Eyes on Site
Project status
Collaborators
Thomasine Gorry, MD, MGA
Eydie Miller, MD
Tomas Aleman, MD
Innovation leads
Funding
Innovation Accelerator Program
Opportunity
Diabetic retinopathy (DR) is the most common cause of vision loss among working-age adults. Treatment of late-stage DR can cost as much as $28,000 per patient, while early-stage treatment costs are minimal.
No one has to lose vision to DR — those who do usually don't know they have it or find out too late. Early screening and treatment prevent vision loss in 90 percent of cases. However, because it is asymptomatic until later stages, many DR patients are unaware of the disease.
Traditional eye exams require an office visit to an eye doctor, take considerable time, and require pupillary dilation, which causes hours of disruptive blurred vision. Because of this time-consuming and negative experience, some patients are reluctant to complete screening.
In 2015, only 22 percent of Penn Medicine patients met recommended screening standards for diabetic eye care. However, 8,900 of these patients came to Penn Medicine for other services. These "on-site" health care interactions represented a missed opportunity to assist non-adherent patients in getting sight-saving diabetic eye exams.
Intervention
Eyes on Site (EOS) is a retinal screening model that makes it easy for patients to meet recommended screening standards for diabetic eye care.
Rather than requiring a standalone visit for screening, EOS is deployed in Penn Medicine locations with high volumes of diabetic patients, such as endocrinology and primary care. Patients are offered free, rapid retinal screening while they are on-site for other appointments. Most notably, EOS leverages non-mydriatic cameras – which do not require pupil dilation – to conduct screening.
Images are interpreted remotely, and findings are quickly communicated back to patients and providers.
Impact
EOS offers a superior retinal screening experience and drives better patient outcomes.
We saw impressive results during our initial pilots, including:
- Increased screening rates: We engaged non-adherent patients in diabetic eye screenings. Of the 125 patients screened, 47 percent did not know when their last screening was or reported never completing one.
- Improved patient experience: EOS screenings are 18 times faster than traditional retinal screenings, and they don't require pupil dilation, which means patients can drive themselves home afterward.
- Earlier diagnosis: We discovered previously undiagnosed diseases among pilot participants, with 57 percent requiring a referral, either for baseline or detected eye disease, and 11 percent presenting with evidence of DR.
The EOS model enables earlier diagnosis and treatment for DR, reducing poor patient outcomes and decreasing the need for costly late-stage diabetic eye disease treatments. If EOS screened 890 patients yearly, we predict 356 cases of undiagnosed disease, amounting to more than $290,000 in cost avoidance.
Innovation Methods
Deletion
Deletion
The EOS model was conceived of, in part, by using the deletion method.
We visualized the patient journey for the traditional eye exam and removed some drivers of negative patient experience.
For example, we asked, "If we took away pupil dilation, how could we solve for its absence?"
Deletion
Show me
Show me
During contextual inquiry, we had several a-ha moments.
For example, during observations, we noticed that front desk staff were as influential as providers in recommending the use of the new technology, underscoring how much setting and relationships matter.
Show me
Instead of relying on a verbal recount of experience, ask users to show you how they use a product or service. What people say they do is often quite different than what they do.
Observing users in action will help you understand the spectrum of experiences users can have with the same product or service.
Surveys, interviews, questionnaires, and focus groups don’t tell you what you need to know. Prompting users to show instead of tell often reveals what others have missed.
Mini-pilot
Mini-pilot
Mini-pilot
High-fidelity learning can come from low-fidelity deployment.
Mini-pilots will allow you to learn by doing, usually by deploying a fake back end. You might try a new intervention with ten patients over two days in one clinic, using manual processes for what might ultimately be automated.
Running a "pop-up" novel clinic or offering a different path to a handful of patients will enable you to learn what works and what doesn't more quickly. And, limiting the scope can help you gain buy-in from stakeholders to get your solution out into the world with users and test safely.
Mini-pilot
We ran time-limited mini-pilots at three clinics to test the EOS model.
These pilots helped us learn what did and didn't work about the EOS model quickly and at low cost. We were also able to test risky assumptions. For example, we demonstrated that we could capture adequate retinal images in various settings without pupil dilation during early pilots.