Designing a Model for Distribution of Intensive Care Beds in Iranian Hospitals

 Hospital beds are the most expensive part of the service delivery system in the health system of the countries, and the intensive care beds are more important. This study has been conducted with the aim of designing a model for distribution of intensive care beds in the country.

The current study is a descriptive-analytical type that has been performed through 2018-19. The study population consisted of 340 health managers and experts in 10 health centers of medical universities in Iran.  Data were collected through a researcher-made questionnaire and analyzed by SPSS 25 and Lisrel8.8 software. The main components affecting the distribution of intensive care beds were identified by exploratory and confirmatory factor analysis to model confirmation and the method of analyzing the main elements by vertical rotation and also Varimax technique.

 In exploratory factor analysis, 34 variables were divided into 6 main components. Results of fitting indices for the model indicates acceptance of the studied index and acceptance of the model. Also six economic factors (with 5 components), organizational (with 7 components), political-social (with 5 components), structural (with 7 components), demographic (with 5 components), geographical (with 5 components), were identified as main dimensions which covered 59.36 percent of the total variance of the variables. After confirmatory factor analysis, all factors were in good order, and the model was well fitted and validated. The demographic dimension had the highest weight (0.80) and the economic dimension (0.53) had the least effect on the distribution of intensive care beds. Discussion and

 In this study, a model of distribution of intensive care beds was explained and among the influential components, demographic factor component plays a very important role in the distribution of intensive care beds. Health system policymakers and managers must pay particular attention to the effective components in decision-making for proper allocation of hospital resources, especially hospital beds to achieve justice in health.