“How Is My Child’s Asthma?” Digital Phenotype and Actionable Insights for Pediatric Asthma

Jaimini, Utkarshani; Thirunarayan, Krishnaprasad; Kalra, Maninder; Venkataramanan, Revathy; Kadariya, Dipesh; Sheth, Amit P.

doi:10.2196/11988

Cited by 38 publications

(31 citation statements)

References 20 publications

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“…Personalized insights gathered using the kHealth kit are explained in detail in the Discussion section by choosing 1 patient from each season for illustration. The cohort-level and adherence statistics have already been presented in our previous study [45].…”

Section: Resultsmentioning

confidence: 99%

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

Venkataramanan¹,

Thirunarayan²,

Jaimini³

et al. 2019

JMIR Pediatr Parent

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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 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 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 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 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.

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Section: Resultsmentioning

confidence: 99%

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

Venkataramanan¹,

Thirunarayan²,

Jaimini³

et al. 2019

JMIR Pediatr Parent

Self Cite

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“… 40 The kHealth system and Automated Device for Asthma Monitoring assist in remote monitoring gathering real-time data. 41 , 42 …”

Section: Discussionmentioning

confidence: 99%

Developing and evaluating ASTHMAXcel adventures

Hsia

Singh

Njeze

et al. 2020

Annals of Allergy, Asthma & Immunology

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Background The ASTHMAXcel mobile application has been linked to favorable outcomes among adult patients with asthma. Objective We assessed the impact of ASTHMAXcel Adventures, a gamified, guideline-based, pediatric version on asthma control, knowledge, health care utilization, and patient satisfaction. Methods Pediatric patients with asthma received the ASTHMAXcel Adventures mobile intervention on-site only at baseline (visit 1), 4 months (visit 2), and 6 months (visit 3). The asthma control test, asthma illness representation scale–self-administered, pediatric asthma impact survey, and Client Satisfaction Questionnaire-8 were used to assess asthma control, knowledge, and patient satisfaction. Patients reported the number of asthma-related emergency department (ED) visits, hospitalizations, and oral prednisone use. Results A total of 39 patients completed the study. The proportion of controlled asthma increased from visit 1 to visits 2 and 3 (30.8% vs 53.9%, P = .04; 30.8% vs 59.0%, P = .02), and largely seen in boys. The mean asthma illness representation scale–self-administered scores increased from baseline pre- to postintervention, with sustained improvements at visits 2 and 3 (3.55 vs 3.76, P < .001; 3.55 vs 3.80, P = .001; 3.55 vs 3.99, P < .001). The pediatric asthma impact survey scores improved from baseline to visits 2 and 3 (43.33 vs 34.08, P < .001; 43.33 vs 31.74, P < .001). ED visits and prednisone use significantly decreased from baseline to visits 2 and 3 (ED: 0.46 vs 0.13, P = .03; 0.46 vs 0.02, P = .02; prednisone use, 0.49 vs 0.13, P = .02; 0.49 vs 0.03, P = .003. Satisfaction was high with mean client satisfaction questionnaire score of approximately 30 (out of 32) at all visits. Conclusion ASTHMAXcel Adventures improved asthma control, knowledge, and quality of life, and reduced ED visits and prednisone use with high satisfaction scores.

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“…The Fitbit device tended to overestimate sleep efficiency and underestimate wake counts compared with actigraphy. Two additional studies were conducted in pediatric populations and focused on correlating Fitbit-derived sleep measures to patient-reported outcomes such as asthma control and asthma impact [21,22]. Bian and colleagues assessed the association between self-reported asthma impact and Fitbit-derived sleep quality (the ratio of minutes asleep to minutes in bed) and physical activity measures (daily minutes of moderate and vigorous activity) in adolescents with asthma [21].…”

Section: Wearable Devices In Asthmamentioning

confidence: 99%

“…These findings suggest that measurement of sleep quality, using the Fitbit device, may help develop personalized asthma management strategies for children and their caregivers in real time. The final study measured several mobile metrics of asthma including physical activity and sleep using Fitbits, forced expiratory volume in 1 s and peak expiratory flow, indoor air quality using Foobot (https://foobot.io/), and a mobile app that collected information on asthma control (symptoms, physical limitations due to asthma, nighttime awakenings, and medication intake) [22]. These metrics were used together to digitally phenotype children with asthma and provide a better measure of the patient's asthma control to their clinician when compared with the Asthma Control Test scores taken infrequently during clinic visits.…”

Section: Wearable Devices In Asthmamentioning

confidence: 99%

Wearable Technology and How This Can Be Implemented into Clinical Practice

Greiwe

Nyenhuis

2020

Curr Allergy Asthma Rep

110

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Purpose of Review Our day-today life is saturated with health data that was previously out of reach. Over the last decade, new devices and fitness technology companies are attempting to tap into this data, uncovering a treasure trove of useful information that, when applied correctly, has the potential to revolutionize the way we approach healthcare and chronic conditions like asthma, especially in the wake of the COVID-19 pandemic. Recent Findings By harnessing exciting developments in personalization, digitization, wellness, and patient engagement, care providers can improve health outcomes for our patients in a way we have never been able to do in the past. While new technologies to capture individual health metrics are everywhere, how can we use this information to make a real difference in our patients' lives? Navigating the complicated landscape of personal wearable devices, asthma inhaler sensors, and exercise apps can be daunting to even the most tech savvy physician. Summary This manuscript will give you the tools necessary to make lasting changes in your patients' lives by exposing them to a world of usable, affordable, and relatable health technology that resonates with their personal fitness and wellness goals. These tools will be even more important post-COVID-19, as the landscape of clinical outpatient care changes from mainly in-person visits to a greater reliance on telemedicine and remote monitoring. Keywords Telemedicine. Wearable devices. Personalized healthcare devices. Remote monitoring. COVID-19. Connected health This article is part of the Topical Collection on Telemedicine and Technology

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“How Is My Child’s Asthma?” Digital Phenotype and Actionable Insights for Pediatric Asthma

Cited by 38 publications

References 20 publications

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

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

Developing and evaluating ASTHMAXcel adventures

Wearable Technology and How This Can Be Implemented into Clinical Practice

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