Objective: A United Kingdom Department of Health directive (EL[94]72) asked Health Authorities to manage the entry of new drugs into practice. There seem to be costs associated with the decision-making process of managed entry, but no clear evidence of benefit to patient populations. The objective of this study was to assess the potential costs and outcomes of different models of managed entry, using the example of donepezil in the North West Health Region of the U.K. National Health Service. This is a preliminary study designed to identify the key pieces of information required to evaluate the value of managed entry.

Methods: Decision analytic models of three Health Authorities' approaches to manage the entry of donepezil were used to estimate the expected costs and effectiveness of the process. Resource use data were obtained from published sources and the relevant Health Authority. Probabilistic sensitivity analysis was used to determine the robustness of the results.

Results: The process of managed entry of donepezil was associated with higher expected costs and higher expected outcome than no managed entry. The 95% confidence intervals for the net expected costs and net expected outcomes were relatively narrow and did not cross zero, which suggests a statistical difference between managed entry and no managed entry for donepezil. The incremental cost-effectiveness ratios for managed entry of donepezil indicate that, compared with no managed entry, there were substantial differences between the different models used in the three study sites. The expected cost per unit of cognitive function gained was between £18,000 in study site 001 to £28,000 in study site 010. The expected cost per person with a clinically significant improvement was between £140,000 and £230,000. The expected cost per QALY ranged from £470,000 to £19.3 million.

Conclusions: Managed entry does not appear to be a worthwhile mechanism to introduce drugs into practice. However, poor accessibility and availability of data means that the results are highly uncertain. The lack of data presents serious obstacles for both researchers and policy makers wishing to develop evidence-based policy and practice.