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Complex socio-technical systems: Characterization and management guidelines.

Angela Weber Righi1, Tarcisio Abreu Saurin1

  • 1DEPROT/UFRGS (Industrial Engineering and Transportation Department, Federal University of Rio Grande do Sul), Av. Osvaldo Aranha, 99, 5. Andar, Porto Alegre, RS CEP 90035-190, Brazil.

Applied Ergonomics
|May 12, 2015
PubMed
Summary
This summary is machine-generated.

This study presents a new framework to measure complexity in socio-technical systems (STS). It helps identify areas for improving system design and management in fields like healthcare ergonomics.

Keywords:
ComplexityEmergency departmentSocio-technical systems

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Area of Science:

  • Ergonomics and Human Factors
  • Systems Engineering
  • Organizational Psychology

Background:

  • Ergonomics increasingly recognizes complexity's role, yet lacks operational methods.
  • Existing approaches to complexity in socio-technical systems (STS) are limited.
  • A structured framework is needed to analyze and manage complexity in STS.

Purpose of the Study:

  • To introduce and validate a framework for operationalizing the "attribute view" of complexity in STS.
  • To provide a systematic method for assessing complexity attributes and management guidelines.
  • To identify leverage points for optimizing STS design based on complexity analysis.

Main Methods:

  • Delimitation of the socio-technical system (STS).
  • Description of four key complexity attributes: element number/interactions, diversity, variability, and resilience.
  • Assessment of six management guidelines for complexity.
  • Identification of leverage points based on attribute relationships and classification (irreducible/manageable, liability/asset).
  • Case study application in a university hospital's emergency department using document analysis, observations, interviews, and questionnaires.

Main Results:

  • The study successfully operationalized the "attribute view" of complexity.
  • The framework facilitated the analysis of complexity within the emergency department.
  • Specific leverage points for improving STS design were identified.
  • The classification of complexity attributes (irreducible/manageable, liability/asset) proved useful.

Conclusions:

  • The proposed framework offers a practical approach to assessing and managing complexity in socio-technical systems.
  • It provides valuable insights for improving the design and resilience of complex systems, such as those in healthcare.
  • The framework supports evidence-based decision-making for enhancing system performance and safety.