The performance follow-up of Finnish occupational health services

Int J Qual Health Care. 1997 Aug;9(4):289-95. doi: 10.1093/intqhc/9.4.289.

Abstract

Objectives: The aim of the study was to describe the structure, input and output figures of occupational health services (OHS) in Finland as basic data for a revised follow-up system.

Design: A cross-sectional postal survey.

Study participants: All OHS units in Finland (n = 1025). The response rate was 94%. The more extensive questionnaire was returned by 82% (n = 837), and an additional 12% (n = 127) returned a shorter questionnaire.

Main outcome measures: The variation in structure (number and education of personnel, number of clients and size of client enterprises), input indicators (employees per full-time equivalent physician and nurse) and output indicators (worksite visits per 100 employees, health checks per 100 employees, office visits per 100 employees) were compared by the five prevailing OHS models and within the models.

Results: There were often two- to threefold differences in the median figures of the different manpower and performance indicators between the OHS models. Although the lowest and highest deciles were excluded, the differences within the models were usually even greater.

Conclusions: We found a great variation in both input and output figures within OHS in Finland. Part of this variation can be explained by the different needs and contents of services. The data can serve as a basis for evaluation of OHS activities both at the national level and as benchmark data for the individual OHS units. However, these types of data do not allow us to assess the quality or outcome of services.

MeSH terms

  • Cross-Sectional Studies
  • Data Collection / methods
  • Data Interpretation, Statistical
  • Finland
  • Follow-Up Studies*
  • Health Care Surveys*
  • Health Policy
  • Humans
  • Occupational Health Services / organization & administration*
  • Occupational Health Services / standards
  • Occupational Health Services / statistics & numerical data
  • Quality Assurance, Health Care / methods*