Health data such as pharmacy records, individual claims, and other public information are the usual go-to sources when you’re trying to plan accurately for next year’s benefits plan. Tying together those disparate data sets and identifying actionable insights in order to make changes to your health and wellness programs is what’s known as Health Intelligence. To see beyond what’s happened in the past year and predict the future needs of an organization, employers and the consultants who advise them need actionable insights.
But how do you extract health intelligence from a moving target? With COVID-19, health benefits planners are going to have to make decisions with incomplete underlying data while the medical industry catches up. Additionally, the amount of available healthcare data since 2016 has increased by 878%, which creates more grist to churn through to find the data that you actually need. Experts in analyzing health data to help organizations make decisions about health benefits planning need to be aware of the three ways COVID-19 will impact planning for 2021:
We’re in uncharted territory with COVID-19
Planning is going to be especially challenging due to lagging access to reliable data around the effects of the coronavirus. Although other diseases have decades of reliable data to compare, COVID-19 is new and we’re still currently in the thick of it. And many experts predict that we won’t see the peak of people being infected until later this year — some say we may not reach that peak until 2021. On top of that, the medical community is still discovering new, long-term effects of the virus every week it seems. This has caused the underlying data to be rife with experimentation that only now is finding some uniformity nationally.
We have decades of data about other diseases and can predict the course of treatments, how patients respond, what other health complications arise, and costs associated with those diseases when treated and left untreated. We can even predict typical patient behaviors, like how likely they are to take prescribed medications or what other health complications will occur if they don’t follow medical advice. Tracking those issues and leveraging a variety of data sets will help to predict the long-term effects of particular diseases.
However, in the case of COVID-19, the data remains in flux. We don’t know enough about the disease to make accurate predictions at this point. It could take several years before there’s enough data to look back and get a definitive picture of what happened. Once we reach that point and the data is more reliable, we can get more accurate health intelligence. We do have somedata 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.
We’re still learning how COVID-19 affects underlying health conditions
We were all made aware of the risk to the elderly and those with certain underlying health conditions when the pandemic struck. Government officials and the CDC let us know that people with respiratory and heart conditions were particularly vulnerable, as well as those with other conditions such as asthma, diabetes, and liver disease. Until we have more data, we won’t know the disease’s effects on any number of other underlying health conditions.
If someone contracts COVID-19, what effect will that have on their liver condition or respiratory disease down the road? On top of that, consider that some infected people will be asymptomatic and may never know they were infected — how will that impact their health in the future? And what about the impact of missing preventative care visits as the health system came to a crawl for general procedures and elective surgeries? Without widespread testing, it may be many months — even years — before the testing and the data catch up.
Other data is emerging that the coronavirus may be causing complications for those with mental health issues. In addition to the physical impact the virus could have on those with mental health diagnoses, it could also impact mental health, according to a recently published article by Dr. Betty Pfefferbaum and Dr. Carol North in the New England Journal of Medicine.
New virus, new health codes
Because COVID-19 is a new virus, the information experts have access to is limited and constantly changing. The American Medical Association published the medical billing codes, called CPT (Current Procedural Terminology), for COVID-19 in mid-March. Sharing definitions and educating front-line staff, physicians, and healthcare providers on a new CPT is a complicated process. Getting one organization up to speed on a new procedure can be difficult. Now multiply that by the thousands of healthcare organizations across the country that are introducing a new medical billing code, and it’s easy to see that the underlying data is going to be challenging for quite a while.
As it relates to billing codes, what we’re concerned with 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 to expect next year to adequately cover their employee base.
With the new billing code having just been introduced, and since this disease is new and hasn’t yet run its course, it will probably be a few months 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.
Pinning down the health intelligence you need to make important decisions in the coming year is going to be a challenge. However, it will be vital to helping employers and benefits consultants predict costs and suitable coverage for their employees. This next year is certain to be chaotic, 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 unpredictability 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.
