Search

TB Screening: Using Low Entry Technology for Maximum Results

TB screening data is frequently captured via paper-based methods or a combination of paper-based and digital methods. This is less than ideal, as such methods for screening don’t provide real-time data or georeferencing - an absence that impacts negatively on the mapping and modelling of predictive AI systems. A digital capturing system needs to be:

  • Easy to use by people of all backgrounds;

  • Available to all healthcare workers at minimal cost and without the need for advanced devices;

  • Able to integrate smoothly with existing workflow;

  • Capable of complementing the existing data collection strategy rather than replacing it.

With this in mind, EPCON has developed a novel way of integrating WhatsApp - a fast, simple, secure and free messaging technology - into its state-of-the-art AI models for tracking TB hotspots in Nigeria.



The Better Solution

By incorporating Chatbot functionality into WhatsApp, EPCON is able to offer an excellent solution for the digital capturing of community TB screening data. WhatsApp is widely used across different regions, and most people are familiar with its function. The solution allows for live location coordinates to be captured during the screening process.


Even though a proprietary or open-source system might offer added functionality, WhatsApp was the better solution. Installing and learning the flow of a proprietary application is less convenient and potentially more complicated. WhatsApp offers very low barriers to entry - in terms of both using and downloading the application.


The WhatsApp Chatbot: What Can It Do?

The Chatbot functionality, which is integrated into WhatsApp, offers multiple advantages for healthcare workers, as well as EPCON.


For healthcare workers, benefits include:

  • Receiving estimates of TB in a table or image from a requested area

  • Planning screening locations - healthcare workers can access the model’s predictions and the numbers anticipated for screening in an area of interest

  • Reporting key indicators - healthcare workers can report their activities during the day; the system pre populates the mandatory cascade reports and digitises the programmatic data


For EPCON, benefits include:

  • Sharing coordinates of screened locations - communities screened can be accurately georeferenced; the information is automatically captured in the weekly data sheet

  • Reporting findings from the screening activity - these findings, including people screened, presumptive TB cases, and more, will be automatically captured in the weekly Google sheet. This updates the predictive abilities of EPCON’s AI engine, which in turn assists with the location of TB hotspots and ‘missing’, or undiagnosed, TB cases


In resource-constrained settings with limited budgets, a low entry technology like WhatsApp offers a viable and creative solution to advance health technology and predictive modelling of high-risk neighbourhood disease hotspots.