Evidence map›Paper›PMID 36261114›Full record

ArticleApplied clinical informatics2022

Evaluating Digital Health Capability at Scale Using the Digital Health Indicator.

Leanna Woods, Rebekah Eden, Andrew Pearce, Yu Ching Ides Wong, Lakshmi Jayan, Damian Green, Keith McNeil, Clair Sullivan

Abstract read
In one paragraph

Article in Applied clinical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. 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

8 authors.

Leanna WoodsCentre for Health Services Research, The University of Queensland, Brisbane, Australia.
Rebekah EdenSchool of Information Systems, Queensland University of Technology, Brisbane, Australia.
Andrew PearceHealthcare Information and Management Systems Society, Singapore, Singapore.
Yu Ching Ides WongPrevention Division, Queensland Health, Brisbane, Australia.
Lakshmi JayanHealthcare Information and Management Systems Society, Singapore, Singapore.
Damian GreeneHealth Queensland, Queensland Health, Brisbane, Australia.
Keith McNeilPrevention Division, Queensland Health, Brisbane, Australia.
Clair SullivanCentre for Health Services Research, The University of Queensland, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth service providers must understand their digital health capability if they are to drive digital transformation in a strategic and informed manner. Little is known about the assessment and benchmarking of digital maturity or capability at scale across an entire jurisdiction. The public health care system across the state of Queensland, Australia has an ambitious 10-year digital transformation strategy.

objectiveThe aim of this research was to evaluate the digital health capability in Queensland to inform digital health strategy and investment.

methodsThe Healthcare Information and Management Systems Society Digital Health Indicator (DHI) was used via a cross-sectional survey design to assess four core dimensions of digital health transformation: governance and workforce; interoperability; person-enabled health; and predictive analytics across an entire jurisdiction simultaneously. The DHI questionnaire was completed by each health care system (

resultsThe results reveal a variation in DHI scores reflecting the diverse stages of health care digitization across the state. The average DHI score across sites was 143 (range 78-193; SD35.3) which is similar to other systems in the Oceania region and global public systems but below the global private average. Governance and workforce was on average the highest scoring dimension (x̅= 54), followed by interoperability (x̅ = 46), person-enabled health (x̅ = 36), and predictive analytics (x̅ = 30).

conclusionThe findings were incorporated into the new digital health strategy for the jurisdiction. As one of the largest single simultaneous assessments of digital health capability globally, the findings and lessons learnt offer insights for policy makers and organizational managers.

Indexed as

BenchmarkingDelivery of Health CareAustraliaCross-Sectional StudiesHumansQueensland

Identifiers

PMID36261114
PMCPMC9581585

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.