Fast Track to Fertility
Project status
Innovation leads
Funding
Innovation Accelerator Program
External partners
Memora Health
Opportunity
Nationally, one in eight couples has trouble getting pregnant. Infertility can lead to substantial distress due to the emotional, physical, financial, and logistical burden it places on patients.
Most patients have been trying to get pregnant for at least a year, if not several years, before seeking fertility care. So, when they make an appointment, the emotional stakes can be high, and patients are eager to get started.
After an initial visit with a doctor, couples must complete a fertility workup so that a personalized treatment plan can be developed. Both partners are assigned steps to complete, which can include blood work, ultrasound, X-ray tests, semen analysis, and genetic testing. Many of the tests and procedures for the female partner are menstrual cycle-dependent, which can lead to significant delays in completion if testing windows are missed.
When this work began, the wait time for new patient appointments at Penn Fertility Care was about four to six weeks. And the time it took couples to complete their fertility workup spanned between two to three months.
Each month that goes by for patients represents a missed opportunity to get pregnant.
Intervention
Fast Track to Fertility (FTF) is a novel care delivery model that introduces a digital front door to improve access to fertility care.
When patients call for an appointment, they are scheduled for a telehealth visit with an advanced practice provider (APP). During these visits, APPs obtain information about the couple’s medical history, provide education, and answer questions. They also enroll patients in a texting program that leverages artificial intelligence to support users in navigating the complicated, time-sensitive, and cycle-dependent workup process in the shortest time possible.
Historically, patients had to wait until their first appointment with a physician to begin intake and workup. Leveraging APPs to complete this step enables patients to get started on their journey sooner. It also sets the stage for more productive and personalized physician visits once workup is complete.
Impact
FTF improves patient access and enhances care delivery while streamlining provider and care team workflows.
The redesigned model has increased annualized new patient access by 24 percent and decreased both time to initial appointment and time to initiation of treatment by approximately 50 percent. And the delivery of educational materials and anticipatory guidance via text has contributed to increased patient engagement and satisfaction.
In June 2021, it became the standard care model across all Penn Fertility Care sites. The team is actively exploring ways to continue to enhance and expand the program.
Innovation Methods
A day in the life
A day in the life
We immersed ourselves in the patient process by making calls to schedule new fertility appointments at Penn Medicine and non-affiliated clinics.
This helped us learn all the ins and outs of the intake process from the patient's perspective and identify areas that could be optimized.
A day in the life
One of the best ways to learn more about a problem area is to experience it yourself. Immerse yourself in the physical environment of your user.
Do the things they are required to do to gain a firsthand experience of the challenges they face. Completing a day in the life exercise will enable you to uncover actionable insights and build empathy for the people you're hoping to help.
Fake back end
Fake back end
Fake back end
It is essential to validate feasibility and understand user needs before investing in the design and development of a product or service.
A fake back end is a temporary, usually unsustainable, structure that presents as a real service to users but is not fully developed on the back end.
Fake back ends can help you answer the questions, "What happens if people use this?" and "Does this move the needle?"
As opposed to fake front ends, fake back ends can produce a real outcome for target users on a small scale. For example, suppose you pretend to be the automated back end of a two-way texting service during a pilot. In that case, the user will receive answers from the service, just ones generated by you instead of automation.
Fake back end
We used a fake back end to test the impact of texting patients to guide them through their fertility workup.
Members of our team mimicked the communication of an automated bot during initial pilots. Running a fake back end helped us validate that texting information and reminders could reduce the time it took for patients to complete their workup before building an automated program.