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Emergency department patients who left within four hours by hospital and patient group, Australia

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Publisher Australian Institute of Health and WelfareUpdated several times a yearLicence CC BY 4.0Latest 2026-10-27Rows 36,289Fields 9

The Time in ED - within 4 hrs 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 percentage of patients who departed within four hours and the peer group average.

Also called: ED four hour rule by hospital, Emergency department length of stay within 4 hours, Patients leaving ED within four hours.

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, Time spent in emergency departments 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.

Before you use it
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 and the share of patients who left the emergency department within four hours of arriving, beside the average for the hospital's peer group.
Which patient groups are there?
The Institute gives all patients, patients admitted from the emergency department to the same hospital, patients not admitted, and each of the five triage categories. The share is a fraction, so 0.8 means 80 per cent.
What do the blanks mean?
The Institute writes <5 for a count under five, NP where the data did not meet its criteria to calculate the figure and NP† where more than 10 per cent of presentations had missing or invalid time data. Those cells are null here with a suppressed flag. 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 a column with no heading, which is not carried here.

Made for agents

Connect your AI agent

Any agent that connects to publicdata.au/mcp can find this dataset, read its 9 fields, count and filter across all 36,289 rows and diff its versions. Every answer names the version and carries AIHW's attribution. No key.

Then ask it: What does Emergency department patients who left within four hours by hospital and patient group, Australia hold, and what changed in the newest version?

claude mcp add --transport http publicdata https://publicdata.au/mcp

One command. No key, no account, no sign-up.

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.

Format
"Latest" redirects to the newest version and will change when the publisher releases again. A dated version keeps its content.
https://publicdata.au/d/au-ed-time-within-4-hours/latest/data.xlsx
Download this file

One workbook with a records sheet of 36,289 typed rows, a fields sheet and a publicdata sheet with the provenance. Dates are real Excel dates. Opens in Excel, Numbers, LibreOffice and Sheets.

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-within-4-hours/latest/ redirects to the newest version.

https://publicdata.au/d/au-ed-time-within-4-hours/latest/data.csv

In 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.

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.

FieldTypePublisher's headerNote
reporting_unitstringReporting unit
reporting_unit_typestringReporting unit type
statestringState
peer_groupstringPeer group
yearstringYear
patient_cohortstringPatient cohort
presentationsintegerNumber of presentations
share_within_4_hoursnumberPercentage who depart ED within 4 hrsThe fraction of patients who departed the emergency department within four hours of arrival, 0.8 for 80 per cent.
peer_group_averagenumberPeer group average
suppressedarrayNames of the fields the publisher suppressed in this row. The cells are null.
markersobjectThe 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_unitreporting_unit_typestatepeer_groupyearpatient_cohortpresentationsshare_within_4_hourspeer_group_average
Gold Coast University HospitalHospitalQldMajor hospitals2024–25All patients1252150.440.46
The Northern Hospital [Epping]HospitalVicLarge metropolitan hospitals2024–25All patients1177890.460.46
Fiona Stanley HospitalHospitalWAMajor hospitals2024–25All patients1109980.390.46
The Canberra HospitalHospitalACTMajor hospitals2024–25All patients1035840.610.46
Campbelltown HospitalHospitalNSWLarge metropolitan hospitals2024–25All patients914550.390.46
Royal Adelaide HospitalHospitalSAMajor hospitals2024–25All patients793860.330.46
Royal Hobart HospitalHospitalTasMajor hospitals2024–25All patients787970.430.46
Royal Darwin HospitalHospitalNTMajor hospitals2024–25All patients688830.380.46
The Prince Charles HospitalHospitalQldMajor hospitals2024–25All patients1136260.60.46
Sunshine HospitalHospitalVicLarge metropolitan hospitals2024–25All patients1127370.510.46
The first row as JSON

As it appears in data.json.

GET https://publicdata.au/d/au-ed-time-within-4-hours/latest/data.json
{
  "reporting_unit": "National",
  "reporting_unit_type": "National",
  "state": "NAT",
  "peer_group": null,
  "year": "2011–12",
  "patient_cohort": "All patients",
  "presentations": 6547342,
  "share_within_4_hours": 0.64,
  "peer_group_average": 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.

Try rows or aggregate for this dataset. The query builder needs JavaScript.

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.

OperatorWhat it matches
eq.valueEqual to the value.
neq.valueNot equal to the value. A blank cell does not match.
gt.valueGreater than the value.
gte.valueGreater than or equal to the value.
lt.valueLess than the value.
lte.valueLess 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.nullBlank in the source, or suppressed by the publisher.
ParameterWhat it does
selectFields to return, comma-separated. Every field when absent.
orderfield.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.
limitRows per page, 1 to 10,000. 100 when absent.
offsetRows to skip. The next URL in each answer sets it for you.
groupOn aggregate, fields to group by, comma-separated.
metricOn aggregate, count, sum.field, avg.field, min.field or max.field, comma-separated. count when absent.
formatjson, 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
    36,289 rows9 fieldsxlsx49d99ec1517e

    The publisher's server states no change date, so this version is dated by the fetch.

versions.json · changes.json · history.tar.zst (162 KB, every version's Parquet and manifest)

Questions

How do I download Emergency department patients who left within four hours by hospital and patient group as a CSV file?

Open https://publicdata.au/d/au-ed-time-within-4-hours/latest/data.csv. It redirects to the newest dated version, which is https://publicdata.au/d/au-ed-time-within-4-hours/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 Emergency department patients who left within four hours by hospital and patient group in Excel?

Yes. https://publicdata.au/d/au-ed-time-within-4-hours/v/2026-10-27/data.xlsx is a workbook with the 36,289 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-within-4-hours/v/2026-10-27/data.csv.gz is the CSV at about a tenth of the size.

What years does Emergency department patients who left within four hours 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 Emergency department patients who left within four hours 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 Emergency department patients who left within four hours 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 Emergency department patients who left within four hours 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-within-4-hours/v/2026-10-27/by/state/index.json. For example https://publicdata.au/d/au-ed-time-within-4-hours/v/2026-10-27/by/state/nsw.json holds the 19,472 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.

Attribution and citation

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-within-4-hours/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.

Licence record

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.

Also published on
  • Hugging Faceload_dataset("National-Digital/au-ed-time-within-4-hours")
  • Kagglewith a starter notebook
  • ZenodoDOI 10.5281/zenodo.23678922

Each copy carries the same attribution and links back to this page.

For agents and tools

This page carries a schema.org Dataset record and is listed in /.well-known/ard.json and /catalog.json.

Source

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…

Improve this dataset

This page is built from register/au-ed-time-within-4-hours.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