1. Population-based Registers in Europe: results from the EUROCISS Project Agreement n° 2003118 Simona Giampaoli Istituto Superiore di Sanità, Rome, Italy 5° Meeting of the Task Force on Major and Chronic Diseases Luxembourg, 19 June 2007 Cardiovascular Indicators Surveillance Set

2. Participating countries K. Steinbach BELGIUM M the NETHERLANDS S. Graff-Iversen P. Primatesta AUSTRIA M. Kornitzer DENMARKM. Madsen FINLANDV. Salomaa franceS. Paterniti GERMANY A. Doring ITALY S. Giampaoli, L. Palmieri, S. Panico, F. Seccareccia, D. Vanuzzo ICELAND V. Gudnason GREECE A. Trichopoulou M. Verschuren NORWAYPOLAND A. Pajak PORTUGAL E. Rocha SPAINS. SansSWEDENN. HammarUKP. PrimatestaEUROPEAN HEART NETWORK AUSTRIAK. Steinbach – Austrian Hearth Foundation, Wien BELGIUMM. Kornitzer – School of Public Health, Bruxelles CZECH REPUBLICJ. Holub – Institute of Health Information and Statistics, Praha DENMARKM. Madsen – National Institute of Public Health, Copenhagen FINLANDV. Salomaa – National Public Health Institute, Helsinki FRANCEJ. Bloch – Institut de Veille Sanitarie, Saint Maurice GERMANYA. Doering – Insitute für Epidemiologie GSF, Neuherberg HUNGARYR. Adany – School of Public Health, Debrecen ITALY (coordinator)S. Giampaoli, L. Palmieri, P. Ciccarelli, S. Panico, D. Vanuzzo, Rome ICELANDV. Gudnason – Iceland Heart Association, Kopavogur GREECEA. Trichopoulou – School of Medicine, Athens The NETHERLANDSM. Verschuren – National Institute of Public Health and Environment, Bilthoven NORWAYS. Graff-Iversen – Norvegian Insitute of Public Health, Oslo POLANDA. Pajak – Institut of Public Health, Krakow PORTUGALE. Rocha – Insituto de medicina Preventiva, Lisbon SPAINS. Sans – Institut d'Estudis de la Salut, Barcelona SWEDENN. Hammar – Karolinska Institute, Stockholm UKP. Primatesta – Univ. College London Medical School, London EUROPEAN HEART NETWORKS. Allender – University of Oxford, Oxford

4. Main objectives To prioritise cardiovascular disease of major interest in EU countries To provide a list of recommended indicators and sources of information for monitoring CVD To prepare the Manual of Operations for the implementation of population-based registers of acute myocardial infarction/acute coronary syndrome, stroke and of CVD surveys

5. Tools for monitoring cardiovascular disease Type of registers/health surveys Data sourcesData collectionIndicators Specific disease registers Mortality HDR GP Records fatal and non fatal events in and outside hospital by hot/cold pursuit Attack rate Incidence rate Prevalence Case fatality rate Treatment Years of life lived with disability (YLDS) Estimate of long-term care needs Registers based on routine administrative data Mortality registers HDR Drug-dispensing registers HDR and mortality data unlinked with or without validation Mortality Hospitalisation Length of stay HDR and mortality data linked with or without sample validation Attack rate Case fatality rate Surveys Health interview and/or health examination Questionnaire and medical examination of population samples Prevalence Risk factors

6. NATIONAL AMI/ACS and STROKE Population-based Registers: population characteristics and case definition CountryAge range Population (x 1000) ICD version Mortality ICD codes (*) HDR ICD codes (*) Mortality ICD codes (+) HDS ICD codes (+) AMI/ACSSTROKE DenmarkAll5,411 X 410-414, 798 410, 411, PTCA, CABG 430-438 FinlandAll5,200X 410-414, 428, 798, 799 410-414, 428, PTCA, CABG 430-438 Iceland25-74170IX, X 410-414, 428, 798, 799 410-412, 414, PTCA, CABG SwedenAll9,011X410 430-434, 436-438 430-438 (*) all codes are presented in the ICD-9 revision to facilitate the comparison The EUROCISS Working Group. European J of Public Health 2003; 13 (Suppl 3): 55-60.

7. CountryICD version Mortality ICD codes(*) HDR ICD codes(*) Linkage Mortality / HDR Validation BelgiumIX, X 410-414, 428, 798, 799 410-414, 428 PTCA, CABG Name, date of birth ECG, enzymes, symptoms, MONICA Northern DenmarkX410 PIN- FinlandX 410, 411, 428, 798, 799 410, 411 PTCA, CABG PIN- FranceIX, X 410-414, 428, 798, 799, others 410-414, 428Name, date of birthMONICA GermanyX410-414, 798, 799 410, 411 PTCA, CABG Name, date of birthMONICA, ESC/ACC ItalyIX 410-414, 798, 799, others 410-414Name, date of birthMONICA NorwayX410 PTCA, CABG PIN- SpainIX 410-414, 428, 798, 799 410-414Name, date of birthMONICA Northern Sweden – MONICA X410, 411 PINMONICA (*) all codes are presented in the ICD-9 revision to facilitate the comparison REGIONAL AMI/ACS Population–based Registers: case definition The EUROCISS Working Group. European J of Public Health 2003; 13 (Suppl 3): 55-60.

8. CountryICD version Mortality ICD codes HDR ICD codes Linkage Mortality / HDR Validation FinlandX430-432, 435, 436 PINMONICA FranceX430-438, 442.81 Name, date of birth WHO clinical criteria, CT-Scan or MRI GermanyX430-438 Name, date of birth CT-Scan, Health Insurance Italy MONICAIX430-434, 436-438 Name, date of birthMONICA NorwayX430-438 PINMONICA Sweden MONICA X430-438, 798, 799430-438PINMONICA REGIONAL Stroke Population–based Registers: case definition (*) all codes are presented in the ICD-9 revision to facilitate the comparison The EUROCISS Working Group. European J of Public Health 2003; 13 (Suppl 3): 55-60.

9. ECHIM shortlist Suggestions from the EUROCISS Project - Attack rate as the most informative source of information for acute coronary and cerebrovascular events (it includes in- and out-of- hospital fatal and non-fatal first and recurrent events): data can be obtained through the population-based registers - Prevalence of ischemic heart disease and cerebrovascular accidents: data can be obtained through HIS/HES

10. ECHIM shortlist Suggestions from the EUROCISS Project The manuals of operations produced by the EUROCISS Project describe the core indicators recommended by the Project and provide a simple guide and updated methods to support those EU countries lacking an appropriate cardiovascular surveillance systems but willing to implement a population-based register

11. AMI/ACS and Stroke Population-based Registers - Manuals of Operations Objectives monitoring disease occurrence (attack and incidence rates) understanding differences between genders, age groups, social classes, ethnic groups, etc. identifying vulnerable groups monitoring in- and out-of-hospital case fatality monitoring the consequences of disease in terms of treatment and rehabilitation tracing the utilization and impact of new diagnostic tools and treatments

12. AMI/ACS and Stroke Population-based Registers – Manuals of Operations Target population men and women aged 35-74 years well defined geographical area vital statistics routinely collected and easily available each year Completeness and representativeness Minimum of 300 fatal events every year

13. AMI/ACS and Stroke Population-based Registers – Manuals of Operations Data sources Minimum sources of information required: mortality record with causes of death hospitalised discharge records with clinical information from cardiology, heart surgery, intensive care, medical, rehabilitation, neurological/neurosurgical, stroke, other (e.g. radiology) units nursing home and clinic autopsy register emergency and ambulance service (General Practitioner)

14. AMI/ACS and Stroke Population-based Registers – Manuals of Operations Onset and survival First ever or recurrent event, with non-fatal and fatal outcome: first ever event refers to people who have never had an event before recurrent event: for a new episode occurring after 28 days from onset. Onset is day 1 Non-fatal event: refers to patients surviving at least 28 days after the symptoms onset Fatal event: refers to an event causing death within 28 days of symptoms onset

15. AMI/ACS and Stroke Population-based Registers – Manuals of Operations Identification of events Fatal events include: ICD9 codes 410-414 (ICD10: I20-I25) as underlying cause of death Non-fatal events include: ICD9 codes 410-411 (ICD10: I20.0, I21-I22) as primary or secondary hospital discharge diagnosis Fatal events include: ICD-9 430, 431, 432, 434, 436 (ICD-10 I60, I61, I62, I64) as underlying cause of death Non-fatal events include the same codes as primary or secondary hospital discharge diagnosis AMI/ACS STROKE

16. AMI/ACS and Stroke Population-based Registers – Manuals of Operations Identification of events Record linkage between mortality and hospital discharge records: manual deterministic probabilistic Hot and cold pursuit approaches for detecting in- hospital events

17. AMI/ACS and Stroke Population-based Registers – Manuals of Operations Quality control Quality control is extremely important for a valid monitoring and comparison and depends: completeness of cases [out of area event] completeness of information

18. AMI/ACS and Stroke Population-based Registers – Manuals of Operations Validation provides the means to: take into account bias from diagnostic practices and changes in coding systems trace the impact of new diagnostic tools and re-definition of events ensure data comparability within the register (i.e. different sub- populations, different time points, etc) ensure data comparability with other registers within and between countries

19. AMI/ACS and Stroke Population-based Registers – Manuals of Operations Internal Validity Validation evaluates the sensitivity, specificity and predictive value of the registered diagnosis compared to a golden standard To validate coronary events, the MONICA diagnostic criteria or the New Criteria of the Joint ESC/ACC may be applied as golden standard To validate stroke, MONICA criteria may be applied as golden standard

20. AMI/ACS and Stroke Population-based Registers – Manuals of Operations External Validity All events occurring in the target population must be registered It is important to know how representative the register is for the whole country according to: Ischemic heart disease mortality rate distribution of risk factors (socioeconomic status and health behaviour) distribution of health service (specialized hospitals, GPs)

21. EUROCISS recommends Population-based Registers STEPWISE Procedure STEP 1, Target population and routine data: select a geographical administrative area (e.g. with a stable population big enough to collect more than 300 events for ICD-9 410-414 in the age range 35-74), check the availability of hospital discharge records and death certificates with underlying and secondary causes of death, identify problems with these data STEP 2, Pilot study and validation of routine data: estimate coverage, validate discharge diagnoses and mortality causes, analyze demography and representativeness STEP 3, Record linkage: explore the feasibility of record linkage a) within Hospital Records, b) between Hospital Records and Mortality Register, c) with other sources of information (GPs) STEP 4, Set up a population-based register STEP 5, Analyse and disseminate the data from the register

22. Stepwise procedure for HIS/HES CVD Surveys – Manuals of Operations

23. Conclusions CVD are responsible of a great number of hospitalisation and deaths Many sources of information must be integrated, including population-based registers and HIS/HES A surveillance system based on the collection of comparable and valid data is essential for evaluating the burden of CVD, time trends and geographical distribution and for planning and implementing appropriate preventive actions http://www.cuore.iss.it/eurociss/en/progetto/progetto.asp