Evidence map›Paper›PMID 29961014›Full record

ArticleBMJ open2018

Accuracy and utility of using administrative healthcare databases to identify people with epilepsy: a protocol for a systematic review and meta-analysis.

Gashirai K Mbizvo, Kyle Bennett, Colin R Simpson, Susan E Duncan, Richard F M Chin

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Unsupervised algorithms to identify potential under-coding of secondary diagnoses in hospitalisations databases in Portugal.Health information management : journal of the Health Information Management Association of Australia · 2024
    Article
  3. Review
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

5 authors at 4 institutions in 2 countries.

Gashirai K MbizvoMuir Maxwell Epilepsy Centre, University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK.
Kyle BennettMuir Maxwell Epilepsy Centre, University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK.
Colin R SimpsonFaculty of Health, Victoria University of Wellington, Wellington, New Zealand.ORCID 0000-0002-5194-8083
Susan E DuncanMuir Maxwell Epilepsy Centre, University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK.
Richard F M ChinMuir Maxwell Epilepsy Centre, University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK.
Western General Hospital · GBRoyal Hospital for Children · GBUniversity of Edinburgh · GBVictoria University of Wellington · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn an increasingly digital age for healthcare around the world, administrative data have become rich and accessible tools for potentially identifying and monitoring population trends in diseases including epilepsy. However, it remains unclear (1) how accurate administrative data are at identifying epilepsy within a population and (2) the optimal algorithms needed for administrative data to correctly identify people with epilepsy within a population. To address this knowledge gap, we will conduct a novel systematic review of all identified studies validating administrative healthcare data in epilepsy identification. We provide here a protocol that will outline the methods and analyses planned for the systematic review. METHODS AND ANALYSIS: The systematic review described in this protocol will be conducted to follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE and Embase will be searched for studies validating administrative data in epilepsy published from 1975 to current (01 June 2018). Included studies will validate the International Classification of Disease (ICD), Ninth Revision (ICD-9) onwards (ie, ICD-9 code 345 and ICD-10 codes G40-G41) as well as other non-ICD disease classification systems used, such as Read Codes in the UK. The primary outcome will be providing pooled estimates of accuracy for identifying epilepsy within the administrative databases validated using sensitivity, specificity, positive and negative predictive values, and area under the receiver operating characteristic curves. Heterogeneity will be assessed using the I ETHICS AND DISSEMINATION: Ethical approval is not required as primary data will not be collected. Results will be disseminated in peer-reviewed journals, conference presentations and in press releases. PROSPERO REGISTRATION: CRD42017081212.

Indexed as

Data AccuracyDatabases, FactualInternational Classification of DiseasesMedical InformaticsAlgorithmsChecklistEpilepsyHumansMeta-Analysis as TopicObservational Studies as TopicResearch DesignSystematic Reviews as Topicadministrative claimsalgorithmsepilepsyfactual databasevalidation studies

Identifiers

PMID29961014
PMCPMC6042541
OpenAlexW2811145058

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.