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

Telemonitoring of pediatric asthma in outpatient settings: A systematic review

Telemonitoring technologies are rapidly evolving, offering a promising solution for remote monitoring and timely management of asthma acute episodes. We aimed to describe current pediatric asthma telemonitoring technologies. A systematic review was conducted until September 2023 on Medline, Scopus, and Web of Science. We included studies of children (0-18 years) with asthma or recurrent wheezing whose respiratory condition was telemonitored outside the healthcare setting. A narrative synthesis was performed. We identified 40 telemonitoring technologies described in 40 studies. The more frequently used technologies for telemonitoring were mobile applications (n = 21) and web-based systems (n = 14). Telemonitoring duration varied between 2 weeks and 32 months. Data collection included asthma symptoms (n = 30), patient-reported outcome measures (PROMs) (n = 11), spirometry/peak flow readings (n = 20), medication adherence (n = 17), inhaler technique (n = 3), air quality (n = 2), and respiratory sounds (n = 2). Both parents and children were the technology target users in most studies (n = 23). Technology training was reported in 23 studies of which 3 provided ongoing support. Automatic feedback was found in 30 studies, mostly related with asthma control. HCP were involved in data management in 27 studies. Technologies were tested in samples from 4 to 327 children, with most studies including school-aged children and/or adolescents (n = 38) and eight including preschool children. This review provides an overview of existing technologies for the outpatient telemonitoring of pediatric asthma. Specific technologies for preschool children represent a gap in the literature that needs to be specifically addressed in future research.

Implementation of digital home monitoring and management of respiratory disease

PURPOSE OF REVIEW

Digital respiratory monitoring interventions (e.g. smart inhalers and digital spirometers) can improve clinical outcomes and/or organizational efficiency, and the focus is shifting to sustainable implementation as an approach to delivering respiratory care. This review considers key aspects of the technology infrastructure, discusses the regulatory, financial and policy context that influence implementation, and highlights the over-arching societal themes of equity, trust and communication.

RECENT FINDINGS

Technological requirements include developing interoperable and connected systems; establishing stable, wide internet coverage; addressing data accuracy and monitoring adherence; realising the potential of artificial intelligence; and avoiding clinician data overload. Policy challenges include concerns about quality assurance and increasingly complex regulatory systems. Financial barriers include lack of clarity over cost-effectiveness, budget impact and reimbursement. Societal concerns focus on the potential to increase inequities because of poor e-health literacy, deprivation or lack of available infrastructure, the need to understand the implications for patient/professional interactions of shifting care to remote delivery and ensuring confidentiality of personal data.

SUMMARY

Understanding and addressing the implementation challenges posed by gaps in policy, regulatory, financial, and technical infrastructure is essential to support delivery of equitable respiratory care that is acceptable to patients and professionals.

Home monitoring in asthma: towards digital twins

PURPOSE OF REVIEW

We highlight the recent advances in home monitoring of patients with asthma, and show that these advances converge towards the implementation of digital twin systems.

RECENT FINDINGS

Connected devices for asthma are increasingly numerous, reliable and effective: new electronic monitoring devices extend to nebulizers and spacers, are able to assess the quality of the inhalation technique, and to identify asthma attack triggers when they include a geolocation function; environmental data can be acquired from databases and refined by wearable air quality sensors; smartwatches are better validated. Connected devices are increasingly integrated into global monitoring systems. At the same time, machine learning techniques open up the possibility of using the large amount of data collected to obtain a holistic assessment of asthma patients, and social robots and virtual assistants can help patients in the daily management of their asthma.

SUMMARY

Advances in the internet of things, machine learning techniques and digital patient support tools for asthma are paving the way for a new era of research on digital twins in asthma.

Personalised management and supporting individuals to live with their asthma in a primary care setting

INTRODUCTION

Complementing recognition of biomedical phenotypes, a primary care approach to asthma care recognizes diversity of disease, health beliefs, and lifestyle at a population and individual level.

AREAS COVERED

We review six aspects of personalized care particularly pertinent to primary care management of asthma: personalizing support for individuals living with asthma; targeting asthma care within populations; managing phenotypes of wheezy pre-school children; personalizing management to the individual; meeting individual preferences for provision of asthma care; optimizing digital approaches to enhance personalized care.

EXPERT OPINION

In a primary care setting, personalized management and supporting individuals to live with asthma extend beyond the contemporary concepts of biological phenotypes and pharmacological 'treatable traits' to encompass evidence-based tailored support for self-management, and delivery of patient-centered care including motivational interviewing. It extends to how we organize clinical practiceand the choices provided in mode of consultation. Diagnostic uncertainty due to recognition of phenotypes of pre-school wheeze remains a challenge for primary care. Digital health can support personalized management, but there are concerns about increasing inequities. This broad approach reflects the traditionally holistic ethos of primary care ('knowing their patients and understanding their communities'), but the core concepts resonate with all healthcare.

PM2.5 aggravates airway inflammation in asthmatic mice: activating NF-κB via MyD88 signaling pathway

The role of PM2.5 in the bronchial asthma remains unclear. In this study, the deficient mice of TLR4-/-, TLR2-/- and MyD88 -/- were used to establish asthma model. The effects of PM2.5 on the inflammatory response in lung tissue of these mice were observed. PM2.5 increased alveolar macrophages and neutrophils, up-regulated the IL-12 and KC expression in WT mice, but down-regulated their levels in TLR2 -/-, TLR4 -/- and MyD88 -/- mice. OVA+PM2.5 stimulated neutrophil count in WT mice, but it decreased in TLR2 -/- and TLR4 -/- mice. OVA+PM2.5 also increased the Eotaxin, IL-5, IL-13 and MCP-3 expression levels, and OVA specific IgE and IgG1 in serum also increased in WT group. PM2.5 may activate NF-κB through the TLR2/TLR4/MyD88 signaling pathway and aggravate allergic inflammation of lung in asthmatic mice. The microelements in PM2.5 granules, such as lipopolysaccharide, may be an important factor in the high incidence of asthma.

Correlation of digital flow peak with spirometry in children with and without asthma

INTRODUCTION

Spirometry and peak expiratory flow measurement (PEF) are combined during functional respiratory assessments. The new digital peak flow meter (DPM) evaluates the forced expiratory volume in the first second (FEV₁) and PEF.

OBJECTIVE

To compare lung function measurements using spirometry and DPM.

METHODS

This cross-sectional analytical study assessed FEV₁ and PEF in children with and without asthma. Statistical analysis was performed to assess the agreement between the measures using the intraclass correlation coefficient (ICC), Bland-Altman, and survival agreement plot.

RESULTS

125 (3-12 y) and 196 (6-18 y) children without and with asthma, respectively, were studied. In children without asthma, the ICC for FEV₁ and PEF were 0.89 and 0.86, respectively, while the corresponding values were 0.87 and 0.79, respectively, in patients with asthma. The Bland-Altman method showed a difference of -0.4 to 0.5 for FEV₁ in patients without asthma, with a tendency to increase as the FEV₁ increased to a certain extent. In patients with asthma, the pattern was similar for FEV₁, and the PEF had a greater dispersion than among those without asthma; however, a good agreement pattern was maintained. In the survival agreement plot, when accepting a tolerance of 0.150 mL for FEV₁, there was an agreement of close to 55% in both groups. Likewise, when accepting a tolerance of 0.5 L/s for PEF, an agreement of close to 60% and 50% was observed in patients without and with asthma, respectively.

CONCLUSION

DPM was effective as a measure of lung function in pediatric patients with and without asthma.

Utility of Fitbit devices among children and adolescents with chronic health conditions: a scoping review

Background

While Fitbit® devices were initially intended for leisurely, consumer use, there has been recent interest among scientific and medical communities in the prospective use of Fitbit devices for clinical and research purposes. Those who have chronic health conditions are often required to spend considerable amounts of money and time undergoing physiological tests and activity monitoring to support, stabilize, and manage their health. This disease burden is only amplified in pediatric populations. Devices that are used to collect these data can be invasive, uncomfortable, and disconcerting. Using the Fitbit tracker to acquire such biometric data could ease this burden. Our scoping review seeks to summarize the research that has been conducted on the utilization of Fitbit devices in studies of children and adolescents with chronic health conditions and the feasibility, accuracy, and potential benefits of doing so.

Methods

Searches were conducted on PubMed for articles relating pediatric health to Fitbit device usage (using a Boolean search strategy). The eligibility criteria included trials being clinical and/or randomized controlled and articles being in English. Once articles were obtained, they underwent screening and exclusion processes and were charted for their titles, authors, objectives, results, and respective chronic illnesses. In the subsequent full-text review, further charting was conducted, collecting study designs, Fitbit parameters, feasibility, accuracy, and related health and clinical outcomes.

Results

Fitbit trackers were unanimously demonstrated to be feasible devices in this population for physical activity monitoring and were determined to be potentially beneficial in measuring and improving overall wellbeing and physical health in children with chronic illness. Nevertheless, sufficient evidence was not found in support of Fitbit accuracy. Additional biases were identified against the population of children with chronic health conditions that may further enable inaccurate data.

Conclusions

While Fitbit devices may be beneficial for those interested in improving physical health, discretion is advised for those seeking to collect accurate and/or medically necessitated data. Given the existing literature evaluated, medical-grade technologies are preferred in instances of the latter, as Fitbit devices have not been found to provide reliably accurate data.

Smart Insulin Pens: Advancing Digital Transformation and a Connected Diabetes Care Ecosystem

With the first commercially available smart insulin pens, the predominant insulin delivery device for millions of people living with diabetes is now coming into the digital age. Smart insulin pens (SIPs) have the potential to reshape a connected diabetes care ecosystem for patients, providers, and health systems. Existing SIPs are enhanced with real-time wireless connectivity, digital dose capture, and integration with personalized dosing decision support. Automatic dose capture can promote effective retrospective review of insulin dose data, particularly when paired with glucose data. Patients, providers, and diabetes care teams will be able to make increasingly data-driven decisions and recommendations, in real time, during scheduled visits, and in a more continuous, asynchronous care model. As SIPs continue to progress along the path of digital transformation, we can expect additional benefits: iteratively improving software, machine learning, and advanced decision support. Both these technological advances, and future care delivery models with asynchronous interactions, will depend on easy, open, and continuous data exchange between the growing number of diabetes devices. SIPs have a key role in modernizing diabetes care for a large population of people living with diabetes.

Using Telemedicine to Care for the Asthma Patient

Purpose of Review

To review the data supporting the use of telemedicine (TM) and to provide practical guidance for practitioners to optimize the care of their asthmatic patients.

Recent Findings

Previous to the pandemic, TM was little used in various aspects of asthma care. Since the pandemic, TM has been increasingly used in new ways to care for asthma patients at various locations. In addition to direct-to-consumer visits for asthma care, other forms of telehealth visits have been increasing such as facilitated visits, asynchronous, remote patient monitoring, e-consults, and mHealth. Moreover, patient and provider satisfaction with the use of TM has been increasing and is comparable at times with face-to-face visits. In this review, best practices for starting a telemedicine asthma service with patients at home, distant clinic sites, and various other locations, including school-based asthma programs, are reviewed.

Summary

TM is a valuable adjunct to face-to-face visits for asthma care. Following the recommended best practices can strengthen the implementation of a telemedicine asthma program (TMAP) into clinical practice. Providers must be vigilant in keeping current with the various nuances required for asthma telemedicine care in preparation for the post-pandemic environment.

The Impact of Wearable Technologies in Health Research: Scoping Review

Background

Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research.

Objective

In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research.

Methods

We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing.

Results

We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%).

Conclusions

Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.

Effective German and English Language mHealth Apps for Self-management of Bronchial Asthma in Children and Adolescents: Comparison Study

Background

Mobile health (mHealth) apps hold great potential for asthma self-management. Data on the suitability of asthma apps intended for children are insufficient, and the availability of German language apps is still inadequate compared with English language apps.

Objective

This study aims to identify functional asthma apps for children in German and to compare them with English language apps. In line with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, the Google Play Store and Apple App Store are systematically searched to preselect the most efficient apps, which are then compared according to a self-compiled criteria catalog.

Methods

Both app stores were screened for the term asthma. Following a PRISMA preselection process, the apps that met the inclusion criteria (ie, available free of charge, German or English language, and suitable for children) were rated by 3 independent persons following a criteria catalog consisting of 9 categories, some conceived for this purpose (availability, child-friendly, learning factor, and range of functions) and some adopted from existing validated catalogs (functionality and design, ease of use, potential for improving asthma self-management, fun factor and incentives, and information management and medical accuracy). The highest rated apps in German and English were compared.

Results

A total of 403 apps were identified on the Google Play Store and the Apple App Store. Finally, 24 apps that met the inclusion criteria were analyzed. In the first step of the quality assessment, only 4 available German language asthma apps were compared with 20 English language asthma apps. The 4 German language apps were then compared with the 4 highest rated English language apps. All selected apps, independent of the language, were comparable in the following categories: availability, functionality and design, ease of use, and information management and medical accuracy. The English language apps scored significantly higher in the following categories: potential for improving self-management, child-friendly, fun factor, learning factor, and range of function. English language apps (mean total points 34.164, SD 1.09) performed significantly better than German language asthma apps (mean total points 22.91, SD 2.898; P=.003). The best rated English language app was Kiss my asthma (36/42 points), whereas the best rated German language app Kata achieved only 27.33 points.

Conclusions

The recommended English language apps are Kiss my asthma, AsthmaXcel, AsthmaAustralia, and Ask Me, AsthMe!, whereas the only recommended German language app is Kata. The use of apps plays an increasingly important role in patients’ lives and in the medical field, making mHealth a staple in the future of asthma treatment plans. Although validated recommendations on rating mHealth apps have been published, it remains a challenging task for physicians and patients to choose a suitable app for each case, especially in non–English-speaking countries.

Digital Health Technology and Telemedicine-Based Hospital and Home Programs in Pulmonary Medicine During the COVID-19 Pandemic

BACKGROUND

The current coronavirus disease 2019 (COVID-19) pandemic has caused a significant strain on medical resources throughout the world. A major shift to telemedicine and mobile health technologies has now taken on an immediate urgency. Newly developed devices designed for home use have facilitated remote monitoring of various physiologic parameters relevant to pulmonary diseases. These devices have also enabled home-based pulmonary rehabilitation programs. In addition, telemedicine and home care services have been leveraged to rapidly develop acute care hospital-at-home programs for the treatment of mild-to-moderate COVID-19 illness.

AREAS OF UNCERTAINTY

The benefit of remote monitoring technologies on patient outcomes has not been established in robust trials. Furthermore, the use of these devices, which can increase the burden of care, has not been integrated into current clinical workflows and electronic medical records. Finally, reimbursement for these telemedicine and remote monitoring services is variable.

DATA SOURCES

Literature review.

THERAPEUTIC ADVANCES

Advances in digital technology have improved remote monitoring of physiologic parameters relevant to pulmonary medicine. In addition, telemedicine services for the provision of pulmonary rehabilitation and novel hospital-at-home programs have been developed. These new home-based programs have been adapted for COVID-19 and may also be relevant for the management of acute and chronic pulmonary diseases after the pandemic.

CONCLUSION

Digital remote monitoring of physiologic parameters relevant to pulmonary medicine and novel hospital-at-home programs are feasible and may improve care for patients with acute and chronic respiratory-related disorders.

Patient-Generated Health Data in Pediatric Asthma: Exploratory Study of Providers' Information Needs

BACKGROUND

Adolescents are using mobile health apps as a form of self-management to collect data on symptoms, medication adherence, and activity. Adding functionality to an electronic health record (EHR) to accommodate disease-specific patient-generated health data (PGHD) may support clinical care. However, little is known on how to incorporate PGHD in a way that informs care for patients. Pediatric asthma, a prevalent health issue in the United States with 6 million children diagnosed, serves as an exemplar condition to examine information needs related to PGHD.

OBJECTIVE

In this study we aimed to identify and prioritize asthma care tasks and decisions based on pediatric asthma guidelines and identify types of PGHD that might support the activities associated with the decisions. The purpose of this work is to provide guidance to mobile health app developers and EHR integration.

METHODS

We searched the literature for exemplar asthma mobile apps and examined the types of PGHD collected. We identified the information needs associated with each decision in accordance with consensus-based guidelines, assessed the suitability of PGHD to meet those needs, and validated our findings with expert asthma providers.

RESULTS

We mapped guideline-derived information needs to potential PGHD types and found PGHD that may be useful in meeting information needs. Information needs included types of symptoms, symptom triggers, medication adherence, and inhaler technique. Examples of suitable types of PGHD were Asthma Control Test calculations, exposures, and inhaler use. Providers suggested uncontrolled asthma as a place to focus PGHD efforts, indicating that they preferred to review PGHD at the time of the visit.

CONCLUSIONS

We identified a manageable list of information requirements derived from clinical guidelines that can be used to guide the design and integration of PGHD into EHRs to support pediatric asthma management and advance mobile health app development. Mobile health app developers should examine PGHD information needs to inform EHR integration efforts.

Wearable Technology and How This Can Be Implemented into Clinical Practice

PURPOSE OF REVIEW

Our day-to-day 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. 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.

kBot: Knowledge-enabled Personalized Chatbot for Asthma Self-Management

There is a well-recognized need for a shift to proactive asthma care given the impact asthma has on overall healthcare costs. The demand for continuous monitoring of patient's adherence to the medication care plan, assessment of environmental triggers, and management of asthma can be challenging in traditional clinical settings and taxing on clinical professionals. Recent years have seen a robust growth of general purpose conversational systems. However, they lack the capabilities to support applications such an individual's health, which requires the ability to contextualize, learn interactively, and provide the proper hyper-personalization needed to hold meaningful conversations. In this paper, we present kBot, a knowledge-enabled personalized chatbot system designed for health applications and adapted to help pediatric asthmatic patients (age 8 to 15) to better control their asthma. Its core functionalities include continuous monitoring of the patient's medication adherence and tracking of relevant health signals and environment data. kBot takes the form of an Android application with a frontend chat interface capable of conversing in both text and voice, and a backend cloud-based server application that handles data collection, processing, and dialogue management. It achieves contextualization by piecing together domain knowledge from online sources and inputs from our clinical partners. The personalization aspect is derived from patient answering questionnaires and day-to-day conversations. kBOT's preliminary evaluation focused on chatbot quality, technology acceptance, and system usability involved eight asthma clinicians and eight researchers. For both groups, kBot achieved an overall technology acceptance value of greater than 8 on the 11-point Likert scale and a mean System Usability Score (SUS) greater than 80.