Evidence map›Paper›PMID 25986472›Full record

Trial reportMedical decision making : an international journal of the Society for Medical Decision Making2015

An Approach to Assess Generalizability in Comparative Effectiveness Research: A Case Study of the Whole Systems Demonstrator Cluster Randomized Trial Comparing Telehealth with Usual Care for Patients with Chronic Health Conditions.

Adam Steventon, Richard Grieve, Martin Bardsley

Registry-linked trialOpen access · greenAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Medical decision making : an international journal of the Society for Medical Decision Making, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03713333 (Implementation of High Definition Screening Using Handheld Imaging and Digital Health Technologies Within a Learning Health System to Identify Cardiovascular Disease at the Point-of-care), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
8.7field-weighted citation impact, top 3% 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.

NCT03713333 nacompletednot on this mapstarted 2018, after this paper: background citation

Implementation of High Definition Screening Using Handheld Imaging and Digital Health Technologies Within a Learning Health System to Identify Cardiovascular Disease at the Point-of-care: The ASE-INNOVATE Program

TypeinterventionalSponsorScripps HealthRan2018 to 2020Enrolled374ConditionsCardiovascular Diseases, Hypertension, Heart Failure, Atrial FibrillationArmsDigital Health Device Diagnostics
3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
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

3 authors at 2 institutions in 1 country.

Adam SteventonHealth Foundation, London, UK (AS)
Richard GrieveLondon School of Hygiene and Tropical Medicine, Keppel Street, London (AS, RG)
Martin BardsleyNuffield Trust, London (MB).
University of London · GBLondon School of Hygiene & Tropical Medicine · GB

Funding

Department of Health SRF-2013-06-016Medical Research Council G106/1173
6 · The paper itself

Abstract

backgroundPolicy makers require estimates of comparative effectiveness that apply to the population of interest, but there has been little research on quantitative approaches to assess and extend the generalizability of randomized controlled trial (RCT)-based evaluations. We illustrate an approach using observational data.

methodsOur example is the Whole Systems Demonstrator (WSD) trial, in which 3230 adults with chronic conditions were assigned to receive telehealth or usual care. First, we used novel placebo tests to assess whether outcomes were similar between the RCT control group and a matched subset of nonparticipants who received usual care. We matched on 65 baseline variables obtained from the electronic medical record. Second, we conducted sensitivity analysis to consider whether the estimates of treatment effectiveness were robust to alternative assumptions about whether "usual care" is defined by the RCT control group or nonparticipants. Thus, we provided alternative estimates of comparative effectiveness by contrasting the outcomes of the RCT telehealth group and matched nonparticipants.

resultsFor some endpoints, such as the number of outpatient attendances, the placebo tests passed, and the effectiveness estimates were robust to the choice of comparison group. However, for other endpoints, such as emergency admissions, the placebo tests failed and the estimates of treatment effect differed markedly according to whether telehealth patients were compared with RCT controls or matched nonparticipants.

conclusionsThe proposed placebo tests indicate those cases when estimates from RCTs do not generalize to routine clinical practice and motivate complementary estimates of comparative effectiveness that use observational data. Future RCTs are recommended to incorporate these placebo tests and the accompanying sensitivity analyses to enhance their relevance to policy making.

Indexed as

Primary Health CareTelemedicineChronic DiseaseCluster AnalysisComparative Effectiveness ResearchElectronic Health RecordsEmergency Service, HospitalEnglandHumansPlacebosTreatment OutcomePlaceboscausal inferencechronic health conditionsexternal validitygeneralizabilityrandomized trialstelehealth

Identifiers

PMID25986472
PMCPMC4592957
OpenAlexW2152994989

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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.