Affinity: Finding Doctors Based on People Like you.

Client: Premera Health Insurance

Role: UX&UI Designer

Collaborators: Taysser Gherfal, Chris Jung, Irene Yuan

Date: October. 2014- December. 2014 

  Execute Summary

 

When searching for a health care provider, many consumers rely heavily on information from friends and family rather than seeking online reviews. Reviews have the potential to provide an exceptionally rich source of information that could help guide patients’ critical decisions.

 

However, due to the subjective nature of doctor reviews, research indicates that they are often not trusted by consumers. In order to better utilize reviews, consumers must feel connected to the reviewer in some way. Thus, the goal of this project is to connect consumers with doctor recommendations based on patients with similar values and contexts.

  Secondary Research

 

We used our secondary research as an opportunity to gain a baseline understanding of the problem space. We wanted to understand the context of the issues at hand, so we began by researching how recent changes in the healthcare system (via the Affordable Care Act) has impacted consumers in the healthcare industry.

 

 

With a better understanding of the problem context, we shifted our secondary research focus to better understanding the way patients search for doctors. Throughout our research process, creating frameworks helped us organize our findings visually and identify insights to inform our ultimate solution.

Implication of Affordable Care Act

What provider attributes do patients care about?

What provider attributes do patients care about?

Framework: Information Existing and Desired

We created this three-by-two diagram to organize our research findings. Aspects of medical care are organized by those that consumers report caring about (green) and that research indicates they should care about (red). This visual representation also helped us track what current provider search tools offer (top versus bottom).

  Problem Context

 

As indicated through our research, the anonymous and impersonal aspect of reviews make them only marginally helpful to consumers searching for healthcare providers. The subjective nature of finding the right doctor creates uncertainty about evaluations of important provider attributes. In contrast, word of mouth is a highly regarded source of information for finding providers. We assume this is related the familiarity and increased trust associated with the process.

 

Thus, the most significant problem associated with this space is how to match consumers with providers based on reviews from patients with similar values and preferences across various situations and without requiring reviewers to disclose too much personal information.

Privacy

Personal privacy is the most threatening constraint to our proposed solution. Creating a framework to help patients find providers based on the experiences of similar people requires gathering more personal information. 

Information overload and prioritization

Another significant limitation taken into consideration is the amount of provider information that is available to the Premera search tool. Matching patients with the right doctor not only requires gathering detailed information from patients, but also having access to provider information.

Information

availibility

Finding providers based on reviews from similar people Affinity - Fall 2014

requires that consumers are able to articulate what is important to them in unfamiliar situations. This is especially daunting to inexperienced consumers who may not be familiar with various aspects of medical care or what they should prioritize when searching for a provider.

Other Tools

considered

In developing our solution, we considered several different types of existing tools to gain a better understanding of current solutions to similar problems.

  Solution

 

Our solution is designed to help Premera customers find providers based on recommendations from people who are similar to them. In identifying what makes people “similar”, we were able to group shared attributes into two categories: “who they are” and “what they care about”.

 

 

 

Who they are encapsulates stable demographic information that will re- main largely consistent over time (name, age, location, etc.). What they care about reflects personal preferences related to healthcare that are likely to change over time and between situations.

All rights reserved by Xianglian(Necklace) Zhang 2019

Step 2- Login Pop Up