Use of predictive algorithms in-home monitoring of chronic obstructive pulmonary disease and asthma A systematic review

Major reported factors associated with the limited effectiveness of home telemonitoring interventions in chronic respiratory conditions include the lack of useful early predictors, poor patient compliance and the poor performance of conventional algorithms for detecting deteriorations. This article...

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Bibliographic Details
Published in:Chronic respiratory disease Vol. 13; no. 3; pp. 264 - 283
Main Authors: Sanchez-Morillo, Daniel, Fernandez-Granero, Miguel A, Leon-Jimenez, Antonio
Format: Journal Article
Language:English
Published: London, England SAGE Publications 01.08.2016
Sage Publications Ltd
Subjects:
Algorithms
Asthma
Asthma - physiopathology
Chronic obstructive pulmonary disease
Humans
Monitoring, Ambulatory - methods
Physiology
Pulmonary Disease, Chronic Obstructive - physiopathology
Review Series
Telemedicine - methods
telemedicine
pulmonary disease
hospitalization/statistics
predictive analytics
physiological measurements
asthma
machine learning
decision support systems
Algorithms
telemonitoring
exacerbations
prediction
chronic obstructive pulmonary disease
ISSN:1479-9723, 1479-9731, 1479-9731
Online Access:Get full text
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Summary:Major reported factors associated with the limited effectiveness of home telemonitoring interventions in chronic respiratory conditions include the lack of useful early predictors, poor patient compliance and the poor performance of conventional algorithms for detecting deteriorations. This article provides a systematic review of existing algorithms and the factors associated with their performance in detecting exacerbations and supporting clinical decisions in patients with chronic obstructive pulmonary disease (COPD) or asthma. An electronic literature search in Medline, Scopus, Web of Science and Cochrane library was conducted to identify relevant articles published between 2005 and July 2015. A total of 20 studies (16 COPD, 4 asthma) that included research about the use of algorithms in telemonitoring interventions in asthma and COPD were selected. Differences on the applied definition of exacerbation, telemonitoring duration, acquired physiological signals and symptoms, type of technology deployed and algorithms used were found. Predictive models with good clinically reliability have yet to be defined, and are an important goal for the future development of telehealth in chronic respiratory conditions. New predictive models incorporating both symptoms and physiological signals are being tested in telemonitoring interventions with positive outcomes. However, the underpinning algorithms behind these models need be validated in larger samples of patients, for longer periods of time and with well-established protocols. In addition, further research is needed to identify novel predictors that enable the early detection of deteriorations, especially in COPD. Only then will telemonitoring achieve the aim of preventing hospital admissions, contributing to the reduction of health resource utilization and improving the quality of life of patients.
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ISSN:1479-9723
1479-9731
1479-9731
DOI:10.1177/1479972316642365