Determination of Personalized Asthma Triggers From Multimodal Sensing and a Mobile App: Observational Study.

asthma control asthma management childhood asthma medical internet of things medication adherence patient-generated health data pediatric asthma personalized digital health understanding and treatment of asthma

Journal

JMIR pediatrics and parenting
ISSN: 2561-6722
Titre abrégé: JMIR Pediatr Parent
Pays: Canada
ID NLM: 101727244

Informations de publication

Date de publication:
27 Jun 2019
Historique:
received: 06 04 2019
accepted: 09 06 2019
revised: 22 05 2019
entrez: 14 9 2019
pubmed: 14 9 2019
medline: 14 9 2019
Statut: epublish

Résumé

Asthma is a chronic pulmonary disease with multiple triggers. It can be managed by strict adherence to an asthma care plan and by avoiding these triggers. Clinicians cannot continuously monitor their patients' environment and their adherence to an asthma care plan, which poses a significant challenge for asthma management. In this study, pediatric patients were continuously monitored using low-cost sensors to collect asthma-relevant information. The objective of this study was to assess whether kHealth kit, which contains low-cost sensors, can identify personalized triggers and provide actionable insights to clinicians for the development of a tailored asthma care plan. The kHealth asthma kit was developed to continuously track the symptoms of asthma in pediatric patients and monitor the patients' environment and adherence to their care plan for either 1 or 3 months. The kit consists of an Android app-based questionnaire to collect information on asthma symptoms and medication intake, Fitbit to track sleep and activity, the Peak Flow meter to monitor lung functions, and Foobot to monitor indoor air quality. The data on the patient's outdoor environment were collected using third-party Web services based on the patient's zip code. To date, 107 patients consented to participate in the study and were recruited from the Dayton Children's Hospital, of which 83 patients completed the study as instructed. Patient-generated health data from the 83 patients who completed the study were included in the cohort-level analysis. Of the 19% (16/83) of patients deployed in spring, the symptoms of 63% (10/16) and 19% (3/16) of patients suggested pollen and particulate matter (PM2.5), respectively, to be their major asthma triggers. Of the 17% (14/83) of patients deployed in fall, symptoms of 29% (4/17) and 21% (3/17) of patients suggested pollen and PM2.5, respectively, to be their major triggers. Among the 28% (23/83) of patients deployed in winter, PM2.5 was identified as the major trigger for 83% (19/23) of patients. Similar correlations were not observed between asthma symptoms and factors such as ozone level, temperature, and humidity. Furthermore, 1 patient from each season was chosen to explain, in detail, his or her personalized triggers by observing temporal associations between triggers and asthma symptoms gathered using the kHealth asthma kit. The continuous monitoring of pediatric asthma patients using the kHealth asthma kit generates insights on the relationship between their asthma symptoms and triggers across different seasons. This can ultimately inform personalized asthma management and intervention plans.

Sections du résumé

BACKGROUND BACKGROUND
Asthma is a chronic pulmonary disease with multiple triggers. It can be managed by strict adherence to an asthma care plan and by avoiding these triggers. Clinicians cannot continuously monitor their patients' environment and their adherence to an asthma care plan, which poses a significant challenge for asthma management.
OBJECTIVE OBJECTIVE
In this study, pediatric patients were continuously monitored using low-cost sensors to collect asthma-relevant information. The objective of this study was to assess whether kHealth kit, which contains low-cost sensors, can identify personalized triggers and provide actionable insights to clinicians for the development of a tailored asthma care plan.
METHODS METHODS
The kHealth asthma kit was developed to continuously track the symptoms of asthma in pediatric patients and monitor the patients' environment and adherence to their care plan for either 1 or 3 months. The kit consists of an Android app-based questionnaire to collect information on asthma symptoms and medication intake, Fitbit to track sleep and activity, the Peak Flow meter to monitor lung functions, and Foobot to monitor indoor air quality. The data on the patient's outdoor environment were collected using third-party Web services based on the patient's zip code. To date, 107 patients consented to participate in the study and were recruited from the Dayton Children's Hospital, of which 83 patients completed the study as instructed.
RESULTS RESULTS
Patient-generated health data from the 83 patients who completed the study were included in the cohort-level analysis. Of the 19% (16/83) of patients deployed in spring, the symptoms of 63% (10/16) and 19% (3/16) of patients suggested pollen and particulate matter (PM2.5), respectively, to be their major asthma triggers. Of the 17% (14/83) of patients deployed in fall, symptoms of 29% (4/17) and 21% (3/17) of patients suggested pollen and PM2.5, respectively, to be their major triggers. Among the 28% (23/83) of patients deployed in winter, PM2.5 was identified as the major trigger for 83% (19/23) of patients. Similar correlations were not observed between asthma symptoms and factors such as ozone level, temperature, and humidity. Furthermore, 1 patient from each season was chosen to explain, in detail, his or her personalized triggers by observing temporal associations between triggers and asthma symptoms gathered using the kHealth asthma kit.
CONCLUSIONS CONCLUSIONS
The continuous monitoring of pediatric asthma patients using the kHealth asthma kit generates insights on the relationship between their asthma symptoms and triggers across different seasons. This can ultimately inform personalized asthma management and intervention plans.

Identifiants

pubmed: 31518318
pii: v2i1e14300
doi: 10.2196/14300
pmc: PMC6716491
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e14300

Subventions

Organisme : NICHD NIH HHS
ID : R01 HD087132
Pays : United States

Informations de copyright

©Revathy Venkataramanan, Krishnaprasad Thirunarayan, Utkarshani Jaimini, Dipesh Kadariya, Hong Yung Yip, Maninder Kalra, Amit Sheth. Originally published in JMIR Pediatrics and Parenting (http://pediatrics.jmir.org), 27.06.2019.

Références

JMIR Pediatr Parent. 2018 Jul-Dec;1(2):e11988
pubmed: 31008446
An Esp Pediatr. 2000 Apr;52(4):327-33
pubmed: 11003923
J Allergy Clin Immunol. 2006 Mar;117(3):549-56
pubmed: 16522452
BMJ Open Sport Exerc Med. 2015 Jul 8;1(1):e000013
pubmed: 27900119
J Pediatr Psychol. 2003 Jul-Aug;28(5):323-33
pubmed: 12808009
J Am Med Inform Assoc. 2017 May 01;24(3):619-632
pubmed: 27694279
JMIR Mhealth Uhealth. 2017 Aug 02;5(8):e113
pubmed: 28768606
J Clin Invest. 1994 Dec;94(6):2200-8
pubmed: 7989575
Chron Respir Dis. 2017 Nov;14(4):407-419
pubmed: 27512084
Ann Allergy Asthma Immunol. 2000 Nov;85(5):416-21
pubmed: 11101187
Chronobiol Int. 2018 Apr;35(4):465-476
pubmed: 29235907
Ann Allergy Asthma Immunol. 2017 Nov;119(5):415-421.e1
pubmed: 29150069
RTSI. 2017 Sep;2017:
pubmed: 29399675
IEEE Internet Comput. 2019 Mar-Apr;23(2):6-12
pubmed: 33746506
Arch Pediatr. 1995 Apr;2(4):324-7
pubmed: 7780539
Nature. 2005 Dec 1;438(7068):667-70
pubmed: 16319891
Proc Int Conf Smart Comput SMARTCOMP. 2019 Jun;2019:138-143
pubmed: 32832938
J Asthma. 2012 Dec;49(10):991-8
pubmed: 23574397
Eur Clin Respir J. 2015 Jan 16;2:
pubmed: 26557257
Eur Respir J. 2015 Feb;45(2):396-407
pubmed: 25323234
J Allergy Clin Immunol. 2005 Apr;115(4):689-99
pubmed: 15805986
J Asthma. 2004 Jun;41(4):471-6
pubmed: 15281333
JMIR Mhealth Uhealth. 2018 Jun 04;6(6):e133
pubmed: 29866644
IEEE Sens Lett. 2017 Apr;1(2):
pubmed: 29082361

Auteurs

Revathy Venkataramanan (R)

Ohio Center of Excellence in Knowledge-enabled Computing, Wright State University, Dayton, OH, United States.

Krishnaprasad Thirunarayan (K)

Ohio Center of Excellence in Knowledge-enabled Computing, Wright State University, Dayton, OH, United States.

Utkarshani Jaimini (U)

Ohio Center of Excellence in Knowledge-enabled Computing, Wright State University, Dayton, OH, United States.

Dipesh Kadariya (D)

Ohio Center of Excellence in Knowledge-enabled Computing, Wright State University, Dayton, OH, United States.

Hong Yung Yip (HY)

Ohio Center of Excellence in Knowledge-enabled Computing, Wright State University, Dayton, OH, United States.

Maninder Kalra (M)

Dayton Children's Hospital, Dayton, OH, United States.

Amit Sheth (A)

Ohio Center of Excellence in Knowledge-enabled Computing, Wright State University, Dayton, OH, United States.

Classifications MeSH