Evidence map›Paper›PMID 32239462›Full record

ReviewJournal of general internal medicine2020

A Narrative Review and Proposed Framework for Using Health System Data with Systematic Reviews to Support Decision-making.

Jennifer S Lin, M Hassan Murad, Brian Leas, Jonathan R Treadwell, Roger Chou, Ilya Ivlev, Devan Kansagara

Abstract readReview
In one paragraph

Review in Journal of general internal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 5 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, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Review
  7. Article
  8. Review
  9. Review
  10. 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

7 authors.

Jennifer S LinKaiser Permanente Research Affiliates Evidence-based Practice Center, Portland, OR, USA. Jennifer.s.lin@kpchr.org.
M Hassan MuradMayo Clinic Evidence-based Practice Center, Rochester, MN, USA.
Brian LeasECRI Institute-Penn Medicine Evidence-based Practice Center, Plymouth Meeting, PA, USA.
Jonathan R TreadwellECRI Institute-Penn Medicine Evidence-based Practice Center, Plymouth Meeting, PA, USA.
Roger ChouPacific Northwest Evidence-based Practice Center, Portland, OR, USA.
Ilya IvlevKaiser Permanente Research Affiliates Evidence-based Practice Center, Portland, OR, USA.
Devan KansagaraVeterans Health Administration Health Services Research Department Evidence Synthesis Program, Portland, OR, USA.

Funding

NW Center of Excellence & K12 in Patient Centered Learning Health Systems ScienceK12HS026370 · AHRQ · OREGON HEALTH & SCIENCE UNIVERSITY · PI EDEN, KAREN BEEKMAN, GUISE, JEANNE-MARIE · 2018 to 2022
$4.0M
AHRQ HHS 290-2015-00005-IAHRQ HHS 290-2015-00009-IAHRQ HHS 290-3200-1T-05AHRQ HHS HHSA 290-2015-00007-IAHRQ HHS K12 HS026370
6 · The paper itself

Abstract

Systematic reviews are a necessary, but often insufficient, source of information to address the decision-making needs of health systems. In this paper, we address when and how the use of health system data might make systematic reviews more useful to decision-makers. We describe the different ways in which health system data can be used with systematic reviews, identify scenarios in which the addition of health system data may be most helpful (i.e., to improve the strength of evidence, to improve the applicability of evidence, and to inform the implementation of evidence), and discuss the importance of framing the limitations and considerations when using unpublished health system data in reviews. We developed a framework to guide the use of health system data alongside systematic reviews based on a narrative review of the literature and empirical experience. We also offer recommendations to improve the transparency of reporting when using health system data alongside systematic reviews including providing rationale for employing additional data, details on the data source, critical appraisal to understand study design biases as well as limitations in data and information quality, and how the unpublished data compares to the systematically reviewed data. Future methodological work on how best to handle internal and external validity concerns of health system data in the context of systematically reviewed data and work on developing infrastructure to do this type of work is needed.

Indexed as

Government ProgramsResearch DesignHumanshealth system datalearning health system(s)systematic review(s)unpublished data

Identifiers

PMID32239462
PMCPMC7280421

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.