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Critical Device Reliability Assessment in Healthcare Services.

Noorul Husna Abd Rahman1,2, Ayman Khallel Ibrahim3, Khairunnisa Hasikin1

  • 1Department of Biomedical Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia.

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This summary is machine-generated.

Medical device reliability is crucial for patient care. This review highlights gaps in assessing critical device reliability, emphasizing the need for better protocols and predictive models, especially using AI.

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Area of Science:

  • Biomedical Engineering
  • Healthcare Management
  • Reliability Engineering

Background:

  • Medical device reliability is essential for consistent patient service delivery.
  • Existing reporting guidelines for medical device reliability require evaluation.
  • Interconnected medical device systems increase complexity in reliability assessment.

Purpose of the Study:

  • To summarize current literature on medical device reliability.
  • To identify research gaps in medical device reliability assessment.
  • To investigate factors influencing medical device reliability.

Main Methods:

  • A systematic review using Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines.
  • Searched eight databases for articles published between 2010 and May 2021.
  • Shortlisted 36 relevant articles for analysis.

Main Results:

  • Key topics identified: risk management, AI/machine learning for performance prediction, and management systems.
  • Challenges include: insufficient maintenance data, parameter selection, access to facilities, and limited device age data.
  • Current AI/ML models are limited to specific devices like infant incubators and defibrillators.

Conclusions:

  • There is a lack of explicit protocols and predictive models for medical device reliability assessment.
  • A comprehensive strategy for critical medical device reliability is missing.
  • Further research focusing on critical medical devices in healthcare is needed to improve current knowledge.