Dynamic Talks Seattle: Patient No-shows and Late Cancelations is estimated to cost around $150B across the nation. Providence St. Joseph Health, Healthcare Intelligence Group has been working on this pain point for the past couple of years and has developed a software solution leveraging a predictive engine to identify high risk patients at risk of No-show and Late Cancellation on a daily basis. More than 25 clinics have been using this solution for about 2 years now to optimize their reminder call strategy and to have a meaningful reduction of No-shows and Late Cancellations. In addition, a call center pilot was designed recently to standardize this process end-end. Pilot results will be evaluated to prove the impact at scale.

1. 1
Product Management and Advanced Analytics
Shervin Majd
No Show Application
Prevent Missed Appointments

2. 2
Pain: No Show Impact in Healthcare
Limited effect
of Automated
reminders/calls
$196
Avg. Cost of
a single No
Show
600,000
No
Shows/year
(PSJH)
(Conservative estimate
based on national avg.)
997
PSJH
Clinics
*: Late Cancels have similar economic burden to no shows
$150B/Year
nationally
Total Cost
12%-50%
No Show
Rate*

3. 3
Solution: No Show Application
• PSJH has developed the No Show Web Application (Nov 2017) to reduce high rates of late cancels and
no shows
• It works based on a statistically-accurate multi-variable predictive model (more than 50 discreet
parameters) using PSJH data
– Parameter Categories: patient’s past appointment history, demographics, clinical and social history, and
appointment-specific factors
• An 8 week pilot in 2015 with two clinics validated the No Show predictive model (3,235 calls made, 49% of
high risk expected no shows were avoided)
• Near-real time data from Epic (updated every 2 minutes) keeps clinics from calling people who have
already cancelled/confirmed

4. 4
Product Release | Customer Traction
“…I believe it has helped our
no-show rate. I also have
noticed that those patients on
the No Show [app] seem to
realize why they are being
contacted and are more diligent
about coming for their
appointments.”
-- Becky Anderson, PMG
Newberg Orthopedics
“Everything worked well for
me…overall [No Show] was very
easy to use”
-- Melissa Harrison, PMG Sunset
Internal Medicine
• No Show Application Version 1 release was launched in
November 2017, deployed enterprise-wide, with active sites -
14 Clinics- in Oregon.
• In December 2017 and January 2018, average of 1500 calls
per month were made and average no show rate was
reduced by about 20%.
• Currently, covering 45 active clinics in Oregon, Kadlec,
Swedish and Washington regions. We make close to 9000
calls/month (~500% increase).
• In October 2018, achieved 100% compliance for 10 am daily
data refresh.
• In February 2019, we optimized application performance
(response time <1.2 s)

5. 5
ROI Case Study – Sunset Medical Plaza
• Sunset clinic was early adopter of the No-Show App,
with calls starting in October of 2017
• Approximately called 30% of patients using No-Show
app
• ROI case study compared year-over-year data to see
impact for next-day call model
• ROI >400% (conservative estimate)
Sunset Internal Medicine, Portland OR

6. 6
Education drives adoption: Manager Graph 2.0
No Show / Late Cancel Visibility Impact on Adoption

7. 7
2019: Validate ROI at scale (Critical Step for Enterprise Adoption)
Call Center Pilot
Overview
• Small call center to validate no show impact and ROI at scale
• Duration: 6 months; 20 clinics
• Focus on Primary Care and two areas of specialty care – Neurology and Gastroenterology
• Streamline the end-end protocol (automated text, IVR and No Show calls)
Key Objectives
• Engage with clinics with high No Show/Late Cancel rates to reduce No Shows and Late Cancels
• Examine impact of personal calls and increased engagement with high No Show risk patients
• Implement a consistent end-end protocol to generate clear data for validation of impact at scale

8. 8
9:00 AM – 10:00 AM
Liaisons will work to
enter confirmations and
cancellations from
Automated Text/IVR
vendor reports from
9:00 – 10:00 AM
10:00 AM
Data in the No
Show application
will be refreshed
daily by 10:00 AM
Liaisons will begin calling
(high risk) patients that
appear in No Show
Exclusions:
• New and Clinical Support
appointment types
• Appointments already
confirmed or canceled (via all
channels, myChart, etc.)
Liaisons document
call outcomes in
the No Show app
and Epic
Overview of Daily Workflow
10:00 AM – 5:30 PM

9. 9
Measuring the Impact
Metrics & Analysis
Success Measures
• Reduction in No Show / Late Cancel Rate
• Patient Experience (testimonials, qualitative)
• Increase in additional arrivals and minimize empty slots
Metrics
• No Show / Late Cancel Rates (YoY data, before and after pilot start)
• Empty slot metric per provider per clinic (YoY data, before and after pilot start)

10. 10
Questions?