When you’re trying to accurately plan for next year’s benefits plan, you usually consult public-health data such as individual claims and health records. Additionally, you look at data such as pharmacy records, individual claims, and other public information. Developing insights and decisions based on these disparate sets of data is known as “health intelligence.”
But how do you extract health intelligence from a moving target? With COVID-19, we must all make do with convoluted information while the medical industry catches up. Additionally, the amount of available healthcare data since 2016 has increased by 878%. All of which makes analyzing relevant information difficult.
Planning is going to be challenging this year due to lagging access to reliable data around the effects of COVID-19. The novel coronavirus is just that — novel. We’re currently still in the middle of this pandemic, and some experts predict that we won’t see the peak of infections until later this year or even next year. As the medical community is still discovering new, long-term effects of the virus, this has caused the underlying data to be rife with experimentation that is only now finding some national uniformity.
When it comes to other diseases, there is decades of data to help predict who’s most vulnerable, which treatments work best, which health complications may arise, how patients respond, and associated costs associated. We can even predict typical patient behaviors, such as how likely people are to take prescribed medications or what health problems will occur if they neglect to follow medical advice.
But in the case of COVID-19, the data’s still flooding in. We don’t have enough information to make accurate predictions right now, and it could take years before there’s enough data to look back and get a definitive picture of what happened. (However, it’s worth pointing out that we do have some data right now — patients are filing claims and physicians and healthcare providers are creating electronic medical records that will be examined by many experts in the coming year.)
The American Medical Association published the medical billing codes, called CPT (Current Procedural Terminology), for COVID-19 in mid-March. Sharing definitions and educating frontline staff, healthcare providers, and physicians on a new CPT is a complicated undertaking. Moreover, getting one healthcare organization informed abou a new procedure can be a demanding task. Multiply that by the thousands of healthcare organizations across the country and it’s clear that introducing new medical codes can create all sorts of challenges.
With billing codes, we’re most concerned with the claims at the back end after tracking treatment has taken place. We’ll need to evaluate the aggregate data and extract health intelligence that can inform employers as well as insurance brokers about what to expect in the coming year to adequately cover their employees.
It’s critical to have health intelligence that not only shows what’s already happened but that provides actionable insights to help make changes to benefits offerings in real time.
There’s no easy way to say this: Getting the information to make important decisions in the coming year will be challenging, but no less crucial for employers and benefits consultants. More powerful technology, such as AI and machine learning, and being able to compare complex data sets to gain meaningful insights will be key to navigating the chaos in the coming year.
