Where We Were

Prior to the COVID-19 pandemic, the healthcare system for commercially-insured individuals in the United States was by no means perfect, but it was at least relatively predictable. The demand for services was reasonably stable over time, and the pricing, while far from transparent, was somewhat consistent. The healthcare industry understood the drivers of spending and the challenges involved in utilizing healthcare services appropriately. We worked to develop mitigation strategies designed to pull the right levers and influence behavior to improve both clinical quality and cost-effectiveness. Our primary challenge as an industry was the consistent rising trend in cost (which did not correspond with a rising trend in quality). We might not have had the answers, but we understood the questions.

Where We Are

All of that changed with the onset of COVID-19. Today, during the heart of the pandemic, we are seeing significant shifts in demand for services (primarily, an apparent decrease across the board), along with an influx of unanticipated costs to test for and treat the virus. In addition to these trends, which are making themselves known early on, there are many more economic and social impacts of the current situation that are still evolving. It is very probable that these will continue to affect healthcare access and utilization well into the future.

The current “disruption period” shown above suggests a single decline followed by a single surge. However, no one truly knows whether this will be one overarching cycle or multiple dips and surges as additional outbreaks may occur. We also don’t know exactly how long the disruption period may last. But eventually, history promises that we will achieve some sort of immunity balance, either by natural exposure rates or through the development of an effective vaccine (note that the same effect could be achieved sooner via a safe, effective treatment). After that point, healthcare spending will eventually land at a “new normal”.

Where We’re Going

The new normal is unlikely to look like the previous normal. We anticipate shifts in demand, changes in the healthcare system capacity (hospitals consolidating, provider burnout, etc.), and new behavior patterns among patients. There will likely be some long term health effects of either the virus or the secondary effects that may last well into the future. Finally, new technologies or treatments utilized during the disruption period may influence the way care is delivered in the future.

The First Step

The uncertainty is almost overwhelming. How can we plan for future healthcare expenditures if we have no data-based knowledge of what will change, when it will change, and how much it will change? How can we ensure high-quality care and cost mitigation to continue when we don’t yet know the new drivers and the risks involved? It’s like playing a new sport without any written rules. Many respectable organizations are giving it a shot, creating various impact models using what little data is currently available together with assumptions and expertise. The wildly different predictions that have resulted only emphasize the level of uncertainty with which we are confronted. So what can we do?

Chinese philosopher Lau Tzu is quoted as saying, “The journey of a thousand miles begins with one step.” As an organization focused on identifying actionable insights for our customers, what can our first step be? Many experts across the country are spending countless hours identifying possible ramifications of this pandemic and its resulting social and economic effects on healthcare delivery. We can capitalize on this unprecedented level of research to identify the specific effects we believe are most likely to impact our commercially-insured populations. We believe that the key to understanding the overall healthcare spending trend, both during the disruption period and into the new normal, is to recognize that it is not a single trend at all. Instead, multiple “micro-trends” will drive the larger trend to various degrees and during different time periods. While predicting the overall trend is overwhelming, we have a much better chance of identifying and predicting specific areas of impact via these micro-trends.

Springbuk’s team of healthcare experts is combing through research and data to identify what we believe will be the key micro-trends that affect our customers’ populations. We are prioritizing them based on the scope of expected impact, the timeframe of anticipated effects, and the actionability around the particular trend. Although at the time of this writing the data is only beginning to arrive, multiple research papers and results from data sources closer to the delivery end of the spectrum (providers) are available to inform our work. This will allow us to proactively examine the historical patterns for each micro-trend, understand the best way to measure the significance of deviations within each trend, and prepare to measure it in real-time as the data appear. To put it simply, we will start with “what we think” and later allow the data to inform “what we know”.

The micro-trends we are focusing on first include the impact on elective procedures, mental health and substance abuse, chronic care management, and preventive services. In addition to measuring these (and more) categories of care for the entire population, we also plan to drill into specific population segments whom we believe might be at higher risk for experiencing unusual fluctuations in these trends, such as the chronically ill, patients who had severe COVID-19 infections, cancer patients, and those in specific geographic areas.

Finally, we are considering a variety of factors that might play a part in some or all of these trends, such as disruption in claim payment cycles and healthcare system capacity. Future blog entries will keep you posted on our approach and, eventually, findings.

In summary, although this disruption period may be unpredictable in length and scope, by focusing on specific, understandable components, we will be able to provide our customers with insights into changes as they occur. This will help inform the overall trend to come, as well as the necessary mitigation strategies.

Meet the Author: Janet Young, M.D.
With more than 30 years of experience, Janet Young has provided clinical expertise to the development of healthcare analytics used in provider, payer, employer, and government sectors. Previously, Janet served as a Lead Clinical Scientist at IBM Watson Health, guiding clinical content development related to new models, methods, and analytics using claims, EMR, Health Risk Assessment, and socio-demographic data. 

Janet joined the Data Science and Methods team at Springbuk in Dec. 2019, and has been responsible for clinical oversight of methods and models. Janet received her M.D. from Yale University School of Medicine.