Literature DB >> 32095763

A Pilot Study to Assess the Feasibility of Collecting and Transmitting Clinical Trial Data with Mobile Technologies.

Colleen Russell1, Nadir Ammour2, Toby Wells1, Nicolas Bonnet3, Matthias Kruse1, Agnes Tardat3, Christel Erales3, Thomas Shook1, Stephane Kirkesseli2, Lionel Hovsepian2, Sy Pretorius1.   

Abstract

BACKGROUND: The use of mobile technologies for data capture and transmission has the potential to streamline clinical trials, but researchers lack methods for collecting, processing, and interpreting data from these tools.
OBJECTIVES: To assess the performance of a technical platform for collecting and transmitting data from six mobile technologies in the clinic and at home, to apply methods for comparing them to clinical standard devices, and to measure their usability, including how willing subjects were to use them on a regular basis.
METHODS: In part 1 of the study, conducted over 3 weeks in the clinic, we tested two device pairs (mobile vs. clinical standard blood pressure monitor and mobile vs. clinical standard spirometer) on 25 healthy volunteers. In part 2 of the study, conducted over 3 days both in the clinic and at home, we tested the same two device pairs as in part 1, plus four additional pairs (mobile vs. clinical standard pulse oximeter, glucose meter, weight scale, and activity monitor), on 22 healthy volunteers.
RESULTS: Data collection reliability was 98.1% in part 1 of the study and 95.8% in part 2 (the percentages exclude the wearable activity monitor, which collects data continuously). In part 1, 20 of 1,049 overall expected measurements were missing (1.9%), and in part 2, 45 of 1,083 were missing (4.2%). The most common reason for missing data was a single malfunctioning spirometer (13 of 20 total missed readings) in part 1, and that the subject did not take the measurement (22 of 45 total missed readings) in part 2. Also in part 2, a higher proportion of at-home measurements than in-clinic readings were missing (12.6 vs. 2.7%). The data from this experimental study were unable to establish repeatability or agreement for every mobile technology; only the pulse oximeter demonstrated repeatability, and only the weight scale demonstrated agreement with the clinical standard device. Most mobile technologies received high "willingness to use" ratings from the patients on the questionnaires.
CONCLUSIONS: This study demonstrated that the wireless data transmission and processing platform was dependable. It also identified three critical areas of study for advancing the use of mobile technologies in clinical research: (1) if a mobile technology captures more than one type of endpoint (such as blood pressure and pulse), repeatability and agreement may need to be established for each endpoint to be included in a clinical trial; (2) researchers need to develop criteria for excluding invalid device readings (to be identified by algorithms in real time) for the population studied using ranges based on accumulated subject data and established norms; and (3) careful examination of a mobile technology's performance (reliability, repeatability, and agreement with accepted reference devices) during pilot testing is essential, even for medical devices approved by regulators.
Copyright © 2018 by S. Karger AG, Basel.

Entities:  

Keywords:  Agreement; Correlation; Data collection; Data transmission; Feasibility study; Mobile technologies; Usability

Year:  2018        PMID: 32095763      PMCID: PMC7015356          DOI: 10.1159/000493883

Source DB:  PubMed          Journal:  Digit Biomark        ISSN: 2504-110X


  11 in total

Review 1.  Measuring agreement in method comparison studies.

Authors:  J M Bland; D G Altman
Journal:  Stat Methods Med Res       Date:  1999-06       Impact factor: 3.021

2.  Working Group on Blood Pressure Monitoring of the European Society of Hypertension International Protocol for validation of blood pressure measuring devices in adults.

Authors:  Eoin O'Brien; Thomas Pickering; Roland Asmar; Martin Myers; Gianfranco Parati; Jan Staessen; Thomas Mengden; Yutaka Imai; Bernard Waeber; Paolo Palatini; William Gerin
Journal:  Blood Press Monit       Date:  2002-02       Impact factor: 1.444

3.  Mixed models for assessing correlation in the presence of replication.

Authors:  Anthony Hamlett; Louise Ryan; Paulina Serrano-Trespalacios; Russ Wolfinger
Journal:  J Air Waste Manag Assoc       Date:  2003-04       Impact factor: 2.235

Review 4.  How to regress and predict in a Bland-Altman plot? Review and contribution based on tolerance intervals and correlated-errors-in-variables models.

Authors:  Bernard G Francq; Bernadette Govaerts
Journal:  Stat Med       Date:  2016-01-28       Impact factor: 2.373

5.  Reproducibility and validity of a handheld spirometer.

Authors:  R Graham Barr; Kimberly J Stemple; Sonia Mesia-Vela; Robert C Basner; Susan J Derk; Paul K Henneberger; Donald K Milton; Brenda Taveras
Journal:  Respir Care       Date:  2008-04       Impact factor: 2.258

Review 6.  Selection of and Evidentiary Considerations for Wearable Devices and Their Measurements for Use in Regulatory Decision Making: Recommendations from the ePRO Consortium.

Authors:  Bill Byrom; Chris Watson; Helen Doll; Stephen Joel Coons; Sonya Eremenco; Rachel Ballinger; Marie Mc Carthy; Mabel Crescioni; Paul O'Donohoe; Cindy Howry
Journal:  Value Health       Date:  2017-11-07       Impact factor: 5.725

7.  Relationship between Clinic and Ambulatory Blood-Pressure Measurements and Mortality.

Authors:  José R Banegas; Luis M Ruilope; Alejandro de la Sierra; Ernest Vinyoles; Manuel Gorostidi; Juan J de la Cruz; Gema Ruiz-Hurtado; Julián Segura; Fernando Rodríguez-Artalejo; Bryan Williams
Journal:  N Engl J Med       Date:  2018-04-19       Impact factor: 91.245

8.  Mobile health: the power of wearables, sensors, and apps to transform clinical trials.

Authors:  Bernard Munos; Pamela C Baker; Brian M Bot; Michelle Crouthamel; Glen de Vries; Ian Ferguson; John D Hixson; Linda A Malek; John J Mastrototaro; Veena Misra; Aydogan Ozcan; Leonard Sacks; Pei Wang
Journal:  Ann N Y Acad Sci       Date:  2016-07-06       Impact factor: 5.691

Review 9.  Wearable Devices in Clinical Trials: Hype and Hypothesis.

Authors:  Elena S Izmailova; John A Wagner; Eric D Perakslis
Journal:  Clin Pharmacol Ther       Date:  2018-04-02       Impact factor: 6.875

Review 10.  Use of Mobile Devices to Measure Outcomes in Clinical Research, 2010-2016: A Systematic Literature Review.

Authors:  Brian Perry; Will Herrington; Jennifer C Goldsack; Cheryl A Grandinetti; Kaveeta P Vasisht; Martin J Landray; Lauren Bataille; Robert A DiCicco; Corey Bradley; Ashish Narayan; Elektra J Papadopoulos; Nirav Sheth; Ken Skodacek; Komathi Stem; Theresa V Strong; Marc K Walton; Amy Corneli
Journal:  Digit Biomark       Date:  2018-01-31
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  2 in total

1.  A systematic review of methods used to conduct decentralised clinical trials.

Authors:  Amy Rogers; Giorgia De Paoli; Selvarani Subbarayan; Rachel Copland; Kate Harwood; Joanne Coyle; Lyn Mitchell; Thomas M MacDonald; Isla S Mackenzie
Journal:  Br J Clin Pharmacol       Date:  2022-01-27       Impact factor: 3.716

Review 2.  Patient and clinician use characteristics and perceptions of pulse oximeter use: A scoping review.

Authors:  Tamara Rosic; Neysa Petrina; Melissa Baysari; Angus Ritchie; Simon K Poon
Journal:  Int J Med Inform       Date:  2022-03-18       Impact factor: 4.730

  2 in total

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