About CareCompass

Why this exists

228,438 people are waiting for treatment in Ireland's public hospitals right now. That number is public. The National Treatment Purchase Fund publishes the data every month — 46 hospitals, more than 50 specialties, broken down by waiting time bands. All there, free, up to date.

But it's buried in CSVs and PDFs that no ordinary patient can interpret. The data exists, but it doesn't reach the people who need it most: patients trying to understand their options, GPs guiding referrals, journalists investigating the system. Publishing is not the same as making accessible.

At some point in recent years, it became possible for a single person to do the work that used to require a team. I wanted to test where that limit is — and a real problem, with under-utilised public data and direct impact on the lives of hundreds of thousands of people, seemed like the right test.

CareCompass is the result: one person, 46 hospitals, 228,438 patients tracked, €7.25/month in infrastructure. Public data transformed into useful data.

How it was built

CareCompass is a full-stack platform designed around a data ingestion pipeline that normalises the NTPF's monthly publications — CSVs and PDFs with inconsistent schemas across the years — into a unified relational model. The data layer consolidates historical time series by hospital, specialty, and waiting time band, enabling longitudinal and comparative analyses that are not available in the original publications.

On top of that foundation, I built an API that serves aggregated queries with low latency, and an interface that prioritises clinical readability and decision-making — search by specialty, hospital comparisons, month-over-month and year-over-year trends, and supporting tools such as a public vs. private cost calculator. I also developed a proprietary AI agent that continuously monitors NTPF publications and triggers the ingestion pipeline whenever new data is released, ensuring the platform reflects the most recent state of the system without manual intervention. Every derived metric (median estimates, rankings, trend indicators) has its methodology publicly documented, because transparency about public data demands transparency about how that data is processed.

The architecture was designed to operate in an economical and sustainable way over the long term. The €7.25/month infrastructure cost is not a vanity detail: it's proof that public utility does not require an institutional budget to exist.

What CareCompass does

CareCompass transforms Ireland's publicly available hospital waiting list data into a clear, searchable platform. Patients, GPs, and healthcare professionals can search by specialty, compare hospitals, view time-band breakdowns, track trends over time, and use decision-making tools — all based on official NTPF data.

Beyond displaying data, CareCompass includes tools that help patients act on what they learn: a public-vs-private cost calculator, guidance on patient rights, and resources for having informed conversations with their GP.

Data source

All data is sourced directly from the National Treatment Purchase Fund (NTPF), published monthly on data.gov.ie. The NTPF collects and publishes Inpatient/Day Case (IPDC) and Outpatient (OP) waiting list figures for every public hospital in Ireland, broken down by specialty.

We do not alter, estimate, or editorialize the source data. Where we compute derived metrics (median wait estimates, rankings, trends), the methodology is documented below.

Methodology

Time band distribution

The NTPF publishes patient counts in five time bands: 0-3 months, 3-6 months, 6-12 months, 12-18 months, and 18+ months. We display these directly as reported.

Estimated median wait

We estimate the median waiting time using linear interpolation across the time band distribution. This is an approximation — the actual median depends on the precise distribution of patients within each band, which is not published. The estimate gives a reasonable indication but should not be taken as exact.

Rankings

Hospitals are ranked by total waiting list size for each specialty. A lower total means a shorter queue on average, but individual wait times depend on clinical urgency, referral pathway, and hospital capacity. Rankings are descriptive, not prescriptive.

Trend indicators

Month-over-month changes compare the current month's total with the previous month's total. Year-over-year changes compare with the same month in the prior year. A decrease indicates the queue is shrinking; an increase indicates it is growing.

What the numbers do NOT mean

• A shorter waiting list does not guarantee a shorter individual wait time.
• Rankings do not reflect the quality of care at any hospital.
• We do not provide medical advice. Always speak to your GP about your referral options.
• Data is updated monthly. It represents a point-in-time snapshot.