Final Report Part III ECHIM Pilot Data Collection Analyses and Dissemination

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So the entire quest was depending on the ability and commitment of the Joint Action partner countries and their National Implementation Teams (further details see Report I). The WP 5 study secretariat kept to extensive email and telephone communications with national contact points and individual data holders, respectively. This included both further instructions in response to comprehension- related enquiries from participating countries’ contact points / data holders and attempts to sustain contacts in order to maintain the study compliance. The latter was successful for a number of partner countries, even if they were only able to deliver a few indicator data or fewer stratums than defined by ECHI definitions. Once a personal contact was established, it proved to raise and keep commitment by the partners. Ultimately, this approach completed the picture on data types and sources availability at national level. In the course of the collection period several Joint Action partners reported on serious difficulties to deliver the requested data. Hence, for one reason or another ECHIM WP 5 extended the deadline for redelivery of questionnaires but obtained no pilot data at all from nine countries (BG, GR, LU, PT, SE, SI, SK, HR and TR). On the other hand, the majority of Joint Action partner countries redelivered the questionnaire (N = 25, response rate = 73.5%) and the related metadata file. A comprehensive indicator-per-country response overview is presented in Annex I of this report. Main outcomes: The ECHI Pilot Collection was a first-time-exercise for all partner countries involved beside the established statistical reporting schemes to DG Eurostat, WHO or OECD. It represented the first pan-European gathering of health indicators according to ECHI- definitions and yielded more recent estimates derived from population based interview surveys. The Pilot Collection revealed that the majority of participating partner countries keep national (survey) data that could build the fundament for an ECHI- based health reporting system. However, the results of this Pilot Study yielded indicator data of a varying extend of completeness and ECHI- conform breakdowns, respectively. Both attempts to collect prevalence percentages on alcohol and tobacco pattern of consumption proved insufficient in order to compute ECHI#15 (smoking-attributable deaths) and ECHI# 16 (alcohol-attributable deaths). Beside the fact that surveys on alcohol consumption are prone to a larger social desirability bias (underreporting), the alcohol module of EHIS first wave proved unsuitable to assess the daily mean pure ethanol intake [in 7
grams] which is required for collating the four WHO drinking categories 9 . The data obtained were assessed as too underestimated figures if roughly compared with alcohol production and sale figures, and expert reports 10 , too. Regarding ECHI#15 (smoking-attributable deaths), several Pilot Collection countries as well as the central EHIS computations of DG Eurostat delivered too many statistical uncertain prevalence data for former and non/never- smokers. The latter represent the reference group for the relative risk (RR) calculation of ECHI#15 (see: Report II: Part II. ECHI indicator documentation, chapter 15.) In the course of the collection period several Joint Action partners reported on serious difficulties to deliver the indicator data in its requested form. Main factors to mention are shortage of manpower at national statistical offices or public health institutes, lack of institutional and / or political commitment, shift of personnel, and cumbersome fragmentation of data sources. Several countries, in particular in Eastern Europe, have no consistent system of health monitoring and reporting or are in a transitional phase in order to build such structures, which included the lack of appropriate registers. Generally, the collection of administrative/ register- based indicator data was less successful than initially expected. Often countries either maintain available morbidity registers and keep no corresponding survey data or vice versa. Additionally, the 'quality’ of registers depends strongly on proper IDC-9/10 coding practice (sometimes also matching with causes of death tables) and a sufficient coverage of the national population. The lack of SES information is register inherent (also stratification to age bands is not granted) and was therefore expected in advance. Except for ECHI#24 AMI and #25 Stroke attack rates the registers of morbidity and healthcare utilisation predominantly keep data on total numbers and often only differentiated by sex but not stratified by age groups according to ECHI. Additionally, the register-based indicator values for ECHI should be reported as age-standardised (WHO-EU 1976 population), while the EHIS data are not standardised but should gain population 9 Comparative Quantification of Health Risks, Vol. 1, Chapter 12: Alcohol Use, pp. 968, Nonserial Publication, WHO (2004); http://www.who.int/publications/cra/chapters/volume1/0959-1108.pdf (lastly accessed on June 05 2012) 10 WHO Expert Committee on Problems related to Alcohol Consumption, Technical Report Series, No. 944, WHO Geneva (2007); http://www.who.int/substance_abuse/expert_committee_alcohol_trs944.pdf (lastly accessed on June 05 2012) 8
Page 2 and 3: Joint Action for European Community
Page 4 and 5: 1. New ECHI data: ECHIM Pilot Data
Page 6 and 7: DG Health & Consumers and DG EMPL n
Page 8 and 9: In addition to survey-derived indic
Page 12 and 13: epresentativeness through the sampl
Page 14 and 15: 1.3.1. ECHI# 21 Diabetes ECHIM Indi
Page 16 and 17: Fig.1.3.1.2 Diabetes by educational
Page 18 and 19: Fig.1.3.1.3 Correlation between BMI
Page 20 and 21: This phenomenon might be explainabl
Page 22 and 23: B Table 1.3.2 Fig. 1.3.2.1 DATA PRE
Page 24 and 25: C DATA ANALYSIS Overall depression
Page 26 and 27: months. A glance at the ICD-10 cata
Page 28 and 29: 1.3.3. ECHI# 24 Acute Myocardial In
Page 30 and 31: C DATA ANALYSIS A high percentage o
Page 32 and 33: Fig.1.3.3.2 Compatibility of submit
Page 34 and 35: Fig. 1.3.3.3 Differences in mortali
Page 38 and 39: The submitted stroke attack rates i
Page 40 and 41: Fig.1.3.4.3 Differences in mortalit
Page 42 and 43: 1.3.5. ECHI# 26 Asthma ECHIM Indica
Page 44 and 45: Fig.1.3.5.2 Asthma by educational l
Page 46 and 47: For ECHI#26, it was not differentia
Page 48 and 49: [2] ERS European Lung White Book- S
Page 52 and 53: C DATA ANALYSIS Overall COPD preval
Page 54 and 55: Administratively deduced and/or reg
Page 56 and 57: 1.3.7. ECHI# 29 A-1 Injuries: home,
Page 58 and 59: Fig. 1.3.7.2 Injuries at home, leis
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Compared to the EHIS, in Switzerlan
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1.3.8. ECHI# 29 A-2 Injuries: home,
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Fig. 1.3.8.2 Injuries at home, leis
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accidents in separate categories an
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B Table 1.3.9 Fig. 1.3.9.1 DATA PRE
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C DATA ANALYSIS The 16-country aver
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1.3.10. ECHI# 30 A-2 Injuries: road
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Fig. 1.3.10.2 Road traffic injuries
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The EHIS questions on “road traff
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B Table 1.3.11 Fig. 1.3.11.1 DATA P
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The non-fatal injury statistic of t
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C DATA ANALYSIS In the adult popula
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1.3.13. ECHI# 43 Blood pressure ECH
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Fig. 1.3.13.2 Prevalence of high bl
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D REMARKS AND FURTHER INFORMATION A
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C DATA ANALYSIS The percentage of r
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population. Information on effectiv
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C DATA ANALYSIS In the adult popula
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1.3.16. ECHI# 50 Consumption of veg
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Fig. 1.3.16.2 Daily consumption of
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The Irish data were extracted from
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C DATA ANALYSIS Overall influenza u
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for all people at high risk defined
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The lower figures reported from eas
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General remark on the preferred dat
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1.3.20. ECHI Indicator Data Sheet #
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Fig. 1.3.20.2 Colon cancer screenin
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[3] Eurostat database, see (http://
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C DATA ANALYSIS In a cross-country
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Further data were delivered by Icel
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1.3.22. ECHI# 72-1 Selected outpati
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Fig. 1.3.22.2 Mean number of self-r
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NB: The data from Finland originate
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Fig. 1.3.22.3 Administratively dedu
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Fig. 1.3.23.2 Mean number of self-r
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NB: The German data are the most re
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Fig. 1.3.24.2 Proportion of populat
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[1a+b] EHIS description http://circ
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Possible solutions and appropriate
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Table 2.1 Data sources for the ECHI
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Table 2.1 (continued) Data sources
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Table 2.1. (continued) Data sources
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2.1 Presentation of the ECHI shortl
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2.2 Content of the HEIDI data tool
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3. Lessons learned, Conclusions and
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4. Acknowledgement This work was en
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ECHI# 29 (A) 29 (B) 30 (A) 30 (B) 4
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Annex II EHIS data collection: Surv
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Annex III Data tables of indicators
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1.3.3 Data Table ECHI#24 Acute myoc
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1.3.5 Data Table ECHI#26 Asthma "Pr
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1.3.7 Data Table ECHI#29 (A) -1 Inj
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1.3.9 Data Table ECHI#30 (A)-1 Inju
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1.3.11 Data Table ECHI#30 (B) Injur
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1.3.13 Data Table ECHI#43 Blood Pre
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1.3.15 Data Table ECHI#49 Consumpti
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1.3.17 Data Table ECHI#57 Influenza
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1.3.19 Data Table ECHI#59 Cervical
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1.3.21 Data Table ECHI#71 General p
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1.3.23 Data Table ECHI#72-2 Selecte
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Annex IV List of Abbreviations Abbr
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