Electronic Inhaler Monitoring for Chronic Airway Disease: Development and Application of a Multidimensional Efficacy Framework

The emerging role of digital health in the management of asthma

The most common reasons seen for lack of asthma control include misconceptions about disease control, low controller treatment adherence, poor inhaler technique, and the resulting underuse of controllers and overuse of short-acting beta2 agonists (SABAs). Narrowing these care gaps may be achieved through well-designed patient education that considers the patient's motivation, beliefs, and capabilities regarding their asthma and its management and empowers the patient to become an active participant in treatment decisions. Digital health technologies (DHTs) and digital therapeutic (DT) devices provide new opportunities to monitor treatment behaviors, improve communication between healthcare providers and patients, and generate data that inform educational interactions. DHT and DT have been proven effective in enhancing patient self-management in other chronic conditions, particularly diabetes. Accelerated integration of DHT and DT into the management of asthma patients is facilitated by the use of digital inhalers that employ sensor technology ("smart" inhalers). These devices efficiently provide real-time feedback on controller adherence, SABA use, and inhaler technique that have the strong potential to optimize asthma control.

Self-reported medication adherence instruments and their applicability in low-middle income countries: a scoping review

Introduction

Medication non-adherence is an important public health issue, associated with poor clinical and economic outcomes. Globally, self-reported instruments are the most widely used method to assess medication adherence. However, the majority of these were developed in high-income countries (HICs) with a well-established health care system. Their applicability in low- and middle-income countries (LMICs) remains unclear. The objective of this study is to systematically review the applicability of content and use of self-reported adherence instruments in LMICs.

Method

A scoping review informed by a literature search in Pubmed, EBSCO, and Cochrane databases was conducted to identify studies assessing medication adherence using self-reported instruments for patients with five common chronic diseases [hypertension, diabetes, dyslipidemia, asthma, or Chronic Obstructive Pulmonary Disease (COPD)] in LMICs up to January 2022 with no constraints on publication year. Two reviewers performed the study selection process, data extraction and outcomes assessment independently. Outcomes focused on LMIC applicability of the self-reported adherence instruments assessed by (i) containing LMIC relevant adherence content; (ii) methodological quality and (iii) fees for use.

Findings

We identified 181 studies that used self-reported instruments for assessing medication adherence in LMICs. A total of 32 distinct types of self-reported instruments to assess medication adherence were identified. Of these, 14 self-reported instruments were developed in LMICs, while the remaining ones were adapted from self-reported instruments originally developed in HICs. All self-reported adherence instruments in studies included presented diverse potential challenges regarding their applicability in LMICs, included an underrepresentation of LMIC relevant non-adherence reasons, such as financial issues, use of traditional medicines, religious beliefs, lack of communication with healthcare provider, running out of medicine, and access to care. Almost half of included studies showed that the existing self-reported adherence instruments lack sufficient evidence regarding cross cultural validation and internal consistency. In 70% of the studies, fees applied for using the self-reported instruments in LMICs.

Conclusion

There seems insufficient emphasis on applicability and methodological rigor of self-reported medication adherence instruments used in LMICs. This presents an opportunity for developing a self-reported adherence instrument that is suitable to health systems and resources in LMICs.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier: CRD42022302215.

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.

Digital health in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) can be prevented and treated through effective care, reducing exacerbations and hospitalizations. Early identification of individuals at high risk of COPD exacerbation is an opportunity for preventive measures. However, many patients struggle to follow their treatment plans because of a lack of knowledge about the disease, limited access to resources, and insufficient clinical support. The growth of digital health-which encompasses advancements in health information technology, artificial intelligence, telehealth, the Internet of Things, mobile health, wearable technology, and digital therapeutics-offers opportunities for improving the early diagnosis and management of COPD. This study reviewed the field of digital health in terms of COPD. The findings showed that despite significant advances in digital health, there are still obstacles impeding its effectiveness. Finally, we highlighted some of the major challenges and possibilities for developing and integrating digital health in COPD management.

Interval change in fractional exhaled nitric oxide (FENO) reflects short-term change in adherence following electronic inhaler reminders

BACKGROUND

In asthma, suppression of fractional exhaled nitric oxide (FENO) is a marker of adherence in the short-term. The usefulness of FENO to indicate change in adherence in the longer term is unknown. The aims of this study were to determine the relationship between changes in adherence and corresponding changes in FENO over short (1 week) and long-term (3 month) periods.

METHODS

After establishing initial ICS adherence using electronic inhaler monitor (EIM) devices, reminders were switched on for 1 week ('short-term') to optimize adherence. Reminders were then switched off and patients followed up after 3 months ('long-term'). FENO was measured at the start and end of each period. Using linear regression, we analyzed change in FENO in relation to change in adherence.

RESULTS

Forty-two patients contributed complete data for analysis. In the short-term, change in adherence was independently associated with change in FENO (β = -0.36, p = 0.036) even after adjusting for initial adherence and ICS dose. The higher the initial FENO, the greater the decline in FENO with improved adherence. This relationship between change in adherence and change in FENO was not observed in the long-term.

CONCLUSION

Change in adherence over 1 week following the use of EIM reminders independently predicted change in FENO. This relationship was not maintained at 3 months.