Modelling Dual Market Healthcare Sectors – A Systemic Perspective Applying the CIMO Framework
Building contextual evidence for the basis of better decision making is a cornerstone of good policy making. It is known that policy interventions in healthcare are reliant on the contextual setting of the intervention. Dual market healthcare sectors make up one such interesting context. These sectors of healthcare are characterized by a heavy reliance on both public and private service production. In Finland, these sectors include for example, dental care, mental health, and elderly care. I propose a theoretical model that can be used to model the outcomes of policy interventions in a dual market healthcare sector.
Using the Context-Intervention-Mechanism-Outcome (CIMO) framework, I studied the Finnish dental care sector during the years 2010-2016 in Espoo, Helsinki, and Oulu. This exploratory registry study included a dataset of 17,111,625 dental operations and enveloped two interesting policy interventions. During the years 2015 and 2016 the average reimbursement of private dental care operations was cut from 33 % to 25 % and 15 % respectively.
The mechanisms at work and the outcomes produced develop within differing timespans and examining changes in data within one calendar year is not sufficient to conclude how an intervention has affected the entire system. After the intervention of 2015, the out-of-pocket payments increased in the private sector, yet no significant changes were observed in any other metrics. The public sector, however, showed an increase in capacity, in patients treated and in productivity.
After the intervention of 2016, the private sector out-of-pocket payments increased further, this time resulting in a significant reduction in patients treated, in capacity, in operations produced, and in productivity. This time, however, the public sector did not seem capable of handling the new inflow of patients. Only a small increase was observed in patients treated in the public sector. In addition, a reduction in capacity and a no significant change in productivity were observed. Thus, the data would lead to the conclusion that the intervention of 2015 activated any slack and additional capacity available leading to a tipping point in 2016, after which the public sector could not receive the inflow of new patients anymore.
In summary, when conducting policy interventions in a dual market healthcare sector, a systemic perspective should be adopted. It is no sufficient to study only one sector within the entire system since changes in one significantly affect the other. To model these relationships and monitor the success of policy interventions I propose a theoretical model and guidelines for intervention monitoring in my master’s thesis “Building Contextual Evidence for Outcomes of Policy Interventions in Healthcare: A Case Study of the Finnish Dental Care Sector.”