Evidence map›Paper›PMID 35251753›Full record

ArticleJournal of pathology informatics2022

Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software.

Simone Arvisais-Anhalt, Christoph U Lehmann, Justin A Bishop, Jyoti Balani, Laurie Boutte, Marjorie Morales, Jason Y Park, Ellen Araj

Abstract read
In one paragraph

Article in Journal of pathology informatics, 2022. 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

8 authors.

Simone Arvisais-AnhaltDepartment of Hospital Medicine and Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA.
Christoph U LehmannClinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Justin A BishopDepartment of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Jyoti BalaniDepartment of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Laurie BoutteHealth System Quality & Operational Excellence, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Marjorie MoralesHealth System Quality & Operational Excellence, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Jason Y ParkDepartment of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Ellen ArajDepartment of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Funding

UT Southwestern Center for Translational MedicineUL1TR003163 · NCATS · UT SOUTHWESTERN MEDICAL CENTER · PI TOTO, ROBERT DANIEL · 2021 to 2025
$39.3M
NCATS NIH HHS UL1 TR003163
6 · The paper itself

Abstract

Although the laboratory information system has largely solved the problem of storing anatomic pathology reports and disseminating their contents across the healthcare system, the retrospective query of anatomic pathology reports remains an area for improvement across laboratory information system vendors. Our institution desired the ability to query our repository of anatomic pathology reports for clinical, operational, research, and educational purposes. To address this need, we developed a full-text anatomic pathology search tool using the business intelligence software, Tableau. Our search tool allows users to query the 333,685 anatomic pathology reports from our institutional clinical relational database using the business intelligence tool's built-in regular expression functionality. Users securely access the search tool using any web browser, thereby avoiding the cost of installing or maintaining software on users' computers. This tool is laboratory information system vendor agnostic and as many institutions already subscribe to business intelligence software, we believe this solution could be easily reproduced at other institutions and in other clinical departments.

Identifiers

PMID35251753
PMCPMC8892022

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.