Evidence map›Paper›PMID 37524426›Full record

ArticleClinical medicine (London, England)2023

Streams, rivers and data lakes: an introduction to understanding modern electronic healthcare records.

Esther Ayobamidele Abisola Idowu, James Teo, Sabrine Salih, Joshua Valverde, Joshua Au Yeung

Abstract read
In one paragraph

Article in Clinical medicine (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Esther Ayobamidele Abisola IdowuGuy's and St Thomas' NHS Foundation Trust, London, UK Esther.idowu@nhs.net.
James TeoKing's College Hospital and Guy's and St Thomas' Hospital NHS Foundation Trust, London UK.
Sabrine SalihDartford and Gravesham NHS Trust, Dartford, UK.
Joshua ValverdeChesterfield Royal Hospital NHS Foundation Trust, Chesterfield, UK.
Joshua Au YeungGuy's and St Thomas' Hospital NHS Foundation Trust, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As foundation doctors, we have often found ourselves informing patients that a certain aspect of their medical information cannot be immediately found, either because it is on an electronic system we cannot access, or it is in a hospital that is unlinked to our own. Unsurprisingly, this frequently leaves patients flabbergasted and confused. We started to wonder: if patients' data are entered onto an electronic system: where do those data go? If medical data are searched for, where do those data come from? Why are there so many hidden sources of information that clinicians cannot access? In an ever-increasing digital sphere, electronic data will be the future of holistic health and social care planning, impacting every clinician's day-to-day role. From electronic healthcare records to the use of artificial intelligence solutions, this article will serve as an introduction to how data flows in modern healthcare systems.

Indexed as

Artificial IntelligencePhysiciansDelivery of Health CareElectronic Health RecordsHospitalsHumansRiversartificial intelligencedata ethicsdata standardisationelectronic health recordshealthcare data

Identifiers

PMID37524426
PMCPMC10541049

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.