Waiting time: 12-18 months — every county ranked
Higher figures on this page are generally worse, not the opposite.
These are raw counts, not rates — a larger area ranks higher on this page mainly because it has more people, not necessarily a worse underlying rate.
Figures as of July 2026, published by National Treatment Purchase Fund. Accessed 2026-10-12.
Colour shows the 12-month change in inpatient/day-case waiting-list numbers, published by NTPF per hospital and mapped to the hospital's county.
Each figure is the median across every hospital reporting in that county, not one hospital's own wait time — a county with more hospitals is not more likely to look extreme. See the county's own page for each hospital's individual figure.
| Rank | County | Waiting time: 12-18 months |
|---|---|---|
| 1 | Galway | 698 |
How this median is computed (2 hospitals)Galway's own figure, 698, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 2 | Waterford | 578 |
How this median is computed (1 hospital)Waterford's own figure, 578, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 3 | Offaly | 350 |
How this median is computed (1 hospital)Offaly's own figure, 350, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 4 | Sligo | 281 |
How this median is computed (1 hospital)Sligo's own figure, 281, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 5 | Limerick | 203 |
How this median is computed (3 hospitals)Limerick's own figure, 203, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 6 | Dublin | 176 |
How this median is computed (15 hospitals)Dublin's own figure, 176, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 7 | Tipperary | 142 |
How this median is computed (2 hospitals)Tipperary's own figure, 142, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 8 | Donegal | 131 |
How this median is computed (1 hospital)Donegal's own figure, 131, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 9 | Clare | 91 |
How this median is computed (1 hospital)Clare's own figure, 91, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 10 | Wexford | 61 |
How this median is computed (1 hospital)Wexford's own figure, 61, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 11 | Kilkenny | 46 |
How this median is computed (2 hospitals)Kilkenny's own figure, 46, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 12 | Cork | 44 |
How this median is computed (6 hospitals)Cork's own figure, 44, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 13 | Mayo | 41 |
How this median is computed (1 hospital)Mayo's own figure, 41, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 14 | Kildare | 35 |
How this median is computed (1 hospital)Kildare's own figure, 35, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 15 | Westmeath | 32 |
How this median is computed (1 hospital)Westmeath's own figure, 32, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 16 | Laois | 27 |
How this median is computed (1 hospital)Laois's own figure, 27, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 16 | Roscommon | 27 |
How this median is computed (1 hospital)Roscommon's own figure, 27, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 18 | Kerry | 6 |
How this median is computed (1 hospital)Kerry's own figure, 6, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 18 | Meath | 6 |
How this median is computed (1 hospital)Meath's own figure, 6, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 20 | Louth | 4 |
How this median is computed (2 hospitals)Louth's own figure, 4, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
| 21 | Cavan | 0 |
How this median is computed (1 hospital)Cavan's own figure, 0, is the median of:
The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties. | ||
Two or more areas with the same figure share a rank — the next rank is skipped (e.g. two areas tied for 1st means the next entry is ranked 3rd, not 2nd).
Before you use these figures
- A waiting list is not a scorecard of hospital performance: The number of people waiting reflects how many are being REFERRED at least as much as how well a hospital is treating them. A hospital seeing more patients than ever can still show a rising list if referrals grow faster than capacity; a falling list can follow fewer referrals rather than better care. NTPF itself also actively funds treatment to reduce specific hospitals' backlogs, which can move a figure independently of that hospital's own capacity. Comparing hospitals directly is further complicated because they cover very different population sizes and specialties.
- Hospital location, not patient catchment: This figure is attributed to the county the hospital is physically in, not to where its patients live. Every public hospital treats some patients referred from outside its own county, so a county's figure should be read as "waiting at a hospital located here", not "how long people from this county wait".
- Adult and child patients are combined: NTPF publishes separate Adult and Child waiting lists for most hospitals; the two are summed here into one hospital total per band, since both are on the same list and a person can only be on one. A small number of children's cases in 2021-2023, published by NTPF in an unattributed 'Small Volume Hospitals' bucket rather than under a named hospital, are excluded entirely because they cannot honestly be assigned to one hospital or county.
- Bands may differ from NTPF's own published total by a patient or two: In roughly a quarter to a third of the source's own monthly rows, the four waiting-time bands NTPF publishes do not sum to exactly the Total figure NTPF publishes alongside them, always by one or two patients. This reads as a minor timing artefact in how NTPF computes the two figures rather than a double-count. The total shown here is the sum of the four bands, which may therefore differ very slightly from NTPF's own headline total for the same hospital and month.
- Latest figure: July 2026 — 3 months old: This dataset is published monthly and the publisher hasn't released anything newer. Nothing is missing from this page.
Cite this ranking:
Waiting time: 12-18 months, every county ranked Caveats: A waiting list is not a scorecard of hospital performance; Hospital location, not patient catchment; Adult and child patients are combined; Bands may differ from NTPF's own published total by a patient or two; Latest figure: July 2026 — 3 months old StatsMapped last confirmed these figures unchanged on 22 Aug 2026. Source: National Treatment Purchase Fund https://statsmapped.com/ireland/rankings/ntpf-ipdc?facet=12to18
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