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1
Product Management and Advanced Analytics
Shervin Majd
No Show Application
Prevent Missed Appointments
2
Pain: No Show Impact in Healthcare
Limited effect
of Automated
reminders/calls
$196
Avg. Cost of
a single No
Show
600,00...
3
Solution: No Show Application
• PSJH has developed the No Show Web Application (Nov 2017) to reduce high rates of late c...
4
Product Release | Customer Traction
“…I believe it has helped our
no-show rate. I also have
noticed that those patients ...
5
ROI Case Study – Sunset Medical Plaza
• Sunset clinic was early adopter of the No-Show App,
with calls starting in Octob...
6
Education drives adoption: Manager Graph 2.0
No Show / Late Cancel Visibility Impact on Adoption
7
2019: Validate ROI at scale (Critical Step for Enterprise Adoption)
Call Center Pilot
Overview
• Small call center to va...
8
9:00 AM – 10:00 AM
Liaisons will work to
enter confirmations and
cancellations from
Automated Text/IVR
vendor reports fr...
9
Measuring the Impact
Metrics & Analysis
Success Measures
• Reduction in No Show / Late Cancel Rate
• Patient Experience ...
10
Questions?
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Reducing No-shows and Late Cancelations in Healthcare Enterprise" - Shervin Majd, Ph.D

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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.

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Reducing No-shows and Late Cancelations in Healthcare Enterprise" - Shervin Majd, Ph.D

  1. 1. 1 Product Management and Advanced Analytics Shervin Majd No Show Application Prevent Missed Appointments
  2. 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. 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. 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. 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. 6 Education drives adoption: Manager Graph 2.0 No Show / Late Cancel Visibility Impact on Adoption
  7. 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. 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. 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. 10 Questions?

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.

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