Evidence map›Paper›PMID 32599144›Full record

ArticleThe spine journal : official journal of the North American Spine Society2021

SMART on FHIR in spine: integrating clinical prediction models into electronic health records for precision medicine at the point of care.

Aditya V Karhade, Joseph H Schwab, Guilherme Del Fiol, Kensaku Kawamoto

Abstract read
In one paragraph

Article in The spine journal : official journal of the North American Spine Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Review
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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

4 authors.

Aditya V KarhadeDepartment of Orthopedic Surgery, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, MA 02114, USA. Electronic address: akarhade@partners.org.
Joseph H SchwabDepartment of Orthopedic Surgery, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, MA 02114, USA.
Guilherme Del FiolDepartment of Biomedical Informatics, University of Utah, 421 Wakara Way, Ste 140, Salt Lake City, UT 84108, USA.
Kensaku KawamotoDepartment of Biomedical Informatics, University of Utah, 421 Wakara Way, Ste 140, Salt Lake City, UT 84108, USA.

Funding

Scalable Clinical Decision Support for Individualized Cancer Risk ManagementU24CA204800 · NCI · UNIVERSITY OF UTAH · PI DEL FIOL, GUILHERME, KAWAMOTO, KENSAKU · 2017 to 2021
$3.7M
Promoting Real World Implementation of an Evidence-Based Weight Management Intervention in Primary CareR18DK123372 · NIDDK · UNIVERSITY OF UTAH · PI CONROY, MARGARET B, KAWAMOTO, KENSAKU · 2020 to 2024
$3.1M
NCI NIH HHS U24 CA204800NIDDK NIH HHS R18 DK123372
6 · The paper itself

Abstract

Recent applications of artificial intelligence have shown great promise for improving the quality and efficiency of clinical care. Numerous clinical decision support tools exist in today's electronic health records (EHRs) such as medication dosing support, order facilitators (eg, procedure specific order sets), and point of care alerts. However, less has been done to integrate artificial intelligence (AI)-enabled risk predictors into EHRs despite wide availability of validated risk prediction tools. An interoperability standard known as SMART on FHIR (substitutable medical applications and reusable technologies on fast health interoperability resources) offers a promising path forward, enabling digital innovations to be seamlessly integrated with the EHR with regard to the user interface and patient data. For the next step in progress towards the goal of learning healthcare and informatics-enabled spine surgery, we propose the application of SMART on FHIR to integrate existing and new risk predictions tools in spine surgery through an EHR add-on-application.

Indexed as

Electronic Health RecordsPrecision MedicineArtificial IntelligenceHumansModels, StatisticalPoint-of-Care SystemsPrognosisSoftwareArtificial intelligenceClinical decision supportDiagnosisElectronic medical recordsIntegrationMachine learningNatural language processingPredictionSMART on FHIRSpine

Identifiers

PMID32599144
PMCPMC7762727

What OpenQuestion holds

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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.