Evidence map›Paper›PMID 36451257›Full record

ReviewJournal of the American Medical Informatics Association : JAMIA2023

Digital health and capability maturity models-a critical thematic review and conceptual synthesis of the literature.

Siaw-Teng Liaw, Myron Anthony Godinho

Abstract readReview
In one paragraph

Review in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

  1. Pooled it
  2. The current state of electronic health records across Canada: an environmental scan and interoperability maturity assessment.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2026
    Article
  3. Article
  4. Review
  5. 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
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. A maturity model for Clinical Trials Management Ecosystem.Journal of clinical and translational science · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. 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

2 authors.

Siaw-Teng LiawWHO Collaborating Centre for eHealth (AUS-135), School of Population Health, UNSW Sydney, Sydney, Australia.ORCID 0000-0001-5989-3614
Myron Anthony GodinhoWHO Collaborating Centre for eHealth (AUS-135), School of Population Health, UNSW Sydney, Sydney, Australia.ORCID 0000-0002-0081-2506

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveA literature review of capability maturity models (MMs) to inform the conceptualization, development, implementation, evaluation, and mainstreaming of MMs in digital health (DH).

methodsElectronic databases were searched using "digital health," "maturity models," and related terms based on the Digital Health Profile and Maturity Assessment Toolkit Maturity Model (DHPMAT-MM). Covidence was used to screen, identify, capture, and achieve consensus on data extracted by the authors. Descriptive statistics were generated. A thematic analysis and conceptual synthesis were conducted.

findingsDiverse domain-specific MMs and model development, implementation, and evaluation methods were found. The spread and pattern of different MMs verified the essential DH foundations and five maturity stages of the DHPMAT-MM. An unanticipated finding was the existence of a new category of community-facing MMs. Common characteristics included:1. A dynamic lifecycle approach to digital capability maturity, which is:a. responsive to environmental changes and may improve or worsen over time;b. accumulative, incorporating the attributes of the preceding stage; andc. sequential, where no maturity stage must be skipped.2. Sociotechnical quality improvement of the DH ecosystem and MM, which includes:a. investing in the organization's human, hardware, and software resources andb. a need to engage and improve the DH competencies of citizens.

conclusionsThe diversity in MMs and variability in methods and content can create cognitive dissonance. A metamodel like the DHPMAT-MM can logically unify the many domain-specific MMs and guide the overall implementation and evaluation of DH ecosystems and MMs over the maturity lifecycle.

Indexed as

Concept FormationEcosystemComputersHumansInformation SystemsSoftwarecapability maturityconceptual frameworkdigital healthdigital maturitymaturity modelmodel development

Identifiers

PMID36451257
PMCPMC9846694

What Socratic 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 Socratic graph.