Time spent in emergency departments by hospital and patient group, Australia
liveThe Time in ED sheet of the MyHospitals emergency department data extract from the AIHW MyHospitals Data API. Each row is one reporting unit, financial year and patient group, with the number of presentations, the median time in the emergency department, the time until 90 per cent of patients departed and the peer group average of that time.
Also called: ED length of stay by hospital, Median time in emergency department, How long patients spend in ED.
Part of AIHW MyHospitals, 12 tables the publisher releases together: Hospitals, Local Hospital Networks and Primary Health Networks in MyHospitals, Australia, Reported measures and their codes in MyHospitals, Australia, Reporting unit mappings to health networks and states in MyHospitals, Australia, Reporting unit codes and alternative names in MyHospitals, Australia, Emergency department patients seen on time by hospital and triage category, Australia, Emergency department presentations by hospital and triage category, Australia, Emergency department patients who left within four hours by hospital and patient group, Australia, Cancer surgery waiting times by hospital and cancer type, Australia, Elective surgery waiting times by hospital and urgency category, Australia, Elective surgery waiting times by hospital and intended procedure, Australia, Elective surgery waiting times by hospital and surgical specialty, Australia.
- What is in each row?
- One public hospital, Local Hospital Network, state or the nation, one financial year from 2011-12 and one patient group. It gives the number of emergency presentations, the median time patients spent in the emergency department and the time by which 90 per cent of them had left, beside the peer group average of that second figure.
- Which patient groups are there?
- The Institute gives all patients, patients admitted from the emergency department to the same hospital, and patients not admitted.
- Why are the times text?
- The Institute writes each time in hours and minutes, such as
2 hrs 58 mins. This site publishes the times as the Institute wrote them. For some unpeered hospitals the file gives a peer group average of0 hrs 0 mins, and that value is kept as written. - What do the blanks mean?
- The Institute writes
<5for a count under five. Those cells are null here with a suppressed flag. In the times,NPmeans the data did not meet the Institute's criteria to calculate the figure andNP†means more than 10 per cent of presentations had missing or invalid time data. Those cells, a dash meaning no patients were reported, and Not peered are null. The markers column keeps each code. The Institute's file also marks with an asterisk the figures to interpret with caution, in columns with no heading, which are not carried here.
Made for agents
Connect your AI agent
Any agent that connects to publicdata.au/mcp can find this dataset, read its 10 fields, count and filter across all 13,611 rows and diff its versions. Every answer names the version and carries AIHW's attribution. No key.
Then ask it: What does Time spent in emergency departments by hospital and patient group, Australia hold, and what changed in the newest version?
claude mcp add --transport http publicdata https://publicdata.au/mcpOne command. No key, no account, no sign-up.
Settings, then Connectors, then Add custom connector, and paste https://publicdata.au/mcp.
On the web and in the desktop app.
https://publicdata.au/mcpStreamable HTTP. Cursor, VS Code or any client that connects to a remote MCP server.
Using https://publicdata.au/llms.txt, how many people died on Queensland roads in 2025, by month?For an assistant that reads the web and has no connector.
A dashboard over every row. Click to filter, add panels, share a link or embed a frame.
Query APIFilter and count from a URLaggregate?group=reporting_unit&metric=sum.presentations&year=eq.2024%E2%80%9325&reporting_unit_type=eq.State&patient_cohort=eq.All%20patients
Emergency department presentations in each state in the newest year: 3,157,236 New South Wales, 1,978,267 Victoria, 1,766,835 Queensland, 1,026,887 Western Australia.
Download it as Excel, CSV, JSON and 5 more formats
Pick a format and a version. Excel is picked first because it opens in the tools most offices have. The URL is yours to keep. A dated version keeps its content.
One workbook with a records sheet of 13,611 typed rows, a fields sheet and a publicdata sheet with the provenance. Dates are real Excel dates. Opens in Excel, Numbers, LibreOffice and Sheets.
UTF-8 without a byte-order mark, RFC 4180 quoting, one header row using the normalised field names. Opens in Excel, Numbers and Sheets.
One object with a publicdata header (publisher, licence, attribution, version, source hash), a fields list and a records array of 13,611 objects with typed values. Blank cells are null.
Columnar and typed. The smallest download and the fastest to query. Reads directly in DuckDB, pandas, Polars, Arrow and Spark. The provenance header is in the file metadata.
One database with a records table, a fields table and a publicdata metadata table. Open it with any SQLite client.
One DuckDB database with a records table of typed columns, a fields table and a publicdata metadata table. It attaches read-only over HTTPS, so DuckDB, Python and R can query it without downloading it.
The first line is the provenance header, then one JSON object per line. For streaming and for tools that read line by line.
The same CSV, gzipped, at about a tenth of the size. curl, pandas, DuckDB and R read it directly.
One JSON file per value of state, 9 files. The example is by/state/nsw.json. Every file carries the same header and a partition note.
In your own tools
Use it in Excel, R, Python and more
Excel and Power BI read the CSV from its address and refresh from it. The R and Python packages take any dataset on this site by its slug, so a new dataset needs no new release. The DuckDB file attaches read-only over HTTPS, and a query reads only the blocks it touches.
The dated URL in the code never changes. https://publicdata.au/d/au-ed-time-in-ed/latest/ redirects to the newest version.
https://publicdata.au/d/au-ed-time-in-ed/latest/data.csvIn Excel choose Data, then From Web, and paste this address. Excel keeps it, so Refresh All reads the newest version. A sheet holds about a million rows; past that, load the query to the Data Model.
https://publicdata.au/d/au-ed-time-in-ed/latest/data.csvIn Power BI Desktop choose Get data, then Web, paste this address and choose Anonymous when asked how to sign in. A scheduled refresh reads the same address, so the report follows each new version.
library(publicdataau)
df <- pd_read("au-ed-time-in-ed")
pd_attribution(df)install.packages("publicdataau"). pd_read() fetches the version's Parquet file; pd_rows() and pd_aggregate() ask the query API instead, and pd_connect() attaches the DuckDB file.
import publicdata_au as pd_au
df = pd_au.read("au-ed-time-in-ed")
df.attrs["publicdata"]["attribution"]pip install "publicdata-au[pandas]". read() fetches the version's Parquet file; rows() and aggregate() ask the query API, and connect() attaches the DuckDB file.
INSTALL httpfs; LOAD httpfs;
ATTACH 'https://publicdata.au/d/au-ed-time-in-ed/v/2026-10-27/data.duckdb' AS au_ed_time_in_ed (READ_ONLY);
SELECT state, count(*) FROM au_ed_time_in_ed.records GROUP BY 1 ORDER BY 2 DESC;The DuckDB file attaches read-only over HTTPS and only the blocks a query touches are read. Parquet works the same way: FROM read_parquet(url).
const res = await fetch("https://publicdata.au/api/v1/datasets/au-ed-time-in-ed/aggregate?group=reporting_unit&metric=sum.presentations&year=eq.2024%E2%80%9325&reporting_unit_type=eq.State&patient_cohort=eq.All%20patients");
const { rows, publicdata } = await res.json();
console.log(rows, publicdata.attribution);The query API answers a page on any site as well as Node, with no key. It returns the rows and the attribution the licence asks for.
What is in it
Column names are made snake_case and the publisher's original header is kept beside each one. Blank cells are null. Nothing is added, removed, ranked or summarised.
| Field | Type | Publisher's header | Note |
|---|---|---|---|
| reporting_unit | string | Reporting unit | |
| reporting_unit_type | string | Reporting unit type | |
| state | string | State | |
| peer_group | string | Peer group | |
| year | string | Year | |
| patient_cohort | string | Patient cohort | |
| presentations | integer | Number of presentations | |
| median_time | string | Median time | The time by which half of the patients had departed the emergency department, in hours and minutes as the Institute writes it. |
| time_90_percent_departed | string | Time until most patients (90%) depart ED | The time by which 90 per cent of the patients had departed the emergency department, in hours and minutes as the Institute writes it. |
| peer_group_average_90 | string | Peer group average (90%) | The peer group average of the time until 90 per cent of patients departed, in hours and minutes as the Institute writes it. |
| suppressed | array | Names of the fields the publisher suppressed in this row. The cells are null. | |
| markers | object | The token the publisher wrote in each cell of this row that is null here, as a JSON object of field name to token. "<5" means: The Institute's notes do not define this code. It appears only in the number of presentations. "NP" means: Reported data did not meet the criteria to calculate this indicator. "NP†" means: Results could not be accurately calculated as more than 10% of presentations had missing or invalid time data. "-" means: There were no patients reported for this indicator in this time period. "Not peered" means: The Institute's notes do not define this code. It appears in place of a peer group figure. |
Download this table as a data dictionary (Excel), or read it as a Frictionless Table Schema at schema.json. The key is reporting_unit, reporting_unit_type, year, patient_cohort.
A sample of 10 rows
All patients at the busiest hospitals in the newest year, the busiest hospital in each state first, then the next busiest. A blank cell is shown as null.
| reporting_unit | reporting_unit_type | state | peer_group | year | patient_cohort | presentations | median_time | time_90_percent_departed | peer_group_average_90 |
|---|---|---|---|---|---|---|---|---|---|
| Gold Coast University Hospital | Hospital | Qld | Major hospitals | 2024–25 | All patients | 125215 | 4 hrs 30 mins | 11 hrs 40 mins | 12 hrs 34 mins |
| The Northern Hospital [Epping] | Hospital | Vic | Large metropolitan hospitals | 2024–25 | All patients | 117789 | 4 hrs 22 mins | 12 hrs 32 mins | 12 hrs 54 mins |
| Fiona Stanley Hospital | Hospital | WA | Major hospitals | 2024–25 | All patients | 110998 | 5 hrs 1 mins | 12 hrs 51 mins | 12 hrs 34 mins |
| The Canberra Hospital | Hospital | ACT | Major hospitals | 2024–25 | All patients | 103584 | 3 hrs 31 mins | 6 hrs 48 mins | 12 hrs 34 mins |
| Campbelltown Hospital | Hospital | NSW | Large metropolitan hospitals | 2024–25 | All patients | 91455 | 4 hrs 59 mins | 15 hrs 33 mins | 12 hrs 54 mins |
| Royal Adelaide Hospital | Hospital | SA | Major hospitals | 2024–25 | All patients | 79386 | 5 hrs 50 mins | 18 hrs 36 mins | 12 hrs 34 mins |
| Royal Hobart Hospital | Hospital | Tas | Major hospitals | 2024–25 | All patients | 78797 | 4 hrs 34 mins | 12 hrs 36 mins | 12 hrs 34 mins |
| Royal Darwin Hospital | Hospital | NT | Major hospitals | 2024–25 | All patients | 68883 | 5 hrs 4 mins | 14 hrs 15 mins | 12 hrs 34 mins |
| The Prince Charles Hospital | Hospital | Qld | Major hospitals | 2024–25 | All patients | 113626 | 3 hrs 25 mins | 7 hrs 52 mins | 12 hrs 34 mins |
| Sunshine Hospital | Hospital | Vic | Large metropolitan hospitals | 2024–25 | All patients | 112737 | 3 hrs 58 mins | 13 hrs 46 mins | 12 hrs 54 mins |
The first row as JSON
As it appears in data.json.
GET https://publicdata.au/d/au-ed-time-in-ed/latest/data.json
{
"reporting_unit": "National",
"reporting_unit_type": "National",
"state": "NAT",
"peer_group": null,
"year": "2011–12",
"patient_cohort": "All patients",
"presentations": 6547342,
"median_time": "2 hrs 58 mins",
"time_90_percent_departed": "8 hrs 28 mins",
"peer_group_average_90": null,
"suppressed": [],
"markers": null
}
Query it without downloading
The query API returns only the rows you ask for, as JSON, NDJSON or CSV, from the same typed rows as the files. It needs no key. Build a query here and run it, then copy the URL or the code into your own work.
How filters work
Each filter is field=operator.value in the query string, and every filter must match. A number or date field compares as a number or date, and a text field compares as text. Values are case-sensitive, except that like and ilike ignore case in the ASCII letters A to Z. Prefix not. to negate a filter, as not.eq.value.
| Operator | What it matches |
|---|---|
| eq.value | Equal to the value. |
| neq.value | Not equal to the value. A blank cell does not match. |
| gt.value | Greater than the value. |
| gte.value | Greater than or equal to the value. |
| lt.value | Less than the value. |
| lte.value | Less than or equal to the value. |
| like.*text* | Matches a pattern where * stands for any run of characters, ignoring case in the ASCII letters A to Z. |
| ilike.*text* | The same as like. Both ignore case in ASCII letters only, so É and é differ. |
| in.(a,b,c) | Equal to any value in the list. A value cannot contain a comma. |
| is.null | Blank in the source, or suppressed by the publisher. |
| Parameter | What it does |
|---|---|
| select | Fields to return, comma-separated. Every field when absent. |
| order | field.asc or field.desc, comma-separated. When absent, rows come in the order of the file they are read from. For the newest versions that is the version's own data.parquet, which keeps the publisher's order unless the dataset sorted it. Any other version is read from the Parquet file the answer names in file, and when that file is sorted the answer names its sort in order, which ties follow too. |
| limit | Rows per page, 1 to 10,000. 100 when absent. |
| offset | Rows to skip. The next URL in each answer sets it for you. |
| group | On aggregate, fields to group by, comma-separated. |
| metric | On aggregate, count, sum.field, avg.field, min.field or max.field, comma-separated. count when absent. |
| format | json, ndjson or csv. JSON carries the provenance header, and the others carry it in response headers. |
Without a version the API answers from the newest version, and that answer changes when the publisher releases again. Put versions/<date>/ before rows or aggregate for an answer from that version alone. Every version with a table can be queried, and /api/v1/datasets/<slug>/versions lists them. A query on a version the database does not hold is read from its Parquet file, and one that would read too much of it is refused with DuckDB SQL that answers it from the file. The 1 newest version is loaded; versions lists them.
The API allows 60 requests in 10 seconds from one address. Above that it answers 429 for 10 seconds with a Retry-After header, a RateLimit-Policy header and a JSON body that gives the limit. Every API answer carries the same RateLimit-Policy. A client should wait the Retry-After seconds, or read the files, which have no limit. openapi.json describes this dataset's query paths for client generators and agents.
https://publicdata.au/mcp is a remote MCP server over Streamable HTTP with the same tools, defined in the same place, so a tool added to the pages is added here too. It needs no key and no account. Its row tools and the query API answer every version through one query path, so a tool's answer and the query URL it cites give the same rows. A query that would read too much of a file is refused with DuckDB SQL that answers it from the file. It also has search and fetch, the two tools ChatGPT's deep research and company knowledge call by name, which run search_datasets and read a dataset's record in the shapes those features expect. The row tools are held to the query API's limit of 60 queries in 10 seconds from one address, and each call is two queries because it also counts the matching rows. Add it to Claude Code with claude mcp add --transport http publicdata https://publicdata.au/mcp, add the URL in Claude as a custom connector, or give it to any client that connects to remote MCP servers. Each dataset with a table is also a resource at https://publicdata.au/d/<slug>/fields.json, which lists its fields with their types, the publisher's descriptions, their ranges and the values they hold, so an agent can read a dataset's shape before it writes a query.
Smaller files
The same rows split by a field, one JSON file each. Each file carries the same provenance header.
By state (9 files)
by/state/index.json lists every file with its row count.
What changed
One version for every release the publisher has made since this site started following the dataset. The date is the day the file changed on the portal.
- 2026-10-27 13,611 rows10 fieldsxlsx49d99ec1517e
The publisher's server states no change date, so this version is dated by the fetch.
versions.json · changes.json · history.tar.zst (108 KB, every version's Parquet and manifest)
Questions
How do I download Time spent in emergency departments by hospital and patient group as a CSV file?
Open https://publicdata.au/d/au-ed-time-in-ed/latest/data.csv. It redirects to the newest dated version, which is https://publicdata.au/d/au-ed-time-in-ed/v/2026-10-27/data.csv today. The same path serves Excel, JSON, Parquet, SQLite, DuckDB, NDJSON. A dated URL never changes, so use it when the file must stay the same.
Can I open Time spent in emergency departments by hospital and patient group in Excel?
Yes. https://publicdata.au/d/au-ed-time-in-ed/v/2026-10-27/data.xlsx is a workbook with the 13,611 rows on a records sheet, the field list on a second sheet and the provenance on a third. The CSV also opens in Excel. https://publicdata.au/d/au-ed-time-in-ed/v/2026-10-27/data.csv.gz is the CSV at about a tenth of the size.
What years does Time spent in emergency departments by hospital and patient group cover?
The current version covers the years since 2011. Each release from AIHW becomes a new dated version here, and earlier versions stay online.
How often is Time spent in emergency departments by hospital and patient group updated?
AIHW releases it several times a year. This site checks the portal every week and adds a dated version when the file changes.
Can I use Time spent in emergency departments by hospital and patient group commercially?
Yes. CC BY 4.0 allows commercial use, redistribution and derived works as long as the attribution is kept. The attribution string is in this page's side column and inside every file.
Is this the official source for Time spent in emergency departments by hospital and patient group?
No. The publisher is Australian Institute of Health and Welfare, and its page is https://www.aihw.gov.au/copyright. National Digital converted the publisher's file to other formats. It renamed and typed the columns and kept only those the schema lists. It made each suppressed value a null with a flag. It kept the publisher's marker for each empty cell in a markers column. National Digital made these changes, and the publisher is not responsible for them. The original sits beside every version as source.xlsx with its SHA-256, so the two can be compared.
How do I get only the rows for one state?
Every version has one JSON file per value of state, 9 files in the current version, listed with row counts at https://publicdata.au/d/au-ed-time-in-ed/v/2026-10-27/by/state/index.json. For example https://publicdata.au/d/au-ed-time-in-ed/v/2026-10-27/by/state/nsw.json holds the 7,302 rows where state is NSW.
What this site did to the data. Cells were typed, headers were renamed and the encoding was made UTF-8. Rows were left alone. The publisher's file sits beside every version as source.xlsx so the change can be checked.
AIHW MyHospitals is 12 tables here, and each takes its version date from its own file.
The licence requires the publisher's attribution. We ask that you also name publicdata.au and link to the version you used.
Based on Australian Institute of Health and Welfare material. Australian Institute of Health and Welfare, Australian Government, MyHospitals Data API, emergency department data extract, sourced 26 October 2026, https://myhospitalsapi.aihw.gov.au/, licensed under CC BY 4.0. Serialised and versioned by National Digital at publicdata.au, https://publicdata.au/d/au-ed-time-in-ed/v/2026-10-27/
The attribution alone is inside every file. Harvard is the author-date form a report or a brief asks for. Paste the HTML on a web page so the links carry.
Australian Institute of Health and Welfare states the licence, CC BY 4.0, on its own page, which was read and recorded here on 23 October 2026.
Every fetch reads the licence again and stops when it has changed. The fetch that made version 2026-10-27 read it from www.aihw.gov.au on 26 October 2026.
- Hugging Faceload_dataset("National-Digital/au-ed-time-in-ed")
- Kagglewith a starter notebook
- ZenodoDOI 10.5281/zenodo.23678918
Each copy carries the same attribution and links back to this page.
- datapackage.jsonFrictionless data package pointing at the latest version
- schema.jsonTable Schema for every field
- schema.xlsxthe same field list as an Excel data dictionary
- versions.jsonevery version with date, rows, fields and hash
- changes.jsondiff for every consecutive pair
- manifest.jsonwhere the bytes came from and when
- Query APIfiltered rows and counts without a download
- openapi.jsonOpenAPI 3.1 for this dataset's query paths
- explore/charts and dashboards in the browser, shareable and embeddable
- index.mdthis page as Markdown
This page carries a schema.org Dataset record and is listed in /.well-known/ard.json and /catalog.json.
Australian Institute of Health and Welfare publishes this table on myhospitalsapi.aihw.gov.au. Questions about the content go to the publisher. Questions about the files here go to corrections.
Fetched 26 October 2026. Source SHA-256 49d99ec1517e3ef4…
This page is built from register/au-ed-time-in-ed.yaml on GitHub. Anyone can propose a fix to it, such as a clearer description or a field the publisher renamed, as a pull request.
Report a file that differs from the publisher's · How to contribute