3 COVID-related variables that will impact health plans
Employers need actionable insights to see beyond what has happened in the past year and predict the future needs of the organization.
Accurate planning for an upcoming year’s benefits plan begins with access to real health data, including individuals claims, pharmacy records, and other disparate health information. Tying those disparate data sets together and sussing out actionable insights so you can make changes to your health and wellness programs is what we call Health Intelligence. Employers and the consultants who advise them need actionable insights to see beyond what has happened in the past year and predict the future needs of the organization.
Related: Considerations for group health plans in 2021
How exactly can we extract health intelligence from a moving target? The entire industry is going to have to work from convoluted underlying data while the medical industry plays a little catch-up. Additionally, the amount of available health care data since 2016 has increased by 878%. This creates even more noise when you’re trying to find relevant data. As an expert in analyzing these disperse data sets to help companies make the best decisions about the health and benefit plans for employees, I believe there are three ways COVID-19 will impact planning for next year:
1. Coronavirus is new
The effects of COVID-19 are going to make planning challenging due to the lagging access to reliable data. Unlike other diseases that have decades of reliable data to compare, the coronavirus is new and is still running its course. In fact, many experts predict that we won’t see the peak of infections until later this year and maybe into 2021. And the medical community is still discovering new, long-term effects of the virus seemingly weekly. This has caused the underlying data to be rife with experimentation, just now finding some national uniformity.
By comparison, we know a lot about many other diseases and can predict the course of treatments, how patients tend to respond, what other health complications can occur, and what are the costs associated with those diseases when treated and untreated. We can even predict typical patient behaviors — such as how likely they are to take prescribed medications or what other health complications will occur because they are not following medical advice. Tracking those issues and leveraging a variety of data sets helps predict the downstream effects of a particular disease.
But in the case of the coronavirus, the data remains in flux. We don’t know enough about the disease yet to make accurate predictions. It may take several years before the medical community has enough data to look back and say definitively what happened. Once the data is more reliable, we can extract more accurate health intelligence. That’s not to say we don’t have some data. Patients are filing claims, and physicians and health care providers are creating electronic medical records that will be examined by many experts in the coming year.
2. The health codes are new
Because COVID-19 is a new virus, the information experts have access to is limited and changing hourly. The medical billing codes, called CPT (Current Procedural Terminology), for COVID-19 were published by the American Medical Association in mid-March. The process of sharing definitions and educating front-line staff, physicians, and health care providers on a new CPT are messy. As you can imagine, getting one organization up to speed on a new procedure can be difficult. Now, multiply that by the thousands of health care organizations across the country that are introducing a new medical billing code, and you might imagine that the underlying data is going to be challenging for some time.
What we are concerned with, as it relates to billing codes, are the claims at the back end after tracking treatment has taken place. We need to evaluate the aggregate data and extract health intelligence that can inform employers and insurance brokers alike on what they might expect next year to adequately cover their employee base.
Since we’ve introduced a new billing code and since this disease is new and hasn’t yet run its course, we’re likely a few months out before we’ll have enough reliable data to begin generating predictive analytics on the impacts of this disease.
All of these insights tie back to real health data. They’re not made up and they’re not presented with bias. You can draw a straight line from your data to your insights.
Health intelligence doesn’t simply show you what’s already happened, it provides you with real, actionable insights so that you can make changes to your benefits offerings in real time.
3. Underlying health conditions affected
We all heard about the risk to the elderly and people with certain underlying health conditions when the coronavirus pandemic struck. CDC and government officials let us know that people with respiratory and heart conditions were particularly vulnerable, as well as those with other conditions such as diabetes, liver disease, and asthma. Until more data is collected, we won’t know the effects that the disease will have on any number of underlying health conditions.
How much worse will someone’s respiratory disease or liver condition be in the coming year as a result of being infected by coronavirus? What about those who miss preventative care visits as the health system came to a crawl for general procedures and elective surgeries? Complicating these questions is the fact that many people are likely unaware that they were even infected by the virus. Widespread testing has still not occurred and it may be many months, or perhaps years, before the testing and data catch up.
Other data is emerging that COVID-19 may be causing complications for those with mental health issues. Beyond the direct, physical impact of the disease on those with mental health diagnoses, there could be a mental health effect on those infected with the disease, according to a recently published article by Dr. Betty Pfefferbaum and Dr. Carol North in the New England Journal of Medicine.
Extracting health intelligence in the coming year is going to be challenging and, at the same time, critical to helping employers and benefits consultants predict costs and suitable coverage for their employees. The chaos and uncertainty may be higher than ever, but we have more powerful technology, such as AI and machine learning, and the ability to compare complex data sets to extract meaningful insights like never before. Despite the uncertainty that COVID-19 brings to the health benefits planning process, solutions like Springbuk help drive the most meaningful action with the most relevant and actionable data available.
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