Evidence map›Paper›PMID 33616663›Full record

ArticleJAMA network open2021

Feasibility of Embedding a Scalable, Virtually Enabled Biorepository in the Electronic Health Record for Precision Medicine.

Kimberley M DeMerle, Jason N Kennedy, Octavia M Peck Palmer, Emily Brant, Chung-Chou H Chang, Robert P Dickson, David T Huang, Derek C Angus, Christopher W Seymour

Abstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Guideline
  2. Article
  3. Article
  4. Article
  5. Article
  6. Focusing on optimality for the translation of precision medicine.Journal of clinical and translational science · 2022
    Article
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

9 authors.

Kimberley M DeMerleThe Clinical Research, Investigation, and Systems Modeling of Acute illness Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Jason N KennedyThe Clinical Research, Investigation, and Systems Modeling of Acute illness Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Octavia M Peck PalmerDepartment of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
Emily BrantThe Clinical Research, Investigation, and Systems Modeling of Acute illness Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Chung-Chou H ChangThe Clinical Research, Investigation, and Systems Modeling of Acute illness Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Robert P DicksonDivision of Pulmonary and Critical Care Medicine, Department of Medicine, University of Michigan, Ann Arbor.
David T HuangThe Clinical Research, Investigation, and Systems Modeling of Acute illness Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Derek C AngusThe Clinical Research, Investigation, and Systems Modeling of Acute illness Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Christopher W SeymourThe Clinical Research, Investigation, and Systems Modeling of Acute illness Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.

Funding

Multidisciplinary Training in Critical Care Outcomes ResearchT32HL007820 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Timothy D Girard, Jeremy M Kahn · 1996 to 2026
$6.4M
Sepsis subtypes: biology, treatment, and bedside applicationR35GM119519 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Christopher W. Seymour · 2016 to 2026
$4.9M
REMISE study: REMnant biospecimen Investigation in SEpsisR21GM144851 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SEYMOUR, CHRISTOPHER WARREN · 2022 to 2023
$438k
NHLBI NIH HHS T32 HL007820NIGMS NIH HHS R21 GM144851NIGMS NIH HHS R35 GM119519
6 · The paper itself

Abstract

Importance: A cornerstone of precision medicine is the identification and use of biomarkers that help subtype patients for targeted treatment. Such an approach requires the development and subsequent interrogation of large-scale biobanks linked to well-annotated clinical data. Traditional means of creating these data-linked biobanks are costly and lengthy, especially in acute conditions that require time-sensitive clinical data and biospecimens. Objectives: To develop a virtually enabled biorepository and electronic health record (EHR)-embedded, scalable cohort for precision medicine (VESPRE) and compare the feasibility, enrollment, and costs of VESPRE with those of a traditional study design in acute care. Design, Setting, and Participants: In a prospective cohort study, the EHR-embedded screening alert was generated for 3428 patients, and 2199 patients (64%) were eligible and screened. Of these, 1027 patients (30%) were enrolled. VESPRE was developed for regulatory compliance, feasibility, internal validity, and cost in a prospective cohort of 1027 patients (aged ≥18 years) with sepsis-3 within 6 hours of presentation to the emergency department. The VESPRE infrastructure included (1) automated EHR screening, (2) remnant blood collection for creation of a virtually enabled biorepository, and (3) automated clinical data abstraction. The study was conducted at an academic institution in southwestern Pennsylvania from October 17, 2017, to June 6, 2019. Main Outcomes and Measures: Regulatory compliance, enrollment, internal validity of automated screening, biorepository acquisition, and costs. Results: Of the 1027 patients enrolled in the study, 549 were included in the proof-of-concept analysis (305 [56%] men); median (SD) age was 59 (17) years. VESPRE collected 12 963 remnant blood and urine samples and demonstrated adequate feasibility for clinical, biomarker, and microbiome analyses. Over the 20-month test, the total cost beyond the existing operations infrastructure was $39 417.50 ($14 880.00 project management, $22 717.50 laboratory supplies/staff, and $1820.00 data management)-approximately $39 per enrolled patient vs $239 per patient for a traditional cohort study. Conclusions and Relevance: Results of this study suggest that, in a large US health system that collects data using a common EHR platform and centralized laboratory system, VESPRE, a large-scale, inexpensive EHR-embedded infrastructure for precision medicine can be used. Tested in the sepsis setting, VESPRE appeared to capture a high proportion of eligible patients at low incremental cost.

Indexed as

Electronic Health RecordsPrecision MedicineAdultAgedAutomationBiological Specimen BanksBiomarkersCohort StudiesData CollectionFeasibility StudiesFemaleHumansInformation Storage and RetrievalMaleMiddle AgedProspective StudiesBiomarkers

Identifiers

PMID33616663
PMCPMC7900864

What OpenQuestion holds

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LicenceCC BY
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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.