Tips from Tanya – Healthcare and Analytics – No Show Rates

My career in healthcare started in longitudinal qualitative research and programming, and project and data management have been foundational in all of my professional roles. In this blog I will focus on a specific application of data. Data work best when you have them, understand them, and apply them (and YES, data are plural!)

No Show Rates (NSR) are an oft-used measure of ambulatory productivity, and they vary in definition, depending upon the breadth, and depth, of an EHR’s definition and statuses of a visit. For today, let us say that a NS is a scheduled visit for which a patient does not show at the clinic within 15 minutes of the scheduled time. You can use whatever definition you want, I offer this as a starting point – there are easier to implement definitions – what is important is to be clear about the definition, and consistent about its application.

Once you have a definition of a NS, which will lead to a NSR (number of NS divided by total number of visits – be sure to use the same time period for numerator and denominator), identify a target. Do you want to reduce your NSR by a specific percentage decrease (from 28% to 20%), over a specified time (within 12 months of go-live)? Do you want to focus on Primary Care, or a specialty? If a specialty, are there patient considerations that are unique to the specialty (I do not recommend starting with psychiatry, for example)? Do you have buy-in from the clinic, both leadership and the care teams? Most importantly, if you decrease NSR, can you handle the uptick in visit volume at the site?

What will be your ROI? There are many reasons to reduce NSR (improve patient care; revenue generation associated with the visit itself, but moreso, with ancillary tests and procedures which follow a visit; optimization of staffing and capacity planning, etc.) and many approaches to do that (double or triple-booking, pre-visit contact, either automated or live contact, etc.). Some of those approaches are more labor, or technology-intensive. How do you justify the expenditure for these resource asks?

If you average 20,000 visits a week, and your NSR is 28%, that means that 5,600 visits a week are not happening. This cannot be good for patients’ health, and it is clearly not good for the staff who prepped for the visits, the offices that were open to receive those visits, and for the patients who could not get an appointment, because these other visits were scheduled. And obviously it does not help the bottom line of the institution. Now let’s say that your average visit brings in $25. You are losing $140,000 a week!

Let’s say that you want to reduce NSR from 28% to 20%. This would mean that ‘only’ 4000 visits a week would NS (20,000*20%). This would mean that across your institution, you have to prepare for 1600 more visits a week (5600-4000). Are you ready for that, from scheduling and staffing perspectives? If you generate 1600 additional visits a week, at an average of $25 per visit, you now are bringing in $40,000 a week, to offset the additional staffing needs. PLUS, the revenue from the ancillary test and procedures, which can be significant, depending upon the department.

You will never achieve a zero NSR – it is not realistic. But you can calculate what the impact of decreasing your NSR might be, in terms of revenue, and resources needed, which can help you determine if a new piece of technology to help identify patient likely to NS, is worth the investment (especially if it integrates with your EHR!) Just think, what if you could proactively identify the patients most likely to NS, and contact them in advance, or send them a ride-share, or reschedule before the visit?

The opportunities for improvement in healthcare are endless, but improving NSR can be a win for patients, providers, and institutions alike. Data are your friend – and like your friendships, the more you invest in them, the more you get from them!

Contributed by Tanya Zucconi, WHCM Steering Committee Member