Evidence map›Paper›PMID 32333160›Full record

ArticleWorld journal of surgery2020

Outcome Measurement at a Ugandan Referral Hospital: Validation of the Mbarara Surgical Services Quality Assurance Database.

Gustaf Drevin, Katherine Albutt, Moris Baluku, Caleb Tuhumwiire, Hao Deng, Nicholas Musinguzi, Vicki Modest, Joseph Ngonzi, Stephen Ttendo, Paul Firth

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in World journal of surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Article
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

10 authors at 4 institutions in 3 countries.

Gustaf DrevinProgram in Global Surgery and Social Change, Harvard Medical School, Boston, MA, USA.
Katherine AlbuttProgram in Global Surgery and Social Change, Harvard Medical School, Boston, MA, USA.
Moris BalukuDepartment of Anaesthesia and Critical Care, Mbarara Regional Referral Hospital, Mbarara University of Science and Technology, Mbarara, Uganda.
Caleb TuhumwiireDepartment of Surgery, Mbarara Regional Referral Hospital, Mbarara University of Science and Technology, Mbarara, Uganda.
Hao DengDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
Nicholas MusinguziHarvard-Mbarara University of Science and Technology Collaborative, Mbarara, Uganda.
Vicki ModestDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
Joseph NgonziDepartment of Obstetrics and Gynaecology, Mbarara Regional Referral Hospital, Mbarara University of Science and Technology, Mbarara, Uganda.
Stephen TtendoDepartment of Anaesthesia and Critical Care, Mbarara Regional Referral Hospital, Mbarara University of Science and Technology, Mbarara, Uganda.
Paul FirthProgram in Global Surgery and Social Change, Harvard Medical School, Boston, MA, USA. pfirth@partners.org.
Massachusetts General Hospital · USMbarara University of Science and Technology · UGHarvard University · USMbarara National Referral Hospital · UG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFive billion people lack access to surgery. Accurate and complete data have been identified as essential to the global scale-up of perioperative care. This study retrospectively validates the Mbarara Surgical Services Quality Assurance Database (SQUAD), an electronic outcomes database at a Ugandan secondary referral hospital.

methodsSQUAD data were compared to paper records from August 2013 to January 2017. To assess data entry accuracy, two researchers independently extracted 24 patient variables from 170 charts. To assess completeness of patient capture, SQUAD entries were compared to a sample of charts returned to the Medical Records Department, and to a sample of entries in ward and operating room logbooks. Two-tailed binomial proportions with 95% CI were calculated from the comparative results of patient observations, against a predefined accuracy of 0.85-0.95.

resultsAgreement between completed validation observations from charts and SQUAD data was 91.5% (n = 3734/4080 data points). Binomial tests indicated that 15 variables had higher than 95% accuracy. A total 19 of 24 variables had ≥ 85% accuracy. The completeness of SQUAD patient capture was 98.2% (n = 167/170) of charts returned to the Medical Records Department, 97.5% (n = 198/203) of operating logbook entries, and 100% (n = 111/111) of ward logbook entries, respectively.

conclusionSQUAD closely reflects the primary surgical and anaesthetic data at a Ugandan secondary hospital. Data accuracy of key variables and completeness of population capture were comparable to those of databases in high-income countries and outperformed those of other low- and middle-income countries.

Indexed as

HospitalsOutcome Assessment, Health CareQuality Assurance, Health CareAdolescentAdultChildCritical CareDatabases, FactualData CollectionFemaleHumansMaleMiddle AgedRetrospective StudiesSecondary Care CentersUganda

Identifiers

PMID32333160
OpenAlexW3019389531

What OpenQuestion holds

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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.