Developing a prioritisation framework in an English Primary Care Trust

Abstract

Background: In the English NHS, Primary Care Trusts (PCTs) are required to commission health services, to maximise the well-being of the population, subject to the available budget. There are numerous techniques employed to make decisions, some more rational and transparent than others. A weighted benefit score can be used to rank options but this does not take into account value for money from investments.

Methods: We developed a weighted benefit score framework for use in an English PCT which ranked options in order of 'cost-value' or 'cost per point of benefit'. Our method differs from existing techniques by explicitly combining cost and a composite weighted benefit score into the cost-value ratio.

Results: The technique proved readily workable, and was able to accommodate a wide variety of data and competing criteria. Participants felt able to assign scores to proposed services, and generate a ranked list, which provides a solid starting point for the PCT Board to discuss and make funding decisions. Limitations included potential for criteria to be neither exhaustive nor mutually exclusive and the lack of an interval property in the benefit score limiting the usefulness of a cost-value ratio.

Conclusion: A technical approach to decision making is insufficient for making prioritisation decisions, however our technique provides a very valuable, structured and informed starting point for PCT decision making.

Figure 1

Criteria and weights. Mean weightings of the criteria relative to one another.

Figure 2

Variance in criteria weights. Variation in criteria weightings between groups.

Figure 3

Sensitivity analysis. Changes in the cost-value ratios from using mean criteria weights versus each individual group's. The ranking is from lowest to highest cost-value ratio. Note that the lines do not cross meaning the ranked order does not change no matter which set of weights are used. This suggests the ranking is robust to variations in criteria weightings.