mHealth Labs
Fall 2015-Spring 2016 Projects
Definition of terms
 UPHS: University of Pennsylvania Health System, also known as Penn
Medicine. Comprises several hospitals and dozens of clinics in and around
Philadelphia. In top 10 healthcare system in the country.
 Attending physician: senior level doctor
 Resident physician: junior level doctor
 HCAHPS scores: standardized measurement of patient satisfaction around
healthcare experiences.
Team member roles
 Sponsor: Penn Medicine faculty or executive staff member who identifies the
project “problem” and its importance.
 Manager: Penn Medicine faculty, staff, or student who leads the project on a
weekly basis.
 Advisor: An expert who can provide mentorship in the project.
Links to Project Descriptions
1) Create a More Efficient Tool for UPHS Staff Announcements
2) PAT: Penn Appreciation Thread
3) Design a Dashboard for Apple HealthKit Data
4) Patient Discharge/Followup Appointment Tool
5) Visit planner for colon cancer screening
6) Text messaging appointment reminders and late notices
7) Re-Designing the System of Trainee Evaluation (NEW)
8) Increasing Clinical Trial Enrollment (NEW)
1)
Create a More Efficient Tool for UPHS Staff Announcements
Sponsors:
 Regina Cunningham (Chief Nursing
Officer)
 Jeffrey S. Berns, MD (Associate Dean
for Graduate Medical Education,
HUP)
Managers:
 Suzanna Ho, MSN (Coordinator of
Patient Safety & Quality Nursing,
HUP)
Advisors:
 Subha Airan-Jaiva, MD (Attending
physician; Associate CMIO)
Problem:
 Current announcements to the thousands of UPHS doctors and nurses are
disjointed and inconsistent.
Solution ideas:
 A way to publish announcements to UPHS staff that allows consistency,
coordination, tailoring.
 User behavior can be tracked to close the feedback loop
Proposed Implementation ideas
 A responsive web app with tailoring by user role, interests, and priority
levels
 Occasional Email and Cureatr (secure text) messages can be triggered for
high priority messages and to draw users back to the app.
User setting
 Doctors, nurses, other UPHS staff in a mobile setting
Riskiest assumptions to validate
 Content providers will use the app; will be able to fit their content effectively.
 Users will access the app regularly over time; will effectively consume the
content.
Example evaluation plan
 Beta tester nurses: have read and understood more of the announcements
than status quo.
2)PAT: Penn Appreciation Thread
Managers:
 Kat Lee, MD (ED resident physician)
 Ian Oppenheim, MD (medicine resident
physician)
 Clint Orloski, MD (resident physician)
Advisors:
 Jennifer Barger, MS, BSN, RNED (Quality
and Safety Coordinator for the ED)
 Jen Myers, MD (Associate Designated
Institutional Official for Quality and
Euromedic.
Safety, Graduate Medical Education,
ie
UPHS)
Problem
 Currently, employees and health care providers at all levels and departments
within the hospital are limited in the ways that they can communicate and
document positive feedback/recognition in realtime manner
 Current positive feedback/recognition methods include paper/pencil
modalities (ex. nursing recognition boxes) as well as digital ones (ex.
Electronic Evaluation Forms, email). The former methods are typically
limited to nursing staff, require manual data entry and processing before
reaching both the employee and manager and therefore lengthy delivery
times. Digital methods present their own set of unique challenges. Electronic
Evaluation Forms do not typically facilitate real-time data collection and are
limited to certain individuals being able to provide feedback on a given
employee.
Solution ideas
 Facilitate positive feedback among care providers
 Aggregate positive feedback/recognition reports so that both employees and
managers may view compiled submissions.
Implementation ideas
 Mobile/desktop web app allowing structured feedback about patient care
delivery among the care team. Integration with the UPHS phonebook.
User setting
 Doctors, nurses, or any UPHS employee
Riskiest assumptions to validate
 Users will be motivated and remember to enter data
 The data will lead to behavior and culture change
Example evaluation plan
 Proximal: adoption of the system by a certain number/range of users
 Distal: behavior change; job satisfaction, inter-departmental collegiality
Data sensitivity: Minimal (no patient data)
3) Design a Dashboard for Apple HealthKit Data
Sponsors:
 Susie Day (MD and director of Ambulatory
Quality Improvement DGIM, EPIC Ops)
Managers:
 Angela Starnes (Practice Manager PIMA
clinic)
Engineering faculty:
 John Smith, CIS
Advisors:
 Michelle Hu, MD
 Kate McGill-Armento, NP (lead NP DGIM)
 Chileshe Nkonde-Price, MD (Director of Women’s
Cardiovascular Center)
www.appleheal
thkit.com
Problem
 Integrations such as Apple Healthkit now allow data from patient’s phones to
be sent automatically to their health providers. This includes passive sensor
data such as activity tracking as well as data from specialized apps such as
glucose trackers for people with diabetes. When the data arrive in the
electronic medical record, however, they are not currently organized in a
useful way for providers to understand quickly and make clinical decisions.
Solution idea
 Healthkit data is processed with enough sophistication that the right
provider is given actionable information at the right time.
Implementation ideas
 Web dashboard and/or push notifications when certain conditions are met
 Data analytics or visualization techniques to assist the primary care
providers
 Future integration with electronic medical record
User setting
 Primary care providers and their teams, either through pull or push style
access to data from patients’ phones.
 Patient data can focus on patients with diabetes, of which there are many at
these clinics
Riskiest assumptions
 Data from patient phones will be of sufficient quality.
 Providers will be motivated to use these data rather than the status quo.
 Providers will be able to act and change patient outcomes more effectively
using these data.
Example evaluation plan


Proximal: Providers are able to answer the questions they have about the
patient’s data and in a timely manner.
Distal: Providers action on these data and improve patient health outcomes.
4) Patient Discharge/Followup Appointment Tool
Sponsors:
 Scott Schlegel (Associate Vice President, Electronic
Health Record Integration, UPHS)
Managers:
 Michael McFall (Admission and Discharge
Coordinator, Martin Teaching Service, HUP)
 Rahul Banerjee, MD (Resident, Internal Medicine
Residency Program, HUP)
 Alex Suarez (Medical Student)
Advisors:
 Jen Myers, MD (Associate Designated Institutional
Official for Quality and Safety, Graduate Medical
Education, UPHS)
Problem
 Follow up appointments are a key component of a patient’s post-discharge
plan and for ensuring a safe transition between inpatient and outpatient
care. The current system is inefficient, however. Providers make
appointments with minimal patient input and, as a result, only 49% of posthospitalization outpatient follow-up appointments at HUP are currently
being kept as scheduled.
Solution ideas
 The goal would be to create a platform that would enable patients and
families to be involved in the scheduling process. The interface could convey
preferences regarding timing of followup appointments and relay this to the
schedulers. This interface would also potentially help to streamline
information about existing appointments.
At discharge patients provide specific data about their preferences for
scheduling and other aspects of follow-up appointments.
Implementation ideas
 Web app or interface that prints out patient’s existing scheduled
appointments along with directions to different locations
 Mobile web app that records patient’s followup preferences and helps
schedule appointments in epic (if possible). Potential for fake back end that
feeds to the schedulers who presently work to make patient appointments

Ability for patients to get numbers to make the followup appointments - and
perhaps a dashboard for tracking them if they did make the f/u
appointment? (added in by Eugene, not in Rahul’s initial email)
User setting
 Hospital patients
Riskiest assumptions to validate
 Patients will want to use the web interface
 Having patients involved will result in higher show rate
 We will be able to match the patient’s requests to open appointments
 Potential data need - inputting appointments into epic
Example evaluation plan
 Proximal: ability to use it within workflow
 Distal: rate of patients showing up for followup visits
Data sensitivity: Yes, should use schedules of real patients

5) Visit planner for colon cancer screening
Sponsor:
 Carmen Guerra, MD (Attending physician)
Manager:
 Christy Hong (Med student)
Advisors:
 Shivan Mehta, MD (Attending physician)
Problem:
 Some visits such as colonoscopies for preventative screening have a high noshow rate. Nurse navigators can improve show rates, but it takes them hours
per patient.
Solution ideas
 Streamlined interfaces for identifying patients eligible for navigator program
and following up with these patients
 Tailored information to patients of how to plan for a visit and what happens
during one.
Implementation ideas
 Automated voice/text messaging.
 Mobile web such as videos and information, can be linked from text messages
or email. Can be embedded in MyChart.
 Dashboard for keeping track of information for nurse navigator
User setting
 Patients to prepare for and remember an appointment
 Staff responsible for visit attendance
Riskiest assumptions to validate
 Data can be entered either automatically and/or conveniently enough by a
staff member.
 Patients will answer the calls and listen to the messages.
Patients want to comply with the schedule.
Example evaluation plan
 Proximal: Patients randomized to the intervention have a lower no-show
rate. Number of patients a single nurse navigator can maintain
 Distal: HCAHPS scores for these patients. Number of missed screenings.
Data sensitivity: Yes, should use schedule of real patients

6) Text messaging appointment reminders and late notices
Sponsors:
 Scott Schlegel
Managers:
 Marguerite Balasta, MD (resident
coordinator PIMA clinic)
 Angela Starnes (Practice Manager
PIMA clinic)
Advisors:
 Gillian Lautenbach, MD (lead
physician, PIMA clinic, Co Chair CPUP
Service Domain)
 Kristen Christenson, MD (lead
physician, Cooper clinic)
Problems
 Patient no-show rate for appointments.
 Patient dissatisfaction over long waits without knowing when they will be
seen by the doctor.
 No immediate and actionable way to get feedback after primary care
appointment.
Solution ideas
 Patients confirm appointment and receive a count-down.
 Patients know how long the wait is the day of the appointment
 Patients receive feedback solicitation immediately after appointment.
Implementation ideas
 Mobile web app that can be embedded within MyChart app (leveraging
existing patient login). Patients consent to communication, enter texting
phone number, and confirm their appointment.
 Responsive web page can also be accessed from the desktop kiosks in
waiting room, for patients who did not confirm remotely in advance.
 Text messages are sent prior to appointment as reminders.
 Texts are sent based on doctor lag time (available in Epic EMR) in the style of
Apple Store (10 minute warning).
 Texts are sent for feedback afterward. Some day these can be actionable such
as that we pay for parking (as an apology) before they get back to their car.
User Setting:
 Patients of a Primary Care Practice (3701 Market St, 6th and 7th floors)
Riskiest assumptions
Patients will have a MyPennMedicine registration.
Patients will be motivated and able to confirm, starting the process.
Patients will change behavior and/or satisfaction level based on the text
message reminders, alerts, and follow-ups.
Example evaluation plan
 Proximal: Quality of user experience.
 Distal: Patient satisfaction scores.
Data sensitivity: Yes, should use real patient schedules



7)
Re-Designing the System of Trainee Evaluation
Advisor:
 Dayna Levin (Program Director,
Radiology Residency)
Manager:
 Ben Hammelman (Associate Residency
Director, Radiology) or Mark Bolden
(Residency Coordinator)
Problem
 As trainees advance through medical
training, evaluation relies less on vetted and validated written or
computerized tests and more on observation, mentorship, and on-job
performance. This continues in post-graduate medical training where a
trainee's progress is typically measured using numeric scales filled out by
physician educators who may contribute a few comments along the way. It is
our observation that this information is unreliable and generally unhelpful
for both residency directors who are responsible for resident progress and
residents who are performing their own self-assessment and charting their
progress through medical training.
Solution idea
 A more accurate, valid system of trainee evaluation would chiefly benefit
medical residents in their training to have accurate feedback created through
a robust process they can trust in.
Implementation ideas
 A cloud-based tool for capturing small pieces of resident feedback from
faculty. A web could be placed on all computers which will allow faculty to
access a text box to enter small pieces of feedback about the resident
 A cloud-based entry and database system for coordinating a modified Delphi
process
User setting
 Radiology attendings and residents
Riskiest assumptions
 Evaluators will use this application to evaluate residents
 This system will lead to more accurate evaluation
 Residents will find the feedback derived from this system to be useful
Example evaluation plan:
 A mixed methods survey of physician educators and residents to evaluate the
content and face validity of our new evaluation process in anticipation of
publication and marketing
Data Sensitivity: Minimal (no patient data)
8) Increasing Clinical Trial Enrollment
Manager: Jennifer Monti, MD (Cardiology Fellow)
Problem: There is low enrollment in clinical trials for cardiovascular conditions. In
spite of patient interest in participating in clinical trials, there is lack of patient and
physician awareness and difficulty navigating the current system of identifying
clinical trials.
Solution Ideas:
 Deliver cardiovascular clinical trial options to patients that are interested
with description of clinical trials in basic language
Implementation Ideas:
 Design a website and mobile app that would deliver a list of available clinical
trials after a short patient survey
 Include options for paid individual and organizational subscription, which
would include a dedicated clinical trial team
User setting:
 Patients interested in finding clinical trials
 Physicians aware of the service would refer their patients
Riskiest assumptions:
 Physicians will take the time to refer patients to the website
 Patients will be willing to pay for such a service
Example evaluation plan:
 Beta testing of website with physicians and potential users, assessing:
number of patients engaged, number of free searches converted to paid
engagement, number of patients enrolled in a clinical trial
Data Sensitivity: Minimal