Evidence map›Paper›PMID 28149446›Full record

ArticleOnline journal of public health informatics2016

Modelling Medications for Public Health Research.

D van Gaans, S Ahmed, K D'Onise, J Moyon, G Caughey, R McDermott

Open access · goldAbstract read
In one paragraph

Article in Online journal of public health informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 87% 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, 1 synthesis or guideline pooled it, 0 citations in OpenAlex.

  1. Pooled it
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 at 2 institutions in 1 country.

D van GaansCentre for Research Excellence in the Prevention of Chronic Conditions in Rural and Remote Populations, University of South Australia, South Australia.
S AhmedCentre for Research Excellence in the Prevention of Chronic Conditions in Rural and Remote Populations, University of South Australia, South Australia.
K D'OniseCentre for Research Excellence in the Prevention of Chronic Conditions in Rural and Remote Populations, University of South Australia, South Australia.
J MoyonInformation Strategy and Technology, University of South Australia, South Australia.
G CaugheyPharmacy and Medical Sciences, University of South Australia, South Australia.
R McDermottCollege of Public Health, Medical and Veterinary Sciences, James Cook University, Queensland.
University of South Australia · AUJames Cook University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most patients with chronic disease are prescribed multiple medications, which are recorded in their personal health records. This is rich information for clinical public health researchers but also a challenge to analyse. This paper describes the method that was undertaken within the Public Health Research Data Management System (PHReDMS) to map medication data retrieved from individual patient health records for population health researcher's use. The PHReDMS manages clinical, health service, community and survey research data within a secure web environment that allows for data sharing amongst researchers. The PHReDMS is currently used by researchers to answer a broad range of questions, including monitoring of prescription patterns in different population groups and geographic areas with high incidence/prevalence of chronic renal, cardiovascular, metabolic and mental health issues. In this paper, we present the general notion of abstraction network, a higher level network that sits above a terminology and offers compact and more easily understandable view of its content. We demonstrate the utilisation of abstraction network methodology to examine medication data from electronic medical records to allow a compact and more easily understandable view of its content.

Indexed as

Data MappingMedicationModellingPublic Health

Identifiers

PMID28149446
PMCPMC5266755
OpenAlexW2527386613

What OpenQuestion holds

Textmetadata
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.