Strategic Intelligence Monitor on Personal Health Systems, Phase 2. Impact Assessment Final Report

The report presents two different methodologies and indicators to assess the economic impact of eHealth technologies, with a focus on Integrated Personal Health Systems and telehealth. The first part, presents a cost-effectiveness indicator representing the break even between the market value of teleheath applications and the savings in hospitalisation they lead to. The break even thus measures the daily cost per monitored patient for which the telehealth monitoring costs equal the savings from reduced hospitalisation. The main contribution of this methodology, which is based on an extrapolation model, lies in the level of detail and the novelty of the international database constructed for clinical metrics and health expenditures in relation to three chronic conditions: chronic heart failure (CHF), chronic obstructive pulmonary disease (COPD), and diabetes. Furthermore, the assumption made on the parameters, prices and deployment levels used to measure typical levels of impact of telecare and teleheath treatments are based on documented evidence from the most recent and relevant projects in the field, such as the Whole System Demonstrator in England, and an ongoing telehealth project for cardiac patients in Lombardy, Italy. The saving in hospilatisation obtained, which are on the order of 2 per patient-day for several countries such as the UK, Luxembourg, Netherlands, and Belgium, suggest an acceptable price or reimbursement rate for providers, should the deployment level be sufficiently high and technologies capable of tackling co-morbidities so as to exploit economies of scale and scope. Secondly, the report presents projections to 2020 and 2030 for total health, public and hospital expenditures in the EU27 Member States. These projections result from the use of econometric models to measure the contribution of health technologies to the growth in real per capita health expenditure, taking into account country-specific supply-side effects. The projections presented contribute to recent studies, in particular to the model presented by DG ECFIN in The 2012 Ageing Report, by estimating the effect of eHealth, represented through several country-level indicators, on country-specific total supply-side effects. As a result, the impact of eHealth is quantified by comparing the projections from what we define as the baseline scenario (i.e. constant eHealth deployment level) and those from two different policy scenarios which assume two different levels of increase in eHealth deployment. Despite country heterogeneity, the expected results at EU27 level from a strong eHealth intervention - with increasing deployment at hospital level, broadband penetration and general ICT health expenditure point out a decrease in the hospital spending-to-GDP ratio. This reduction can be very important in countries where the contribution of supply-side factors to the growth of health spending is high, such as Estonia, Poland, Romania, and Slovakia. In the case of total and public health spending, it is remarkable that countries leading the implementation of eHealth projects (i.e. UK and Ireland) can benefit from an expected reduction in real health expenditures.