Interpretive Structural Modeling of the Factors Affecting Induced Demand for Health Services

Induced demand is an important challenge in national healthcare systems, and can waste their resources. The likelihood of induced demand and the intensity of its effects are the results of an interaction between a wide range of factors. Therefore, this study was designed for structural modeling of the factors affecting induced demand.
This applied study was carried out using a descriptive-analytic design. First, the factors affecting induced demand were identified by a thorough literature review. Then, using interpretive structural modeling (ISM), the relationship between the factors was determined and categorized, and the final model  developed. In addition, using MICMAC analysis, the types of variables have been identified with respect to their driving and dependency power.
Lack of clinical guidelines, increased number of providers, weakness of education system, weakness of Health Supervisory System, poor supervision of insurance companies, improper payment system, providers' insufficient knowledge, skills and clinical uncertainty, defensive medicine, patient preferences, information asymmetry, the collusion of service providers, and their incentives to earn more income were identified as the most important factors affecting management and control of induced demand.
Induced demand reduction requires finding the relationships between the key factors to provide a clear framework for determining the best controlling policies, thereby preventing the loss of healthcare resources. This study provided a new insight into the factors affecting induced demand leading to prioritization of decision-making and policymaking measures.