Evidence map›Paper›PMID 29874687›Full record

ArticleApplied clinical informatics2018

Semiautomated System for Nonurgent, Clinically Significant Pathology Results.

Stacy D O'Connor, Ramin Khorasani, Stephen M Pochebit, Ronilda Lacson, Katherine P Andriole, Anuj K Dalal

Abstract read
In one paragraph

Article in Applied clinical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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.

Stacy D O'ConnorCenter for Evidence-Based Imaging and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States.
Ramin KhorasaniCenter for Evidence-Based Imaging and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States.
Stephen M PochebitDepartment of Pathology, Brigham and Women's Faulkner Hospital, Boston, Massachusetts, United States.
Ronilda LacsonCenter for Evidence-Based Imaging and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States.
Katherine P AndrioleCenter for Evidence-Based Imaging and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States.
Anuj K DalalDepartment of Internal Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States.

Funding

RESEARCH TRAINING-MEDICAL INFORMATICS 90T15LM007092 · NLM · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Nils Gehlenborg · 1992 to 2026
$32.8M
NLM NIH HHS T15 LM007092
6 · The paper itself

Abstract

backgroundFailure of timely test result follow-up has consequences including delayed diagnosis and treatment, added costs, and potential patient harm. Closed-loop communication is key to ensure clinically significant test results (CSTRs) are acknowledged and acted upon appropriately. A previous implementation of the Alert Notification of Critical Results (ANCR) system to facilitate closed-loop communication of imaging CSTRs yielded improved communication of critical radiology results and enhanced adherence to institutional CSTR policies.

objectiveThis article extends the ANCR application to pathology and evaluates its impact on closed-loop communication of new malignancies, a common and important type of pathology CSTR. MATERIALS AND

methodsThis Institutional Review Board-approved study was performed at a 150-bed community, academically affiliated hospital. ANCR was adapted for pathology CSTRs. Natural language processing was used on 30,774 pathology reports 13 months pre- and 13 months postintervention, identifying 5,595 reports with malignancies. Electronic health records were reviewed for documented acknowledgment for a random sample of reports. Percent of reports with documented acknowledgment within 15 days assessed institutional policy adherence. Time to acknowledgment was compared pre- versus postintervention and postintervention with and without ANCR alerts. Pathologists were surveyed regarding ANCR use and satisfaction.

resultsAcknowledgment within 15 days was documented for 98 of 107 (91.6%) pre- and 89 of 103 (86.4%) postintervention reports (

conclusionANCR expansion to facilitate closed-loop communication of pathology CSTRs was favorably perceived and associated with significant improved time to documented acknowledgment for new malignancies. The rate of adherence to institutional policy did not improve.

Indexed as

CommunicationLaboratory Critical ValuesPathologyAutomationDocumentationFemaleHumansMaleMiddle AgedNatural Language Processing

Identifiers

PMID29874687
PMCPMC5996775

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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.