Health and long-term care data needs: the Ageing Report and the European Semester Public Health Statistics Working Group Luxembourg, 16-17 December 2014.

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Presentation transcript:

Health and long-term care data needs: the Ageing Report and the European Semester Public Health Statistics Working Group Luxembourg, December 2014 Santiago Calvo Ramos Sustainability of Public Finances DG Economic and Financial Affairs European Commission

Unit C2, DG ECFIN: Main tasks and data needs EPC-EC Ageing Report European Semester and analysis of sustainability of EU health systems Other publications and analysis

The EPC-EC Ageing Report 2006, 2009 and 2012: public expenditure projections health care long-term care pensions Project expenditure until 2060 Departing point: population projections and ageing. Impact on expenditure? Consider other drivers of expenditure

Data needs Need data on many things! Population by age and gender Eurostat population data Data on overall public expenditure on health care SHA data; when not available ESSPROS Data on overall public expenditure on long-term care SHA data; when not available ESSPROS data from Eurostat In-kind and cash benefits – for cash use ESSPROS data from Eurostat Data on overall public expenditure on pensions

Data needs Data on health status Life expectancy from Eurostat Dependency rates = severe disability rates as in EU-SILC from Eurostat Data on age-gender specific expenditure profiles Per capita for healthcare – national data Per user for long-term care – national data Data on users of long-term care – national data Separated in institutional and home care

Data needs Data to run specific scenarios: Health care: –Wages, capital, pharmaceutical, appliances, administration LTC: –Expenditure on Institutional and home care, –Number of users of institutional and home care Pensions: –Used for comparison with national data.

Data problems encountered Comparability not yet there Two sources of data: SHA and ESSPROS Not fully comparable No data for specific categories if do not use SHA: e.g. pharmaceutical expenditure Difficulty in obtaining comparable data on capital and wages use additional sources like COFOG or EUKLEMS National data on age-profiles not fully comparable

Data problems encountered Bigger problems with LTC data: No data on cash-benefits from SHA: Use ESSPROS but difficult to agree categories with Member States So need to improve comparable data collection

Data problems encountered Bigger problems with LTC data (cont.): Data on social services of LTC not available for all: Part of previous HCR6 in SHA but not reported for all and not always possible to disentangle from other benefits Use ESSPROS but need for adjustments So need to improve comparable data collection

Data problems encountered Bigger problems with LTC data (cont.): Number of people receiving long-term care in a) institutions and b) at home, by sex and single age or five- year cohorts From? National data so far… number of recipients of long-term care-related cash benefits, by sex and single age or five-year cohorts From? National data so far…

European Semester Support Country Desks in analysis of public finances in HC and LTC Set of commonly used indicators on expenditure but also on areas of provision and health status Pharmaceuticals Hospitals: beds, ALOS Ambulatory: staff and staff mix Prevention and Promotion Spending on administration Health status

European Semester: Health care TAF Hospital care Public hospital expenditure as % of GDP, Public hospital expenditure as % of public CHE, Acute hospital beds per pop, Acute care bed occupancy rates, Average acute care length of stay in days**, % of day in total discharges Ambulatory care Public ambulatory care expenditure as % of GDP, Public exp. on ambulatory care as % of public CHE, Number of GPs per inhabitants, Share of GPs in total number of physicians, Ratio of nurses to physicians, Ratio of outpatient to inpatient contacts per capita Pharmaceutical spending Public outpatient pharmaceutical expenditure as % of GDP, Public exp. on outpatient pharmaceuticals as % of public CHE, Public as % of total expenditure on pharmaceuticals, Expenditure in per capita PPS, Generic market shares in volume Administrative spending Public administrative expenditure as % of GDP, Public exp. On administration and insurance as % of public CHE. Health status Life expectancy at birth for females, Life expectancy at birth for males, Amenable mortality, Infant mortality rate per life births

European Semester: Long-Term Care TAF Distribution of LTC spending % of spending on institutional as part of formal in-kind spending, % of formal in-kind spending in total spending LTC coverage % of population (aged 15+) receiving formal in-kind LTC and/or cash benefits, % of dependents (aged 15+) receiving formal in-kind LTC and/or cash benefits Unit costs Unit costs in institutional care per recipient, as % of GDP per capita, Ratio of unit cost per recipient in institutional to home care System features Eligibility: means tested criterion, Eligibility: minimum dependency criterion Need for LTC care services Expected years in sickness or disability over life time, Expected years in sickness or disability from age 65 onwards*, People having a long-standing illness or health problem, in % of pop., Self-perceived severe limitations in daily activities, in % of pop.

Other publications by C2 Medeiros J. and Schwierz C. (2013), "Estimating the drivers of and projecting public health care expenditure in the European Union: Baumol's "cost-disease" revisited, forthcoming. Carone, G., C. Schwierz and A. Xavier (2012), “Cost-containment policies in public pharmaceutical spending in the EU”, European Economy, Economic Paper No. 461, European Commission.Cost-containment policies in public pharmaceutical spending in the EU: htm htm European Commission (DG ECFIN)-EPC (AWG) (2010), 'Joint Report on Health Systems', European Economy. Occasional Papers, Vol. 74: en.pdf en.pdf

DG ECFIN supports better data collection Through implementation of SHA 2011 Through ESSPROSS improvements Through collection of consistent and comparable non- monetary health statistics Thank you!