweight female, who has had two falls requiring trips to the emergency room in the last five years. Analyzing a dataset on individuals with similar profiles shows that Jane has a 75% chance of suffering another fall within the next six months.
To avoid this needless pain and expense, Jane can be encouraged to engage in exercise therapy programs, gait training sessions, and balance-building exercises to lessen the chances of a fall occurring.
Proof Points
Before piloting to an active member population, you will want proof of the effectiveness of the app you’re considering. If it is from a startup company, they should be able to demonstrate they can generate meaningful outcomes by sharing the results of an independently reviewed clinical trial.
The data from a properly conducted clinical trial serves as a building block for the further data gathering needed for predictive analytics, and it builds confidence in the minds of managed care leaders about scaling a young digital health company’s new approach.
Personalization
Predictive analysis applied to individuals is one of the hottest concepts to come along in the last decade. Personalization is made possible through a complex system of customer loyalty data, metadata, and cloud computing that enables the continuous collection, storage, combination, and analysis of “big data” about each of us from a number of disparate sources.
For example, when there are thousands of data points on 45-year-old men, all with body mass indexes (BMI) of 37 and similar self-reported pain scores, treatments for knee pain can be tailored to these individuals. Certain exercises may not be well-tolerated by these individuals, and therefore removed from an exercise therapy regimen. This type of personalization is the future.
Participation
A good digital health product requires participation, particularly if it wishes to successfully utilize user data. Netflix and OK Cupid improve their algorithms when users rate movies and potential partners respectively. Google and Facebook monitor your browsing habits when you’re logged in.
Analyzing these patterns, such as when and how an individual responds to incentives coming from a predictive model, allows for personalized interventions.
These results then become sustainable as the interventions generated by predictive model continuously adapt to individuals, rolling up to significant population change. Prediction paired with personalization also generates more participation. Designing systems that are engaging and drive willing and informed user participation will only generate better data and prediction.
Practicality
The best way to go about collecting user data and increasing participation is to make the product or service so practical to use that it becomes effortless. In the case of digital health, this can mean eliminating the need to purchase expensive hardware or cumbersome non-integrative software.
Using the Five Ps as the framework for a decision will help leaders make choices that will lead to greater consumer engagement and ultimately result in better outcomes and lower healthcare costs.
Arpit Khemka is the chief technology officer for SimpleTherapy, Inc.
