MétaCan
Menu
Back to cohort
Record W2762496328 · doi:10.1186/s12913-017-2628-y

The quality of medical death certification of cause of death in hospitals in rural Bangladesh: impact of introducing the International Form of Medical Certificate of Cause of Death

2017· article· en· W2762496328 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBMC Health Services Research · 2017
Typearticle
Languageen
FieldMedicine
TopicAutopsy Techniques and Outcomes
Canadian institutionsnot available
FundersMedical Research CouncilNational Health and Medical Research CouncilGlobal Affairs CanadaDepartment for International DevelopmentInternational Centre for Diarrhoeal Disease Research, BangladeshStyrelsen för Internationellt Utvecklingssamarbete
KeywordsMedicineDeath certificateCause of deathHealth administrationCertificationMedical recordPublic healthMedical emergencyEmergency medicineFamily medicineNursingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Accurate and timely data on cause of death are critically important for guiding health programs and policies. Deaths certified by doctors are implicitly considered to be reliable and accurate, yet the quality of information provided in the international Medical Certificate of Cause of Death (MCCD) usually varies according to the personnel involved in certification, the diagnostic capacity of the hospital, and the category of hospitals. There are no published studies that have analysed how certifying doctors in Bangladesh adhere to international rules when completing the MCCD or have assessed the quality of clinical record keeping. METHODS: The study took place between January 2011 and April 2014 in the Chandpur and Comilla districts of Bangladesh. We introduced the international MCCD to all study hospitals. Trained project physicians assigned an underlying cause of death, assessed the quality of the death certificate, and reported the degree of certainty of the medical records provided for a given cause. We examined the frequency of common errors in completing the MCCD, the leading causes of in-hospital deaths, and the degree of certainty in the cause of death data. RESULTS: The study included 4914 death certificates. 72.9% of medical records were of too poor quality to assign a cause of death, with little difference by age, hospital, and cause of death. 95.6% of death certificates did not indicate the time interval between onset and death, 31.6% required a change in sequence, 13.9% required to include a new diagnosis, 50.7% used abbreviations, 41.5% used multiple causes per line, and 33.2% used an ill-defined condition as the underlying cause of death. 99.1% of death certificates had at least one error. The leading cause of death among adults was stroke (15.8%), among children was pneumonia (31.7%), and among neonates was birth asphyxia (52.8%). CONCLUSION: Physicians in Bangladeshi hospitals had difficulties in completing the MCCD correctly. Physicians routinely made errors in death certification practices and medical record quality was poor. There is an urgent need to improve death certification practices and the quality of hospital data in Bangladesh if these data are to be useful for policy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.212
GPT teacher head0.534
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it