Evidence map›Paper›PMID 23304387›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012

Harnessing a health information exchange to identify surgical device adverse events for urogynecologic mesh.

Jeanne Ballard, Marc Rosenman, Michael Weiner

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012. 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. Review
  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

3 authors.

Jeanne BallardIndiana University School of Medicine, Indianapolis, IN, USA.
Marc Rosenman
Michael Weiner

Funding

REGENSTRIEF MEDICAL INFORMATICS RESEARCH FELLOWSHIPST15LM007117 · NLM · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI FINNELL, JOHN T · 1997 to 2011
$5.0M
NLM NIH HHS 5T 15 LM007117-1
6 · The paper itself

Abstract

We sought to create an automated means to conduct surveillance of complications related to urogynecologic mesh because current postmarket surveillance fails to detect the true incidence of device-related adverse events. Using health information exchange data, we developed a search algorithm to identify urogynecologic surgeries with mesh implantation and associated inpatient adverse events. We validated the algorithm search results against those obtained from a manual case review of mesh surgical records. Our refined automated search strategy matched 93% of the 2874 mesh cases manually identified, and further identified 97% of 2103 vaginal mesh cases. Complications were identified in 380 of the 2874 mesh cases. This is the first known report of an automated process for identifying urogynecologic surgical mesh implantation cases from a health information exchange. Automated surveillance of health information exchange data may contribute to tracking of device-related adverse events.

Indexed as

Health Information ManagementHealth Information SystemsAlgorithmsElectronic Health RecordsFemaleHumansProduct Surveillance, PostmarketingSurgical MeshUrinary Incontinence, StressUterine Prolapse

Identifiers

PMID23304387
PMCPMC3540568

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.