Estimating the societal costs and benefits of de-implementation of low-value care: developing a modelling approach through case assessment

Previous estimates of potential costs savings from de-implementation of low-value care have been calculated with simple modelling approaches, focused on direct medical costs and did not take substitution into account. Therefore, the aim of this study was to develop and evaluate a modelling approach to calculate a more realistic estimate of societal costs and benefits of de-implementation of low-value care. The modelling approach was developed and evaluated in three steps: (1) review of reviews to identify aspects that may affect the costs and benefits of de-implementation, (2) selection of three cases of low-value care, (3) development and evaluation of the modelling approach for each case. Desk research and interviews with actors were used in step 3 to define input parameters. The modelling approach was build and evaluated for the following cases: (1) surgery for achilles tendon rupture, (2) mammography for women < 30 years with focal breast complaints, and (3) imaging for non-specific low back pain. From the interviews, it appeared that case 2 had already been fully disinvested. Hence, calculating the societal costs and benefits for this case was not considered valuable. For case 1 and 3 it was considered valuable and feasible to calculate the societal costs and benefits. Compared to the adapted societal business case approach used in case 1, the adapted societal cost-benefit analysis approach used for case 3 provided a more realistic and better estimate. It is feasible to calculate a more elaborate and realistic estimate of societal costs and benefits of the de-implementation of low-value care than previous estimates. Nevertheless, it was not feasible to include the costs of de-implementation itself as these are highly reliant on the specific de-implementation strategy employed, which is context specific. Furthermore, the time needed to calculate a more elaborate and realistic estimate stresses the need to carefully select low-value care cases for which the value of calculating such an elaborate and realistic estimate outweighs the effort required to do so.