Monitoring access to health care and health care costs on a population level
Summary
The aim of this task is to move a step further in the direction of developing and implementing procedures and methodologies to monitor the impact of NCDs in terms of access to health care services and corresponding expenditures related to diagnosis, treatment and follow-up of NCDs patients considering the entire disease pathway from diagnosis to possible recovery or end-of-life. The task is developed in the following steps: (i) Mapping of available data for the estimating patterns of care and costs of NCDs; (ii) Identification of healthcare cost components; (iii) Definition of standards and framework for collecting, linking and selecting health care access and costs of cancer patients; (iv) Definition, measurement of indicators of cancer burden, and costs at population level; (v) Modelling approaches in cancer costs evaluation and projections of cancer burden indicators; (vi) Comparing data on cancer burden costs at across European countries.
Piloting the implementation of the Epicost model in European countries
A model focused on CRs data which allows to estimate the amount of people living with a cancer diagnosis (prevalent cases) and to classify them into three phases of care: initial, monitoring and final, reflecting different patterns of care, is proposed. By linking individual data from CRs to administrative data (hospital admissions, ambulatory services, drug prescriptions) profiles of health care direct cost are estimated, in each phase of the disease.
Piloting the estimation of the probability of progressing to cancer recurrence and long-term side-effects
By combining population-based CRs data, estimates of the cure fraction (from mixture cure models) and survival data of patients with de novo metastatic patients, and available health system databases, including exhaustive information on medical prescriptions and procedures.
Piloting modelling of health care costs at micro-economic level
This pilot aims to investigate the relationship between the economic burden of cancer and a set of possible predictors, typically involving patients’ socio-demographic, as well as clinical conditions and management systems.
Decision analytic modelling of cancers and other non-communicable diseases
The pilot uses advanced simulation modelling and unique combinations of linked data sources to inform current and future priority setting. Focus will be on cancers in combinations with other non-communicable diseases (NCDs).