Whether you’re watching television or listening to the radio, you’re bound to catch an ad soliciting participants for a clinical trial.
These trials can’t take just anyone; participants must meet strict requirements, including age, lifestyle or prescription drug use. Pharmaceutical companies running those ads are often looking for needles in a haystack, but unfortunately, they’re using one of the costliest shotgun methods available.
Using high-visibility but inefficient television media to reach specific audiences is just one symptom of the challenges facing health care, which desperately needs to move into the digital age.
When we discuss the big data revolution transforming health care, we tend to fixate on the diagnostic and cost-savings benefits of patient records being available to health care providers on demand. Questions about how data is collected, distributed and privacy-protected soon follow.
What gets less attention is how data could be applied to improve health care distribution. How could existing health care and pharmaceutical data sets be combined with commercial data to provide cost-saving benefits in many health care distribution information systems?
Could applying ad tech’s capacity to leverage analytics advance health care services?
Localizing Our Understanding Of Pharmaceutical Consumption
Much has been written about America’s deadly opioid crisis, and CDC data has helped paint a vivid picture of its widespread impact on society. But a national profile doesn’t mean a lot to local health care providers or communities on the ground that may not have the tools to deal with an opioid problem.
The most insightful data may exist in the commercial sector. Local pharmacies fill prescriptions and over-the-counter medications. Doctors write these prescriptions and insurance companies provide benefit coverage.
Communities and providers can draw real insights at the local level by leveraging sales transactions data of highly correlated medications in the supply chain and combining them with local community demographic data sets. Executed in a privacy-safe way, those insights could help at-risk populations by taking preventative action through communication and outreach.
The kind of data-driven targeting tools commonly used throughout ad tech aren’t limited to specific diseases or public health issue. Like all tools, it’s really a question of where we choose to apply them.
A Better Health Care Delivery System
Over the past few years, the Affordable Care Act has begun to transform the American health care system. We are seeing a series of experiments on the health care service model so that it can still deliver the care we get today at a lower cost.
Bending the cost curve of health care could hinges on creating efficiencies in diagnostics, logistics and information transfer through the use of big data analytics and some of the optimization techniques currently used in programmatic. And while analytics and a digitally enabled supply chain may be our greatest asset in this battle, we don’t know who will be able to put these tools to best use.
In the same way that Amazon used consumer transaction data to create a high-value distribution engine for delivering just-in-time goods and services at a transparent price, health care delivery can also optimize the mountains of data about provider services, pharmaceutical distribution and local demographic profiles.
Localizing health care specialty coverage to at-risk populations will help control costs. Optimizing pharmaceutical inventory to patient disease frequencies within a trade area of each hospital will lower drug costs. Taking promotional overhead out of clinical trials will also bend the cost curve. Likewise, improving patient-doctor communications and access through opt-in data sharing and just-in-time care, we can bend the cost curve again.
The race to build a better health care delivery system is well underway, but the question isn’t so much about what it will look like but how health care’s established players will take advantage of the digital revolution?