A simulation tool for better management of retinal services

Background: Advances in the management of retinal diseases have been fast-paced as new treatments become available, resulting in increasing numbers of patients receiving treatment in hospital retinal services. These patients require frequent and long-term follow-up and repeated treatments, resulting in increased pressure on clinical workloads. Due to limited clinic capacity, many National Health Service (NHS) clinics are failing to maintain recommended follow-up intervals for patients receiving care. As such, clear and robust, long term retinal service models are required to assess and respond to the needs of local populations, both currently and in the future. Methods: A discrete event simulation (DES) tool was developed to facilitate the improvement of retinal services by identifying efficiencies and cost savings within the pathway of care. For a mid-size hospital in England serving a population of over 500,000, we used 36 months of patient level data in conjunction with statistical forecasting and simulation to predict the impact of making changes within the service. Results: A simulation of increased demand and a potential solution of the 'Treat and Extend' (T&E) regimen which is reported to result in better outcomes, in combination with virtual clinics which improve quality, effectiveness and productivity and thus increase capacity is presented. Without the virtual clinic, where T&E is implemented along with the current service, we notice a sharp increase in the number of follow-ups, number of Anti-VEGF injections, and utilisation of resources. In the case of combining T&E with virtual clinics, there is a negligible (almost 0%) impact on utilisation of resources. Conclusions: Expansion of services to accommodate increasing number of patients seen and treated in retinal services is feasible with service re-organisation. It is inevitable that some form of initial investment is required to implement service expansion through T&E and virtual clinics. However, modelling with DES indicates that such investment is outweighed by cost reductions in the long term as more patients receive optimal treatment and retain vision with better outcomes. The model also shows that the service will experience an average of 10% increase in surplus capacity.Peer reviewedFinal Published versio

Expression of L1CAM in curettage or high L1CAM level in preoperative blood samples predicts lymph node metastases and poor outcome in endometrial cancer patients

Item does not contain fulltextBACKGROUND: Several studies have identified L1 cell adhesion molecule (L1CAM) as a strong prognostic marker in endometrial cancer. To further underline the clinical usefulness of this biomarker, we investigated L1CAM as a predictive marker for lymph node metastases and its prognostic impact in curettage specimens and preoperative plasma samples. In addition, we aimed to validate the prognostic value of L1CAM in hysterectomy specimen. METHODS: Immunohistochemical staining of L1CAM was performed for 795 hysterectomy and 1134 curettage specimen from endometrial cancer patients. The L1CAM level in preoperative blood samples from 372 patients was determined using ELISA. RESULTS: Expression of L1CAM in curettage specimen was significantly correlated to L1CAM level in corresponding hysterectomy specimen (P<0.001). Both in curettage and preoperative plasma samples L1CAM upregulation was significantly associated with features of aggressive disease and poor outcome (P<0.001). The L1CAM was an independent predictor of lymph node metastases, after correction for curettage histology, both in curettage specimen (P=0.002) and plasma samples (P=0.048). In the hysterectomy samples L1CAM was significantly associated with poor outcome (P<0.001). CONCLUSIONS: We demonstrate that preoperative evaluation of L1CAM levels, both in curettage or plasma samples, predicts lymph node metastases and adds valuable information on patient prognosis