Polycystic Kidney Disease (PKD) is a lifelong condition that requires doctors to track a patient’s history, treatments, scans, and progress over many years. This project explores how a web-based application can help doctors record and track patient data, making disease progression easier to understand over time.

The Indian Association of Polycystic Kidney Disease wanted a simple web application to help doctors record and review patient information in one place.

Doctors across India were maintaining PKD records in manual files, with no easy way to review a patient’s history over time or understand how many PKD cases they were actively managing.

The PKD association logo sits alongside the patient list screen, grounding the tool in its real clinical context. Clinical decisions in chronic conditions depend on understanding change over time, not isolated visits.

Patient information for Polycystic Kidney Disease is collected over many visits and follow-ups. While the data exists, it is scattered across records, making it hard to quickly review a patient’s full history.

Doctors need a clearer way to see past information together, instead of piecing it together manually.

Make patient history easy to review without reconstructing past visits

Reduce effort required to understand what changed since the last visit

Support long-term tracking without overwhelming doctors with detail

This project focused on one critical moment in a doctor’s workflow, reviewing patient history to make informed decisions over time. Given the short timeline, the scope was intentionally limited to review and follow-up, not diagnosis or treatment.

The solution prioritises continuity over completeness. Instead of surfacing all available data, the system focuses on helping doctors quickly understand patient context, spot changes over time, and decide what needs attention next.

Rather than explaining every screen, the solution highlights a few key moments where design decisions directly support long-term clinical review.

A focused system that helps doctors review, track, and act on patient data without reconstructing history.

Reduced the effort required for doctors to understand patient history and make follow-up decisions

Makes disease progression easier to understand at a glance

Reduces effort needed to compare past and current records

Supports ongoing updates without breaking historical continuity

Designing for a real clinical setting reinforced that good systems reduce interpretation effort, not just interaction effort.

Small framing choices (what’s shown first, what’s grouped) heavily influence clinical decision making

Showing change over time is more valuable than showing complete data at once

Doctors value systems that reduce interpretation effort, not just data entry effort

Consistent layout patterns helped users trust and scan information faster across visits

If this system evolved further, the focus would remain on supporting review and prioritisation, not adding more screens.

Trend-based alerts for significant changes in imaging or follow-up delays

Smarter summaries that surface what changed since the last visit

Custom views based on disease stage or clinician preference

Deeper integration between imaging data and follow-up planning