Evidence map›Paper›PMID 31239899›Full record

ArticleAcademic forensic pathology2016

Surveillance of Drug Overdoses Using Google Fusion Tables.

Matthew D Cain, Gerald McGwin, Daniel Atherton

Erratum issuedAbstract read
In one paragraph

Article in Academic forensic pathology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Matthew D CainUniversity of Alabama at Birmingham - Pathology.
Gerald McGwinUniversity of Alabama-Birmingham - School of Public Health.
Daniel AthertonUniversity of Alabama at Birmingham - Pathology.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDrug use is a constantly evolving public health challenge. We present the use of Google Fusion Tables and Google Maps for the surveillance of drug-related deaths and discuss its potential large-scale use.

methodsDemographic and geographic data for deaths related to cocaine and heroin use occurring from 2012-2014 was queried from the Jefferson County Coroner/Medical Examiner's Office. Fusion Tables was then used to plot each address onto a map.

resultsWe developed a method to automatically import data into Fusion Tables. Individualized icons were then used to denote specific demographics and locations on a Google Map where filters could be applied to visualize findings such as only 18-25 year old white males. These features provided an easy means to visualize the relative high frequency of heroin-related deaths in white males. Furthermore, the date filters highlighted heroin-related deaths more than doubled in 2014 compared to previous years.

conclusionsMapping of health-related data has a long-standing history in public health, though its use in the forensic pathology community is limited. Fusion Tables provides users with the ability to visualize and analyze patterns and share data. Many geocoding solutions exist; however, we found this software to be user friendly and flexible. Our office now includes these visualizations into the annual summary that is provided to local law enforcement, public health officials, and the general public.

Indexed as

DrugsForensic pathologyFusion tablesMapOverdose

Identifiers

PMID31239899
PMCPMC6507003

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.