Healthcare
23 columns
200 rows
8 formats

Healthcare Appointment No-Show Rates

This dataset provides detailed records of healthcare appointments, capturing patient demographics, scheduling details, clinic and provider information, reminders, and final attendance status. It is designed to help clinics analyze no-show rates, identify contributing factors, and optimize scheduling strategies to improve operational efficiency and patient care.

last updated 20 Aug 2025
by GoMask

The brief that made it

Analyzing factors contributing to patient no-shows

Sample rows

preview · 8 of 200 rows · all 23 columns

appointment_idstring	insurance_typestring	number_of_previous_no_showsinteger	reminder_sentboolean	patient_zip_codestring	patient_idstring	patient_genderstring	patient_ageinteger	appointment_datedate	appointment_timestring	appointment_created_datetimedatetime	clinic_idstring	clinic_namestring	provider_idstring	provider_specialtystring	appointment_typestring	reminder_methodstring	appointment_statusstring	cancellation_reasonstring	no_show_reasonstring	has_chronic_conditionsboolean	distance_to_clinic_kmfloat	notesstring
APT-000001	private	0	true	94105	PAT-00001	female	32	2024-07-02	09:15	2024-06-26T14:21:00	CLN001	Mission Family Health	PRV-001	general practitioner	consultation	sms	attended	blank	blank	false	2.1	First visit, interested in nutrition counseling
APT-000002	medicare	1	true	75201	PAT-00002	male	68	2024-07-03	13:45	2024-06-29T15:30:00	CLN002	Dallas Geriatric Center	PRV-002	geriatrician	routine check	phone	attended	blank	blank	true	4.6	Requires assistance with mobility
APT-000003	medicaid	0	true	60611	PAT-00003	female	5	2024-07-04	10:00	2024-06-23T11:12:00	CLN003	Lakeshore Pediatrics	PRV-003	pediatrician	routine check	sms	attended	blank	blank	false	1.2	Parent requested school physical form
APT-000004	private	0	true	10016	PAT-00004	male	44	2024-07-05	08:30	2024-06-30T07:50:00	CLN004	NYC Cardiology Associates	PRV-004	cardiologist	consultation	email	attended	blank	blank	true	6.8	Follow-up for heart monitoring
APT-000005	none	4	true	94107	PAT-00005	other	27	2024-07-06	15:10	2024-06-28T10:09:00	CLN001	Mission Family Health	PRV-005	general practitioner	consultation	email	no-show	blank	forgot	false	17.2	Lives outside city, history of no-shows
APT-000006	medicare	2	true	15222	PAT-00006	female	74	2024-07-07	11:20	2024-07-01T09:06:00	CLN005	Pittsburgh Senior Health	PRV-006	neurologist	consultation	phone	cancelled	Transportation issues	blank	true	3.7	Patient called to cancel due to weather
APT-000007	private	0	false	94105	PAT-00007	female	16	2024-07-08	10:45	2024-07-03T08:12:00	CLN003	Lakeshore Pediatrics	PRV-003	pediatrician	routine check	none	attended	blank	blank	false	2.7	Parent opted out of reminders
APT-000008	private	0	false	60611	PAT-00008	male	45	2024-07-09	16:00	2024-07-01T17:49:00	CLN006	Lakeshore Emergency Center	PRV-007	emergency medicine	emergency	none	attended	blank	blank	false	0.7	Arrived for urgent care, no prior appointment
APT-000009	private	1	true	blank	PAT-00009	male	37	2024-07-10	09:40	2024-07-05T12:03:00	CLN007	Downtown Dermatology	PRV-008	dermatologist	consultation	email	attended	blank	blank	false	9.1	Wants results sent electronically
APT-000010	medicaid	0	true	94109	PAT-00010	female	3	2024-07-11	13:00	2024-07-02T08:31:00	CLN003	Lakeshore Pediatrics	PRV-003	pediatrician	routine check	sms	attended	blank	blank	false	0.8	Newborn wellness check
APT-000011	medicare	0	true	blank	PAT-00011	male	71	2024-07-12	11:10	2024-07-06T16:43:00	CLN005	Pittsburgh Senior Health	PRV-009	geriatrician	routine check	phone	attended	blank	blank	true	5.3	Wheelchair access required
APT-000012	private	1	true	94133	PAT-00012	female	55	2024-07-13	15:30	2024-07-03T14:17:00	CLN001	Mission Family Health	PRV-010	general practitioner	follow-up	email	attended	blank	blank	true	3.5	Post-surgery follow-up
APT-000013	none	6	false	75201	PAT-00013	male	23	2024-07-14	08:00	2024-07-10T11:50:00	CLN002	Dallas Geriatric Center	PRV-011	general practitioner	consultation	none	no-show	blank	forgot	false	12.2	Young adult, history of missed appointments
APT-000014	medicare	1	true	15222	PAT-00014	female	65	2024-07-15	14:10	2024-07-08T10:25:00	CLN005	Pittsburgh Senior Health	PRV-006	neurologist	consultation	phone	rescheduled	blank	blank	true	2.2	Patient called to reschedule
APT-000015	medicaid	0	true	94107	PAT-00015	male	14	2024-07-16	12:20	2024-07-09T16:35:00	CLN003	Lakeshore Pediatrics	PRV-003	pediatrician	routine check	sms	attended	blank	blank	false	2.3	Annual physical, parent present
APT-000016	private	0	true	10016	PAT-00016	female	42	2024-07-17	09:00	2024-07-11T15:15:00	CLN004	NYC Cardiology Associates	PRV-004	cardiologist	follow-up	sms	attended	blank	blank	true	8.5	Heart medication review
APT-000017	private	0	false	94109	PAT-00017	male	50	2024-07-18	17:30	2024-07-13T09:10:00	CLN006	Lakeshore Emergency Center	PRV-007	emergency medicine	emergency	none	attended	blank	blank	false	1.5	Walk-in for acute injury
APT-000018	private	0	true	94105	PAT-00018	female	36	2024-07-19	08:50	2024-07-15T07:22:00	CLN001	Mission Family Health	PRV-001	general practitioner	consultation	sms	attended	blank	blank	false	2.8	Sports physical requested
APT-000019	medicare	0	false	15222	PAT-00019	male	120	2024-07-20	09:25	2024-07-17T16:19:00	CLN005	Pittsburgh Senior Health	PRV-009	geriatrician	emergency	none	attended	blank	blank	true	0.5	Walk-in for urgent care, advanced age
APT-000020	private	0	true	94133	PAT-00020	female	29	2024-07-21	14:40	2024-07-16T12:32:00	CLN001	Mission Family Health	PRV-001	general practitioner	consultation	sms	attended	blank	blank	false	1.9	Discussing allergy symptoms

What the 200 rows show

from the 200-row sample

None (insurance type) stands out: mean number_of_previous_no_shows is 6.2, against 0.74 for the rest.

74%reminder_sent = true
1median number_of_previous_no_shows
3patient genders
4reminder methods
4appointment statuses
5appointment types

Mean number_of_previous_no_shows by insurance_type200 rows

number_of_previous_no_shows200 rows, in bands of 1

Median 1, from 0 to 10.

patient_zip_code180 rows with a value · 20 left blank

6061127
1001620
1522220
9410518
7520118
3030913
1910310
770027
941096
941075

23 columns by typefrom the column list below

string 16
integer 2
float 1
date 1
datetime 1
boolean 2

Columns

23 columns in four groups

blueprint · 23 columns
column	type	description	example
Text 16 columns
`appointment_id`	string	Unique identifier for each appointmentunique	APT-000001
`patient_id`	string	Unique identifier for each patient	PAT-00001
`patient_gender`	string	Gender of the patientmale · female · other	female
`patient_zip_code`	string	Postal code of the patient's residenceoptional	94105
`appointment_time`	string	Scheduled time of the appointment (24-hour format, e.g., '14:30')	09:15
`clinic_id`	string	Unique identifier for the clinic where the appointment is scheduled	CLN001
`clinic_name`	string	Name of the clinicoptional	Mission Family Health
`provider_id`	string	Unique identifier for the healthcare provider assigned to the appointmentoptional	PRV-001
`provider_specialty`	string	Specialty of the healthcare provider (e.g., 'general practitioner', 'pediatrician')8 specialties · optional	general practitioner
`appointment_type`	string	Type of appointment (e.g., 'consultation', 'follow-up', 'routine check')consultation · follow-up · routine check · emergency · other	consultation
`reminder_method`	string	Method used to send the reminder (e.g., 'sms', 'email', 'phone', 'none')sms · email · phone · none · optional	sms
`appointment_status`	string	Final status of the appointment (e.g., 'attended', 'no-show', 'cancelled', 'rescheduled')attended · no-show · cancelled · rescheduled	attended
`cancellation_reason`	string	Reason for cancellation if appointment_status is 'cancelled'optional	Transportation issues
`no_show_reason`	string	Reason for no-show if known (e.g., 'forgot', 'transportation', 'illness')7 reasons · optional	forgot
`insurance_type`	string	Type of insurance coverage for the patient (e.g., 'private', 'medicare', 'medicaid', 'none')private · medicare · medicaid · none · other · optional	private
`notes`	string	Additional notes or comments regarding the appointment or patientoptional	Newborn wellness check
Numbers 3 columns
`patient_age`	integer	Age of the patient at the time of appointment0 to 120	32
`number_of_previous_no_shows`	integer	Number of previous appointments missed by the patient0 or more · optional	0
`distance_to_clinic_km`	float	Estimated distance from patient's residence to the clinic in kilometers0 or more · optional	2.1
Dates and times 2 columns
`appointment_date`	date	Scheduled date of the appointment	2024-07-02
`appointment_created_datetime`	datetime	Date and time when the appointment was created	2024-06-26T14:21:00
True or false 2 columns
`reminder_sent`	boolean	Indicates whether a reminder was sent to the patient prior to the appointment	true
`has_chronic_conditions`	boolean	Indicates whether the patient has any chronic medical conditionsoptional	false

Use it for

A healthcare dashboard
The reminder_sent rate, number_of_previous_no_shows by insurance_type and a breakdown of patient_zip_code. Excel, Power BI or Tableau.
Why do the 26 none rows have a mean number_of_previous_no_shows of 6.2?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Appointments200
APT-0000010private
APT-0000021medicare
APT-0000070private
A software demo
Believable appointments with patient_id, patient_gender and patient_age to fill a screen in front of a buyer.

This dataset200 rows23 columns

Yours1,000 rows23 columnspatient_zip_code: UK only

blueprint · healthcare-appointment-no-show-rates

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 23 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

Track attendance per appointment type
Segment reasons for no-show
Include patient demographics
Measure impact of reminder notifications

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: healthcare-appointment-no-show-rates

What should your data show?

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Sample rows

What the 200 rows show

Columns

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?