Evidence map›Paper›PMID 31316270›Full record

ArticleClinical Medicine Insights. Cardiology2019

A Review of Randomized Controlled Trials Utilizing Telemedicine for Improving Heart Failure Readmission: Can a Realist Approach Bridge the Translational Divide?

Manuel Gonzalez Garcia, Farhad Fatehi, Nazli Bashi, Marlien Varnfield, Pupalan Iyngkaran, Andrea Driscoll, Christopher Neil, David L Hare, Brian Oldenburg

Open access · goldAbstract read
In one paragraph

Article in Clinical Medicine Insights. Cardiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
1.9field-weighted citation impact, top 12% of its field
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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Observational
  7. 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 at 4 institutions in 3 countries.

Manuel Gonzalez GarciaAustralian eHealth Research Centre, CSIRO, Brisbane, QLD, Australia.ORCID https://orcid.org/0000-0002-4338-7335
Farhad FatehiAustralian eHealth Research Centre, CSIRO, Brisbane, QLD, Australia.
Nazli BashiAustralian eHealth Research Centre, CSIRO, Brisbane, QLD, Australia.
Marlien VarnfieldAustralian eHealth Research Centre, CSIRO, Brisbane, QLD, Australia.
Pupalan IyngkaranNT Medical School, Flinders University, Darwin, NT, Australia.
Andrea DriscollSchool of Nursing and Midwifery, Deakin University and Austin Health, Geelong, VIC, Australia.
Christopher NeilDepartment of Medicine - Western Health, The University of Melbourne, Melbourne, VIC, Australia.
David L HareThe University of Melbourne, Austin Health, Melbourne, VIC, Australia.
Brian OldenburgWHO Collaborating Centre on Implementation Research for Prevention & Control of NCDs, Melbourne School of Population and Global Health, The University of Melbourne, VIC, Australia.
Commonwealth Scientific and Industrial Research Organisation · AUThe University of Melbourne · AUDeakin University · AUFlinders University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelemedicine and digital health technologies hold great promise for improving clinical care of heart failure. However, inconsistent and contradictory findings from randomized controlled trials have so far discouraged widespread adoption of digital health in routine clinical practice. We undertook this review study to summarize the study outcomes of the use of exploring the evidence for telemedicine in the clinical care of patients with heart failure and readmissions.

methodsWe inspected the references of guidelines and searched PubMed for randomized controlled trials published over the past 10 years on the use of telemedicine for reducing readmission in heart failure. We utilized a modified realist review approach to identify the underlying contextual mechanisms for the intervention(s) in each randomized controlled trial, evaluating outcomes of the intervention and understanding how and under what conditions they worked. To provide uniformity, all extracted data were synthesized using adapted domains from the taxonomy for disease management created by the Disease Management Taxonomy Writing Group.

resultsA total of 12 papers were eligible, 6 of them supporting and 6 others undermining the use of telemedicine for improving heart failure readmission. In general terms, those studies not supporting the use of telemedicine were multicentre, publicly funded, with large amount of participants, and long duration. The patients had also better rates of treatment with angiotensin-converting enzyme inhibitors/angiotensin II receptor blocker and beta-blockers, and telemonitoring and automatic transmission of vital signs were less utilized, in comparison with the studies in which telemedicine use was supported. The analysis of the environment, intensity, content of interventions, method of communication, quality of the underlying model of care and the ability, capability, and interest from health workers can help us to envisage probabilities of success of telemedicine use.

conclusionsA realist lens may aid to understand whom and in which circumstances the use of telemedicine can add any substantial value to traditional models of care. Wider outcome criteria beyond major adverse cardiovascular events, for example, cost efficacy, should also be considered as appropriate for effecting guidelines on care delivery when robust prognostic therapeutics already exist.

Indexed as

Heart failurereadmissionreviewtechnologytelemedicine

Identifiers

PMID31316270
PMCPMC6620724
OpenAlexW2958199041

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.