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Quality Framework for cRVS Civil Registration Process

This session discusses the quality framework for the civil registration process in cRVS, covering topics such as place, time, cost, and late registration. It emphasizes the importance of evaluation, confidentiality, and privacy in maintaining a reliable vital statistics system.

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Quality Framework for cRVS Civil Registration Process

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  1. Session 17. Quality framework of cRVS Civil Registration Process: Place, Time, Cost, Late Registration UNITED NATIONS STATISTICS DIVISION Workshop on Operation of Civil Registration, Vital Statistics and Identity Management Systems and the Production of Vital Statistics Reports for the Eastern Mediterranean Countries (Group 1) Casablanca, Morocco, 19 - 23 March 2018

  2. Live births Health services Certification of cause of death Complementary/ Interim sources Population census Surveys Sample registration areas Deaths Civil Registration, including population registers Principles: • Compulsory • Universal • Continuous • Confidentiality Fetal deaths Vital Statistics Compilation Processing Validation Quality control Dissemination Authorized institutions Marriages Divorces Additional administrative sources Coronary Police Registries Health records Annulments Judicial separations Courts Judicial institutions Adoptions Legitimation National IDs’ Electoral lists Passports … Recognition Evaluation is essential Vital Statistics System

  3. Evaluation is essential Adequately funded evaluation activities are essential • For improving systems that have deficiencies • For maintaining systems that function satisfactorily • Findings from data quality evaluation are useful to • identify and quantify data biases and correct them to derive more reliable vital statistics and indicators • identify systemic issues and make interventions to prevent weaknesses in data quality

  4. Evaluation is essential • Strong mandate in Sustainable Development Agenda • Indicator 16.9.1: Percentage of children under 5 whose births have been registered • Indicator 17.19.2: Proportion of countries that… (b) have achieved 100 per cent birth registration and 80 per cent death registration • Other 18 indicators that use CRVS data as direct input

  5. Confidentiality and privacy • Evaluation exercises should be conducted with a degree of independence • So that an objective assessment can be achieved • Systemic issues affecting data quality should be discussed in terms of processes rather than specific institutions and/or personnel • Findings from evaluation should be discussed and utilised in a constructive environment.

  6. Quality basic framework Quality assessment Quality assurance • Specific studies for specific questions • Completeness of registration of vital events • Accuracy of variables • Overall functioning of sub-systems • Can be ad hoc or regular exercises • Encompasses each stage of CRVS operations • Identifies bottle necks

  7. Quality assurance • Ensure that: • All vital events are registered without duplication • All related information is recorded • Information is compiled, validated and processed • Vital statistics are released in timely manner • Focused on: • Processes • Functions • Protocols WHO tools “Rapid assessment” “Comprehensive assessment”

  8. Quality assessment: Standards

  9. 1. Completeness * Every vital event is registered * Statistical report is filed for every registered event * Coverage error • 2. Accuracy Quality assessment: Standards 4. Timeliness 3. Availability

  10. 1. Completeness 2. Accuracy * Every data item is filled * Data items are accurately filled * Content error Quality assessment: Standards 4. Timeliness 3. Availability

  11. 1. Completeness 2. Accuracy Quality assessment: Standards 4. Timeliness 3. Availability * Data and statistics are available to users in a friendly format * Difficult to satisfy, as demands have grown

  12. 1. Completeness 2. Accuracy Quality assessment: Standards 4. Timeliness * CR: events are registered within time limit and statistical reports are filed according to schedule * VS: prompt dissemination 3. Availability

  13. Quality assessment: Methods Matching of records Direct methods Demographic analysis Indirect methods

  14. Quality assessment. Direct methods Matching of records Match registration records with records from an independentsource

  15. Quality assessment. Direct methods Matching: • Birth registration with death registration • limited to infants deaths • can be carried out routinely • With administrative records • a variety of sources can be used • however, none is complete • useful to detect certain type of underreporting

  16. Quality assessment. Direct methods Matching: • Lists from population censuses and surveys • compiled from questions on births and deaths • can lead to an estimate of completeness • national or sub-national level • Dual records system • a particular case of the lists • survey specifically to collect information on vital events • the two sources are confronted

  17. Quality assessment. Direct methods Matching basic logic:

  18. Quality assessment. Direct methods Matching basic logic: Chandrasekaran-Demingformula

  19. Quality assessment. Direct methods Matching basic logic: Chandrasekaran-Demingformula 147 257 =1377

  20. Quality assessment. Indirect methods • Comparison of trends • Delayed registration • Questions on birth registration in surveys or censuses • Comparison with census data • If at least two censuses: balancing equation, Lexis diagram • If only one census: compare aggregates • Methods for incomplete data • Manual X • Tools for Demographic Estimation (online and print update of Manual X, http://demographicestimation.iussp.org/) Demographic analysis

  21. Direct or indirect ?

  22. Direct or indirect ? • Objectives • Degree of precision • Timeliness • Type of event • Resources Choosing the appropriate method depends on:

  23. Thank You Спасибо 谢谢 Gracias Merci ﺷﻜﺮﺍﹰ

  24. Quality assessment. Direct methods Practical example: Health services of the state of Queensland, Australia Primarysource: Perinatal Data Collection Secondary source: Birth registration Linkage file: file containing person identifiers from various admin. sources

  25. Directmethods. Practical example: Health services of the state of Queensland, Australia • Some results • 2.7% of Perinatal Data records could not be linked to Registration data. • Significant differences in linkage according to ethnic groups • Remote and very remote geographical areas also had high rates of under-registration https://www.health.qld.gov.au/hsu/peri/underreg.pdf

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