Evidence map›Paper›PMID 41716854›Full record

ArticleHealth systems (Basingstoke, England)2026

Accessibility of big data in medicine: adjusting the duration of antibiotic treatment for gram-negative bloodstream infections.

Liat Toderis, Iris Reychav, Roger McHaney, Itai Gueta, Dafna Yahav, Ronen Loebstein

Abstract read
In one paragraph

Article in Health systems (Basingstoke, England), 2026. 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

6 authors.

Liat ToderisIndustrial Engineering & Management Department, Ariel University, Ariel, Israel.
Iris ReychavIndustrial Engineering & Management Department, Ariel University, Ariel, Israel.
Roger McHaneyManagement Information Systems, Kansas State University, Manhattan, KS, USA.
Itai GuetaInternal Medicine VI and the Clinical Pharmacology Unit, Tel Aviv Medical Center, Tel Aviv, Israel.
Dafna YahavGray School of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
Ronen LoebsteinGray School of Medicine, Tel-Aviv University, Tel-Aviv, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current article describes a process to mitigate challenges that arise when medical practitioners and data specialists operate with differing terminologies and face technological and organizational barriers in accessing and utilizing medical big data. We present a structured methodology for improving access to clinical data and apply this approach using a case study focused on optimizing antibiotic management for patients with gram-negative bloodstream infections. Using the ArchiMate® organizational architecture language, we developed a project framework that aligns strategic, business, application, and technological layers of hospital operations. Each component was used to articulate project goals, guide the implementation process, and track intervention outcomes. After implementing a real-time monitoring tool and engaging clinicians directly in the data workflow, 65% of the identified patients received targeted interventions, and the median duration of antibiotic therapy was reduced from 6 to 5 days. Our approach enabled faster decision-making, and drove meaningful organizational change - demonstrating how structured data access can lead to improved healthcare delivery and patient outcomes.

Indexed as

antibiotic stewardshipArchiMate®Big datagram-negative bloodstream infectionsmedical data

Identifiers

PMID41716854
PMCPMC12915387

What OpenQuestion holds

Textmetadata
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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.