Problem:

Create a mobile application (mHealth) solution to assist public health practitioners find patients affordable, preventative care.  This solution can address patients in South and Central Texas, or scale up to address larger, national needs.  Time frame: 7 days.

Discovery:

  • User Interviews with public health practitioners, patient navigators, and translators in Austin and Houston
  • Contextual inquiry at a nonprofit clinic targeting uninsured populations
  • Mind mapping and analysis:

User interviews revealed that for someone who recently arrived to Texas or the United States, finding an appropriate doctor is a complex endeavor involving factors such as insurance, state and federal programs, public transportation, translation, lost patient records and pharmaceuticals.  Visualizing a unique user story helped bring this problem to life:

Screen Shot 2015-09-17 at 2.39.44 PMScreen Shot 2015-09-17 at 2.40.07 PM

Additionally mindmapping helped break down these complexities to digestible problems that could be addressed via a mobile application.  Given mobile’s advanced translation and mapping capabilities, I chose to focus on problems of healthcare literacy.  Specifically, I chose to look at problems (identified with red dots) of translation and lack of information on existing resources.  This app would aim to directly help patients navigate clinics without asking them to reveal sensitive information about their current health. Secondly, it could help current public health practitioners and patient navigators – who currently cross reference many databases to help a handful of patients – scale up their information delivery.

cura mind map2

  • Develop primary and secondary personas
  • Comparative and competitive audit of current doctor and clinic navigating mobile applications

Task Flows and Initial Wireframes:

Cura 2

Cura 1

User Testing:

  • Test paper prototype
  • Refine paper prototype and test with mobile prototyping tool, Pop App.

Takeaways and Next Steps:

Research revealed that though there are multiple low cost clinics that offered insurance waivers for low income or rural patients,  patients still felt uncomfortable communicating specific ailments to doctors who didn’t speak their language.  Thus, this app would not only require data about low cost clinics (which is available through many large public health databases), but also the languages and translators at that facility.  This poses a challenge to app development.  Therefore, the next step of this app would be a robust component diagram that clarified the types of data necessary to generating a interactive map for patients to navigate.

The biggest UX challenge was communicating specific ailments to better direct the patient to a specialist or family in multiple languages and visually.  In this short project window, I was able to concept and test two visual filters to help patients narrow down the specialty they were seeking.  In second iterations, I learned I needed to add hotspots to make clicking easier.   A translation toggle feature was also added after testing to enable patients to check their selections in a mother tongue, which may also help patients communicate with their doctor or a receptionist on the phone or at the clinic.