Clinical Research Oriented Workshop (CROW) Meeting: April 1, 2021

 

Present:   Levi Bonnell, Justine Dee, Juvena Hitt, Emily Houston, Ben Littenberg, Charlie MacLean, Jen Oshita, Adam Sprouse Blum, Connie van Eeghen, Mariana Wingood (10)

 1.                   Warm Up: happy April Fool’s Day 😊

2.                   Emily Houston: an outline to request EPIC data on comparing pre and post pandemic no-show rates for UVMMC Neurology dept.  Interested in the group's thoughts on what is important to collect and analyze. Tips on using EPIC reports.

a.       The question is: does telehealth affect no-shows (not: does a pandemic affect no-shows)

                                                   i.      There is a range of individual preferences, affected by experience

                                                 ii.      Consider collecting qualitative data

                                               iii.      Social needs are related to no shows, including transportation

b.       Audience: Neurology

c.       What are the rules about cancellation vs. no-show

                                                   i.      It is possible to tell when a cancellation/no-show was identified

                                                 ii.      Is there a business group that can extract the data for Emily?

1.       Business Enterprise group?  Depends on your intentions.  There is a common request through the data management office (part of Jeffords or vice versa). 

a.       If research: secular activities of No Shows – IRB

b.       If QI: no IRB (exemption 4)

c.       Use “Service Now” for a service IT request

d.       Is this FINER, especially, interesting to Emily?

                                                   i.      Long standing value of telehealth; would like to be able to support the department’s switch to telehealth

1.       Is there a reason the department wouldn’t do it?  Same payment; less costly.

2.       Chiefs of divisions were curious; questioning telehealth

3.       Can the use of telehealth be customized at the patient level?

e.       Surveys of patients about telehealth in place? Don’t know

f.        Analysis

                                                   i.      Analyze by division and appointment types

1.       Sit with the schedulers and find out how the system actually works

2.       What if a provider no-shows?

                                                 ii.      Variables include patient preferences, social needs, weather, no show history… also context: providers coming in new with open schedules vs providers leaving that adds more volume to remaining providers

                                               iii.      Focus on one location with several providers to pilot the study

1.       Startup of telehealth was messy; pick a good period

                                               iv.      Consider using billing data: high quality, in order to drop a claim

                                                 v.      Consider combining what is known from the medical record

1.       Diagnoses

2.       Distance

3.       Snowbird status

4.       Communication disability

5.       Broadband status for address

6.       Analyze according to range of mobility – a perspective that is likely to be FINER

g.       Have fun dredging the data and don’t get lost!

3.                   Next week:  TBA