With the integration of data into decision making, the healthcare industry is turning into an analytics culture, in which data informs how healthcare is practiced. As doctors, patients, and administrators become more comfortable with the numbers, it becomes increasingly obvious that allowing data to drive our decisions can ultimately improve care and lower costs for clinics and practices across every healthcare segment. But where can you find reliable data? Much of the available data has a small sample size, is self-reported, or is not relevant to the industry you’re in. This is where we come in. With urgent cares using Experity’s EMR and PM solutions more than any other—combined with our software’s capabilities to look at data in powerful ways, we are able to present discrete, aggregated data specifically as it relates to urgent care. Our goal is to provide, and interpret, discrete data to our customers and the urgent care community to inform their everyday decisions.
First let’s look at flu trends attached to flu diagnoses as a percent of total visits. [Figure A.]
Once we know the percent of total visits with flu diagnoses, we can determine the number of flu patients the average urgent care will see throughout the flu season. Based on our analysis we consider flu season to have started when one percent or more of total visits result in a flu diagnosis. Once that happens, urgent care clinics are seeing a flu patient every other day. When flu diagnoses have increased to three to five percent of total visits, most urgent care centers are seeing 1.3 to 1.4 patients per day. The number of patient visits continues to increase with an increase in severity— peaking around four flu visits per day. (Figure B.)
Our data indicates that over the last four years, the 2014–2015 flu season had the highest severity of flu (11 percent), translating to 4.3 flu diagnoses per clinic per day. The severity of last year’s flu season was lower, and at its peak, clinics diagnosed 2.7 flu cases per day. One has to also wonder how much the slower flu season last year was affected by patients making different healthcare decisions. Out-of-pocket costs rose sharply over the last few years, causing more patients to skip some kind of care because of cost, as outlined in a USA Today article. “A recent Commonwealth Fund survey found that four in 10 working-age adults skipped some kind of care because of the cost, and other surveys have found much the same.” 1 (Laura Ungar and Jayne O’Donnell, USA TODAY, January 2015.)
Upper respiratory complaints are common during flu season—so we were curious how closely they tracked to the flu season. Is there a connection in the severity of flu season peaks and upper respiratory diagnoses?
Our data suggests that when the flu season starts later, it doesn’t have the same effect on visit volume as when the flu season starts earlier. One driver of this may be tied to upper respiratory increases. [Figure C.]
While pharyngitis, sinusitis, and bronchitis do increase during the traditional flu season, they don’t seem to follow the curve of the flu diagnosis. Put another way, even though the start of the flu season varied year-over-year, the start and end of the upper respiratory diagnoses lift seemed to be more consistent each year. The upper respiratory diagnoses also have a much gentler curve, while the flu season typically comes on quick and then dissipates nearly just as fast. The data tells us that while upper respiratory diagnoses don’t seem to have a direct correlation to the flu, when the flu season starts later, there is no volume lift that a coordinated peak upper respiratory and peak flu season deliver. To illustrate, the 2015–2016 flu season started late and visit volumes at urgent care clinics weren’t affected. [Figure D.]
Beyond a coordinated upper respiratory and flu season, the other components that affect higher patient volumes are the length and severity. The number of weeks the flu season lasts combined with its severity (flu diagnoses as percent of total visits) will help determine how the flu season will affect your overall visit volume. [Figure E.]
The 2014–2015 flu season was particularly severe and long, hitting seven weeks during which more than five percent of urgent care visits included a flu diagnosis. While the peak severity of the 2013–2014 flu season was high (10 percent of all clinic visits resulted in flu diagnoses), it lasted only five weeks. Of the prior four years, last year’s flu season was the least severe, lasting only five weeks and peaking at eight percent of diagnoses.
As our data indicated, the 2014–2015 flu season was the most severe over the four years studied, covering a larger area of the country. [Figure F.]
Data collected from 2014–2015 clearly indicates not only a more widespread flu season, but a significantly more severe flu season when compared with the following years–especially across the South. Even at the beginning of the season that year, the entire southern U.S. was experiencing flu in greater numbers that continued to increase in severity and lasted well into March. In 2015–2016, all regions experienced a similar flu season as the southern region didn’t see its typical bump. Our data also indicates that even in the most severe flu seasons, the number of diagnoses in the northeast and west remain relatively consistent year to year as their peaks are much lower.
As we continue to collect data this year, it will be interesting to compare a similar start to the season with last year’s data to see if we can discover any new correlations.
Compare what’s happening in your clinic with the flu data from the last four years to evaluate whether you’re seeing as many patients as you should be. Are you on track to meet your financial goals? Do you need additional marketing to increase patient traffic? And how can you prepare to better meet the needs of patients that present with conditions often connected to the flu?
Use this data (whether you use Experity software or not) to more effectively meet the needs of your patients. Our goal has always been to provide a better urgent care experience. Collecting and sharing data furthers this goal. Everybody wins.