COVID-19 and Healthcare Analytics

The novel coronavirus responsible for COVID-19.

The following content was initially published in the early days of COVID-19, but helps to serve as the statistical framework that served as the foundational analytic motivation behind our COVID-19 research. 

COVID-19 analytic projects and COVID-19 are the top headlines of the day.

But public health is not only related to COVID-19. The US spends $3.3 Trillion each year and has roughly 2,800,000 deaths irrespective of COVID-19. What are the hidden impacts to public health and mortality because of COVID-19, but not due to COVID-19?

We steer clear of the additionally complex economic, geopolitical, societal, and educational impacts of the economic downturn and current COVID-19 mitigation strategies. We instead attempt to present the opposite side of the coin in terms of deaths caused by the impacts of the coronavirus relative to the predicted fatalities prior to the virus.

According to the US Bureau of Labor Statistics, the unemployment rate of those in the Healthcare and Social Assistance segment rose from 2.0 to 10.4% between Jan 2020 and April 2020. While a shocking number during a world-wide pandemic, the underlying reasons are more disturbing. Due to COVID-19, and the related national response to the pandemic, many private practices are struggling, many hospitals have put off “elective” surgeries, and many patients have reduced their visits to doctors, even when suffering from chronic diseases. ER visits are down 38% for heart attack associated visits, stroke visits by code to 30%, and thousands are missing ongoing cancer treatments. It is estimated that as many as 80,000 cancer diagnoses may have been missed. And “elective” surgeries such as certain cancer surgeries, heart stent surgeries, and other lifesaving procedures have been put on hold.

Non disease-related deaths are also likely to rise. Drug overdoses and suicides increase in proportion to unemployment and other life stressors. One reported statistic for suicide hotline call reported an 890% increase in calls in April alone. Alcohol sales have increased as well, although to what degree is difficult to ascertain, as restaurants and bar liquor sales have shifted to online and brick and mortal sales.  And, while spending time with families is a blessing for some, domestic violence is increasing as well.

While deaths due to COVID-19 are critically important, it is equally important to look at the downstream impact of COVID-19 on death as well. Even ignoring the additional impacts of a waning economy, stay at home orders, and impacts to social interactions, an apples to apples comparison can provide a more comprehensive view of the overall public health impact to COVID-19.

For the reasons above, Lifemesh is developing two unique models dedicated to predicting the hidden casualties of COVID-19. Information has been gathered from the Johns Hopkins, CDC, Department of Labor Statistics, IQVIA Institute for Human Data Science, Meadows Mental Health Policy Institute, and other resources to build models that reflect the likely impact on deaths in 2020 caused by factors related to COVID-19, but not due to COVID-19.

To represent our findings, we have elected to classify the causes of death as categorized by the CDC Mortality Dashboard consisting of 20 larger clusters. While it is theoretically possible that some of these categories could go down as a result of the virus (fewer drivers on the road leads to fewer accidents, and stay at home policies could decrease the flu virus as well), most of these categories are negatively impacted by the pandemic, and some to a significant degree.

We are providing a visual dashboard with our findings, but also provide the ability to apply hypothesis assumptions to the mode to see where targeted approaches in policy, care, social factors, or other interventions might allow us to better find an appropriate equilibrium between COVID-19 and COVID-19 Influenced deaths.

We also invite you to view our geographic propensity models for COVID-19 risk assessments here. We look forward to input and conversation on the topic.