Columbus, OH. Predictive analytics. You know it in your daily life as those mostly helpful, sometimes creepy recommendations from NetFlix or Amazon that tell you what you’re likely to watch or buy. It works by taking information about behaviors and patterns from many users and correlating individualized probabilities. For example, aggregate data would tell us that a large percentage of viewers who liked movie A also liked B, C, and D. Predictive analytics would allow us to deduce that because you like movie, you’ll probably like movies B, C, and D.
It’s been a hot button for marketers, because it allows us to zero in on audiences that are most likely to be interested and respond. And, the promise of predictive analytics is that it will continue to get smarter through more complex algorithms that analyze multiple factors to make the predictions even more accurate.
Predictive analytics in healthcare is a dotted line to personalized medicine. Think about how much more data we will have about ourselves as patients (especially as the cost of genomic testing comes down). This coupled with the development of intelligent analytics programs could mean real impact for what’s prescribed. “As data sources and technology advance, algorithms will be able to improve the odds that a certain treatment will result in a favorable outcome for a specific individual. The goal of predictive analytics is to reliably predict the unknown (i.e., personalize care) using high-confidence algorithms that can predict actionable interventions that improve long-term health outcomes.” Digital health venture funding reflects this trend, with $1.9B raised for companies utilizing predictive analytics. (Rock Health)
A recent article by Jennifer Bresnick in HealthIT Analytics offers an interesting perspective on where we really are with healthcare analytics. Here’s an excerpt from the article:
1) Descriptive analytics: What has happened?
Providers who engage in descriptive analytics have ability to generate reports that illuminate events that have already occurred, resources that have been consumed, or patients who have a new diagnosis on their charts. This can help with population health management tasks such as identifying how many patients are living with diabetes, benchmark outcomes against government expectations, or identify areas for improvement on clinical quality measures or other aspects of care.
2) Predictive analytics: What’s probably going to happen?
Bresnick estimates that only 15% of healthcare providers are currently using predictive analytics. Predictive analytics is one of the hottest topics in healthcare at the moment as providers seek evidence-based ways to reduce unnecessary costs, take advantage of value-based reimbursements that no longer reward voluminous care, and avoid penalties for failing to control chronic diseases or avoid adverse events that are within their power to prevent.
However, it requires access to real-time data that allows nimble decision-making, clinically and financially. That demands a significantly more robust infrastructure than just an EHR.
3) Prescriptive analytics: Making the future work for you
Prescriptive analytics is the future of healthcare big data, and it’s on its way to becoming a reality. As the Internet of Things creates a new way of looking at health information and machine learning advances and algorithms become almost unnervingly sophisticated in their ability to calculate the behaviors of nearly everything, from consumers choosing products at the grocery store to the minute movements of the stock market, the healthcare industry has an enormous opportunity to take advantage of these decision-making abilities.
As a healthcare marketer, this is an interesting trend to watch. As doctors have an increasing amount of information at the point of care, their recommendations and prescribing behaviors will undoubtedly be influenced, and perhaps even prompted by the technology and data behind predictive analytics.
