Tailored health care for chronic disease in primary care: minimising the risks and maximising the benefits - An application of policy simulation

Abstract

The policy of interest is Diabetes Coordinated Care Initiative (DCCI) and DCC Pilot (DCCP). The DCC policy and pilot are intended to improve care for patients whose outcomes, as a group, are suboptimal under mainstream primary care financing (MBS). There is uncertainty as to: how many and which GPs and patients will enrol; the expected benefit to enrolled patients; and potential risks for unenrolled patients. A literature review can inform decision makers about the value of the relevant parameters prior to policy implementation, but gaps in evidence remain. How can these gaps be identified? When do they matter? How can risk management strategies be put in place even if the value of parameters is unknown? Policy simulation is a tool that complements Evidence-Based Medicine. It provides strategies to identify "the known unknowns" and the "what ifs" of policy. Its starting point is: in the absence of evidence, what are we implicitly assuming; does it matter what we assume; and if it does matter, what are the options available to minimise any risks associated with the "known unknowns".