Direct cost of pars plana vitrectomy for the treatment of macular hole, epiretinal membrane and vitreomacular traction: a bottom-up approach

Purpose The direct cost to the National Health Service (NHS) in England of pars plana vitrectomy (PPV) is unknown since a bottom-up costing exercise has not been undertaken. Healthcare resource group (HRG) costing relies on a top-down approach. We aimed to quantify the direct cost of intermediate complexity PPV. Methods Five NHS vitreoretinal units prospectively recorded all consumables, equipment and staff salaries during PPV undertaken for vitreomacular traction, epiretinal membrane and macular hole. Out-of-surgery costs between admission and discharge were estimated using a representative accounting method. Results The average patient time in theatre for 57 PPVs was 72 min. The average in-surgery cost for staff was £297, consumables £619, and equipment £82 (total £997). The average out-of-surgery costs were £260, including nursing and medical staff, other consumables, eye drops and hospitalisation. The total cost was therefore £1634, including 30 % overheads. This cost estimate was an under-estimate because it did not include out-of-theatre consumables or equipment. The average reimbursed HRG tariff was £1701. Conclusions The cost of undertaking PPV of intermediate complexity is likely to be higher than the reimbursed tariff, except for hospitals with high throughput, where amortisation costs benefit from economies of scale. Although this research was set in England, the methodology may provide a useful template for other countries

Mixed observability MDPs for shared autonomy with uncertain human behaviour

Shared autonomy allows humans and AI operators to work towards a common goal. Typically, shared autonomy systems are modelled by combining a single model for human behaviour, and a model for the AI behaviour. In this paper, we attempt to provide a richer human model, which accounts for variation in performance due to factors that are not directly observable. Our shared autonomy system will maintain a belief over the unobservable factors, and update its belief as they make observations. The new belief is used to decide who should operate the shared autonomy system. We show that using our model with a richer human representation results in better performance than using a simplistic human model