Healthcare
20 columns
200 rows
8 formats

Emergency Department Triage Patterns

This dataset provides detailed records of emergency department triage decisions, including patient demographics, structured symptoms, vital signs, and triage outcomes. It enables urgent care optimization, patient flow modeling, and clinical research into triage patterns and outcomes. The comprehensive structure supports both operational analytics and advanced predictive modeling.

opened 17 times
last updated 22 Jul 2025
by GoMask

The brief that made it

Modeling and optimizing emergency department patient flow

Sample rows

preview · 8 of 200 rows · all 20 columns

triage_idstring	arrival_modestring	vital_signs_diastolic_bpinteger	triage_levelstring	patient_idstring	visit_idstring	triage_datetimedatetime	ageinteger	sexstring	chief_complaintstring	symptom_codesstring	vital_signs_temperaturefloat	vital_signs_heart_rateinteger	vital_signs_respiratory_rateinteger	vital_signs_systolic_bpinteger	vital_signs_oxygen_saturationfloat	triage_scalestring	triage_nurse_idstring	dispositionstring	triage_notesstring
TRI0001	ambulance	80	2	P001	V1001	2023-03-05T17:43:00Z	79	female	Acute confusion and generalized weakness	R41.0,R53	36.9	97	20	142	89.2	CTAS	NUR23847	admitted	Elderly patient, confused, oriented to person only. Daughter reports recent falls.
TRI0002	walk-in	56	3	P002	V1002	2023-03-05T18:11:00Z	4	male	Fever and cough for 2 days	R50.9,J00	39.1	132	28	92	98.1	MTS	NUR78234	observation	Child alert, drinking fluids, mild retractions, no cyanosis.
TRI0003	walk-in	76	4	P003	V1003	2023-03-05T19:07:00Z	32	female	Lower abdominal pain, mild nausea	R10.30	37.5	89	17	123	99.2	ESI	NUR12953	discharged	Patient ambulatory, pain intermittent, no vomiting, no fever.
TRI0004	transfer	38	2	P004	V1004	2023-03-05T19:21:00Z	0	unknown	Newborn assessment after transfer	blank	36.3	144	40	70	95.4	other	blank	observation	Stable newborn, transferred for observation due to mild respiratory distress.
TRI0005	ambulance	92	1	P005	V1005	2023-03-05T21:14:00Z	45	male	Chest pain radiating to left arm	R07.9,I20.0	37.2	108	20	155	95.7	ESI	NUR45722	admitted	Sudden onset chest pain, diaphoresis, hypertensive. ECG pending.
TRI0006	walk-in	74	4	P006	V1006	2023-03-06T06:34:00Z	23	female	Ankle sprain during basketball game	S93.4	36.7	78	15	116	100	MTS	NUR67892	discharged	Mild swelling, able to bear weight, no deformity.
TRI0007	ambulance	92	1	P007	V1007	2023-03-06T07:12:00Z	67	male	Sudden onset right-sided weakness	I63.9	36.1	104	22	178	90.6	CTAS	NUR31855	admitted	Slurred speech, facial droop, FAST positive, urgent CT ordered.
TRI0008	ambulance	62	3	P008	V1008	2023-03-06T09:35:00Z	16	male	Concussion after football collision	S06.0	36.5	92	18	116	99.3	MTS	NUR84019	observation	Brief loss of consciousness, no vomiting, GCS 15.
TRI0009	ambulance	88	2	P009	V1009	2023-03-06T11:16:00Z	55	other	Shortness of breath, worsening over hours	R06.0,J44.1	37.8	111	27	138	85.5	CTAS	NUR99426	admitted	COPD exacerbation, accessory muscle use, O2 administered.
TRI0010	walk-in	78	4	P010	V1010	2023-03-06T12:21:00Z	28	female	Mild abdominal pain, no vomiting	blank	37	76	16	120	99.7	ESI	NUR67413	discharged	No peritoneal signs. Patient stable, pain 3/10.
TRI0011	transfer	48	1	P011	V1011	2023-03-06T13:03:00Z	101	other	Weakness and dehydration, nursing home resident	R53,E86.0	35.1	59	14	104	90.1	other	blank	admitted	Bedbound, poor skin turgor, needs IV fluids, power of attorney contacted.
TRI0012	walk-in	81	3	P012	V1012	2023-03-06T13:26:00Z	37	male	Psychiatric evaluation, suicidal ideation	R45.851	36.4	72	14	126	98.6	ESI	NUR71120	observation	Patient calm, no acute distress, no physical injuries.
TRI0013	ambulance	50	2	P013	V1013	2023-03-06T13:53:00Z	88	female	Fall at home, right hip pain	S72.0	36	113	21	108	93.7	MTS	NUR85195	admitted	Unable to weight bear, bruising noted, X-ray ordered.
TRI0014	walk-in	62	2	P014	V1014	2023-03-06T15:40:00Z	8	female	Asthma exacerbation, wheezing	J45.901	37.3	128	36	100	95.8	MTS	NUR45329	observation	Accessory muscle use, O2 started, albuterol administered.
TRI0015	walk-in	74	4	P015	V1015	2023-03-06T16:09:00Z	41	male	Mild head injury, slip in bathroom	S06.0	36.6	71	15	126	99.4	ESI	NUR59906	discharged	GCS 15, no loss of consciousness, scalp hematoma.
TRI0016	ambulance	54	1	P016	V1016	2023-03-06T17:21:00Z	13	female	Severe allergic reaction to peanuts	T78.2	37	142	31	98	94.3	CTAS	NUR31758	admitted	Urticaria, lip swelling, stridor, epinephrine given en route.
TRI0017	walk-in	87	3	P017	V1017	2023-03-06T18:52:00Z	54	male	Worsening back pain, unable to walk	M54.5	36.8	83	14	135	97.1	ESI	NUR40982	observation	Chronic pain, no trauma, neurologically intact.
TRI0018	ambulance	62	2	P018	V1018	2023-03-06T19:44:00Z	72	female	Shortness of breath, fever, productive cough	J18.9,R06.0	38.5	118	31	110	82.7	MTS	NUR82017	admitted	Crackles on auscultation, O2 started, IV access obtained.
TRI0019	walk-in	78	4	P019	V1019	2023-03-07T06:21:00Z	18	male	Knee pain after soccer injury	S83.2	36.8	86	16	124	99.7	ESI	NUR29514	discharged	No instability, swelling noted, neurovascularly intact.
TRI0020	walk-in	46	2	P020	V1020	2023-03-07T07:03:00Z	2	female	Fever, decreased oral intake	R50.9	38.9	137	32	90	97.5	MTS	NUR41267	observation	Child irritable, capillary refill 2s, no rash.

What the 200 rows show

from the 200-row sample

Transfer (arrival mode) stands out: mean vital_signs_diastolic_bp is 39.3, against 70.2 for the rest.

71.5median vital_signs_diastolic_bp
3dispositions
4sexes
4triage scales
37median age
36.8median vital_signs_temperature

Mean vital_signs_diastolic_bp by arrival_mode200 rows

vital_signs_diastolic_bp200 rows, in bands of 10

Median 71.5, from 22 to 94.

triage_level200 rows · 5 values

20 columns by typefrom the column list below

string 12
integer 5
float 2
datetime 1

Columns

20 columns in three groups

blueprint · 20 columns
column	type	description	example
Text 12 columns
`triage_id`	string	Unique identifier for each triage decision record.unique	TRI0001
`patient_id`	string	Unique identifier for the patient associated with this triage event.	P001
`visit_id`	string	Unique identifier for the patient's emergency department visit.	V1001
`sex`	string	Sex of the patient.male · female · other · unknown	female
`chief_complaint`	string	Primary symptom or reason for the patient's visit as described by the patient.	Flank pain, hematuria
`symptom_codes`	string	Comma-separated list of standardized symptom codes (e.g., SNOMED, ICD-10) relevant to this triage event.optional	R41.0,R53
`triage_level`	string	Triage acuity level assigned to the patient (e.g., ESI, CTAS, MTS).6 values	2
`triage_scale`	string	Name of the triage scale used (e.g., ESI, CTAS, MTS, other).ESI · CTAS · MTS · other	CTAS
`triage_nurse_id`	string	Identifier for the nurse or clinician who performed the triage.optional	NUR23847
`arrival_mode`	string	Mode of patient arrival (e.g., ambulance, walk-in, transfer).ambulance · walk-in · transfer · other · optional	ambulance
`triage_notes`	string	Free-text notes or observations recorded by the triage nurse.optional	Elderly patient, confused…
`disposition`	string	Initial disposition decision after triage (e.g., admitted, discharged, observation, transferred).admitted · discharged · observation · transferred · other · optional	admitted
Numbers 7 columns
`age`	integer	Age of the patient at the time of triage (in years).0 to 120	79
`vital_signs_temperature`	float	Patient's body temperature in degrees Celsius at triage.25 to 45 · optional	36.9
`vital_signs_heart_rate`	integer	Patient's heart rate in beats per minute at triage.20 to 250 · optional	97
`vital_signs_respiratory_rate`	integer	Patient's respiratory rate in breaths per minute at triage.5 to 80 · optional	20
`vital_signs_systolic_bp`	integer	Patient's systolic blood pressure in mmHg at triage.40 to 300 · optional	142
`vital_signs_diastolic_bp`	integer	Patient's diastolic blood pressure in mmHg at triage.20 to 200 · optional	80
`vital_signs_oxygen_saturation`	float	Patient's oxygen saturation percentage at triage.50 to 100 · optional	89.2
Dates and times 1 column
`triage_datetime`	datetime	Date and time when the triage assessment was performed.	2023-03-05T17:43:00Z

15 SQL practice questions for the Emergency Department Triage Patterns

Written for this data and checked against it: 12 SQL and 3 Power BI exercises from beginner to advanced. Try the first three free; the practice kit has all 15, a starter .sql file and an answer key with every expected result.

01BeginnerFreeDISTINCT · ORDER BY
Distinct triage scales used
Return each distinct triage scale used in the data as a single column named triage_scale, ordered alphabetically.
Tables: emergency_department_triage_patterns · your result: 1 columns, 4 rows
02BeginnerFreeGROUP BY · COUNT
Visits per disposition
Count the visits for each disposition. Return the columns disposition and visit_count, ordered by visit_count from highest to lowest, then by disposition alphabetically.
Tables: emergency_department_triage_patterns · your result: 2 columns, 3 rows
03BeginnerFreeGROUP BY · AVG · SUM
Average heart rate by triage level
For each triage_level, return triage_level, the average vital_signs_heart_rate rounded to 2 decimals as avg_heart_rate, and the sum of age as total_age. Order by triage_level ascending.
Tables: emergency_department_triage_patterns · your result: 3 columns, 5 rows

04Walk-in patients with low oxygenBeginner
05Table visual: arrivals by modePower BI
06Nurses with many triagesIntermediate
07Age group bucketsIntermediate
08Monthly triage volumeIntermediate
09Arrival modes hotter than averageIntermediate
10Admission rate by triage levelPower BI
11Rank oldest patients per triage levelAdvanced
12Gap since previous triageAdvanced
13Running total of monthly visitsAdvanced
14Share of visits by arrival and dispositionAdvanced
15Heart rate anomalies by triage levelPower BI

Get the practice kit: the full dataset, all 15 exercises, a starter .sql and the answer key. One-time $3.99.

Get the practice kit · $3.99

Use it for

A healthcare dashboard
Vital_signs_diastolic_bp by arrival_mode and a breakdown of triage_level. Excel, Power BI or Tableau.
Why do the 22 transfer rows have a mean vital_signs_diastolic_bp of 39.3?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Triages200
TRI000180ambulance
TRI000256walk-in
TRI000376walk-in
A software demo
Believable triages with patient_id, visit_id and triage_datetime to fill a screen in front of a buyer.

This dataset200 rows20 columns

Yours1,000 rows20 columns

blueprint · emergency-department-triage-patterns

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 20 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Link triage level to presenting symptoms
Simulate wait times and resource allocation
Include patient demographics and outcomes
Annotate emergency severity index

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: emergency-department-triage-patterns

What should your data show?

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Sample rows

What the 200 rows show

Columns

Distinct triage scales used

Visits per disposition

Average heart rate by triage level

Use it for

A healthcare dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Healthcare

What should your data show?