Bridging the Communication Gap in Healthcare with a Text Analysis Tool

strategy

UX/UI design

development

The problem

Inaccessible Medical Content Compromises Health Outcomes

Often, medical professionals communicate in a technical and complex manner that can be difficult for non-medical personnel to understand. This lack of clarity can lead to delays in treatment, inefficiencies in healthcare plans, and potential harm to patients' health.

Poor Communication Leads to Low Engagement and Revenue Loss

The lack of engagement between medical professionals and patients negatively impacts the user experience, health outcomes, and revenue for healthcare entities. Non-medical individuals often struggle to comprehend medical jargon, requiring a shift in approach to communicate important information effectively.

A Clear and Memorable Message is Crucial for Preventative Care

People need a clear understanding of healthcare information to prevent illnesses effectively. However, healthcare experts' use of technical language poses a challenge for the general public. Communicating medical information clearly for patients, medical professionals, and the wider public across various platforms is essential.

Computer with a web app displaying two score measurements for analyzing text complexities

The solution

We created a text analysis tool that allows users to rate their texts based on their readability and the amount of jargon (slang, complex words, etc). This tool enables users to determine whether there is still room for improvement, aiming to make their content accessible to a broad audience, including individuals who may not have expertise in healthcare.
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Light-it's team developed a platform where healthcare technicians can write or paste their content and automatically get a specific score on how difficult the text is to comprehend as a non-medical user.

Tech Stack

React

Tailwind

Docker

Reactpress

Sage

Solution tech's specifics

This custom-built app counts with two different scores to determine the level of complexity of the text:

Readability score measurement tool indicating that the text is at an undergraduate level.

Jargonator score measurement tool indicating that the text is at a non-jargon level.

screen shot of healthcare jargon analysis tool

These scores create six categories to help users grasp the complexity of their text and motivate them to take steps to make it more accessible.

Once they validate the necessity of making another draft, physician users fill in their data. They are directed to a demo with Wellframe, where they can evaluate options to generate an optimum version with their team.

Technical Challenges

Some challenges we faced when developing and designing the product:

Creating and developing the platform separately from their existing web and making a seamless integration between this tool and their current website.

Deep diving into the different mathematical formulas that exist to analyze text, besides the grammatical rules, to minimize the margin of error in the final scores.

Iterating and changing the formula and updating the whole algorithm in the mid-process to seek the optimum results.