Evidence map›Paper›PMID 28555477›Full record

ArticleGeospatial health2017

An analysis of the process and results of manual geocode correction.

Yolanda J McDonald, Michael Schwind, Daniel W Goldberg, Amanda Lampley, Cosette M Wheeler

Abstract read
In one paragraph

Article in Geospatial health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Yolanda J McDonaldDepartment of Geography, College of Geosciences, Texas A&M University, College Station, TX. ymcdonald77@tamu.edu.
Michael Schwind
Daniel W Goldberg
Amanda Lampley
Cosette M Wheeler

Funding

WOMEN'S CANCERS RESEARCH PROGRAMP30CA118100 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Yolanda Sanchez · 2005 to 2026
$57.1M
Patient- and Practice-Centered Assessment of Self-CollectionU54CA164336 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI WHEELER, COSETTE MARIE · 2011 to 2017
$5.5M
NCI NIH HHS P30 CA118100NCI NIH HHS U54 CA164336
6 · The paper itself

Abstract

Geocoding is the science and process of assigning geographical coordinates (i.e. latitude, longitude) to a postal address. The quality of the geocode can vary dramatically depending on several variables, including incorrect input address data, missing address components, and spelling mistakes. A dataset with a considerable number of geocoding inaccuracies can potentially result in an imprecise analysis and invalid conclusions. There has been little quantitative analysis of the amount of effort (i.e. time) to perform geocoding correction, and how such correction could improve geocode quality type. This study used a low-cost and easy to implement method to improve geocode quality type of an input database (i.e. addresses to be matched) through the processes of manual geocode intervention, and it assessed the amount of effort to manually correct inaccurate geocodes, reported the resulting match rate improvement between the original and the corrected geocodes, and documented the corresponding spatial shift by geocode quality type resulting from the corrections. Findings demonstrated that manual intervention of geocoding resulted in a 90% improvement of geocode quality type, took 42 hours to process, and the spatial shift ranged from 0.02 to 151,368 m. This study provides evidence to inform research teams considering the application of manual geocoding intervention that it is a low-cost and relatively easy process to execute.

Indexed as

Geographic MappingDatabases, FactualHumans

Identifiers

PMID28555477
PMCPMC5978681

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.