Evidence map›Paper›PMID 31667818›Full record

ArticleApplied clinical informatics2019

Towards a Maturity Model for Clinical Decision Support Operations.

Evan W Orenstein, Naveen Muthu, Asli O Weitkamp, Daria F Ferro, Mike D Zeidlhack, Jason Slagle, Eric Shelov, Marc C Tobias

Abstract read
In one paragraph

Article in Applied clinical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

  1. Pooled it
  2. Review
  3. The Maturity of Maturity Models in Health Care and Informatics.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026
    Article
  4. Article
  5. Article
  6. The Burden of a Highly Targeted Alert.Applied clinical informatics · 2025
    Article
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  8. Review
  9. 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

8 authors.

Evan W OrensteinDepartment of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States.
Naveen MuthuDepartment of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Asli O WeitkampDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States.
Daria F FerroDepartment of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Mike D ZeidlhackPhrase Health Inc., Philadelphia, Pennsylvania, United States.
Jason SlagleDepartment of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States.
Eric ShelovDepartment of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
Marc C TobiasPhrase Health Inc., Philadelphia, Pennsylvania, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical decision support (CDS) systems delivered through the electronic health record are an important element of quality and safety initiatives within a health care system. However, managing a large CDS knowledge base can be an overwhelming task for informatics teams. Additionally, it can be difficult for these informatics teams to communicate their goals with external operational stakeholders and define concrete steps for improvement. We aimed to develop a maturity model that describes a roadmap toward organizational functions and processes that help health care systems use CDS more effectively to drive better outcomes. We developed a maturity model for CDS operations through discussions with health care leaders at 80 organizations, iterative model development by four clinical informaticists, and subsequent review with 19 health care organizations. We ceased iterations when feedback from three organizations did not result in any changes to the model. The proposed CDS maturity model includes three main "pillars": "Content Creation," "Analytics and Reporting," and "Governance and Management." Each pillar contains five levels-advancing along each pillar provides CDS teams a deeper understanding of the processes CDS systems are intended to improve. A "roof" represents the CDS functions that become attainable after advancing along each of the pillars. Organizations are not required to advance in order and can develop in one pillar separately from another. However, we hypothesize that optimal deployment of preceding levels and advancing in tandem along the pillars increase the value of organizational investment in higher levels of CDS maturity. In addition to describing the maturity model and its development, we also provide three case studies of health care organizations using the model for self-assessment and determine next steps in CDS development.

Indexed as

Decision Support Systems, ClinicalResearch DesignStakeholder Participation

Identifiers

PMID31667818
PMCPMC6821535

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.