Tuberculosis is the world's deadliest infectious disease despite being curable in most cases. In Argentina, treatment for drug-susceptible TB runs six months and is largely self-administered: patients collect about a month of medication at a time, manage it at home, and return to hospital for monthly follow-up. National treatment success has sat between 44% and 66% for a decade.
This project focused on creating a digital adherence tool that would allow providers in Argentina to better treat vulnerable TB patients and improve treatment outcomes. Prior to me joining the team, a beta application had been developed but still needed significant iteration and testing.
Tuberculosis Companion application
Designing TB Companion, a Spanish-language adherence app for patients on self-administered TB treatment in Buenos Aires, later evaluated in a 555-patient randomised controlled trial.
Background
A curable disease that patients abandon before the cure
Deliverables
Qualitative and Quantitative Research Guide,
User Research Report of Findings,
User Interface (UI) Design System,
Lo-Fi & Hi-Fi Prototypes/Wireframes
User Research Report of Findings,
User Interface (UI) Design System,
Lo-Fi & Hi-Fi Prototypes/Wireframes
Role
UX Lead,
UX Researcher,
UX Designer,
Data Analyst
UX Researcher,
UX Designer,
Data Analyst
Timeline
30 weeks design
Industry
Healthcare, Digital health
Global health, Informatics
Global health, Informatics
“How might we empathetically design an application that addresses the barriers that TB patients face during treatment?”
Outcome
Treatment success rose from 10% in a randomised trial
The intervention was evaluated in a pragmatic, two-arm randomised controlled trial across four public reference hospitals in Buenos Aires. 555 patients were enrolled between November 2020 and July 2023, and 525 were included in the intention-to-treat analysis. The cards below describe the subset who used the TB Companion App. The design shipped in 2021 and these results were published in The BMJ, PLOS One, and the Journal of Medical Internet Research.
84%
Treatment success among patients who used the application (181/215)
2.2×
More likely to have a successful treatment if remained engaged with app (n=277)
87%
of Patient would recommend the TB application to other patients (n=52)
Research
Six months of treatment, managed alone between hospital visits
I ran the formative research for the redesign: 12 interviews, 3 focus groups and 49 survey responses across people with TB experience, providers and TB researchers. The figures below record what participants reported about their own treatment, not measured behaviour.
Sample
38 Former TB Patients
4 TB Researchers
7 TB Providers
4 TB Researchers
7 TB Providers
Methods
12 Individual Interviews
49 Survey Responses
3 Focus Groups
49 Survey Responses
3 Focus Groups
Tools
Microsoft 365
Google Sheets
Qualtrics XM
Tableau
Google Sheets
Qualtrics XM
Tableau
Research Findings
Five major findings drove the redesign. Each one names a gap the beta application left open, and the response it produced.
76%
of participants could not say what the daily progress report was for, or where it went after they submitted it (n=49)
Call for
Clarity
96%
of patients wanted a direct line to their care team between monthly hospital visits (n=38)
Call for
Support
98%
of patients met at least one side effect nobody had warned them about (n=38)
Call for
Education
84%
of patients recalled forgetting at least one dose during treatment (n=38)
Call for
Reminders
68%
of participants wanted visible evidence that they were making progress (n=49)
Call for
Motivation
Design Planning
Defining the system before drawing a single screen
The planning artifacts below each settled a question that would otherwise have been re-argued during prototyping: how a patient moves through a report, how much information the app has to hold, and what the interface is allowed to look like. Each went through several rounds of team discussion before it was fixed.
User Flows
The Daily Report was the primary way patients sent information to their providers, so it had to capture everything a provider would normally check during an in-person visit. Mapping it as a flow first made the decision points and drop-off risks visible before any screens existed, and it is where we found that patients were being asked to make choices in an order that did not match how they thought about their own symptoms.
Figure 1: User flow for the daily report. Each colour marks a step in the process.
Information Architecture
Patients needed to know where an action lived before they went looking for it. Each tab owns one task and one kind of information, so nothing appears in two places and no choice between tabs is ambiguous. For example, "History" is the record of submitted results and holds nothing else.
Figure 2: The final information architecture. Five sections mapped onto four tabs.
Design System
The design system fixed the visual language once so there was no ambiguity during the design process. It featured a type ramp sized for small, low-end displays, a restricted color set, and an icon library carrying meaning where text would have added reading burden.
Figure 3: The design system. Type ramp, colour, iconography and core components.
Prototyping
Designing for the days a patient misses
Every screen had to work on a borrowed phone, on an intermittent connection, for someone who had just been told they had a stigmatised disease. That set the constraints: text-light, icon-supported, offline-capable, and nothing on screen that would disclose a diagnosis to anyone glancing over.
Home Page
The home screen answers three questions in priority order: what do I need to do today, how far through am I, and who can I talk to. Cards carry each one, with a single clear action attached.
The progress card came out of two findings: participants wanted to know what to expect, which produced the treatment timeline, and wanted visible evidence of progress, which produced streaks. Medication reminders sit directly beneath, since forgetting doses was the most commonly recalled adherence failure.
The progress card came out of two findings: participants wanted to know what to expect, which produced the treatment timeline, and wanted visible evidence of progress, which produced streaks. Medication reminders sit directly beneath, since forgetting doses was the most commonly recalled adherence failure.
.png)
.png)
Daily Report
The daily report is how information reaches the clinical team between monthly visits: medication taken, side effects, requests for help. Participants were confused about the order of steps, so the flow was linearised into one direction and one decision per screen, with nothing the user has to hold in memory. Across the trial, participants submitted 23,103 medication reports, averaging 91.7 each over the 180-day treatment course.
.png)
%202.png)
.png)
.png)
The Phot Submisison of Strip Test
Once a week, on a random day, the app asked the patient to run a paper urine test that detects an isoniazid metabolite, photograph the strip and submit it. This is the objective adherence check, the thing that separates the TB Companion app from a self-report tracker. It needed to be simple and quick to use.
Calendar
Reporting streaks were the motivational mechanism: report every day, keep the streak, see the pattern of days you struggle with. A calendar was the clearest way to hold six months of that history in one view.
Allowing retroactive reporting for up to seven days was a hedge, so a missed day did not become a wall of failure. Stakeholders at the study sites set that window. In hindsight the deeper problem was that the calendar rewarded consistency rather than surfacing risk, and it is the decision the trial data argues with most directly.
Allowing retroactive reporting for up to seven days was a hedge, so a missed day did not become a wall of failure. Stakeholders at the study sites set that window. In hindsight the deeper problem was that the calendar rewarded consistency rather than surfacing risk, and it is the decision the trial data argues with most directly.
.png)
.png)
Messaging
Messaging was the most-requested feature in formative research and turned out to be the most consequential one. It connects each patient to a named treatment supporter at their own hospital, a nurse, physician or social worker, who reviews their reports daily during clinic hours and replies.
We also explored anonymous peer discussion rooms so patients could hear from others further along in treatment. This was designed but did not ship, and the interview data suggests why it would have been risky: peer contact was valued, but disclosure was the thing patients feared most.
We also explored anonymous peer discussion rooms so patients could hear from others further along in treatment. This was designed but did not ship, and the interview data suggests why it would have been risky: peer contact was valued, but disclosure was the thing patients feared most.
.png)
.png)
.png)
Education
Patients kept meeting side effects nobody had warned them about, so education needed to reach them before symptoms did, instead of waiting in a reference library. Content is indexed by treatment phase, sections collapse to ease navigation, and we defaulted to video over text to reduce reading burden. That last decision is the one I would reverse.
Publications
This design generated 9 peer-reviewed papers
I have contributed to 8 (of 9 total) peer-reviewed papers report on this intervention, covering the design process, the trial itself, patient engagement, patient experience, and the content of messages between patients and their treatment supporters. Please reach out if you'd like access to these papers or to discuss them in further detail.
Reflection
The evidence arrived five years after the design shipped, and it changed my mind
Five years passed between shipping the design and reading the trial results. The three decisions I was most confident about are the ones the data argues with. Each of them now has an answer that did not exist in 2021: an AI model on the device can read a test strip and explain the result back immediately after submission, flag and respond to a patient who has gone quiet, and pitch on-demand education at the reading level of the person holding the phone.
The strip test gave patients nothing back
The urine strip test was the only part of the system that could verify adherence rather than record a claim about it, and participants submitted a mean of 9.2 photos against roughly 26 expected. The interviews suggest why: I designed the submission as a task that returned nothing to the patient. A vision AI model reading the strip on the device could tell the patient what the colour means before the photo is submitted, which priottizes user education and agency.
Silence was the signal we missed
The calendar and the reporting streak came out of a research finding that patients wanted visible evidence of progress, and they delivered that. What they never did was tell anyone when a patient was in trouble: someone who stopped reporting saw a broken streak, and the clinical team recieved no immediate feedback about it. An impactful design opportunity would have been intgration of auto-replies for broken streaks for the patients.
Video cost more than it saved
We defaulted education content to video to reduce the reading burden. The same research told us patients were on borrowed phones and intermittent connections, where HD video is the most expensive thing an app can ask for. Generated text pitched at the reading level of the person asking would carry the same content at a fraction of the data cost, and could answer one specific question instead of making the patient sit through a whole topic.
© Alfie Aguilar Vidrio 2026. All rights reserved.
