A comparative analysis of health surveillance strategies for administrative video display terminal employees

Biomed Eng Online. 2019 Dec 11;18(1):118. doi: 10.1186/s12938-019-0737-z.

Abstract

Background: The objective of this study was to develop a strategy to optimize medical health surveillance protocols for administrative employees using video display terminals (VDTs). A total of 2453 medical examinations were analysed for VDT users in various sectors. From these data, using Bayesian statistics we inferred which factors were most relevant to medical diagnosis of the main disorders affecting VDT users. This information was used to build an influence diagram to evaluate the time and monetary costs associated with each diagnostic test and define an optimal protocol strategy based on occupational risks.

Results: Musculoskeletal and ophthalmological diseases were identified as the most frequent disorders among VDT users. The Bayesian network inferred age, sleep quality, activity level, smoking and the consumption of alcohol as risk factors. The blood count was the most costly test (5.23 USD/employee) and the second most costly test in time terms (4 min/employee), yet is a diagnostic test that has little influence on the medical decision regarding an employee's capacity to perform their job.

Conclusions: Current occupational health surveillance protocols for VDT users may lead to expenditure that is 54% greater than necessary. For many employees and employers, failure to perform a wide range of medical tests for occupational health surveillance purposes is subjectively perceived as a threat to health. Awareness needs to be raised of the appropriate role of different health areas, so as to optimize diagnostic efficiency on the basis of greater flexibility.

Keywords: Clinical decision support systems; Data mining in healthcare; Health informatics; Health strategies; Occupational health surveillance; Video display terminals (VDTs).

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Computer Terminals*
  • Female
  • Humans
  • Male
  • Medical Staff / statistics & numerical data*
  • Public Health Surveillance / methods*