Project Mars | Outpatient Practice Redesign

MICRO-CONSULTS

Iteration 1: Proof of Concept

Experimental Findings & Next Steps

© 2013 MFMER

Iteration 1: Experiment Findings | Overview

WHAT: An integrated care model where multiple providers meet with a patient simultaneously

in a clinical space using technology that allows them to virtually connect and collaborate.

Typically effective for a focused question that leads to diagnosis and adjustment to treatment.

Can be scheduled or unscheduled.

WHY: Not all patients need or have immediate

access for a traditional appointment. Micro-consults

become a more formalized “curbside”. They will

provide:

Increased access

Decreased itinerary length

Improved diagnosis and treatment options

Less duplicity of resources – people and space

Aligns with near-future reimbursement models

© 2013 MFMER

Four separate experiments were completed for Iteration 1 findings

Experiment 1: Scalability Study – Met with providers to review their days’ appointments to identify

which consults could have been a micro-consult

Goal was to understand where micro-consults would have the greatest impact in the practice

5 providers chosen to represent different types of providers; Dr. Feyereisn, Dr. Wermers, Dr. Ommen,

Dr. Lightner, Dr. Huddleston

Experiment 2: GIM – Attempt to predict micro-consults based on pre-visit information. GIM was

identified from the scalability study as a key partner

Goal was to understand the needs for complex, non-acute patients

3 initiating providers; Dr. Feyereisn, Dr. Lundstrom, Dr. Mikhail

Experiment 3: Dialysis – Identify dialysis patients who need micro-consults with a specialist

Goal was to understand the needs for complex, acute patients to intervene to avoid potential ED visits

2 initiating providers; Dr. Williams and Christy Gossett, RN, CNP

36 receiving providers recruited to be “on-call” for potential micro-consults*

*A full list of providers who agreed to participate as receiving specialist can be found in Appendix 1.

Iteration 1: Experiment Findings | Experiment and Partners

© 2013 MFMER

Experiment 4: ECH - Identify patients based on PCP’s predicted benefit from specialist advice

Goal was to support chronic patients to meet their needs in primary care rather than being

referred to a specialist

5 initiating providers; Dr. Allen, Dr. Anderson, Jennifer Bold, RN, CNP, Dr. Furst, Dr. Matthews

37 receiving providers recruited to be “on-call” for potential micro-consults

The process we followed for experimentation in the practice is shown below:

Iteration 1: Experiment Findings | Experiment and Partners

© 2013 MFMER

Experimentation in the practice, all had the following qualitative and quantitative metrics:

Appointment Length: The length of the micro-consult or coordinated care appointment.

Captured through the technology.

Impact and Acceptance of the Technology: Captured qualitatively through debrief interviews

with both providers and the patient regarding their impressions of the technology from a

performance and overall acceptance perspective.

Value: Captured qualitatively through debrief interviews with both providers and the patient

regarding the value of the interaction.

Patient and Provider Satisfaction: Captured qualitatively, and in most instances through

numerical rating, with both providers and the patient, regarding the satisfaction and overall

thoughts about the interaction.

Additional metrics that were experiment specific included:

Frequency of micro-appointment: For the scalability study, the percentage of micro-consults

relative to number of overall appointments.

Referral Status: For the ECH study, if the patient is referred to the outpatient practice

immediately following the micro-consult.

Iteration 1: Experiment Findings | Metrics

© 2013 MFMER

Chart review to identify potential micro-consults. In total we evaluated 154 appointments

comprised of new and established patients. 48 micro-consults were identified* across departments

comprising 31% of overall appointments.

Dr. Ommen: 25 appointments; 6 (23%) could have been micro-consults

Dr. Wermers: 19 appointments; 6 (35%) could have been micro-consults

Dr. Feyereisn: 22 appointments; 11 (50%) could have been micro-consults

Dr. Lightner: 62 appointments; 14 (23%) could have been micro-consults

Dr. Huddleston: 26 appointments; 6 (23%) could have been micro-consults

Implications: There is a significant opportunity for a micro-consult care interaction across Mayo

Clinic, specifically the opportunity to initiate micro-consults in GIM as well as specialties. In

surgical practices the potential is in receiving micro-consults but should be balanced with other

interactions such as eConsults and Remote Recheck.

This study allowed us to focus on GIM as one of our key partners.

*A full list of specialties that would have been on the initiating or receiving end of potential micro-consults is included in Appendix 2.

Iteration 1: Experiment Findings | Results of Scalability Study

© 2013 MFMER

Combining all experimentation, we completed a total of 27 micro-consults

13 in GIM, 5 in dialysis, 8 in ECH, and one additional opportunity arose with our Breast Cancer

Service Line partners while doing a different experiment

The average length was 9 min 15 sec. Individual times are shown below.

Iteration 1: Experiment Findings | Overall Amount of Micro-Consults and Length

© 2013 MFMER

Each micro-consult was evaluated to understand what slot type it would have filled if it had

been a referred consult (e.g. new, established, return)

Matching the appointment time to the slot times in each department and subtracting the

lengths of the micro-consults, we saved a total of 1035 appointment minutes or 17.25 total

appointment hours for 27 micro-consults. Specifically:

146 minutes for 3 Cardiovascular micro-consults; 193 minutes for 6 Endocrinology micro-consults;

136 minutes for 4 Gastrointestinal micro-consults

For each micro-consult we also looked at the approximate availability of the referred to

department or specialty. Overall we saved patients a total of 118 days on their itinerary we

an average of 4 days across all patients. Specifically:

• Longest next available appointment were in the following departments / specialties: Pulmonology,

Cardiology, Endocrinology, and Nephrology

Iteration 1: Experiment Findings | Time Savings

© 2013 MFMER

Value: All of the micro-consults were considered a success (to some degree) except one

which involved an undiagnosed cough. Some of the longer, more unfocused questions, while

not optimal to the receiving provider, did provide initiating providers information they did not

know and helped them move forward with treatment of their patients.

Impact: All but two eliminated the need for an additional referral

Iteration 1: Experiment Findings | Impact and Value

Initiating Provider’s Comments

Dialysis: We were able to schedule an EGD for the

patient, something I could not order without a GI

consult. This allowed patient care to move forward

quickly and satisfy the patient who was significantly

impacted by the condition. – Christy Gossett R.N.,

C.N.P

ECH: The micro-consult saved a full consult to

Endocrinology, avoided unnecessary testing, and

reassured me that my evaluation so-far was

complete. – Jennifer Bold R.N., C.N.P

ECH: The micro-consult helped anxious parents

looking for answers. The specialist re-enforced my

advice and treatment plan. – Dr. Allen

GIM: The micro-consult summed up a two-week

investigation into the patients condition, which was a

rare genetic mutation, that provided her the answers

she needed before returning home to Mississippi.

Speaking with the Geneticist also provided the parent

insights that her brother could also have the same

genetic mutation. – Dr. Feyereisn

GIM - The micro-consult expedited the process a

great deal and after confirming the diagnosis with

Endocrinology the patient changed his travel plans

and opted for surgery the next day at Mayo Clinic.

– Dr. Mikhail

© 2013 MFMER

Iteration 1: Experiment Findings | Impact and Value

Receiving Provider’s Comments

GI: This is excellent. Far superior to a face-to-face

with the patient, because the Dialysis NP was present

and she could help interpret relevant medical

information. There is great potential for this process.

We could potentially do 6 of these in an hour, saving

everyone time and money. - Dr. Loftus

Pediatric Endocrinology: This micro-consult added

value for the PCP and because we did this “face-to-

face” where I was able to see the child, and ask

questions to the mother, I changed my opinion that

immediate bone tests were necessary. Due to this

type of interaction I felt comfortable supporting a wait-

and-see approach. – Dr. Ltief

CV: The micro-consult is what we do everyday, just

with technology. It is essentially how we practice now.

– Dr. Brozovich

Patient Comments

ECH: The most positive thing is that we are all

immediately on the same page. Dr. Allen knows

what the specialist said and can ask questions I

wouldn't have thought of. I don't have to try to

remember for my next appointment, everyone

already knows the story. – Patient

GIM: I liked the practicality of it - I didn't have to

wait a few days to get this appointment. – Patient

GIM: I liked being able to speak with the specialist

sooner and with Dr. Lundstrom in the room, he

knew what to ask and could mediate. - Patient

Dialysis: This was very helpful, we knew Randy

needed to be seen by a specialist and didn't know

when that could happen, the sooner the better. It's

good to use the time that he is in dialysis, he is a

captive patient and driving here on Tuesday or

Thursday would be hard because it is a long drive

and on dialysis days he is so wiped out

afterwards. –Patients wife

© 2013 MFMER

For the most part, initiating providers, receiving providers, and patients all reported high levels of

satisfaction with the experience. We asked the following question*:

On a scale of 1 to 7 with 1 being the lowest and 7 being the highest, please rank your level of satisfaction.

Overall only two people gave the interaction a ranking lower than 5. One was a specialist who was asked to

answer an unfocused question and the second was a dermatologist who participated on a micro-consult that

had technology issues. She also mentioned she would like to see the patient’s rash in better detail.

– The average ranking for initiating providers was 6.1

– The average ranking for receiving providers was 5.7

– The average ranking for patients was 6.2

Specific feedback from receiving providers, essentially those who do not gain any immediate value from

this interaction, was:

Many provides mentioned that if this interaction would become part of their practice they would need to have

time protected to do these and / or get credit for them. Several mentioned that there have been many add-on’s

to the typical day including eConsults and appointment triage which have been maxing out physician time.

While many took the time to review the patients clinical note prior to the micro-consult, a few mentioned feeling

unprepared; however, this concern did not negatively influence any of the interactions. One provider specifically

did not prepare as he wanted to try it as “real-time” as possible.

*Survey questions were developed after experimentation began. 18 of the 26 micro-consults had survey questions captured by all participants.

Iteration 1: Experiment Findings | Overall Satisfaction

© 2013 MFMER

Two challenges emerged related to if, and how, these interactions can occur.

Real-time availability versus scheduled: In experimentation we attempted to identify micro-consults to allow us

time to “schedule” them with the receiving specialists. With all, we reviewed next day appointments and with

GIM also used pre-visit information.

– While we were able to predict some, we often heard from our providers their need arose real-time during

an appointment based on new information or situation.

– With dialysis patients there was more scheduling flexibility as dialysis is multiple times a week and typically

have a 2-4 hour window for the micro-consult as they are receiving dialysis; however, while some could be

scheduled, others needed same day attention.

Timing: Arranging a time for a specialist to connect with a scheduled appointment in GIM and ECH proved

challenging due to real-time variables, such as earlier appointments running late. This impacted when the

connection between two providers and the patient occurred.

– Delays in GIM were approximately 10-15 minutes while in ECH they were much greater. Some micro-

consults in ECH occurred 45 minutes to an hour later than originally scheduled.

Implications: The next round of prototyping should support real-time scheduling and rely on technology

or other solutions that indicate availability of specialists. Additionally, we should better connect pre-visit

information to experimental areas to understand benefits outside of GIM of pre-visit.

Iteration 1: Experiment Findings | Scheduling Challenges

© 2013 MFMER

We had significantly more micro-consult requests than we could schedule, even with 26

providers available to cover the experiment. Specifically we had 26 requests we could

not full in ECH and 5 requests we could not fill in GIM.

Scheduling: Our current scheduling system does not support this type of interaction.

Providers are not given time to do these and, as they are hard to accurately schedule, it is

hard to fit them in between patients.

– Knowing this challenge, we contacted multiple providers in departments with the highest

referrals and focused on recruiting providers who were staffing clinics and / or had

flexibility with administrative time. Even with this planning it wasn’t enough, as providers

get add-on patients and take vacation.

Implications: We need to think creatively and solve this problem for the next round of

experimentation, especially in light of the fact we could not fill 72% of ECH requests and

38% of GIM requests. Ideas include:

Provide protected time for specific providers to participate in the experiment

Scale the next experiment to whole departments and include situational awareness of who

has availability so there is greater possibility of success

Iteration 1: Experiment Findings | Provider Availability

© 2013 MFMER

For Iteration 1 we chose to use Face Time on an iPad and support each micro-consult by bringing

both providers iPads that we knew connected. Even with these precautions, we had the following

technology challenges:

Wi-Fi Connection: In many instances the broadband connection was slow and the video skipped. In two

instances the first calls dropped before connecting and in two instances we could not connect between

locations, specifically locations outside of Gonda / Mayo.

Sound Quality: While most micro-consult participants thought the sound quality was adequate, one provider

hooked his iPad to speakers for better sound. We also observed the dialysis environment made the audio

hard to hear, though participants did not comment on this as being negative, rather it was expected.

Picture Quality: In the cases of our Dermatology consults, it was recommended we take a 'dermascopic'

photo for better visibility. We also heard from Orthopedics that being able to connect to a larger monitor may

help in instances where they may want to see the patients walk.

Limitations of Technology: Using technology as an alternative to face-to-face appointments limits the ability

to execute a physical exam. While none of the providers specifically minded this, understanding this was a

micro-consult instead of a full consult, several did comment that this means they need to trust the other

provider to do a proper exam that may have nuances for each specialty.

Implications: The next iteration prototype should be attempt to be as user friendly as possible and the

technology should be seamless. Many commented if the connection did not work in real-time they

would not try and troubleshoot.

Iteration 1: Experiment Findings | Technology

© 2013 MFMER

Iteration 2: For the next iteration we want to create a lo-fi prototype that will allow micro-

consults to happen between two providers without our involvement in scheduling and

technology support. The specific goals of Iteration 2 include understanding:

Workflow implications: Understanding how providers, on their own, can identify, initiate and

execute a micro-consult.

Scheduling implications: Working to identify and plan micro-consults as well as allow micro-

consults to happen real-time.

Technology implications: Understanding how the prototype changes micro-consult

interactions and learnings for how the micro-consult functionality can best connect to Smart

Space in the next iteration.

Iteration 1: Experiment Findings | Next Steps

© 2013 MFMER

Initiating Providers

GIM Providers

Dr. Feyereisn

Dr. Lundstrom

Dr. Mikhail

ECH Providers

Dr. Anderson

Dr. Furst

Dr. Matthews

Dr. Puffer

Dr. Summer

Jennifer Bold, R.N., C.N.P.

Heather Carrico, R.N., C.N.P.

Dialysis Providers

Dr. Williams

Christy Gossett, R.N., C.N.P.

Iteration 1: Experiment Findings | Appendix 1

Receiving Specialist Providers (Recruited and Participated)

Dr. Maddox, Allergy

Dr. Ghosh, Breast Clinic

Dr. Brozovich, Cardiology

Dr. Ommen, Cardiology

Dr. Wright, Cardiology

Dr. Brewer, Dermatology

Dr. D. Davis, Dermatology

Dr. M. Davis, Dermatology

Dr. McEvoy, Dermatology

Dr. Castro, Endocrinology

Dr. Kennel, Endocrinology

Dr. Lteif, Pediatric Endocrinology

Dr. Montori, Endocrinology

Dr. Wermers, Endocrinology

Dr. Kimori, Genetics

Dr. Loftus, GI

Dr. Schaffner, GI

Dr. Tung, Pediatric GI

Dr. Langstraat, Gynecologic Surgery

Dr. Hansel, GI and Hematology

Dr. Lacy, Hematology

Dr. Dillon, Nephrology

Dr. Williams, Nephrology

Dr. Bartleson, Neurology

Dr. Cutrer, Neurology

Dr. Kantarci, Neurology

Dr. Swanson, Neurology

Nancy Honeychuck., R.N., C.N.P.;

Neurology

Dr. Huddleston, Orthopedic Surgery

Dr. Turner, Orthopedic Surgery

Roger Thomas P.A.-C, Orthopedics

Dr. Moore, Otorhinolaryngology,

Dr. Shelerud, PM&R

Dr. Edell, Pulmonology

Dr. Lim, Pulmonology

Dr. Viggiano, Pulmonology

© 2013 MFMER

Iteration 1: Experiment Findings | Appendix 2

Dr. Feyereisn to Dr. Ommen

Dr. Feyereisn to Dr. Lim

Dr. Feyereisn to Dr. Castro

Dr. Feyereisn to Dr. Wermers

Dr. Feyereisn to Dr. Wood

Dr. Feyereisn to Dr. Williams

Dr. Feyereisn to Dr. Schaffner

Dr. Lundstrom to Dr. Shaffner

Dr. Feyereisn to Dr. Kimori

Dr. Mikhail to Dr. Kennel

Dr. Lundstrom to Dr. Maddox

Dr. Mikhail to Dr. Montori

Dr. Lundstrom to Dr. Edell

Dr. Williams to Dr. Schaffner

Dr. Williams to Dr. Lacy

C. Gossett, CNP to Dr. Loftus

C. Gossett, CNP to Dr. Brewer

C. Gossett, CNP to Dr. Brozovich

Dr. Ghosh to Dr. Langstraat

J. Bold, CNP to Dr. Montori

Dr. Anderson to Dr. Dillon

Dr. Allen to Dr. Ltief

Dr. Puffer to Dr. Kantarci

Dr. Allen to Dr. Davis

H. Carrico, CNP to Dr. Davis

Dr. Puffer to R. Thomas, CNP

Dr. Anderson to R.Thomas, CNP

Providers Reason Providers Reason

Managed heart condition

Undiagnosed cough

Managed diabetes

Managed diabetes

New stent

Low kidney function

GI upset; recent colonoscopy

GI related to neuro symptoms

Diagnosis confirm. & next steps

Medication question

Low levels of IGM

Access issues

New cough

GI upset

Dropping platelets

Stomach upset after surgery

Open wound

Chest pressure

Future care for BRCA1 positive

Elevated labs

Kidney stone follow-up

Decline in growth chart

Parkinson’s management

Rash across body; misdiagnosed

Rosacea and acne

Knee pain – next steps (injection)

Knee pain – next steps (exercises)