Embedding a Medical Search Engine Within an Electronic Health Record.

Patricia Alafaireet, Jeff Belden, Matt Botkin, Karl Kochendorfer, Robin Kruse, Dylan Strecker, Jayne Williams

Abstract read

In one paragraph

Article in Missouri medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Patricia AlafaireetPatricia Alafaireet, PhD, in the Department of Health Management and Informatics, University of Missouri.

Jeff BeldenJeff Belden, MD, in the Department of Family and Community Medicine, University of Missouri.

Matt BotkinMatt Botkin, with MedSocket, Columbia.

Karl KochendorferKarl Kochendorfer, MD, is with the Department of Family and Community Medicine, University of Illinois Hospital and Health System.

Robin KruseRobin Kruse, PhD, in the Department of Family and Community Medicine, University of Missouri.

Dylan StreckerDylan Strecker, BS, in the Department of Health Management and Informatics, University of Missouri.

Jayne WilliamsJayne Williams, MA, with MedSocket, Columbia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates an information retrieval tool embedded in an electronic health record (EHR). 1-Search provides a single search for retrieving information from a variety of content sources. 1-Search's usefulness and impact were determined by measuring the extent of physicians' information needs, pre- and post-implementation user satisfaction, and the impact of 1-Search on clinical decision-making. Results support incorporation of 1-Search into the EHR, the continued use of 1-Search, and further development.

Indexed as

Access to InformationClinical Decision-MakingElectronic Health RecordsHumansMEDLINEPhysician-Patient RelationsPhysiciansQuality of Health CareSearch EngineSurveys and QuestionnairesTime Factors

Identifiers

PMID30228619

PMCPMC6140091

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.