Evidence map›Paper›PMID 28420352›Full record

Trial reportBMC medical informatics and decision making2017

Assessing the reliability of self-reported weight for the management of heart failure: application of fraud detection methods to a randomised trial of telemonitoring.

Adam Steventon, Sarwat I Chaudhry, Zhenqiu Lin, Jennifer A Mattera, Harlan M Krumholz

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

Trial report in BMC medical informatics and decision making, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00303212 (A Study of Telemonitoring to Improve Heart Failure Outcomes), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 35% 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.

NCT00303212 nacompletednot on this map

A Study of Telemonitoring to Improve Heart Failure Outcomes

TypeinterventionalSponsorYale UniversityRan2006 to 2010Enrolled1,660ConditionsCongestive Heart FailureArmsTelemonitoring
3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Telehealth in emergency medicine: A consensus conference to map the intersection of telehealth and emergency medicine.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2021
    Article
  2. Article
  3. 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

5 authors at 2 institutions in 2 countries.

Adam SteventonData Analytics, The Health Foundation, 90 Long Acre, London, WC2E 9RA, UK. adam.steventon@health.org.uk.ORCID http://orcid.org/0000-0001-8247-7520
Sarwat I ChaudhryYale School of Medicine, New Haven, USA.
Zhenqiu LinCenter for Outcomes Research and Evaluation, Yale School of Medicine, New Haven, USA.
Jennifer A MatteraCenter for Outcomes Research and Evaluation, Yale School of Medicine, New Haven, USA.
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale School of Medicine, New Haven, USA.
Health Foundation · GBYale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

backgroundSince clinical management of heart failure relies on weights that are self-reported by the patient, errors in reporting will negatively impact the ability of health care professionals to offer timely and effective preventive care. Errors might often result from rounding, or more generally from individual preferences for numbers ending in certain digits, such as 0 or 5. We apply fraud detection methods to assess preferences for numbers ending in these digits in order to inform medical decision making.

methodsThe Telemonitoring to Improve Heart Failure Outcomes trial tested an approach to telemonitoring that used existing technology; intervention patients (n = 826) were asked to measure their weight daily using a digital scale and to relay measurements using their telephone keypads. First, we estimated the number of weights subject to end-digit preference by dividing the weights by five and comparing the resultant distribution with the uniform distribution. Then, we assessed the characteristics of patients reporting an excess number of weights ending in 0 or 5, adjusting for chance reporting of these values.

resultsOf the 114,867 weight readings reported during the trial, 18.6% were affected by end-digit preference, and the likelihood of these errors occurring increased with the number of days that had elapsed since trial enrolment (odds ratio per day: 1.002, p < 0.001). At least 105 patients demonstrated end-digit preference (14.9% of those who submitted data); although statistical significance was limited, a pattern emerged that, compared with other patients, they tended to be younger, male, high school graduates and on more medications. Patients with end-digit preference reported greater variability in weight, and they generated an average 2.9 alerts to the telemonitoring system over the six-month trial period (95% CI, 2.3 to 3.5), compared with 2.3 for other patients (95% CI, 2.2 to 2.5).

conclusionsAs well as overshadowing clinically meaningful changes in weight, end-digit preference can lead to false alerts to telemonitoring systems, which may be associated with unnecessary treatment and alert fatigue. In this trial, end-digit preference was common and became increasingly so over time. By applying fraud detection methods to electronic medical data, it is possible to produce clinically significant information that can inform the design of initiatives to improve the accuracy of reporting.

trial registrationClinicalTrials.gov registration number NCT00303212 March 2006.

Indexed as

Body WeightSelf ReportDiagnostic ErrorsFemaleFraudHeart FailureHumansMaleMiddle AgedMonitoring, AmbulatoryReproducibility of ResultsTelemedicineAlert fatigueEnd-digit preferenceSelf-reportTelemedicine

Identifiers

PMID28420352
PMCPMC5395848
OpenAlexW2605575488

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.