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Archive:Morbidity statistics methodology pilot studies - introduction

This article provides an introduction to the report 'Morbidity statistics in the EU' (available as downloadable PDF) on a possible methodology for collecting and compiling European Union (EU) morbidity statistics based on pilot studies on diagnosis-specific morbidity statistics conducted by sixteen EU Member States from 2005 to 2011. The report summarises the results of the Eurostat 'Morbidity Task Force'[1] set up to analyse the results of the pilot studies and to formulate a set of recommendations on the feasibility of a regular morbidity statistics data collection, focusing on possible sources and best national estimates on incidence and prevalence of a selected list of diseases. The report was presented to the Working Group on Public Health Statistics in December 2013.

A second article on morbidity statistics provides an overview of the main findings, problematic aspects and proposed solutions for moving towards a Eurostat morbidity data collection, by presenting some prototypal situations the Task Force faced during the analysis of potential sources and estimates with regard to their accessibility, usefulness, overall quality and comparability.

Executive summary

Eurostat activities in the domain of health status and health determinants are currently covered by surveys; however, one core activity is missing: the regular collection of diagnosis-specific morbidity data with incidence and prevalence rates. A legal basis for such data collection is provided by Regulation No 1338/2008 establishing a framework for Community statistics on public health and health and safety at work. That regulation foresees an implementation of morbidity statistics at EU level.

Eurostat’s commitment in developing the conceptual and methodological framework for establishing such data collection on morbidity has a long-standing tradition; however, this ambitious goal has not yet been achieved. The reason behind is that from a methodological and operational point of view, establishing morbidity statistics is an extremely complex exercise, in particular with regards to comparability of data across countries. To guide the Member States in the piloting phase, detailed guidelines were produced by the Morbidity Statistics Development Group in 2007: for each entry in the recommended short list the appropriate measures on incidence and/or prevalence for data delivery were indicated. Each country had to find appropriate sources for producing best national estimates. The main criteria for the inclusion of a data source was statistical robustness on the main data quality parameters and hence permit reliable inter country comparisons. Hence, like many Eurostat statistics, the compilation of diagnosis-specific morbidity statistics is output driven and not source oriented.

Altogether 16 Member States participated at pilot studies on diagnosis-specific morbidity statistic from 2005 to 2011. In 2011, Eurostat established the Task Force on Morbidity Statistics (TF MORB) for analysing the pilots’ results, especially in view of sources and best estimates. TF MORB is presenting this report with an in depth analysis of the pilot studies and methodological recommendations for paving the way ahead to overcome the pioneering stage.

The establishment of diagnosis-based morbidity statistics will be crucial for filling an information gap on the health status of the EU population which has severely hampered the development of public health indicators at EU level.

The draft of this report has been presented and discussed at the Technical Group on Morbidity in June 2013; the final version has been presented at the Working Group on Public Health Statistics (WGPH) in December 2013 which endorsed it.

The importance of having European statistics on diagnoses based morbidity

Eurostat activities in the domain of health status and health determinants are currently covered by three surveys: the five-yearly European health interview survey (EHIS); the newly established disability survey (European Health and Social Integration Survey - EHSIS), and a basic set of health-related questions that are included in the annual EU Survey on Income, Social Inclusion and Living Conditions (EU-SILC).

However, one core activity is missing: the regular collection of diagnosis-specific morbidity data with incidence and prevalence rates. A legal basis for such data collection is provided by Regulation 1338/2008 establishing a framework for Community statistics on public health and health and safety at work. That regulation foresees an implementation of morbidity statistics at EU level. The Community action Programme on Public Health 2008–13 and the Community Statistical Programme 2008–12 foresee the implementation of that Regulation as a key statistical element of a sustainable health monitoring system. In addition, the Commission Communication Solidarity in health (COM/2009/0567 final) also emphasises the importance of having Regulations developed in each domain of public health statistics.

The recent Commission staff working document Investing in health (complementing the Commission Communication ‘Towards Social Investment for Growth and Cohesion’, available as PDF), which is an accompanying document to the ‘Social Investment Package’, defines the role of health as part of the Europe 2020 policy framework and points out that an improvement in health data collection is needed, in particular in using the European Core Health Indicators (ECHI) and developing tools to better assess the efficiency of health systems. In addition, the statistical information on specific chronic diseases is a key component in underpinning and addressing policies to improve the labour market participation, risk of social exclusion and risk of poverty.

Eurostat’s commitment in developing the conceptual and methodological framework for establishing a data collection on morbidity dates back to the mid-nineties. Following the analysis of pilot studies in 16 Member States the report of the Eurostat Task Force on Morbidity (TF MORB) is now paving the way ahead to overcome the pioneering stage with a set of recommendations.

The feasibility of such statistics, in particular in view of using data from different sources, will be markedly enhanced by the current revision of the EU statistical law. It will be the legal basis to ensure and encourage a better use of existing sources by improving access to and exploitation of administrative data, e.g. by merging or linkages of the existing datasets.

The establishment of diagnosis-based morbidity statistics is crucial for filling an information gap on the health status of the EU population. Key elements of innovation for that approach are:

  • the best estimates from multiple sources that can be used (namely physicians issuing diagnoses/prescriptions or health records from registers, health institutions and insurances)
  • the possibility to compare best estimates on incidence and prevalence of diseases
  • the comprehensive coverage of morbidity data
  • the coverage of the whole population, by providing national estimates, and
  • diseases and conditions to be reported in terms of EU relevance and the Public Health perspective.

In 2007 Eurostat and Member States (MS) developed a methodology and a shortlist for collecting such data at EU level. It addresses diseases and conditions with major impact on health care and health-care related costs, annual death rates, or potential years of life lost. Examples range from heart/circulatory and respiratory diseases, cancer or metabolic diseases such as diabetes to mental diseases, injuries and their consequences and external causes. An attempt to highlight the main diseases for which morbidity statistics are needed is presented in the EU short list on morbidity, which has been followed throughout this pilot phase by the participating countries.

The actual lack of systematic and official data on morbidity has severely hampered the development of public health indicators at EU level which are required to support health policy makers.

Diagnoses-based morbidity statistics at EU level: a difficult exercise

For selected diseases the health status of the EU population is known thanks to diseases-registers, ad-hoc studies and as self-reported information from the EHIS or EU-SILC surveys. Currently, the principal and most reliable source for establishing and monitoring public health policies is information derived from Causes of Death statistics. While this type of source is well established and provides reliable and comparable public data collection for all EU countries, Cause of Death data does not provide information on incidence and prevalence of diseases and in particular lacks information on comorbidities that would be necessary for a comprehensive picture of public health.

A regular and systematic data collection and dissemination of statistics[2] on diagnoses-based morbidity does not exist either at EU or at global level[3]. The reason behind this is that from a methodological and operational point of view, the collection of morbidity statistics is an extremely complex exercise, in particular with regards to comparability of data across countries. Specific efforts will be required in each country to produce operational definitions of variables that are based on many different available sources. So far these difficulties have hampered attempts to establish a morbidity data collection based on (mainly) administrative data similar to those already existing for causes of death or for health care data based on hospital discharges.

The recent new release of the work on the Global burden of diseases is a tentative step towards filling in the existing information gap on health.

The demand for statistical data on diagnosis-based morbidity is increasing; however, the capability to respond to this increasing demand is constrained by limited data availability, quality, and use. A set of diagnoses-based morbidity indicators have been developed in the context of the ECHI (European Core Health Indicators[4]) list, but most of these indicators are not collected yet and the list is not exhaustive. It is therefore important to collect morbidity statistics in order to have these indicators thoroughly implemented both in terms of definition and data.[5]

The paradox for Europe is that while sometimes there is a wealth of information available for specific diseases; this information can often be scattered, sparse, not representative of the total population, not collected systematically and not addressing the multidimensional characteristics of health. And for many other diseases there are only scarce examples at national level. The result is:

  • a fragmented picture of the occurrence of diseases in the EU, often driven by the needs of single disease program or ad-hoc data collection;
  • information on incidence (or prevalence) only for those diseases where both indicators should be advisable;
  • an inefficient use of the available sources of collected information and allocated resources.

Lastly, it should not be forgotten that the legal framework for accessing and processing the available data from many different sources poses obstacles that need to be addressed and solved. The proposed revision of the statistical law (COM (2012) 0167) will allow Eurostat and the partner countries within the European Statistical System to use both their technical IT capabilities and the legal mandate for working towards this goal.

The pilot studies in 16 Member States (MS) that were analysed for this report have shown the feasibility of the proposed methodology for many of the 105 indicators (both for incidence and prevalence) included in the Eurostat Morbidity Short List.

Demands for diagnoses-specific morbidity in EU programmes on public health

The responsibility for the organisation and delivery of health services and healthcare is largely held by the Member States at national and sub-national level. However, the Commission is asked for actions whenever there is a need to complement Member States’ health policies, in particular in areas such as health promotion, prevention, research or dissemination of information by public health data collections within the ESS (European Statistical System).

The provision of statistics on public health is closely linked to the Community Action Programme in the field of public health 2008–2013, which covers health status including morbidity and is implementing the strategy ‘Together for health: a strategic approach for the EU 2008-2013’ (COM (2007) 630. The most relevant point addressing the importance of health data is the following: ‘… Finally, health policy must be based on the best scientific evidence derived from sound data and information, and relevant research. The Commission is in a unique position to assemble comparable data from the Member States and regions and must answer calls for better information and more transparent policy making, including through a system of indicators covering all levels (national and sub-national)’ (page 4).

In an ageing society diagnosis-specific morbidity statistics are of particular importance in view of addressing issues such as self-management of multi-morbidity and prevention of long-term care. Time-trends from morbidity statistics will be a major pillar to enhance information and knowledge as requested by the proposed Regulation for establishing a ‘Health for Growth’ Programme, the third multi-annual programme of EU action in the field of health for the period 2014–20 (17). In fact, in the objectives it is stated that ‘… the Programme will support actions on Health information and knowledge to contribute to evidence-based decision making, including collecting and analysing health data and wide-ranging dissemination of the results of the Programme’ (page 7).

The challenge of increasing costs of health in EU economic programme

A population in bad health status is likely to cause higher overall expenditure due to both direct and indirect costs linked to ill-health, such as more people partially or totally inactive during their productive working years, as well as a burden from unhealthy retired people.

Spending on health is not just a cost; it is an investment in order to reduce the burden from diagnosis- and treatment-related costs related to diseases and their derived limitations, impairments and disabilities. Some examples (although not exhaustive) are chronic diseases (diabetes, mental disorders, neurodegenerative conditions, coronary heart disease, cancers, etc...) or diseases impairing the productive years of younger people, such as injuries and their long-lasting consequences.

The recent report on ageing from Directorate General for Economic and Financial Affairs (DG ECFIN) clearly highlights the lack of comparable, quantifiable measures of health status (morbidity) required to evaluate the most likely possible scenario for estimating projections of health care costs in the EU. Providing that data on health expenditure are available, it is assumed that age/gender specific expenditure profiles provides a proxy for health status (i.e. morbidity). In other words, higher expenditure captures higher morbidity [6].

The ageing process in the EU is likely to raise demand for healthcare while also decreasing the working population. This could result in an increase in healthcare spending of 1 % to 2 % of GDP in Member States by 2050. On average this would amount to approximately a 25 % increase in healthcare spending as a share of GDP based on the present health expenditure which ranged from 6 to 12 per cent of GDP in 2009. However, Commission projections show that if people can remain healthy as they live longer, the rise in healthcare spending due to ageing would be halved.

On average across EU MS, health spending per capita increased by 4.6 % per year in real terms between 2000 and 2009, but this was followed by a reduction of 0.6 % in 2010, consequent to the current economic crisis (Figure 1)[7]. Given the significant reduction in health care expenditure in some European countries, the importance of morbidity statistics will be even greater for monitoring the resulting impact on Public Health.

On the other hand more effective prevention influences incidence and/or prevalence of diseases and thus has an impact on health expenditure. Following such developments of morbidity gives indications for expected impacts on health expenditure.


Figure 1: Annual average growth rate in per capita health expenditure, per capita, in real terms, 2000 to 2010 (or nearest year)

In terms of the potential impact of this changing scenario on the development of morbidity statistics, should the costs per capita reduction be confirmed for the next coming years, it could have impact on both the kind of sources to be identified and used for the data collection, with a possible shift from the public sector to the private sector, and of course in terms of changes in the incidence and prevalence of diseases. This illustrates the concept of ‘reverse causation’ meaning that morbidity estimates are not just a cause of expenditure, but also a result of it.

At present information on diagnoses-based incidence and prevalence of diseases to assess the burden at population level or on the cost of diseases to assess the burden on health systems is not yet available in the EU in the form of a harmonised, regular data collection that is capable of delivering this information as part of the disseminated EU official statistics. This information gap is likely to have negative drawbacks on the possibility of establishing effective EU policies for health and efficient allocation of resources, both at the level of the MS and at EU level. These two components of the overall picture on health should be equally developed, and the establishment of morbidity statistics is the first step to be made towards this direction.

An example of how the problem has been addressed at country level is provided by The Netherlands by a RIVM-analysis of the cost of illness conducted in cooperation with Statistics Netherlands. The main reasons for the increase in costs are:

  • 1. ageing of the population (explains about 15 % of the cost rise over the entire period 1999–2010);
  • 2. price inflation (explains about 35 %);
  • 3. interrelated set of causes such as policy changes, easier access to services, the growth of the number of patients treated, more intensive treatment and the implementation of new medical technology (explains about 50 %).

In spite of ageing, the largest increase in costs over 2005–2010 occurred in young people (ages 1–24). A higher use of youth care and a change in the rules for admittance to care for the people with disabilities explain this fast rise. Although women use more health care than men, since 2005 the costs increased faster for men than for women. This is partially due to improved male health: they live longer, and therefore use more health care, particularly at older ages.

Longer lives and Health in EU social programmes

Life expectancy at birth in the EU-28 increased over the last 50 years by about ten years due to several factors, including medical progress and improved hygiene, better living conditions and education and access to high quality health care. In 2012 life expectancy at 65 years of age in EU-28 is 19.6 (Figure 2).

Figure 2: Life expectancy in years at 65 years in the EU-28 countries (2012)

As a result, a significant proportion of the population reaches advanced ages, which is associated with a change in patterns of the diseases from infectious to non-communicable diseases. With respect to the notable gain in life years, a crucial question to be addressed is also how the life of EU population is spent in terms of health. To answer this fundamental question the healthy life years (HLY) indicator was included in 2005 as a Lisbon Structural Indicator, to underline that the population’s life expectancy in good health — not just length of life — was a key factor for economic growth. The increase by two years in the average of HLY in the EU population by 2020 is also one of the aims of the Commission pilot initiative ‘European Innovation Partnership on active and healthy ageing’.

The recent evidence (2007–2011) for HLY indicator shows that the number of healthy life years at birth slightly increased for men — from 61.7 to 61.8 — and decreased for women — from 62.6 to 62.2 years in the EU-27; this represents an average of 80.2 % and 75.4 % of total life expectancy at birth for men and women respectively. Not surprisingly, as life expectancy has still increased during this time, a similar reduction in the proportion of healthy life years occurred in both sexes in the three last years. In fact, for men the observed values range from 81.1 % in 2007 to 79.8 % in 2011 and for women from 76.2 % in 2007 to 74.8 % in 2011. Healthy life years have slightly increased in 2012 compared to 2010, and in 2012 were 61.3 for males and 61.9 for females (Figure 3). The actual data on HLY are derived yearly from EU-SILC, and this measure could be refined and/or complemented by using diagnoses based data, especially prevalence.

Figure 3: Healthy life years in absolute value at birth in EU-28 countries by sex (2012)

For survivors at the age of 65, the number of remaining healthy life years is 8.7 years for men and 8.8 years for women (Eurostat, Key figures on Europe, 2013). It is therefore crucial to know the incidence and prevalence of conditions such as ischemic heart diseases, cerebrovascular diseases, cancers, diabetes, and dementias, which are the largest proportion of causes of deaths after 65 years of age[8]. Diagnosis-based morbidity statistics at EU-level will be essential for delivering that information.

Quality of life and well-being in Commission context

In its Communication on ‘GDP and beyond: measuring progress in a changing world’ the Commission announced that it would work on developing indicators on ‘quality of life’ and this is also a recommendation that is part of the Stiglitz-Sen-Fitoussi Commission (SSFC) report:

'Recommendation 6: Quality of life depends on people’s objective conditions and capabilities. Steps should be taken to improve measures of people’s health, education, personal activities and environmental conditions…’ (Report by the Commission on the Measurement of Economic Performance and Social Progress JE Stiglitz, A Sen, JP Fitoussi.)

In the context of ‘quality of life’ indicators, health is indicated as one of the eight dimensions and within the dimension ‘health’ the emphasis is inter alia not only on physical health but — even more — on mental health.

At present indicators associated with mental health well-being derived from the Official Public Health statistics are death rate for suicides (population-based census), hospitalisation rates and self-reported depression (population-based survey). Undoubtedly these are insufficient indicators for providing a complete picture on such a complex and major health problem in the EU. It is therefore not surprising that the Commission requested that Eurostat address the following: ‘There is a need to improve the knowledge base on mental health: by collecting data on the state of mental health in the population’.

Gradually diagnosis based statistics should replace the self-reported data as sources for the health indicators for specific diseases.

Current data collections completing the information on Health in the EU

The results and indicators derived from some existing data collections would benefit from the extra dimension of diagnosis specific statistics.

Morbidity as perceived and reported by people

The current sources available at Eurostat for assessing self-perceived health are EU- SILC and EHIS. The information available from these sources will still be valuable even if and when the diagnoses-based morbidity statistics is established. The two aspects of measuring health as self-perceived or diagnosed by a professional should be seen as complementary to each other, which is in line with a modern approach of the social and economic role and integration of individuals as the main pillar of Social Statistics. However some well-known limitations of surveys restrict their scope and use. In particular:

  • 1. they miss acute serious illnesses with high fatality rate / low survival;
  • 2. sample sizes often do not allow for more precise estimation of prevalence by age groups (e.g. diabetes in younger age groups) as there are simply too few respondents with a given disease per age group – this is especially a problem in small countries where sample sizes are relatively small;
  • 3. non-response overall (and non-response increases) and biased responses;
  • 4. the financial cost and burden on respondents.

To overcome these limitations morbidity statistics will be comparatively cheap and will provide estimates based on the whole population. Morbidity information on individuals cannot therefore be represented only by ‘diagnoses’ or only by ‘perception’, but hopefully by the full integration of these two components, as the complete description of the status of health should include population based diagnosis, surveys and mortality by cause. Data from health interview surveys and diagnosis-specific morbidity data are therefore complementary sources: both are essential for evidence based policy making. This complementarity will have an invaluable impact on the data produced and their subsequent interpretation and use.

The comparisons between EHIS / MORB estimates have been included in the Annex 1, as part of the data received from the pilot countries (See PDF).

Addressing inequalities and access to health care for all the EU population

While the ageing EU population will require more and more health services, the younger population, especially children, consistently show a higher risk of poverty or social exclusion (Europe 2020 Headline indicator ‘People at risk of poverty or social exclusion’) (26.3 % in the EU-27, Eurostat estimation for the year 2011) compared to the elderly (19.9 % in the EU-27, Eurostat estimation for the year 2011)[9] (Figure 4) with remarkable differences among MS. The data shows that poverty is unevenly distributed, not only by educational level attained or income, but even across generations; this evidence must address the question of how health is accessed from and guaranteed to every segment of the EU population.

Figure 4: People at risk of poverty or social exclusion in the EU-27 by sex and age group, 2006-2012

Data from the 2011 EU-SILC survey shows that unmet needs for medical examination due to barriers to access (too expensive or too far to travel or waiting list) increases with age in the EU-27 and involve on average 3 % of the surveyed population (Figure 5). This percentage shows that contact with the health systems for medical examination is relatively guaranteed; however those below 18 years of age are not included in this analysis from EU-SILC survey.

Figure 5: Self-reported unmet needs for medical examination for reasons of barriers of access (too expensive or too far to travel or waiting list) in the EU-28 by age, 2011(%)

In the scenario where deprivation could increase, a comparison between the explicit demand and access to care will be particularly relevant. Therefore, the availability of more accurate and complete information about which major diseases affect the EU population is going to contribute to:

  • reducing the burden of specific conditions on the population,
  • strengthening those parts of the health systems where necessary (prevention, rehabilitation, etc.),
  • responding to major Public Health challenges (emerging diseases, etc.),
  • tackling inequalities in access to appropriate care for specific diseases (at EU global level, or sub-national-, gender-, education-, age- or income-based),
  • establishing and monitoring adequate actions and policies.

The information currently available on outcome, namely causes of death statistics, only highlight the ‘worst scenarios’ by producing figures on those who died from a certain condition.

There is a strong demand from within the Commission on having evidence where the morbidity statistics are going to be one of the building blocks, as in the case of the communication ‘Solidarity in Health’ where the need for more health data is clearly identified as one of the foreseen EU-level actions: ‘Support the further development and collection of data and health inequalities indicators by age, sex, socio-economic status and geographic dimension’ (page 6) (COM (2009) 567 final).

The importance of morbidity statistics in the International context

The Global Burden of disease 2010

The purpose of this paragraph is not to summarise the overwhelming amount of information that can be derived from this global, world-wide effort on health data, nor to compare the existing differences in estimates provided by the Global Burden of disease 2010 (GBD 2010) in comparison with institutions such as WHO, Eurostat or OECD.

The EU is in several cases in a privileged situation with respect to access to and availability of several of the health data presented by the GBD 2010 study. However, the huge contribution to highlighting the burden of disease for the population and for the national health systems has to be emphasised. In fact, some aspects relevant to the development of EU morbidity statistics should be taken into account from this study [10]:

  • the methods developed and used for measuring the burden of diseases and risk factor prevalence, estimation methods;
  • the efforts made on ensuring a certain level of comparability by involving a consistent number of researchers to estimate incidence and prevalence of diseases, (as well as causes of death, risk-factor exposure and attributable burden, and health life expectancy);
  • An innovative and comprehensive approach to cross-validation of data (mainly against evidence from mortality/causes of death), by including conditions leading to disabilities such as visual impairment, hearing loss and anaemia;
  • Comorbidities that were taken into account for the estimation of the years lived with disability (YLDs) indicator;
  • Quantification of uncertainties across all the components of the study, thus communicating to users the limitations of the estimates for different diseases, injuries and risk factors;
  • The commitment of 486 authors from 302 institutions in 50 countries who reviewed the final articles.

UN sustainable development goals

Building upon the Millennium Development Goals one of the main outcomes of the Rio+20 Conference in 2013 was the agreement to develop a set of Sustainable Development Goals (SDGs). Health is one of the topics that are addressed in the context of the post 2015 strategy. It has been discussed each year as a cross-cutting issue during each two-year cycle. This approach will of course need the availability of selected health indicators that can be used to monitor the specific goals in the social, environmental and economic domains.

The importance of morbidity statistics at National level

The above paragraphs highlighted the increasing demand and importance for having Morbidity Statistics established at EU level. However, the benefits for MS to collect and report a set of data that are comparable at EU level should not to be underestimated. On the one hand morbidity statistics at national level are cornerstones for monitoring and evaluation of morbidity developments in general and programmes in particular. On the other hand morbidity statistics that are comparable to other EU-28 are the basis for comprehensive planning of different nature, e.g. in view of monitoring specific health and welfare programmes as compared to other countries on needs of human and physical resources, insurance costs and expenditures for health care activities.

A specific example for the needs for internationally comparable morbidity data is represented by issues on cross-border health care provisions, an increasing phenomenon and burden in several MS, finally, the pilot studies showed that for several diseases coverage of the total of the population is far from being achieved in all MS. At the same time, some coverage by existing data is missing substantial numbers of cases, such as patients whose diseases are treated by general practitioners who are not part of the national data collection system. Such lack of information may distort the national estimates on the incidence and prevalence of diseases, as well as the sub-national and local allocation of resources.

Background to this report

This paragraph summarizes the development towards the development of morbidity statistics in Eurostat.

The Morbidity Statistics Development Group (MSDG) 2006–2007

Since the mid-90s the Commission (Eurostat and Directorate General SANCO (Health and Consumers) launched several activities aimed at establishing diagnosis-specific morbidity statistics at European level. Initiatives and projects are summarized in the final guidelines of the Morbidity Statistics Development Group (MSDG; see below).

Building on those activities carried out before 2006, the MSDG was set up in order to bring forward the methodological framework for diagnosis-specific morbidity statistics. The purpose of the MSDG [11] was to develop proposals, to produce implementation plans and to monitor the progress of an EU-wide system of disease-specific morbidity statistics to be built on the ‘matrix approach’ for a set of diseases, by identifying and using the best possible sources.

The MSDG revised the morbidity short list and produced guidelines (Annex 4) and recommendations for the piloting phase of the diagnoses-based morbidity data collection covering variables, sources, and methods of data collection (See PDF).

The pilot studies - characteristics of waves I (2005–2006) and II (2007, 2009)

Two waves of pilots have been carried out with common objectives as follows (see Annex 9 for the pilots’ technical descriptions)(See PDF):

a. Inventory of potential national sources for diagnosis-specific morbidity data: The aim of this part of the methodological approach was to identify and to describe and evaluate the potential main national sources for diagnosis-specific morbidity statistics.

b. Elaboration of a methodology for producing best national estimates on incidence and prevalence, according to the short list MORB: The emphasis was on providing the best national estimate through a well described and valid procedure.

c. Pilot data collection: The proposed methodology was subsequently tested by a pilot project, thereby avoiding any duplication of work with on-going data collections such as for infectious diseases and cancers.

The countries participating in the pilots were the following:

  • Wave I (2005–2006). In the context of the pilot projects on morbidity statistics funded by the Transition Facility Programme 2005, 9 MS — Cyprus, the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Malta, Slovenia and Slovakia — assessed the overall practicality and feasibility of the methodology proposed by the MSDG.
  • Wave II (2007, 2009). The projects covering years 2007-2009 involved Austria, Belgium (for a subset of the diseases included in the short list), Finland, Germany, Poland, The Netherlands, and Romania. The final reports from this second wave were completed and made available for analysis in 2011.

The Eurostat task force on morbidity statistics

From 2009 to 2011 Eurostat activities on morbidity stopped for about a year and half due to lack of resources. The activities were resumed in the second half of 2011 when the Task Force on Morbidity (TF MORB) was agreed at the Working Group on Public Health STatistics (WGPH) meeting.

The TF MORB [12] has assisted Eurostat in the preparation of a regular data collection on morbidity within the ESS, with focus on the revision and refinement of existing methodological tools. The goal of the earlier pilot studies was to test the MSDG methodology for accurate morbidity estimates at national level. The aim of the TF MORB has been to help Eurostat in assessing the quality and comparability of those estimates across the Member States, and to revise the methodology in the MSDG guidelines and the short list of conditions. The Task Force Terms of Reference are shown in Annex 5 (See PDF).

The TF MORB concluded its work on autumn 2013.

About this article

This article and the companion article Morbidity statistics methodology pilot studies - examples are extracted from the report on Morbidity Satistics in the EU as prepared by the Morbidity Task Force. The full report and annexes have been published on April 2014 in the Statistical Working papers collection.

  • The article Morbidity statistics methodology pilot studies - introduction (Chapter 1 in the report) is an overview of the current demand for health indicators in the context of the EU policies. Reasons on how the morbidity statistics will improve the different dimensions of health are provided as well. Besides these aspects, the steps and methods followed for establishing the routine data collection of morbidity statistics strand are provided.
  • The article Morbidity statistics methodology pilot studies - examples (Chapter 2 in the report)provides an overview of the main findings, problematic aspects and proposed solutions for moving towards a Eurostat morbidity data collection. In order to present the most relevant aspects in a readable format, it was decided to present some prototypal situations which the TF faced during the analysis of the sources and estimates in view of their accessibility, usefulness, overall quality and comparability. Case studies dealing with the quality of the identified sources and estimates are shown in the form of questions in order to make the report more readable.

See also

Further Eurostat information

Publications

Main tables

Health status (t_hlth_state)

Database

Health status (hlth_state)
Healthy Life Years (hlth_hly)
Self-perceived health and well-being (hlth_sph)
Self-reported chronic morbidity (hlth_srcm)

Dedicated section

Methodology / Metadata

Other information

  • Regulation 2008/1338 of 16 December 2008 on Community statistics on public health and health and safety at work

External links

Notes

  1. Authors and members of the Task Force ‘Morbidity’: Monica Pace (Eurostat, Directorate Social statistics and Seconded National Expert from the Italian National Institute of Statistics), Hartmut Buchow (Eurostat, Directorate Social statistics), Margarida Domingues de Carvalho (Eurostat, Directorate Social statistics), Willem Aelvoet (Belgian Federal Public Service Health), Jacques Bonte (Private Expert), Gráinne Cosgrove (Irish Department of Health), Rita Gaidelyte (Lithuanian Institute of Hygiene), Mika Gissler (Finnish National Institute for Health and Welfare), Georgeta-Marinela Istrate (Romania National Institute for Statistics), Merike Rätsep (Estonian National Institute for Health Development), Ieva Strele (Riga Stradins University, Riga, Latvia), Bogdan Wojtyniak (National Institute of Public Health-National Institute of Hygiene, Warsaw, Poland).Former members of the Task Force ‘Morbidity’: Prof. Howard Meltzer (Department of Health Sciences College of Medicine, Biological Sciences and Psychology University of Leicester, UK (member until September 2012)), Anne Fagot-Campagna (French Institute for Health Surveillance (member until March 2012)), Jean-Marc Schaeffer (Eurostat, Directorate ‘Social Statistics’ (member until April 2012).).
  2. The definition of European statistics is according to Article 2 (2) of the Commission Decision 2012/504/EU of 17 September 2012 on Eurostat.
  3. Chan M, Kazatchkine M, Lob-Levyt J, et al. Meeting the demands for results and accountability: a call for action on health data from eight health agencies. PLoS Med 2010; 7: e100023.
  4. Previously ‘European Community Health Indicators’.
  5. ECHI indicators relevant for diagnoses-based morbidity statistics are: No 20. Cancer incidence; No 21(b). Diabetes: register-based prevalence; No 22. Dementia; No 23(b). Depression: register-based prevalence; No 24. Acute myocardial infarction (AMI); No 25. Stroke; No 26(b). Asthma: register-based prevalence; No 27(b). Chronic obstructive pulmonary disease (COPD): register-based prevalence.
  6. The 2012 Ageing Report: Underlying Assumptions and Projection Methodologies European Economy 4|2011. (DG ECFIN) http://ec.europa.eu/economy_finance/publications/european_economy/2011/pdf/ee-2011-4_en.pdf.
  7. OECD (2012), Health at a Glance: Europe 2012, OECD Publishing. http://dx.doi.org/10.1787/9789264183896-en.
  8. Circulatory diseases – Main causes of death for persons aged 65 and more in Europe, 2009 – Issue number 7/2012 Statistics in focus, Eurostat.
  9. Emilio Di Meglio, Eurostat. Commission en Direct 652, page 4, 23.11-29.11.2012
  10. GBD 2010: a multi-investigator collaboration for global comparative descriptive epidemiology. Murray CJL, Lopez AD, et al. Lancet 2012; 380:2055-2058.
  11. Participants to the MSDG were: Roberta Crialesi (Italy), Liis Rooväli (Estonia), Jacques Bonte (Belgium), Howard Meltzer (United Kingdom), Björn Smedby (Sweden), Sabine Gagel (Eurostat), Marleen De Smedt (Eurostat).
  12. Members of the Eurostat task force on morbidity were: Willem Aelvoet (BE), Merike Rätsep (EE), Mika Gissler (FI), Anne Fagot-Campagna (FR,until March 2012), Gráinne Cosgrove (IE), Rita Gaidelyte (LT), Ieva Strele (LV), Bogdan Wojtyniak (PL), Georgeta-Marinela Istrate (RO), Howard Meltzer (UK, until September 2012), Jacques Bonte (private expert, from October 2012), Hartmut Buchow (ESTAT), Monica Pace (ESTAT), Jean-Marc Schaefer (ESTAT, until April 2012), Margarida Domingues de Carvalho (ESTAT, from August 2012).