Evidence map›Paper›PMID 30509233›Full record

ArticleBMC public health2018

Saving lives through certifying deaths: assessing the impact of two interventions to improve cause of death data in Perú.

Janet Miki, Rasika Rampatige, Nicola Richards, Tim Adair, Juan Cortez-Escalante, Javier Vargas-Herrera

Abstract readEvaluation Study
In one paragraph

Article in BMC public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  5. Digital transformation of mortality reporting using an ICD-11 integrated death certificate system in Suriname.Revista panamericana de salud publica = Pan American journal of public health · 2025
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  14. Automated coding and selection of causes of death in Peru: a descriptive study, 2016-2019.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2023
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  15. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Janet MikiCivil Registration and Vital Statistics, Vital Strategies, Bloomberg Data for Health Initiative, Santiago de Surco, Lima, Peru. chiaki.miki@gmail.com.ORCID http://orcid.org/0000-0002-6894-8346
Rasika RampatigeMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
Nicola RichardsMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
Tim AdairMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
Juan Cortez-EscalanteMelbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
Javier Vargas-HerreraCivil Registration and Vital Statistics, Vital Strategies, Bloomberg Data for Health Initiative, Santiago de Surco, Lima, Peru.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMortality statistics derived from cause of death data are an important source of information for population health monitoring, priority setting and planning. In Perú, almost all death certificates are issued by doctors because it is a legal requirement. However, the quality of cause of death data is poor. In August 2016, the Ministry of Health of Perú decided to make two specific interventions to improve cause of death data: to introduce an online death certification system and to train doctors in standard death certification practices.

methodsThe study comprised a random sample of 300 pre-intervention death certificates, 900 death certificates that were part of the online intervention, and 900 death certificates that were part of both the online and training interventions. All the deaths had occurred between January and September 2017. We used the Assessing the quality of death certification tool from the University of Melbourne for the assessment. We examined the frequency of common errors in death certificates, the frequency of any error and the average error score for each category of: age group, sex, doctor's seniority, doctor's speciality, level of health facility and broad cause of death.

resultsThe average error score declined by 38% due to the online intervention and by a further 26% due to the training intervention. Improved certification practices remained after controlling for potentially confounding factors. Main improvements were reductions in the absence of a time interval (66% of certificates), incorrect sequence of causes (22%), and ill-defined conditions (13%).

conclusionsThis study demonstrates how the two interventions introduced by the Ministry of Health in Perú improved the correctness of death certificates. The study also provides evidence on necessary changes to the training program to address the poor certification practices that have remained after implementation of the online system.

Indexed as

Cause of DeathData AccuracyDeath CertificatesAdolescentAdultAgedAged, 80 and overChildChild, PreschoolEducationFemaleHumansInfantInfant, NewbornMaleMiddle AgedCause of deathCertificationInterventionMortalityOnlinePerúQualityTraining

Identifiers

PMID30509233
PMCPMC6276144

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.