Predicting the behavior of recovering patients could be the next frontier in healthcare.
By Bruce Stanley
As our healthcare system evolves from “fee for service” to “fee for outcomes,” many moving parts are changing – insurance, accountable care organizations, reimbursements, access, and a shift in accountability.
Outcomes are more important than ever, but healthcare providers, manufacturers and distributors know that they can only do so much to affect them. The costs associated with healthcare outcomes can be driven as much by patients’ actions as they are by the clinical team treating those patients. An under-valued component in the new healthcare delivery and payment model is the patient’s behavior. The ability to predict which patients will follow his or her prescribed treatment plan and which one can’t – or won’t – is the potential innovation.
The premise of personal accountability is based on individual life habits, patterns and behaviors. Doctors, ACOs and hospitals should not be penalized for patients who don’t have the stamina, fortitude or desire to follow a treatment protocol. This is quickly becoming the ‘patient vortex,’ that is, the place where the science of healthcare collides with human nature and economics.
Some might suggest that patients be monitored throughout their recovery, utilizing technology. They believe that tracking each movement or noncompliance during recovery is the only way to facilitate treatment compliance. The question is, what type of monitoring is most useful? Wristbands? Apps? Much of this capability exists today, and innovative technology is on the horizon. Often it is being put to great use in tracking clinical components, such as heart rates, blood pressure, glucose and the like.
Patient predictability profile
But what if a patient continues risky pretreatment behaviors during recovery, such as smoking, drinking, or failing to take medications as prescribed? Wouldn’t it be easier and more cost-effective to develop a patient predictability profile, which would indicate the behavioral risks for treating a patient before he or she enters the system? Many partners in the current healthcare model already have behavioral and transactional data that can be structured in such a way as to assess how certain types of patients will respond based on predictive behaviors. The blending of useful data and analysis with technology could help patients recover faster, and help doctors and clinicians treat with greater reliability.
The ability to predict how a patient will act based on past behavior could provide clinicians and insurers with the confidence required for making certain treatment options available to certain patients and not others. Additionally, products and processes could be designed and delivered by the key players in the healthcare system that more effectively treat patients based on behavioral analysis. Is this segregating care? I hardly think so. Is it segmenting care? Yes, indeed; it becomes customized care. The good news is that predictive analysis is based on scientific and mathematical principles grounded in reliable characteristics of human nature. Predicting the behavioral capability of recovering patients could be the next frontier in healthcare.
Challenges
Healthcare clinicians can be equipped with data that helps them determine what individual patient behaviors look like even before specific treatments begin. Based on that profile, they can modify the rigor of a particular treatment or cease it. While predictive analysis could have significant benefit in developing a patient treatment profile, it also raises potential ethical concerns, which would have to be addressed.
Using predictability profiles to guide treatment decisions is not allocating care, but rather, adding a customized behavioral component to it. At the end of the day, all participants in the system win: patients, physicians, manufacturers, hospitals, insurers, and the government. With this tool, delivering care can be a better balanced and effective process from product innovation to patient consumption.
Predictive analytics can’t guarantee favorable outcomes for patients, but it can help caregivers deliver the right care in the right behavioral context. In the end, it is only a tool, but one that may benefit the entire healthcare system.
Bruce Stanley is a supply chain and contracting operations consultant with over 30 years in the healthcare industry, and an adjunct professor at Endicott College’s MBA program, teaching global supply chain, contracting and healthcare informatics and regulations. He served as senior director, contracting operations, for Becton Dickinson. He is a former chairman of the AdvaMed working group focused on vendor access-credentialing, and has collaborated with MassMedic and AdvaMed on legislative initiatives related to this topic. In 2011, he co-founded The Stanley East Consulting Group, in Ipswich, Mass., a global consulting practice specializing in supply chain, contracting, order fulfillment and project management for small and medium-sized companies, startups, and companies in transition or divestiture.