Causes of death (hlth_cdeath)

National Reference Metadata in Single Integrated Metadata Structure (SIMS)

Compiling agency: Centre d'épidémiologie sur les causes médicales de décès (CépiDc)- Institut National de la Santé et de la Recherche Médicale (Inserm)  


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)
 



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1. Contact Top
1.1. Contact organisation
Centre d'épidémiologie sur les causes médicales de décès (CépiDc)- Institut National de la Santé et de la Recherche Médicale (Inserm)
 
1.2. Contact organisation unit

US 10 - Centre d'épidémiologie sur les causes médicales de décès (CépiDc).

1.5. Contact mail address


2. Metadata update Top
2.1. Metadata last certified 09/01/2024
2.2. Metadata last posted 21/12/2023
2.3. Metadata last update 21/12/2023


3. Statistical presentation Top
3.1. Data description

Data on causes of death (CoD) provide information on mortality patterns and form a major element of public health information.

CoD data refer to the underlying cause of death (UCD) which is defined by the World Health Organisation (WHO) as "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury".

CoD data are derived from death certificates. The information provided in the medical death certificate is mapped to the International Statistical Classification of Diseases and Related Health Problems (ICD).

3.2. Classification system

Country codes used for place of occurence and place of residence are two-letter codes (alpha-2) from the International Standard for country codes and codes for their subdivisions, ISO 3166 in effect during the year of death.

The regional breakdown is based on the NUTS 2 codes from the 2016 version of the Nomenclature of Territorial Units for Statistics (NUTS), see Commission Regulation (EU) 2016/2066.

France's CoD statistics is build on standards set out by the World Health Organisation (WHO) in the International Statistical Classification of Diseases and Related Health Problems (ICD).

Classification and updates applied by years :

Data year

ICD classification used (ICD-9, ICD-10) (3 or 4 chars)

For ICD-10: updates used

2011

 ICD-10 4 characters

 2011

2012

 ICD-10 4 characters

 2012

2013

 ICD-10 4 characters

 2013

2014

 ICD-10 4 characters

 2014

2015

 ICD-10 4 characters

 2015

2016

 ICD-10 4 characters

 2016

2017

 ICD-10 4 characters

 2016

2018

ICD-10 4 characters

2016

2019

ICD-10 4 characters

2019

2020

ICD-10 4 characters

2019

2021

ICD-10 4 characters

2019

3.3. Coverage - sector

Public Health

3.4. Statistical concepts and definitions

Concepts and definitions follow the Commission regulation (EU) No 328/2011 in articles 2 and 3.

3.4.1. National definition used for usual residency

Place of residence as declared on the death certificate.

According to the instructions in section 3, subsection 6 of the General Instruction on Civil Status of 11 May 1999 (Annex) given to the civil servants in charge of drawing up acts of civil status, the place of residence declared on the death certificate is "the place where one has the center of one's interests, business, and relations". This definition may differ, in certain cases of dual residence, from that of "habitual residence", but it is consistent with the one used by France to establish its death statistics.

3.4.2. Stillbirth definition and characteristics collected

The French death certificate does not apply to stillbirths.
Stillbirths information is collected from the « programme médicalisé des systèmes d’information » (PMSI) by the Directorate of Research, Study, Evaluation and Statistics (DREES) Population health office depending on the Health Ministry.

All stillbirths with weight births over 500 grams or with gestational ages of at least 22 weeks are collected.
The terminations of pregnancy are included from 22 weeks (gestational age) onwards.

Agregated data on stillbirths provide information on :

  • country/region of residence
  • country/region of occurrence
  • year and month of occurrence
  • sex
  • gestational age
  • mother age
  • cause of death


Causes of deaths are provided using the "P95" and "P964" codes from the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10).

3.5. Statistical unit

Statistical units are deceased persons and stillborns.

3.6. Statistical population

Residents and non-residents who died in France NUTS FR (see 3.7 for geographical scope).

3.6.1. Neonates of non-resident mothers

Neonates death certificates of non resident mothers are included.

3.6.2. Non-residents

Non resident population is included.

3.6.3. Residents dying abroad

Residents dying abroad are not included.

3.7. Reference area

All French NUTS2, including Metropolitan France and overseas departments and regions (la Guadeloupe, la Martinique, la Guyane, la Réunion, Mayotte) + Saint-Martin, according to the French geographical nomenclature as of January 1st of the year of death established by the French National Institute of Statistics (Insee) : https://www.insee.fr/fr/information/2666684#titre-bloc-23

Deaths occuring in other overseas areas (i.e. overseas collectivities) or abroad are not included, except for Saint-Martin, which is included in NUTS 2 (FRY1)

3.8. Coverage - Time

yearly from 2011 (included) onwards.

3.9. Base period

Not applicable.


4. Unit of measure Top

Unit is number


5. Reference Period Top

Data refer to the calendar year (i.e. all deaths occurring during the year).


6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

French law Article L2223-42 of the "Code général des collectivités territoriales" mandates Inserm- CépiDc as in charge of the establishment of causes of death (CoD) national statistics in France.

The Regulation on Community statistics on public health and health and safety at work (EC) No 1338/2008 and the Regulation on Community statistics on public health and health and safety at work, as regards statistics on causes of death (EU) No 328/2011 apply.

CoD data according to these regulations is submitted to Eurostat since reference year 2011.

6.2. Institutional Mandate - data sharing

According to the French Law Article L2223-42 of the "Code général des collectivités territoriales",

CoD data can only be used for public health purposes :

1. For monitoring and warning purposes, by the State, the regional health agencies (ARS) and the national public health agency (Santé publique France)
2. For the production of the national cause of death statistics and for public health research, by the National Institute of Health and Medical Research (Inserm)
3. For the processing of data relative to health, under the conditions set out in Article L1461-3 of the Public Health Code
4. For inclusion into the National Health Data System (SNDS) defined in Article L1461-1 of the same Code
5. For the production of statistics within the framework of the Article 7 bis of the law n° 51-711 from 7 june 1951 on the obligation, the coordination, the statistical secrecy, by the National Institute of Statistics and Economic Studies (Insee), or by the statistical services of the Minister of Health (DREES). These datasets must be kept separatly from the National register for the identification of individuals data owned by the National Institute of Statistics and Economic Studies (Insee)


7. Confidentiality Top
7.1. Confidentiality - policy

Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.

At the national level, Article L1461-3 of the Public Health Code sets out the legal framework which prevents unauthorised disclosure of data that re-identifies a person directly or indirectly within the National Health Data System (SNDS), which includes cause of death data produced by Inserm-CépiDc. The processing of data concerning health mentioned in 1° of I of Article L1461-3 of the Public Health Code shall be authorised in accordance with the procedures defined in Section 3 of Chapter III of Title II of the Act No. 78-17 of 6 January 1978 on Information Technology, Files and Freedoms.

According to Article L1461-1 of the Public Health Code, the persons responsible for processing personal health data from the National Health Data System, as well as those implementing it or authorised to access the personal data resulting from it, shall be subject to professional secrecy under the conditions and under the penalties laid down in Article 226-13 of the Penal Code which states that the disclosure of secret information by a person who is in possession of it either by virtue of his or her status or profession, or by virtue of an office or temporary assignment, is punishable by one year's imprisonment and a fine of 15 000 euros.

The French Council of State decree referred to in Article L1461-7 of the Public Health Code draws up the list of State services, public establishments or bodies entrusted with a public service mission authorised to process personal data from the National Health Data System (SNDS) for the purposes of their missions

7.2. Confidentiality - data treatment

All age groups showing a total mortality of less than 5 cases are considered as confidential. Therefore, any 'confidential' agegroup is grouped with another one to have higher numbers. In practice, this problem mainly occurs for young ages so, either the ages from 0 to 14 years old, or the ages from 0 to 14 and 15 to 24 years old are grouped. The age groups considered as confidential show then the value ':' and the age group '0-14y' (and '15-24y' if needed) shows the sum of all ages before 15 years old (or between 15 and 24 years old). In addition, special measures for ensuring confidentiality may be taken for small countries.
For neonatal figures, no breakdown by parity is displayed to ensure confidentiality.


8. Release policy Top
8.1. Release calendar

Following Regulation (EC) No 328/2011, Inserm-CépiDc has to send data to Eurostat at the latest 24 months after the end of the year of death. National releases follow as soon as possible.

8.2. Release calendar access

Release calendar information is displayed on the the Inserm-CépiDc website, together with major recent CoD trends https://www.cepidc.inserm.fr/donnees-et-publications/grandes-causes-de-deces-en-2021-et-tendances-recentes

8.3. Release policy - user access

Data are released on the website of CepiDc, freely accessible.


9. Frequency of dissemination Top

Annual.


10. Accessibility and clarity Top

News release (not systematic) and publications.

10.1. Dissemination format - News release

The dissemination of the 2021 cause of death data, on December 19th 2023, was accompanied by two publications and a news release. This mirror the approach taken in 2020, where the cause of death data was also disclosed with a new release and two accompanied publications. 

All the relevant news releases and publications can be accessed on the CepiDc website.

 

10.2. Dissemination format - Publications

On-line publications on our website. http://www.cepidc.inserm.fr/

For 2021, data was accompanied by two publications:

Fouillet A, Ghosn W, Rivera C, Clanché F, Coudin É. Grandes causes de mortalité en France en 2021 et tendances récentes. Bull Épidémiol Hebd. 2023;(26):554-69.

Cadillac M, Clanché F, Coudin E, Fouillet A, Riviera C. Les grandes causes de décès en France en 2021 : une année encore fortement impactée par le Covid-19. Études et Résultats. 2023;(1288)

 

For 2020, 

- Fouillet A, Ghosn W, Naouri D, Coudin E. Covid-19 : troisième cause de décès en France en 2020, quand les autres grandes causes baissent. Bull Épidémiol Hebd. 022;(Cov_16):2-15.

- Naouri, D., Fouillet, A., Ghosn, W., Coudin, E. (2022, décembre). Covid-19 : troisième cause de décès en France en 2020, quand les autres grandes causes de décès baissent. DREES, Études et Résultats, 1250.

 

2018 and 2019 final data dissemination, which part of the coding relied on deep learning methods are accompanied by working papers devoted to the production method.

-Zambetta, E. et al (2023) Combining a deep-learning-based approach, rule-based automated expert system and targeted manual coding for ICD-10 cause of death coding of French death certificates in 2018 and 2019 - Document de travail CépiDc n2/2023

- Martin et al. (2013) Rapport de production – Années de décès 2018 et 2019 – Données définitives - Document de travail du CépiDc n3/2023

 

10.3. Dissemination format - online database

Online latest aggregated tables accessible here: https://www.cepidc.inserm.fr/donnees-et-publications/grandes-causes-de-deces-en-2021-et-tendances-recentes

Online more detailed aggregated databases accessible here : https://opendata-cepidc.inserm.fr/

Data on Covid-19 mortality available here : https://opendata.idf.inserm.fr/cepidc/covid-19/

10.3.1. Data tables - consultations

Not available

10.4. Dissemination format - microdata access

Requests to access micro-data can be submitted by authorised third-parties (see concept 7.2 : rules applied for treating the datasets to ensure statistical confidentiality and prevent unauthorised disclosure) on the Inserm-CépiDc website : https://www.cepidc.inserm.fr/je-suis-un-chercheur-etou-jai-un-projet-detude-sur-les-causes-de-deces-ou-le-snds

10.5. Dissemination format - other

Encrypted csv format encoded in UTF8

10.5.1. Metadata - consultations

Not available

10.6. Documentation on methodology

The entire production process is detailed on the CépiDc website see https://www.cepidc.inserm.fr/qui-sommes-nous/les-statistiques-sur-les-causes-medicales-de-deces-de-z

See also https://www.cepidc.inserm.fr/causes-medicales-de-deces/comment-sont-produites-les-donnees

and Rey, 2016 :

"Death certificate data in France: Production process and main types of analyses", La revue de medecine interne, doi : doi.org/10.1016/j.revmed.2016.01.011

The production report concerning CoD data in 2018 and 2019 is available here:

https://www.cepidc.inserm.fr/documentation/rapport-de-production-annees-de-deces-2018-et-2019-donnees-definitives-document-de-travail-du-cepidc-n32023

See also

-Zambetta, E. et al (2023) Combining a a deep-learning-based approach, rule-based automated expert system and targeted
manual coding for ICD-10 cause of death coding of French death certificates in 2018 - 2019 - Document de travail CépiDc n2/2023

10.6.1. Metadata completeness - rate

Metadata about statistical outputs (concepts 2, 3, 4, 7.1, 8, 9) : 1
Metadata about statistical processes (concepts 5, 6, 7.2, 17, 18) : 1
Metadata about quality (concepts 10-16) : 1

10.7. Quality management - documentation

Documentation on quality management can be found on the CepiDc website https://www.cepidc.inserm.fr/qui-sommes-nous/les-statistiques-sur-les-causes-medicales-de-deces-de-z


11. Quality management Top
11.1. Quality assurance

The causes of death data are based on European regulation, which defines scope, definitions of variables and characteristics of the data, and on the WHO guidelines. France follows these clear and detailed  guidelines for recording and coding the causes of deaths using the ICD-10 classification published by the WHO.

 

France also performs a review stage after an initial coding, especially for the most complex cases and the most frequent errors. In order to ensure cause of death coding quality, checks on specific types of coded death certificates are performed regularly. Those manual checks are performed though the Iris coding software user interface.

They concern

Random quality checks are also made to assess the quality of automatic coding and the consistency of manual coding.

For deaths in 2018 and 2019, produced in a context of production catch-up, all usual checks are not performed in the same way as those for deaths in 2020 or 2017 and before. The production report details which types of checks amongst those listed above were performed, entirely, partially or let apart.

In the assessment of coding quality for the years of 2018, 2019, and 2021, a thorough evaluation was conducted employing a method that integrates automated rule-based coding, AI coding, and assisted manual coding. The evaluation for 2018 and 2019 are extensively documented in Zambetta et al 2023. This approach goes beyond the conventional coding campaigns, based on automated rule-based coding, and assisted manual coding, offering a more exhaustive analysis. 

 

11.2. Quality management - assessment

Quality assesment is conducted within the INSEE quality approach framework.

Following an evaluation process by the Official Statistics Authority, French cause of death statistics produced by Inserm-CépiDc was given a quality label by the november 14, 2017 notice for a duration of 5 years. At the end of 2022, CépiDc did not ask for a renewal of the label as the structural delay for transmitting to Eurostat and disseminating annual CoD data was not solved yet.


12. Relevance Top
12.1. Relevance - User Needs

The main users of COD data are Research institutes, Universities, Public Government agencies. The main request from cause of death data users and stakeholders is the access to more recent data.

12.2. Relevance - User Satisfaction

Not available

12.3. Completeness

1

12.3.1. Data completeness - rate

1. For mandatory variables: 1

2. For voluntary variables: 1

3. For additional variables:

  • External CoD: 1
  • Place of occurrence for external CoD: 0
  • Activity for external CoD: 0
 


13. Accuracy Top
13.1. Accuracy - overall

The main issue limiting the accuracy of the cause of death statistics is data coverage : each year, 98% of civil state registered deaths in France match a death certificate received at Inserm-CépiDc. For the other 2% medical death certificates are missing. These remaining 2% are identified by the impossibility of indirect record linkage between civil state mortality data (collected by INSEE) and the medical death certificate data. They are at the end added to the CoD data with"unspecified cause of mortality". Missing data is non random and overrepresents suspicious deaths for which the death certificate can be blocked at various stages of the process, as described in Transmission of death certificates to CepiDc-Inserm related to suspicious deaths, in France, since 2000 (doi.org/10.1016/j.respe.2017.11.006), or some specific small geographical areas, which failed to provide data. However, the accuracy is rather good overall, and at the NUTS 2 level.

13.2. Sampling error

Not applicable. Data collection and processing are based on exhaustive administrative data.

13.2.1. Sampling error - indicators

Not applicable

13.3. Non-sampling error

some due to under-coverage

13.3.1. Coverage error

Missing data is nonrandom and overrepresent suspicious deaths for which death certificates can be blocked at various stages of the process, as described in Transmission of death certificates to CepiDc-Inserm related to suspicious deaths, in France, since 2000:

title : "Transmission of death certificates to CepiDc-Inserm related to suspicious deaths, in France, since 2000"
creator : Elsa Richaud-Eyraud, Claire Rondet and Grégoire Rey
publisher : Revue d'Épidémiologie et de Santé Publique, Volume 66, Issue 2, March 2018, Pages 125-133
created : 2017
language : fr
link : doi.org/10.1016/j.respe.2017.11.006

13.3.1.1. Over-coverage - rate

Duplicates of certificates (which can happen for e-certificates) are removed during the synchronisation process of CoD deaths with deaths registered to INSEE.

Stillbirths and neonatal births do not come from the same source (death certificates vs « programme médicalisé des systèmes d’information ») and those two sources are not linked allowing one to check and correct for double counts. Hence, there is a small risk of overestimating perinatal mortality  due to double counting in each source of deaths/stillbirths at day 0.

13.3.1.2. Common units - proportion

Not applicable. Data collection is from administrative data.

 
13.3.2. Measurement error

Not applicable

13.3.3. Non response error

only partial non-response

13.3.3.1. Unit non-response - rate

Not applicable, deaths with no cause of death certificates are added to the final data set..

13.3.3.2. Item non-response - rate

Total non-response (not receiving causes of death for a person deceased in France) is added to the dataset with COD coded as R99. Information on age, gender and region of death is available. CepiDc-Inserm does not receive around 2% of CoDs.

13.3.4. Processing error

In accordance with WHO recommendations, the physician's description of the cause of death is not questioned when compiling the statistical database. Inserm-CépiDc uses an external service provider to receive, digitize and standardize paper death certificates. Standardization also applies to electronic certificates that are not automatically coded with IRIS/MUSE. During this data entry phase, errors are limited by the use of a transcription software. The service provider sends both the scanned images and the digitized text to Inserm-CépiDc. During the coding phase, the IRIS/MUSE coding software is used both for batch coding and as an interface for manual coding (assisted coding). If the text on a death certificate appears to be inconsistent, the coding team checks the data entry using the scanned image.

For deaths in 2018 and 2019, data were produced in a context of production catch-up: certificates that were not automatically coded by the rule-based coding system (IRIS/MUSE, 36%) were either coded by deep learning algorithms trained on 2011-2017 and 2020 data (33%), or coded manually (3%). This may result in some errors for specific categories. Those are detailed in Zambetta et al. (2023) also reported in the appendix of the present metadata page.

From deaths in 2021 on, AI coding is integrated as a third mode of coding in regular production. 62% of death certificates in 2021 are automatically batch coded up to the UCOD determination by IRIS/Muse, 25% by AI and the remaining by the coding experts (via assisted coding with IRIS/Muse). Manual coding is targeted to certificates the more complex to code.

13.3.5. Model assumption error

not applicable


14. Timeliness and punctuality Top

see below

14.1. Timeliness

Year

Number of months between the end of the reference year and the publication at national level

2011

 32

2012

 31

2013

 25

2014

 25

2015

 26

2016

 30

2017

 47

2018

50 for provisional data +9 for final data

2019

38 for provisional data +9 for final data

2020

24

2021

24

 

 
14.1.1. Time lag - first result

For 2018 and 2019 only – provisional data were disseminated in December 2022.

14.1.2. Time lag - final result

For 2018 and 2019 data only – Final data were sent to Eurostat in September 2023.

14.2. Punctuality

Reference year

Time between the end of the reference year (year of death) and the delivery of final data to Eurostat

2011

 24+8

2012

 24+7

2013

 24+1

2014

 24+1

2015

 24+2

2016

 24+6

2017

 24+23

2018

24+24 for provisional data; 24+33 for final data

2019

24+12 for provisional data; 24+33 for final data

2020

24+0

2021

24+0

14.2.1. Punctuality - delivery and publication

Reference year

Time between the end of the reference year (year of death) and the delivery of final data to Eurostat

2011

 24+8

2012

 24+7

2013

 24+1

2014

 24+1

2015

 24+2

2016

 24+6

2017

 24+23

2018

24+24 for provisional data; 24+33 for final data

2019

24+12 for provisional data; 24+33 for final data

2020

24+0

2021

24+0

 

 


15. Coherence and comparability Top
15.1. Comparability - geographical

The cause of death coding is centralized at Inserm-CépiDc. Each region has a coverage rate higher than 95%.

Causes of death statistics are largely comparable between geographical areas in France. Nevertheless, discrepancies may arise at a granular geographical and COD level due to:

-       some regions (Île-de-France) do not send a countable part of their death certificates on a regular basis. This concerns in particular suspicious deaths in the event of a forensic investigation. The total number of deaths for these kinds of causes is therefore subject to variable underestimation over the territory and over time. The medico-legal institute of Paris transmitted medical causes for deaths subject to autopsy occurring from 2018 onwards.

-       Death certificates can be paper-back or electronic – the rate of electronic death certificates increased in 2020 from 20% at the beginning of the year to 29% in December 2020, it is around 32% in 2021. The certificate model remains consistent, whether is electronically filled or paper, without risk of lack of transmission of data to CepiDc-Inserm for e-certification.

Regional discrepancies are noted as concern the rate of e-certification.

Since 2018, a new model of certificate was introduced. This new model of death certificate allows certifiers to provide additional information on manner of death especially for external causes of death, which enables to identify more accurately suicides for instance. E-certification was adapted to this new model in January 2018. But its use has been more progressive for paper-back certificates. The old model continues to be used especially by certifiers who do not certify deaths very often. The rates of dissemination can differ on a geographical basis.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable

15.2. Comparability - over time

The 10th revision of the International statistical classification of diseases and related health problems (ICD-10) has been implemented by Inserm-CépiDc from reference year 2000 onwards for cause of death statistics production. Except for very specific causes of death, there has been no major changes enough to warrant the designation of a break in series since.

Breaks in time comparability include e-certification deployment since 2007, 2017 new model of death certificate (at stake in 2018), and coverage of causes of deaths when forensic investigations occur  as detailed above.

On electronic death certification, introduced in 2007,



title : "Evolution of the electronic death certification in France from 2011 to 2018"
creator : Anne Fouillet, Dominique Pigeon, Isabelle Carton, Aude Robert, Isabelle Pontais, Céline Caserio-Schönemann and Grégoire Rey
publisher : Bulletin épidémiologique hebdomadaire N° 29-30 - 12 novembre 2019
created : 2019
language : fr
link : beh.santepubliquefrance.fr/beh/2019/29-30/pdf/2019_29-30_2.pdf

15.2.1. Length of comparable time series

from 2011 on

15.3. Coherence - cross domain

Checks are done with death records (INSEE) every week, with indirect record linkage every month and at the end of the coding of a given year, and final data includes demographic information also for missing death certificates

For 2020 data due to the pandemic, checks were done comparing CoD death certificates with mention of COVID on information feedback from the information systems of hospitals and medico-social local units. COVID dead countings differentials were within acceptable range (less than 15% of differential), see

- Fouillet A, Ghosn W, Naouri D, Coudin E. Covid-19 : troisième cause de décès en France en 2020, quand les autres grandes causes baissent. Bull Épidémiol Hebd. 022;(Cov_16):2-15.

- Naouri, D., Fouillet, A., Ghosn, W., Coudin, E. (2022, décembre). Covid-19 : troisième cause de décès en France en 2020, quand les autres grandes causes de décès baissent. DREES, Études et Résultats, 1250.

15.3.1. Coherence - sub annual and annual statistics

Only annual data are available but data are interpretable by month of death

15.3.2. Coherence - National Accounts

Not applicable

15.4. Coherence - internal

The coding team follows the same rules to code the causes of death.

Incoherence between cause of death and age or sex are identified and corrected.


16. Cost and Burden Top

Cause of death statistics production costs approximately 2 million euros annually. This bugdet does not cover the cost of the data collection process and its transmission to Inserm-CépiDc.


The cost and burden of the data collection is reduced by using automatic coding systems and by the increasing coverage of electronic death certification.


17. Data revision Top
17.1. Data revision - policy

There is no data revision and no data revision policy. 2018 and 2019 are exceptions.

17.2. Data revision - practice

not applicable

17.2.1. Data revision - average size

not applicable


18. Statistical processing Top
18.1. Source data

French death certificates comply with the WHO standards. There are two different templates the neonatal death certificate for deaths occuring on the day of birth up to the 27th day of life and the general (adult) model of death certificate for deaths occuring from the 28th day of life (included) onwards. From 2018 on (and slightly 2017) a new templace of the adult death certificate has been disseminated (but has not totally replaced the old ones). The new template offers more details on death circumstances, which has an impact in evaluating external causes of death.

18.2. Frequency of data collection

Daily

18.3. Data collection

Data from administrative sources, collected either electronically or on paper.

18.3.1. Certification

Regarding training, not applicable because there is no survey conducted on death certification training or post mortem examination.

Regarding queries related to medical part of the death certificate, approximately 2000 to 3000 problematic death certificates have been queried for each reference year, with an estimated 50% response rate. For reference year 2017, only death certificates presenting a blank medical part have been queried. The proportion of deaths where the underlying cause is changed as a result of the query is unknown.

Table on certification (Percentage)

 

Years

All doctors (certifiers) trained in the certification

All doctors (certifiers - pathologists or others doctors) trained in the post-mortem examination (autopsies)

Certificates filled by persons who attended a course on certification or post-mortem examination

Death certificates that are queried (only queries related to medical part of the death certificate should be included)

Replies received for queries sent

Deaths where the underlying cause is changed as a result of the query

Death certificates with incorrect sequence

2011 to 2021

Not applicable

Not applicable

Not applicable

Not available

Not available

Not available

Not available

 
18.3.2. Automated Coding
   

Data year

Use of any form of automated coding

System used (IRIS, MICAR, ACME, STYX, MIKADO, others)

2011

 Yes

Partly Styx, Iris, MICAR, ACME tables-Y2011S2, partly manual, with systematic review of deaths

2012

 Yes

Partly Iris 4.0.52, MICAR, ACME tables-Y2012S1, partly manual, with systematic review of deaths

2013

 Yes

Partly Iris 4.3.0, MICAR, ACME tables-Y2013S1, partly manual, with systematic review of deaths

2014

 Yes

Partly Iris 4.3.0, MICAR, ACME tables-Y2014S2, partly manual

2015

 Yes

Partly Iris 4.5.6, MICAR, ACME tables-Y2015S1, , partly manual 

2016

 Yes

Partly Iris 5.4.0, Muse specV2016SR10, partly manual

2017

 Yes

Partly Iris 5. 4 .04, Muse specV2018SR10, partly manual

2018

Yes

Final data : Partly Iris 5.5.0, Muse 2.6 (specV2018SR10), partly with deep learning, partly manual

2019

Yes

Final data : Partly Iris, 5.6.0, Muse 2.7.1 (specV2019SR10), partly with deep learning, partly manual

2020

Yes

 Partly Iris 5.7.0, Muse 2.8 and partly manual

2021

Yes

 Partly Iris 5.8.1, Muse 2.9 and partly manual

 

 

 
18.3.3. Underlying cause of death
   

Data year

Only manual selection of underlying cause

Manual with ACME decision tables (if yes, version of ACME)

ACS utilising ACME decision tables (if yes, version of ACME)

Own system (ACS without ACME)

Comments

2011

No

No

Yes (ACME tables-Y2011S2)

No

 Styx, Iris

2012

No

No

Yes (ACME tables-Y2012S1)

No

Iris 4.0.52

2013

No

No

Yes (ACME tables-Y2013S1)

No

Iris 4.3.0

2014

No

No

Yes (ACME tables-Y2014S2)

No

Iris 4.3.0

2015

No

No

Yes (ACME tables-Y2015S1)

No

Iris 4.5.6

2016

No

No

No

Yes (Muse specV2016SR10)

Iris 5.4.0

2017

No

No

No

 Yes (Muse specV2018SR10)

Iris 5.5.4, no change of code from WHO so the most up-to-date tables at the time of the coding have been used (2018 instead of 2017)

2018

No

No

No

Yes (Muse specV2018SR10 and deep learning)

Iris 5.5.0, Muse 2.6

2019

No

No

No

Yes (Muse specV2019SR10 and deep learning)

  Iris 5.6.0, Muse 2.7.1

2020

No

No

No

Yes (Muse)

Iris 5.7.0, Muse 2.8

 

2021

No

No

No

Yes (Muse specV2021SR30 and deep learning)

Iris 5.8.1, Muse 2.9

18.3.4. Availability of multiple cause
   

Data year

Information stored in the national CoD database, UC (Underlying cause) or MC (Multiple cause)

2011 to 2021

 UC + MC

18.3.5. Stillbirths and Neonatal certificates

French death certificate does not apply to stillbirths.
Stillbirths information is collected from the « programme médicalisé des systèmes d’information » (PMSI) by the Directorate of Research, Study, Evaluation and Statistics (DREES) Population health office depending on the Health Ministry.

All stillbirths with weight births over 500 grams or with gestational ages of at least 22 weeks are collected.
The terminations of pregnancy are included from 22 weeks (gestational age) onwards.

18.4. Data validation

Inconsistencies between the cause of death and other information on the death certificate (age, sex, manner of death) are detected with alerts during coding using the Iris software, so coders can check the original death certificate and correct it. Consistency checks are also run  on specific categories (children below 15, pathologies of particular interest for public health, maternal deaths, external causes) and randomly.
Coverage validation is done by indirect record linkage with population registers (Insee).

18.4.1. Coding

Description of coding procedure (central level, distributed among other bodies, etc.):

Production process is centralised at Inserm-CépiDc. The coding procedure relies on the automated coding system Iris. 58 % of 2017 death certificates and 63% for 2021 were coded automatically by Iris. Rejected certificates are either manually revised by trained coders, and experts if they remain not yet coded, either by coded by AI (for 2018, 2019 and from 2021 on).

For deaths in 2018 and 2019, coding could also be performed by predictive deep learning algorithms trained on past data. From 2021 on, coding strategy relies on the three modes of coding - automatically by the rule-based system IRIS/MUSE (63%), manually and assisted by IRIS/MUSE (12%) and predictive deep learning (25%). Deep learning algorithms are used both to predict CoD (multiple causes and UC) and to target certificates with low confidence levels in predictions in order to send them to manual coding. Manual coding therefore focuses on deaths of special interest for public health and research (maternal deaths, children, AIDS/HIV, research databases) plus those for which AI algorithms performance is not so good (other external causes, blood diseases, musculoskeletal system diseases, accidental poisoning,...)

See Zambetta et al (2023) for details also reported as appendix to this metadata web page, with applications/quantification for 2018 and 2019 data.

Description of the procedures to detect errors (i.e. errors such as potential inconsistency in the death certificate or error due to mistake when filling the deaths certificates):

Inconsistencies between the cause of death and other information on the death certificate (age, sex, manner of death) are detected with alerts during coding using the IRIS/MUSE software, so the coders can check the original death certificate and correct it. A consistency check is also run for the detection of inconsistencies at the end of a given sample coding.

Checks on cause of death coding quality are performed regularly. The manual inconsistency checks performed via the IRIS/MUSE coding software user interface concerns:

correcting coding inconsistencies identified as

 Random quality checks are also considered to assess quality of automated coding quality and consistency of manual coding.

Description of the measures taken in order to solve detected errors:

Errors detected are corrected manually by expert coders using the Iris software.

In the case of death certificates presenting a blank medical part, an e-mail or a paper mail may be sent to the certifier, but most of these queries remain unanswered.

Coding performed by a certifier:

no

Estimation of the percentage of autopsy from which information is available for coding:

Unknown.

Description of double coding exercises and rate of codification errors for underlying cause of death:

Unknown

 
18.4.2. Unspecified CoD code

Year

Unspecified CoD (for ICD10 : R00-R99 codes, for ICD9 : 780-790 codes)

Unknown CoD (for ICD10 : R98-R99 codes, for ICD9 : 799.9, 798.9, 798.2 codes)

Deaths due to senility (for ICD10 : R54 code, for ICD9 : 797 code)

Deaths due to exposure to unspecified factor (for ICD10 : X59 code, ICD9 : 928.9 code)

2011

 8.29

 3.59

 0.76

 1.41

2012

 9.41

 4.47

 0.71

 1.47

2013

 10.14

 5.28

 0.69

 1.44

2014

 9.05

 4.06

 0.68

 1.50

2015

 9.25

 4.02

 0.71

 1.63

2016

 9.35

 4.27

 0.64

 1.61

2017

 9.86

 4.60

 0.65

 1.63

2018

10.22

4.69

0.64

1.51

2019

 11.01

5.34

 0.69

 1.57

2020

10.15

4.9

0.67

1.48

2021

10.46

4.8

0.73

1.53

 

ICD codes for the underlying cause (% of the Total)

18.4.3. Unknown country or region

Unknown country/region (%) for residents and non-residents who died in the country

 

Year

Residents

Non-residents

Unknown residency (NUTS2)

Unknown occurrence (NUTS2)

Unknown residency (country)

Unknown residency (NUTS2)

Unknown occurrence (NUTS2)

2011

 0

 0

 13.05

 100

 10.62

2012

 0

 0

 24.04

 100

 0

2013

 0

 0

 26.38

 100

 0

2014

 0

 0

 28.38

 100

 0

2015

 0

 0

 0

 100

 0

2016

 0

 0

 12.35

 100

 9.47

2017

 0

 0

 6.66

 98.98

 3.97

2018

0

0

3.0%

100%

0

2019

0

0

 1.8%

 100%

0

2020

0

0

3.4%

100%

0

2021

0

0

2.1%

97.8%

0

 
18.4.4. Validation of the coverage

By indirect record linkage with the population registers.

18.5. Data compilation

No operations are performed

18.5.1. Imputation - rate

Not applicable, no imputation is made. For deep learning coding of provisional data in 2018 and 2019 see dedicated report

18.6. Adjustment

Not applicable, no adjustement is made.

18.6.1. Seasonal adjustment

not applicable


19. Comment Top

None.



Annexes:
Combining a deep-learning-based approach, rule- based automated expert system and targeted manual coding for ICD-10 cause of death coding of French death certificates in 2018 - 2019


Related metadata Top


Annexes Top
Report on provisional 2018 and 2019 CoD data partly predicted by deep learning