Predicting asthma exacerbations employing remotely monitored adherence

A Review of Sensor-Based Interventions for Supporting Patient Adherence to Inhalation Therapy

Purpose

This review aims to provide a comprehensive overview of sensor technologies employed in interventions to enhance patient adherence to inhalation therapy for chronic respiratory diseases, with a particular emphasis on human factors. Sensor-based interventions offer opportunities to improve adherence through monitoring and feedback; however, a deeper understanding of how these technologies interact with patients is essential.

Patients and Methods

We conducted a systematic review by searching online databases, including PubMed, Scopus, Web of Science, Science Direct, and ACM Digital Library, spanning the timeframe from January 2014 to December 2023. Our inclusion criteria focused on studies that employed sensor-based technologies to enhance patient adherence to inhalation therapy.

Results

The initial search yielded 1563 results. After a thorough screening process, we selected 37 relevant studies. These sensor-based interventions were organized within a comprehensive HFE framework, including data collection, data processing, system feedback, and system feasibility. The data collection phase comprised person-related, task-related, and physical environment-related data. Various approaches to data processing were employed, encompassing applications for assessing intervention effectiveness, monitoring patient behaviour, and identifying disease risks, while system feedback included reminders and alerts, data visualization, and persuasive features. System feasibility was evaluated based on patient acceptance, usability, and device cost considerations.

Conclusion

Sensor-based interventions hold significant promise for improving adherence to inhalation therapy. This review highlights the necessity of an integrated "person-task-physical environment" system to advance future sensor technologies. By capturing comprehensive data on patient health, device usage patterns, and environmental conditions, this approach enables more personalized and effective adherence support. Key recommendations include standardizing data integration protocols, employing advanced algorithms for insights generation, enhancing interactive visual features for accessibility, integrating persuasive design elements to boost engagement, exploring the advantages of conversational agents, and optimizing experience to increase patient acceptance.

Assessment of Medication Adherence Using Mobile Applications in Chronic Obstructive Pulmonary Disease: A Scoping Review

Chronic obstructive pulmonary disease (COPD) is a condition that significantly impacts both patients and healthcare systems. The management of COPD involves various pharmacological intervention strategies, and addressing the issue of low adherence to these strategies has become a subject of significant interest. In response to this concern, there has been a shift toward utilizing telemedicine and mobile applications. The primary objective of this scoping review is to delineate the usage of mobile applications to enhance medication adherence in adult patients with COPD. This study involved a search of databases such as Medline, Google Scholar, Cochrane, and ClinicalTrial.gov, focusing on the literature published in English and Spanish over the last decade. The selected studies assessed interventions involving mobile applications (mobile apps) designed to improve medication adherence. Four digital aids were identified and available on online platforms, mobile apps, or both: m-PAC, myCOPD, Wellinks mHealth, and Propeller Health. Propeller Health, in particular, is an app that directly measures medication adherence through electronic medication monitors attached to participants' inhalers. Opening the app was associated with higher odds of using control medications compared to participants who did not open the app. The findings suggest that these digital interventions serve as valuable tools to enhance patient adherence to treatment. Future research should focus on evaluating the effectiveness of different digital devices, such as digital inhalers and mobile applications, that directly measure medication adherence.

Advancing Digital Solutions to Overcome Longstanding Barriers in Asthma and COPD Management

Maintenance therapy delivered via inhaler is central to asthma and chronic obstructive pulmonary disease (COPD) management. Poor adherence to inhaled medication and errors in inhalation technique have long represented major barriers to the optimal management of these chronic conditions. Technological innovations may provide a means of overcoming these barriers. This narrative review examines ongoing advances in digital technologies relevant to asthma and COPD with the potential to inform clinical decision-making and improve patient care. Digital inhaler devices linked to mobile apps can help bring about changes in patients' behaviors and attitudes towards disease management, particularly when they build in elements of interactivity and gamification. They can also support ongoing technique education, empowering patients and helping providers maximize the value of consultations and develop effective action plans informed by insights into the patient's inhaler use patterns and their respiratory health. When combined with innovative techniques such as machine learning, digital devices have the potential to predict exacerbations and prompt pre-emptive intervention. Finally, digital devices may support an advanced precision medicine approach to respiratory disease management and help support shared decision-making. Further work is needed to increase uptake of digital devices and integrate their use into care pathways before their full potential in personalized asthma and COPD management can be realized.

Primary Care Management of Asthma Exacerbations or Attacks: Impact of the COVID-19 Pandemic

The COVID-19 pandemic has brought a renewed focus on appropriate management of chronic respiratory conditions with a heightened awareness of respiratory symptoms and the requirement for differential diagnosis between an asthma attack and COVID-19 infection. Despite early concerns in the pandemic, most studies suggest that well-managed asthma is not a risk factor for more severe COVID-related outcomes, and that asthma may even have a protective effect. Advice on the treatment of asthma and asthma attacks has remained unchanged. This article describes some challenges faced in primary care asthma management in adults and in teenagers, particularly their relevance during a pandemic, and provides practical advice on asthma attack recognition, classification, treatment and continuity of care. Acute attacks, characterised by increased symptoms and reduced lung function, are often referred to as exacerbations of asthma by doctors and nurses but are usually described by patients as asthma attacks. They carry a significant and underestimated morbidity and mortality burden. Many patients experiencing an asthma attack are assessed in primary care for treatment and continuing management. This may require remote assessment by telephone and home monitoring devices, where available, during a pandemic. Differentiation between an asthma attack and a COVID-19 infection requires a structured clinical assessment, taking account of previous medical and family history. Early separation into mild, moderate, severe or life-threatening attacks is helpful for continuing good management. Most attacks can be managed in primary care but when severe or unresponsive to initial treatment, the patient should be appropriately managed until transfer to an acute care facility can be arranged. Good quality care is important to prevent further attacks and must include a follow-up appointment in primary care, proactive regular dosing with daily controller therapy and an understanding of a patient's beliefs and perceptions about asthma to maximise future self-management.

Novel Methods of Measuring Adherence Patterns Reveal Adherence Phenotypes with Distinct Asthma Outcomes

RATIONALE

Poor adherence with asthma controller medication contributes to worse symptom control and increased exacerbation risk. Adherence is often expressed as the mean proportion of prescribed doses taken over a period of 6-12 months. New metrics may capture individual day-to-day variability patterns linked with distinct clinical outcomes.

OBJECTIVES

To test the hypotheses that novel time- and dose-based adherence variability metrics offer independent value to mean adherence in identifying distinct adherence patterns, that are associated with symptom control (Asthma Control Test [ACT] score) and exacerbation risk, using electronically-recorded medication data from a 6-month cluster randomized trial examining the effect of inhaler reminders on adherence.

METHODS

Adherence metrics were calculated from the first two months (months 0-2) of the study period. In addition to mean adherence (%prescribed puffs/day taken, PTmean), we examined novel metrics including: time adherence area-under-curve (T-AUC), reflecting cumulative gaps in adherence over time, entropy (H), reflecting disorder in the ways in which a patient changed their medication dose adherence from day to day, and standard deviation of the %prescribed puffs/day taken (PTSD). Dominant metrics identified from factor analysis were included in hierarchical clustering analysis. We compared the resultant clusters in terms of outcomes over months 2-6, and exacerbation risk over the entire study period.

RESULTS

Two factors explained >65% of the total variance in adherence, primarily driven by T-AUC and H. Two main patient clusters based on their adherence metrics were identified: Cluster 1 ("high time adherence", n=75) had better T-AUC, i.e. fewer gaps between medication-taking days, than Cluster 2 ("low time adherence", n=23). Though both clusters had similar symptom control at 2 months, Cluster 1 showed less subsequent decline in ACT over months 2-6 (median(IQR) change in ACT score: 1(-1, 4) vs -2(-3.75,0.75); p=0.012), and had better symptom control at 6 months (ACT score: 20(17, 23) vs 17 (15, 20); p=0.034). There were no significant differences between the clusters in terms of proportion of exacerbators or time to exacerbation.

CONCLUSIONS

Novel metrics showed that low time adherence was associated with greater risk of decline in asthma symptom control. Adherence patterns may exhibit 'memory' relevant to future clinical status, warranting validation in a larger dataset.

Digital Inhalers for Asthma or Chronic Obstructive Pulmonary Disease: A Scientific Perspective

Impressive advances in inhalation therapy for patients with asthma and chronic obstructive pulmonary disease (COPD) have occurred in recent years. However, important gaps in care remain, particularly relating to poor adherence to inhaled therapies. Digital inhaler health platforms which incorporate digital inhalers to monitor time and date of dosing are an effective disease and medication management tool, promoting collaborative care between clinicians and patients, and providing more in-depth understanding of actual inhaler use. With advances in technology, nearly all inhalers can be digitalized with add-on or embedded sensors to record and transmit data quantitating inhaler actuations, and some have additional capabilities to evaluate inhaler technique. In addition to providing an objective and readily available measure of adherence, they allow patients to interact with the device directly or through their self-management smartphone application such as via alerts and recording of health status. Clinicians can access these data remotely and during patient encounters, to better inform them about disease status and medication adherence and inhaler technique. The ability for remote patient monitoring is accelerating interest in and the use of these devices in clinical practice and research settings. More than 20 clinical studies of digital inhalers in asthma or COPD collectively show improvement in medication adherence, exacerbation risk, and patient outcomes with digital inhalers. These studies support previous findings about patient inhaler use and behaviors, but with greater granularity, and reveal some new findings about patient medication-taking behaviors. Digital devices that record inspiratory flows with inhaler use can guide proper inhaler technique and may prove to be a clinically useful lung function measure. Adoption of digital inhalers into practice is still early, and additional research is needed to determine patient and clinician acceptability, the appropriate place of these devices in the therapeutic regimen, and their cost effectiveness.

Digital Health Technology in Asthma: A Comprehensive Scoping Review

BACKGROUND

A variety of digital intervention approaches have been investigated for asthma therapy during the past decade, with different levels of interactivity and personalization and a range of impacts on different outcome measurements.

OBJECTIVE

To assess the effectiveness of digital interventions in asthma with regard to acceptability and outcomes and evaluate the potential of digital initiatives for monitoring or treating patients with asthma.

METHODS

We evaluated digital interventions using a scoping review methodology through a literature search and review. Of 871 articles identified, 121 were evaluated to explore intervention characteristics, the perception and acceptability of digital interventions to patients and physicians, and effects on asthma outcomes. Interventions were categorized by their level of interactivity with the patient.

RESULTS

Interventions featuring non-individualized content sent to patients appeared capable of promoting improved adherence to inhaled corticosteroids, but with no identified improvement in asthma burden; and data-gathering interventions appeared to have little effect on adherence or asthma burden. Evidence of improvement in both adherence and patients' impairment due to asthma were seen only with interactive interventions involving two-way responsive patient communication. Digital interventions were generally positively perceived by patients and physicians. Implementation was considered feasible, with certain preferences for design and features important to drive use.

CONCLUSIONS

Digital health interventions show substantial promise for asthma disease monitoring and personalization of treatment. To be successful, future interventions will need to include both inhaler device and software elements, combining accurate measurement of clinical parameters with careful consideration of ease of use, personalization, and patient engagement aspects.

The Future of Asthma Care: Personalized Asthma Treatment

Although once considered a single disease entity, asthma is now known to be a complex inflammatory disease engaging a range of causal pathways. The most frequent forms of asthma are identified by sputum/blood eosinophilia and activation of type 2 inflammatory pathways involving interleukins-3, -4, -5, and granulocyte-macrophage colony-stimulating factor. The use of diagnostics that identify T2 engagement linked to the selective use of highly targeted biologics has opened up a new way of managing severe disease. Novel technologies, such as wearables and intelligent inhalers, enable real-time remote monitoring of asthma, creating a unique opportunity for personalized health care.

Digital technologies and adherence in respiratory diseases: the road ahead

Outcomes for patients with chronic respiratory diseases remain poor despite the development of novel therapies. In part, this reflects the fact that adherence to therapy is low and clinicians lack accurate methods to assess this issue. Digital technologies hold promise to overcome these barriers to care. For example, algorithmic analysis of large amounts of information collected on health status and treatment use, along with other disease relevant information such as environmental data, can be used to help guide personalised interventions that may have a positive health impact, such as establishing habitual and correct inhaler use. Novel approaches to data analysis also offer the possibility of statistical algorithms that are better able to predict exacerbations, thereby creating opportunities for preventive interventions that may adapt therapy as disease activity changes. To realise these possibilities, digital approaches to disease management should be supported by strong evidence, have a solid infrastructure, be designed collaboratively as clinically effective and cost-effective systems, and reflect the needs of patients and healthcare providers. Regulatory standards for digital interventions and strategies to handle the large amounts of data generated are also needed. This review highlights the opportunities provided by digital technologies for managing patients with respiratory diseases.

Objective Assessment of Patient Inhaler User Technique Using an Audio-Based Classification Approach

Many patients make critical user technique errors when using pressurised metered dose inhalers (pMDIs) which reduce the clinical efficacy of respiratory medication. Such critical errors include poor actuation coordination (poor timing of medication release during inhalation) and inhaling too fast (peak inspiratory flow rate over 90 L/min). Here, we present a novel audio-based method that objectively assesses patient pMDI user technique. The Inhaler Compliance Assessment device was employed to record inhaler audio signals from 62 respiratory patients as they used a pMDI with an In-Check Flo-Tone device attached to the inhaler mouthpiece. Using a quadratic discriminant analysis approach, the audio-based method generated a total frame-by-frame accuracy of 88.2% in classifying sound events (actuation, inhalation and exhalation). The audio-based method estimated the peak inspiratory flow rate and volume of inhalations with an accuracy of 88.2% and 83.94% respectively. It was detected that 89% of patients made at least one critical user technique error even after tuition from an expert clinical reviewer. This method provides a more clinically accurate assessment of patient inhaler user technique than standard checklist methods.

Advances in Audio-Based Systems to Monitor Patient Adherence and Inhaler Drug Delivery

Hundreds of millions of people worldwide have asthma and COPD. Current medications to control these chronic respiratory diseases can be administered using inhaler devices, such as the pressurized metered dose inhaler and the dry powder inhaler. Provided that they are used as prescribed, inhalers can improve patient clinical outcomes and quality of life. Poor patient inhaler adherence (both time of use and user technique) is, however, a major clinical concern and is associated with poor disease control, increased hospital admissions, and increased mortality rates, particularly in low- and middle-income countries. There are currently limited methods available to health-care professionals to objectively and remotely monitor patient inhaler adherence. This review describes recent sensor-based technologies that use audio-based approaches that show promising opportunities for monitoring inhaler adherence in clinical practice. This review discusses how one form of sensor-based technology, audio-based monitoring systems, can provide clinically pertinent information regarding patient inhaler use over the course of treatment. Audio-based monitoring can provide health-care professionals with quantitative measurements of the drug delivery of inhalers, signifying a clear clinical advantage over other methods of assessment. Furthermore, objective audio-based adherence measures can improve the predictability of patient outcomes to treatment compared with current standard methods of adherence assessment used in clinical practice. Objective feedback on patient inhaler adherence can be used to personalize treatment to the patient, which may enhance precision medicine in the treatment of chronic respiratory diseases.