Medical Device Usage Patterns

This dataset provides a comprehensive view of medical device usage across healthcare facilities, detailing allocation, utilization rates, breakdown events, and maintenance scheduling. It enables healthcare organizations to optimize device deployment, improve maintenance efficiency, and reduce downtime, supporting data-driven decisions for patient care and operational excellence.

  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Optimizing medical device allocation across departments

Sample rows

preview · 8 of 200 rows · all 15 columns
device_idstringutilization_ratefloatis_operationalbooleanmanufacturerstringdevice_typestringinstallation_datedatelocation_departmentstringlast_maintenance_datedatenext_scheduled_maintenancedatebreakdown_event_countintegerlast_breakdown_datedateaverage_repair_time_hoursfloatscheduled_usage_start_timedatetimescheduled_usage_end_timedatetimemaintenance_notesstring
MD-000182.3trueSiemensMRI Scanner2018-05-12Radiology2024-03-152024-09-1022024-03-155.22024-06-14T08:00:002024-06-14T16:00:00Routine check performed; minor calibration needed.
MD-000267.8trueGE HealthcareX-Ray Machine2021-11-23Orthopedics2024-04-182024-10-200blankblank2024-06-14T10:00:002024-06-14T13:00:00blank
MD-000391.1truePhilipsCT Scanner2019-07-04Emergency2024-05-012024-07-2912024-05-013.62024-06-14T07:30:002024-06-14T15:30:00Replaced cooling fan during last maintenance.
MD-000479.4trueCanon MedicalUltrasound2020-02-21Obstetrics2023-12-092024-06-200blankblank2024-06-14T09:00:002024-06-14T17:00:00Probe calibration scheduled next cycle.
MD-000556.6trueBaxterInfusion Pump2022-10-14Oncology2024-05-222024-11-220blankblank2024-06-14T12:00:002024-06-14T16:00:00blank
MD-000631.2trueZollDefibrillator2017-08-09Cardiology2024-04-112024-08-1112024-04-112.72024-06-14T11:00:002024-06-14T14:00:00Battery replaced after last breakdown.
MD-000798.6trueMindrayPatient Monitor2021-03-15ICU2024-05-172024-11-1742024-05-176.12024-06-14T00:00:002024-06-14T23:59:00Frequent alarm triggers; sensors checked.
MD-000895.4trueDrägerVentilator2020-06-06ICU2024-01-302024-07-3032024-01-304.82024-06-14T00:00:002024-06-14T23:59:00Circuit replacement completed.

What the 200 rows show

from the 200-row sample
  • 100%is_operational = true
  • 78.5median utilization_rate
  • 15location departments
  • 18device types
  • 1median breakdown_event_count
  • 2.7median average_repair_time_hours
utilization_rate200 rows, in bands of 10
02550000392233464740050100utilization_rate →

Median 78.5, from 31.2 to 99.5.

manufacturer200 rows · top 10 of 31 values
  1. Philips30
  2. GE Healthcare22
  3. Dräger15
  4. Mindray11
  5. Baxter10
  6. Siemens Healthineers10
  7. Medtronic9
  8. Canon Medical8
  9. Nihon Kohden8
  10. Siemens7
15 columns by typefrom the column list below
  • string 5
  • integer 1
  • float 2
  • date 4
  • datetime 2
  • boolean 1

Columns

15 columns in four groups
blueprint · 15 columns
columntypedescriptionexample
Text 5 columns
device_idstringUnique identifier for each medical deviceuniqueMD-0001
device_typestringType or model of the medical deviceMRI Scanner
manufacturerstringName of the device manufacturerSiemens
location_departmentstringHospital or clinic department where the device is locatedRadiology
maintenance_notesstringFree-text notes regarding maintenance or breakdown eventsoptionalBulb tested; no issues.
Numbers 3 columns
utilization_ratefloatPercentage of time the device is in active use (0-100)0 to 10082.3
breakdown_event_countintegerTotal number of breakdown or failure events recorded for the device0 or more2
average_repair_time_hoursfloatAverage time (in hours) taken to repair the device after breakdowns0 or more · optional5.2
Dates and times 6 columns
installation_datedateDate the device was installed or commissioned2018-05-12
last_maintenance_datedateDate of the most recent maintenance performed on the deviceoptional2024-03-15
next_scheduled_maintenancedateDate of the next scheduled maintenance for the deviceoptional2024-09-10
last_breakdown_datedateDate of the most recent breakdown eventoptional2024-03-15
scheduled_usage_start_timedatetimeScheduled start time for device usage (if applicable)optional2024-06-14T08:00:00
scheduled_usage_end_timedatetimeScheduled end time for device usage (if applicable)optional2024-06-14T16:00:00
True or false 1 column
is_operationalbooleanIndicates whether the device is currently operationaltrue

Use it for

  • is operational100%199 of 200 rows

    A healthcare dashboard

    The is_operational rate, utilization_rate and a breakdown of manufacturer. Excel, Power BI or Tableau.

  • Why do 199 of 200 rows have is_operational = true?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 200 rows.

  • A software demo

    Believable devices with device_type, manufacturer and installation_date to fill a screen in front of a buyer.

Not quite right?

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This dataset200 rows15 columns
Yours1,000 rows15 columnslocation_department: UK only

blueprint · medical-device-usage-patterns

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 15 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
  • Device ID and type tracked
  • Usage hours recorded daily
  • Maintenance and breakdown events logged
  • Departmental allocation included
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
medical-device-usage-patterns

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