Evidence map›Paper›PMID 30458804›Full record

ArticlePopulation health metrics2018

Hospital mortality statistics in Tanzania: availability, accessibility, and quality 2006-2015.

Irene R Mremi, Susan F Rumisha, Mercy G Chiduo, Chacha D Mangu, Denna M Mkwashapi, Coleman Kishamawe, Emanuel P Lyimo, Isolide S Massawe, Lucas E Matemba, Veneranda M Bwana and 1 more

Open access · goldAbstract read
In one paragraph

Article in Population health metrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
5.1field-weighted citation impact, top 5% of its field
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

15 citing papers in PubMed, 29 citations in OpenAlex.

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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

11 authors at 2 institutions in 1 country.

Irene R MremiNational Institute for Medical Research, Headquarters, P.O. Box 9653, 11101, Dar es Salaam, Tanzania.
Susan F RumishaNational Institute for Medical Research, Headquarters, P.O. Box 9653, 11101, Dar es Salaam, Tanzania.
Mercy G ChiduoNational Institute for Medical Research, Tanga Research Centre, P.O. Box 5004, Tanga, Tanzania.
Chacha D ManguNational Institute for Medical Research, Mbeya Research Centre, P.O. Box 2410, Mbeya, Tanzania.
Denna M MkwashapiNational Institute for Medical Research, Mwanza Research Centre, P.O. Box 1462, Mwanza, Tanzania.
Coleman KishamaweNational Institute for Medical Research, Mwanza Research Centre, P.O. Box 1462, Mwanza, Tanzania.
Emanuel P LyimoNational Institute for Medical Research, Headquarters, P.O. Box 9653, 11101, Dar es Salaam, Tanzania.
Isolide S MassaweNational Institute for Medical Research, Tanga Research Centre, P.O. Box 5004, Tanga, Tanzania.
Lucas E MatembaNational Institute for Medical Research, Headquarters, P.O. Box 9653, 11101, Dar es Salaam, Tanzania.
Veneranda M BwanaNational Institute for Medical Research, Amani Research Centre, P.O. Box 81, Muheza, Tanzania.
Leonard E G MboeraNational Institute for Medical Research, Headquarters, P.O. Box 9653, 11101, Dar es Salaam, Tanzania. lmboera@gmail.com.
National Institute for Medical Research · TZSouthern African Centre for Infectious Disease Surveillance · TZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate and reliable hospital information on the pattern and causes of death is important to monitor and evaluate the effectiveness of health policies and programs. The objective of this study was to assess the availability, accessibility, and quality of hospital mortality data in Tanzania.

methodsThis cross-sectional study involved selected hospitals of Tanzania and was carried out from July to October 2016. Review of hospital death registers and forms was carried out to cover a period of 10 years (2006-2015). Interviews with hospital staff were conducted to seek information as regards to tools used to record mortality data, staff involved in recording and availability of data storage and archiving facilities.

resultsA total of 247,976 death records were reviewed. The death register was the most (92.3%) common source of mortality data. Other sources included the International Classification of Diseases (ICD) report forms, Inpatient registers, and hospital administrative reports. Death registers were available throughout the 10-year period while ICD-10 forms were available for the period of 2013-2015. In the years between 2006 and 2010 and 2011-2015, the use of death register increased from 82 to 94.9%. Three years after the introduction of ICD-10 procedure, the forms were available and used in 28% (11/39) hospitals. The level of acceptable data increased from 69% in 2006 to 97% in 2015. Inconsistency in the language used, use of non-standard nomenclature for causes of death, use of abbreviations, poorly and unreadable handwriting, and missing variables were common data quality challenges. About 6.3% (n = 15,719) of the records had no patient age, 3.5% (n = 8790) had no cause of death and ~ 1% had no sex indicated. The frequency of missing sex variable was most common among under-5 children. Data storage and archiving in most hospitals was generally poor. Registers and forms were stored in several different locations, making accessibility difficult.

conclusionOverall, this study demonstrates gaps in hospital mortality data availability, accessibility, and quality, and highlights the need for capacity strengthening in data management and periodic record reviews. Policy guidelines on the data management including archiving are necessary to improve data.

Indexed as

Hospital MortalityCross-Sectional StudiesData AccuracyDeath CertificatesHospital RecordsHumansMedical RecordsTanzaniaAvailabilityCause of deathData qualityHospitalMortalityTanzania

Identifiers

PMID30458804
PMCPMC6247530
OpenAlexW2900907762

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.