Data Analytics Can Help Health Care Organizations Track and Analyze COVID-19
As of early August 2020, the United States was leading the world in COVID-19 cases, closely followed by India, Brazil, and South Africa. With the tide of cases and related deaths surging in many states across the U.S., EDs are struggling to admit, test, and successfully treat all patients. EDs are especially swamped in hot spots like Florida and Arizona, but some states like Washington — and Seattle in particular — are seeing a second surge of cases after successfully bringing their numbers down.
Predicting Upcoming COVID-19 Surges
The basic reproduction number, or R0 (pronounced R naught), is a crucial part of public health planning during an outbreak. Widely used in epidemiology, R0 describes the intensity of an outbreak. Although its accuracy depends on many factors, like the general susceptibility of a population and its density, R0 is used to indicate the average number of cases an infected person will cause during their infectious period. An R0 greater than 1 means the disease won’t just die out, but will spread. Highly infectious viruses like measles have a R0 of 12 to 18; the flu’s R0 is only 2 to 3.
To flatten the curve of COVID-19, its R0 must shrink to less than 1, but, unfortunately, we’re not seeing this happening any time soon. Studies of early cases in China reported an R0 of 2-2.5, but later estimates were much higher, at 6.6, which indicates exponential growth. Because the number mainly is calculated by monitoring hospitalization and death figures, it fluctuates as the situation evolves.
Why ED Volume Is More Predictive
The pandemic has brought to light certain shortcomings in testing and data collection. Looking at the number of hospitalizations and deaths is looking into the past. While mostly accurate, public data sources that provide these numbers, plus the number of positive tests, lag at least a few weeks behind what’s happening at the moment.
Random sampling can help governments track the virus with greater accuracy, but it’s also important to monitor ED visits to track where the virus might be spreading more rapidly.
Measuring ED volume is more predictive because it can also help forecast ventilator and PPE availability, bed capacity, patient volumes, and other resources that affect real-time resource planning. Using both historical and real-time data, analytics tools can provide timely, accurate information for HCOs and public health authorities that are trying to optimize care delivery for both COVID-19 and other patients.
How d2i’s Tools Are Working for Health Systems Nationwide
d2i’s COVID-19 surveillance analytics tools can identify trends, extensively filter dimensions, perform correlation tests, and conduct cause-and-effect analyses. HCOs can track and analyze COVID-19, flu-like symptoms, or other critical community health figures to fully understand how COVID-19 is impacting them right now, and how it may change in the future.
With d2i, you have the ability to multiselect from a comprehensive filter list, including age group, chief complaint, diagnosis code, location, and more. Our customizable performance dashboards provide both current and historical data, along with drill-down and dynamic filters so that identifying actionable insights is only a few clicks away. To learn more about how you can track and analyze COVID-19 for resource planning, please contact us.