AI System for Monitoring Medical Device Maintenance Records

The problem

In day-to-day operations, maintenance and fault records may remain fragmented. When device inventory, maintenance, fault, contract and usage-status data are scattered across different screens, documents or team records, problems do not become visible in time.

Fragmented data delays preparation of the device review list and forces staff to search manually for supporting evidence again. Before making a decision, the biomedical specialist and clinical device manager have to complete missing fields and verify inconsistencies one by one.

A common exception is that a backup device, manufacturer extension or out-of-service status may apply. Incomplete or incorrect automation that overlooks this context could take a usable device out of service or leave a potentially unsafe device available, so the output cannot be applied directly.

What we set out to improve

• Rate of confirmed follow-up alerts
• Rate of outputs corrected or rejected by the biomedical specialist and clinical device manager
• Time between the source record and the review output

How the system works

1. 01 Define the scope of the review and the authorised biomedical specialist and clinical device manager roles
2. 02 Collect the inputs: device inventory, maintenance, fault, contract and usage status
3. 03 Check source identity, date, version and data freshness
4. 04 Combine device identity and date records
5. 05 Check faults, parts and contracts
6. 06 Check the exception: a backup device, manufacturer extension or out-of-service status may apply
7. 07 Place low-confidence or inconsistent records in a separate human review queue
8. 08 Write the source identity, rule, output and time to the audit trail
9. 09 Have the biomedical specialist and clinical device manager approve, correct, defer or reject the output

Methods we used

• Date and status rules
• Source, format, version and required-field checks for device inventory, maintenance, fault, contract and usage-status data
• A missing-data warning instead of an estimate when inputs are missing or inconsistent
• Checking exceptions separately from the main rule
• Storing the source identity, rule result, device review list and human decision together

Where people stay involved

Data and security

Access to device inventory, maintenance, fault, contract and usage-status data is limited to the minimum permissions required for each role. Identifiers and sensitive fields are masked where possible, and only the necessary section is sent to the model rather than the entire raw file. Access, outputs and decisions by the biomedical specialist and clinical device manager are recorded; the system does not enter production until the organisation has approved the retention period and data location.

Who this suits

Frequently asked questions