The Clinical Impact of Different Adherence Behaviors in Patients with Severe Chronic Obstructive Pulmonary Disease

A survey and analysis of inhalation medication adherence among 977 COPD patients in a region of northern China

OBJECTIVE

Inhalation therapy is recommended by the World Health Organization as the first-line treatment for chronic obstructive pulmonary disease (COPD) due to its rapid onset of action, good safety profile, ease of use, and portability. High medication adherence in COPD patients is crucial for enhancing disease management. The aim of this study was to assess the level of disease control, adherence to inhaled medication therapy, and potential factors influencing treatment adherence among COPD patients.

METHODS

A paper-based questionnaire was used to survey COPD patients who were outpatients or inpatients at the First Affiliated Hospital of Harbin Medical University between January 2019 and October 2023. Patients were included if they had been diagnosed with stable COPD for more than 12 months, were prescribed inhaled medications for post-consultation or post-discharge management, and had used these medications for at least 8 weeks with follow-up review. Questionnaires were administered at the time of consultation and at the 8-week follow-up to comprehensively evaluate patients' adherence to inhaled medications based on their medication administration methods, frequency, and other relevant factors. Categorical data were described using frequencies and percentages, and comparisons between groups were conducted using the chi-square test. For the analysis of risk factors, binary logistic regression analysis was employed. To avoid collinearity among variables, a stepwise regression method was utilized for variable selection. A P-value < 0.05 was considered statistically significant.

RESULTS

A total of 977 patients were included, with an average age of 63 ± 9 years. Among them, 40.9% of the patients demonstrated high adherence to inhaled medication therapy. Patients who were under 70 years old (P = 0.03), had a higher annual household income (P = 0.04), had family supervision (P = 0.01), and had medical insurance (P = 0.02) exhibited higher adherence to inhaled medication therapy.

CONCLUSION

Among the surveyed patients, those who were under 70 years old (OR = 5.1, CI = 1.13-23.11) and had family supervision (OR = 3.26, CI = 1.3-8.21) demonstrated better medication adherence. This suggests that physicians could potentially improve patient medication adherence, optimize disease control, and enhance the overall quality of life for these patients by considering targeted interventions, such as identifying and educating elderly patients, intensifying tailored promotional activities, and encouraging family members to supervise medication use.

Uncovering patterns of inhaler technique and reliever use: the value of objective, personalized data from a digital inhaler

Electronic inhalers provide information about patterns of routine inhaler use. During a 12-week study, 360 asthma patients using albuterol Digihaler generated 53,083 inhaler events that were retrospectively analyzed. A total of 41,528 (78%) of the recorded inhalation events were suitable for flow analysis (having a PIF ≥ 18 L/min and <120 L/min). Median PIF, inhalation volume, inhalation duration, and time to PIF for these events steadily decreased between the first and last 10 days of the study, by 5.1%, 12.6%, 15.9%, and 6.4%, respectively. Continuous short-acting beta2-agonist (SABA) overuse, defined as ≥2 SABA inhalations/week throughout the study period, was seen in 29% (n = 104) of patients. Of 260 patients with ≥1 instance of acute short-term SABA overuse, 55 (21%) had a confirmed exacerbation. Electronic recording of real-life inhaler use can capture valuable, objective information that could inform disease management and clinical decision-making.

Adherence to single inhaler triple therapy and digital inhalers in Chronic Obstructive Pulmonary Disease: a literature review and protocol for a randomized controlled trial (TRICOLON study)

BACKGROUND

Medication non-adherence is a significant problem in patients with Chronic Obstructive Pulmonary Disease (COPD). Efforts to address this issue are receiving increased attention. Simplifying treatment by prescribing single-inhaler triple therapy (SITT) as an alternative to multi-inhaler triple therapy (MITT) or with smart inhalers are often considered potential solutions. However, the actual impact of these innovations on adherence and clinical outcomes is unclear.

METHODS

To address this knowledge gap we first conducted a literature review focusing on two research questions: 1) the difference in adherence between SITT and MITT users in COPD, and 2) the effect of smart inhalers on adherence in COPD. Separate searches were conducted in PubMed and two authors independently assessed the articles. In addition, we present a protocol for a study to acquire knowledge for the gaps identified.

RESULTS

To address the first research question, 8 trials were selected for further review. All trials were observational, i.e. randomized controlled trials were lacking. Seven of these trials showed higher adherence and/or persistence in patients on SITT compared with patients on MITT. In addition, four studies showed a positive effect of SITT on various clinical outcomes. For the second research question, 11 trials were selected for review. While most of the studies showed a positive effect of smart inhalers on adherence, there was considerable variation in the results regarding their effect on other clinical outcomes. The TRICOLON (TRIple therapy COnvenience by the use of one or multipLe Inhalers and digital support in ChrONic Obstructive Pulmonary Disease) trial aims to improve understanding regarding the effectiveness of SITT and smart inhalers in enhancing adherence. This open-label, randomized, multi-center study will enroll COPD patients requiring triple therapy at ten participating hospitals. In total, 300 patients will be randomized into three groups: 1) MITT; 2) SITT; 3) SITT with digital support through a smart inhaler and an e-health platform. The follow-up period will be one year, during which three methods of measuring adherence will be used: smart inhaler data, self-reported data using the Test of Adherence to Inhalers (TAI) questionnaire, and drug analysis in scalp hair samples. Finally, differences in clinical outcomes between the study groups will be compared.

DISCUSSION

Our review suggests promising results concerning the effect of SITT, as opposed to MITT, and smart inhalers on adherence. However, the quality of evidence is limited due to the absence of randomized controlled trials and/or the short duration of follow-up in many studies. Moreover, its impact on clinical outcomes shows considerable variation. The TRICOLON trial aims to provide solid data on these frequently mentioned solutions to non-adherence in COPD. Collecting data in a well-designed randomized controlled trial is challenging, but the design of this trial addresses both the usefulness of SITT and smart inhalers while ensuring minimal interference in participants' daily lives.

TRIAL REGISTRATION

NCT05495698 (Clinicaltrials.gov), registered at 08-08-2022. Protocol version: version 5, date 27-02-2023.

Digital health delivery in respiratory medicine: adjunct, replacement or cause for division?

Digital medicine is already well established in respiratory medicine through remote monitoring digital devices which are used in the day-to-day care of patients with asthma, COPD and sleep disorders. Image recognition software, deployed in thoracic radiology for many applications including lung cancer screening, is another application of digital medicine. Used as clinical decision support, this software will soon become part of day-to-day practice once concerns regarding generalisability have been addressed. Embodied in the electronic health record, digital medicine also plays a substantial role in the day-to-day clinical practice of respiratory medicine. Given the considerable work the electronic health record demands from clinicians, the next tangible impact of digital medicine may be artificial intelligence that aids administration, makes record keeping easier and facilitates better digital communication with patients. Future promises of digital medicine are based on their potential to analyse and characterise the large amounts of digital clinical data that are collected in routine care. Offering the potential to predict outcomes and personalise therapy, there is much to be excited by in this new epoch of innovation. However, these digital tools are by no means a silver bullet. It remains uncertain whether, let alone when, the promises of better models of personalisation and prediction will translate into clinically meaningful and cost-effective products for clinicians.

Systematic review of the effects of patient errors using inhaled delivery systems on clinical outcomes in COPD

BACKGROUND

Errors using inhaled delivery systems for COPD are common and it is assumed that these lead to worse clinical outcomes. Previous systematic reviews have included patients with both asthma and COPD and much of the evidence related to asthma. More studies in COPD have now been published. Through systematic review, the relationship between errors using inhalers and clinical outcomes in COPD, including the importance of specific errors, was assessed.MethodsElectronic databases were searched on 27 October 2023 to identify cohort, case-control or randomised controlled studies, which included patients with COPD, an objective assessment of inhaler errors and data on at least one outcome of interest (forced expiratory volume in 1 s, (FEV1), dyspnoea, health status and exacerbations). Study quality was assessed using the Newcastle and Ottawa scales. A narrative synthesis of the results was performed as there was insufficient detail in the publications to allow quantitative synthesis. There was no funding for the review.

RESULTS

19 publications were included (7 cohort and 12 case-control) reporting outcomes on 6487 patients. 15 were considered low quality, and most were confounded by the absence of adherence data. There was weak evidence that lower error rates are associated with better FEV1, symptoms and health status and fewer exacerbations. Only one considered the effects of individual errors and found that only some were related to worse outcomes.

CONCLUSION

Evidence about the importance of specific errors using inhalers and outcomes would optimise the education and training of patients with COPD. Prospective studies, including objective monitoring of inhalation technique and adherence, are needed.

PROSPERO REGISTRATION NUMBER

CRD42023393120.

Cost-related medication nonadherence in adults with COPD in the United States 2013-2020

BACKGROUND

Cost-related medication nonadherence (CRN) is associated with poor prognosis among patients with chronic obstructive pulmonary disease (COPD), a population that requires long-term treatment for secondary prevention. In this study, we aimed to estimate the prevalence and sociodemographic characteristics of CRN in individuals with COPD in the US.

METHODS

In a nationally representative survey of US adults in the National Health Interview Survey (2013-2020), we identified individuals aged ≥18 years with a self-reported history of COPD. Cross-sectional study.

RESULTS

Of the 15,928 surveyed individuals, a weighted 18.56% (2.39 million) reported experiencing CRN, including 12.50% (1.61 million) missing doses, 13.30% (1.72 million) taking lower than prescribed doses, and 15.74% (2.03 million) delaying filling prescriptions to save costs. Factors including age < 65 years, female sex, low family income, lack of health insurance, and multimorbidity were associated with CRN.

CONCLUSIONS

In the US, one in six adults with COPD reported CRN. The influencing factors of CRN are multifaceted and necessitating more rigorous research. Targeted interventions based on the identified influencing factors in this study are recommended to enhance medication adherence among COPD patients.

Filling the gaps in the evaluation and selection of mobile health technologies in respiratory medicine

INTRODUCTION

Mobile health (mHealth) technology in respiratory medicine is a fast-growing and promising digital technology that is popular among patients and healthcare providers (HCPs). They provide reminders and step-by-step instructions for the correct inhalation technique, monitor patients' adherence to treatment, and facilitate communication between patients and HCPs.

AREAS COVERED

While numerous mHealth apps have been developed over the years, most applications do not have supporting evidence. Selecting the best mHealth app in respiratory medicine is challenging due to limited studies carrying out mHealth app selection. Although mHealth technologies play an important part in the future of respiratory medicine, there is no single guide on the evaluation and selection of mHealth technologies for patients with pulmonary diseases. This paper aims to provide an overview of mHealth technologies, particularly emphasizing digital inhalers and standalone applications used in asthma. Additionally, it offers insights into the evaluation, selection, and pertinent considerations surrounding mHealth applications in respiratory medicine.

EXPERT OPINION

Evaluating mHealth apps will take time, resources, and collaboration between stakeholders such as governmental regulatory bodies, subject-matter experts, and industry representatives. Filling the gaps in the evaluation and selection of the mHealth app will improve clinical decision-making, personalized treatments, self-management and disease monitoring in respiratory medicine.

Consideration and Assessment of Patient Factors When Selecting an Inhaled Delivery System in COPD

Because guidelines and strategies for pharmacologic treatment of COPD focus on specific classes of inhaled medications, there is an unmet need for information to guide health care professionals for selecting an inhaled medication delivery system that matches the unique characteristics of individual patients. This article provides guidance for selecting an inhaled medication delivery system based on three "key" patient factors: cognitive function, manual dexterity/strength, and peak inspiratory flow. In addition, information is provided about specific tests to assess these patient factors. Cognitive impairment with an estimated prevalence of 25% among patients with COPD adversely affects patients' ability to correctly use a handheld device. To our knowledge, the prevalence of impaired manual dexterity/strength has not been reported in those with COPD. However, 79% of patients with COPD have reported one or more physical impediments that could influence their ability to manipulate an inhaler device. The measurement of peak inspiratory flow against the simulated resistance (PIFr) of a dry powder inhaler establishes whether the patient has the inhalation ability for creating optimal turbulent energy within the device. A suboptimal PIFr for low to medium-high resistance dry powder inhalers has been reported in 19% to 84% of stable outpatients with COPD. Health care professionals should consider cognitive function, manual dexterity/strength, and PIFr in their patients with COPD when prescribing inhaled pharmacotherapy. Impairments in these patient factors are common among those with COPD and can affect the individual's competency and effectiveness of using inhaled medications delivered by handheld devices.

Personalizing Selection of Inhaled Delivery Systems in Chronic Obstructive Pulmonary Disease

It can be challenging for healthcare professionals (HCPs) to prescribe inhaled therapy for patients with chronic obstructive pulmonary disease (COPD) because of the multiple individual and combinations of inhaled medications available in numerous delivery systems. Guidance on the selection of an inhaled delivery system has received limited attention compared with the emphasis on prescribing the class of the inhaled molecule(s). Although numerous recommendations and algorithms have been proposed to guide the selection of an inhaled delivery system for patients with COPD, no specific approach has been endorsed in COPD guidelines/strategies or by professional organizations. To provide recommendations for an inhaler selection strategy at initial and follow-up appointments, we examined the impact of patient errors using handheld inhalers on clinical outcomes and performed a focused narrative review to consider patient factors (continuity of the inhaled delivery system, cognitive function, manual function/dexterity, and peak inspiratory flow) when selecting an inhaled delivery system. On the basis of these findings, five questions are proposed for HCPs to consider in the initial selection of an inhaler delivery system and three questions to consider at follow-up. We propose that HCPs consider the inhaled medication delivery system as a unit and to match appropriate medication(s) with the unique features of the delivery system to individual patient factors. Assessment of inhaler technique and adherence together with patient outcomes/satisfaction at each visit is essential to determine whether the inhaled medication delivery system is providing benefits. Continued and repeated education on device features and correct technique is warranted to optimize efficacy.

Up-to-date guidance towards improving medication adherence in patients with chronic obstructive pulmonary disease

INTRODUCTION

Despite efficacious treatment for chronic obstructive pulmonary disease (COPD), medication adherence remains quite poor, with most estimates based on electronic monitoring devices ranging from 20-30%. This degree of nonadherence represents a significant missed opportunity to realize the benefits of treatment of this disease.

AREAS COVERED

In this article, we review research on the prevalence of nonadherence among patients with COPD, the association of nonadherence with health outcomes, barriers to adherence in this patient population, and potential interventions.

EXPERT OPINION

Integrating research into practice involves assessing patients' adherence, identifying modifiable barriers to adherence, open discussion of these barriers with patients, and tailored interventions to address them. These interventions may include treatment of previously unrecognized comorbid disease, providing educational or behavioral interventions, optimizing prescribing strategies, use of adherence aids, or addressing cost and other access barriers. Electronic inhaler monitors are promising interventions for both monitoring and improving adherence. However, remaining concerns about integration into patient care, data management, cost, acceptability, and ethical and privacy issues must be overcome prior to their implementation in clinical practice.

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.

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.

Adherence to Long-Acting Inhaler Use for Initial Treatment and Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Retrospective Cohort Study

We aimed to determine the effect of long-acting inhaler use adherence on acute exacerbations in treatment-naïve patients with chronic obstructive pulmonary disease (COPD) using claims data from the Korean Health Insurance Review and Assessment Service from July 2015−December 2016. Patients with COPD aged ≥ 40 years who used long-acting inhalers were enrolled and observed for 6 months. Medication adherence was determined by the medication possession ratio (MPR); patients were categorized to adherence (MPR ≥ 80%) and non-adherence (MPR < 80%) groups. Ultimately, 3959 patients were enrolled: 60.4% and 39.6% in the adherence and non-adherence groups, respectively. The relative risk of acute exacerbation in the non-adherence group was 1.58 (95% confidence interval [CI] 1.25−1.99) compared with the adherence group. The adjusted logistic regression analysis revealed a relative risk of acute exacerbation in the non-adherence vs. adherence group of 1.68 (95% CI 1.32−2.14) regarding the number of inhalers used. Poor adherence to long-acting inhalers influenced increased acute exacerbation rates among patients with COPD. The acute exacerbation of COPD risk requiring hospitalization or ED visits was high in the non-adherence group, suggesting that efforts to improve medication adherence may help reduce COPD exacerbations even in the initial management of treatment-naïve patients.

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

Inhaled therapy is the cornerstone of chronic airway disease therapy, but poor adherence to controller inhalers worsens clinical outcomes and increases cost. Monitoring of controller use is needed to improve adherence, and monitoring of reliever use can predict impending exacerbations. Both can be accurately achieved by electronic inhaler monitoring (EIM). However, evidence for EIM use in clinical practice is limited and varied, and knowledge gaps remain across different outcomes and health settings. We aimed to develop a framework to assess EIM systematically across all aspects of efficacy, apply this framework to the current literature, and identify gaps in efficacy to inform future development in the field. We adapted an existing framework for diagnostic tests, consisting of six levels of efficacy with ascending clinical relevance: technical, diagnostic accuracy, diagnostic thinking, therapeutic, patient outcome, and societal efficacy. Tailoring this framework to EIM, we incorporated expert feedback and applied it to the EIM efficacy literature. We found that EIM has good diagnostic accuracy, diagnostic thinking, and therapeutic efficacies, but evidence is lacking for specific aspects of technical, patient outcome, and societal efficacies. Further development of EIM requires improved reliability, usability, and data security for patients, and optimal integration with electronic medical records and overall patient care. Defining appropriate target patient groups and pairing EIM data with effective interventions, in conjunction with reducing costs through technological innovation and economies of scale, will enhance patient and societal outcome efficacies.

Duplicate Prescription Rates of Long-Acting Bronchodilator Inhalers

Background: Long-acting bronchodilator inhalers are widely used with or without inhaled corticosteroids (ICs) by patients with lung diseases. In Israel alone, there are 21 inhalers containing long-acting β2 agonists (LABAs) and/or long-acting muscarinic antagonists (LAMAs). Some patients are treated incorrectly with several inhalers of the same pharmacologic group. Methods: Electronic data of LABA and/or LAMA inhalers purchased during a period of 1 year were extracted in one district of Clalit Health Services in Israel. Patients who were treated with two or more inhalers from the same pharmacologic group were compared with patients without duplicate treatment. Inhaler purchases during the 12 months before and after the first duplicate purchase were compared with the purchases by patients without duplication of treatment. New diagnoses were compared to identify possible side effects. Results: Of the 13,528 patients who were treated with LABA and/or LAMA inhalers, 244 (1.8%) purchased at least two different inhalers from the same pharmacologic group. Inhaler purchases were 3.8 times higher in the duplication group during the 12 months before the first duplication. Inhaler purchase increased by 28% in the duplication group compared with a 4.5% increase in the nonduplication group (p < 0.001) during the following year. The risk for duplicated consumption was significantly higher in patients with a chronic obstructive pulmonary disease (COPD) diagnosis, males, and persons aged between 61 and 80 years. Conclusions: Nearly 2% of the patients treated with long-acting bronchodilators consumed different medications of the same pharmacologic group even when adherence was satisfactory. COPD patients are at higher risk for inhaler duplication. Clinical Trial Registration Number: 0151-20-COM1.

How to Choose the Right Inhaler Using a Patient-Centric Approach?

There are many different inhaler devices and medications on the market for the treatment of asthma and chronic obstructive pulmonary disease, with over 230 drug-delivery system combinations available. However, despite the abundance of effective treatment options, the achieved disease control in clinical practice often remains unsatisfactory. In this context, a key determining factor is the match or mismatch of an inhalation device with the characteristics or needs of an individual patient. Indeed, to date, no ideal device exists that fits all patients, and a personalized approach needs to be considered. Several useful choice-guiding algorithms have been developed in the recent years to improve inhaler–patient matching, but a comprehensive tool that translates the multifactorial complexity of inhalation therapy into a user-friendly algorithm is still lacking. To address this, a multidisciplinary expert panel has developed an evidence-based practical treatment tool that allows a straightforward way of choosing the right inhaler for each patient.

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.

Case Report: Ketogenic Diet Is Associated With Improvements in Chronic Obstructive Pulmonary Disease

Chronic Obstructive Pulmonary Disease (COPD) is a debilitating inflammatory respiratory condition that presents with worsening breathing difficulties and it is assumed to be progressive and incurable. As an inflammatory disease, COPD is associated with recruitment of immune cells to lung tissue and increased levels of pro-inflammatory cytokines, including TNF-α, IL-1β, IL-6, IL-8, and GM-CSF. Low-carbohydrate ketogenic diets have anti-inflammatory properties that could, in theory, improve COPD symptoms and progression. Herein, we report on a 54-year-old patient (C.A.) with COPD who adopted a ketogenic diet (70% calories from fat). Subsequently, C.A. experienced a reduction in inflammatory markers in association with a meaningful improvement in lung function. His inflammatory markers decreased into the normal range and his forced expiratory volume increased by 37.5% relative to its pre-ketogenic diet value. Future research should explore nutritional ketosis and ketogenic diets as possible therapeutic options for individuals with COPD.

Improving adherence in chronic airways disease: are we doing it wrongly?

Non-adherence to medicines is a significant clinical and financial burden, but successful strategies to improve it, and thus bring about significant improvements in clinical outcome, remain elusive. Many barriers exist, including a lack of awareness amongst some healthcare professionals as to the extent and impact of non-adherence and a dearth of skills to address it successfully. Patients may not appreciate that they are non-adherent, feel they cannot disclose it or underestimate its impact on their health in the short and longer term. In describing the evidence-based frameworks that identify the causal factors behind medicines taking (or not taking) behaviours, we can start to personalise interventions to enable individuals to make informed decisions about their treatments and thus overcome real and perceived barriers to adherence.

Medicines non-adherence is common and associated with significant morbidity and mortality. @GrainnedAn and colleagues outline causal factors behind this behaviour and the appropriate individualised interventions available to support optimal medicines use.https://bit.ly/3ejJNTV

Personalized Medication Adherence Management in Asthma and Chronic Obstructive Pulmonary Disease: A Review of Effective Interventions and Development of a Practical Adherence Toolkit

BACKGROUND

The management of medication nonadherence of patients with asthma or chronic obstructive pulmonary disease (COPD) remains challenging. Given the multitude of underlying causes, a personalized approach is required. The Test of Adherence to Inhalers (TAI) can identify reasons for nonadherence, but it does not provide guidance regarding how to act effectively after results.

OBJECTIVE

To develop a practical, evidence-based decision support toolkit for health care professionals managing adult patients with asthma and/or COPD, by matching TAI-identified adherence barriers to proven effective adherence-enhancing interventions.

METHODS

We performed a literature review in PubMed and Embase identifying interventions that enhanced medication adherence in adult patients with asthma and/or COPD. Randomized controlled trials published in English with full texts available were included. Effective interventions assessed by the Cochrane risk of bias tool were categorized, matched with specific TAI responses, and developed into a practical TAI Toolkit. The Toolkit was assessed for content and usability (System Usability Scale) by a multidisciplinary group of health care professionals.

RESULTS

In total, 40 randomized controlled trials were included in the review. Seven effective interventions categories were identified, informing the TAI Toolkit: reminders, educational interventions, motivational strategies, feedback on medication use, shared decision-making, simplifying the medication regimen, and multiple component interventions. Health care professionals rated the TAI Toolkit with a mean System Usability Scale score of 71.4 (range, 57.5-80.0).

CONCLUSIONS

Adherence can be improved using the different interventions that the TAI Toolkit helps select. The TAI Toolkit was well-received by health care professionals. Further research is required to test its validity, practicality, and effectiveness in practice.

Global burden of medication non-adherence in chronic obstructive pulmonary disease (COPD) and asthma: a narrative review of the clinical and economic case for smart inhalers

Medication non-adherence to asthma and chronic obstructive pulmonary disease therapy poses a significant burden for patients and societies. Non-adherence encompasses poor initiation, implementation (including poor inhalation technique) and non-persistence. Globally, non-adherence is associated with poor clinical outcomes, reduced quality of life and high healthcare and societal costs. Costs are mainly caused by excess hospitalizations and impaired work productivity. Multiple intervention programs to increase adherence in patients with asthma and chronic obstructive pulmonary disease have been conducted. However, these intervention programs are generally not as effective as intended. Additionally, adherence outcomes are mostly examined with non-objective or non-granular measures (e.g., self-report, dose count, pharmacy records). Recently developed smart inhalers could be the key to objectively diagnose and manage non-adherence effectively in patients with asthma and chronic obstructive pulmonary disease. Smart inhalers register usage of the inhaler, record time and date, send reminders, give feedback about adherence and some are able to assess inhaler technique and predict exacerbations. Still, some limitations need to be overcome before smart inhalers can be incorporated in usual care. For example, their cost-effectiveness and budget impact need to be examined. It is likely that smart inhalers are particularly cost-effective in specific asthma and chronic obstructive pulmonary disease subgroups, including patients with asthma eligible for additional GINA-5 therapy (oral corticosteroids or biologics), patients with severe asthma in GINA-5, patients with asthma with short-acting beta2 agonists overuse, patients with asthma and chronic obstructive pulmonary disease with frequent exacerbations and patients with asthma and chronic obstructive pulmonary disease of working-age. While there is high potential and evidence is accumulating, a final push seems needed to cost-effectively integrate smart inhalers in the daily management of patients with asthma and chronic obstructive pulmonary disease.

A Generative Adversarial Network (GAN) Technique for Internet of Medical Things Data

The application of machine learning and artificial intelligence techniques in the medical world is growing, with a range of purposes: from the identification and prediction of possible diseases to patient monitoring and clinical decision support systems. Furthermore, the widespread use of remote monitoring medical devices, under the umbrella of the "Internet of Medical Things" (IoMT), has simplified the retrieval of patient information as they allow continuous monitoring and direct access to data by healthcare providers. However, due to possible issues in real-world settings, such as loss of connectivity, irregular use, misuse, or poor adherence to a monitoring program, the data collected might not be sufficient to implement accurate algorithms. For this reason, data augmentation techniques can be used to create synthetic datasets sufficiently large to train machine learning models. In this work, we apply the concept of generative adversarial networks (GANs) to perform a data augmentation from patient data obtained through IoMT sensors for Chronic Obstructive Pulmonary Disease (COPD) monitoring. We also apply an explainable AI algorithm to demonstrate the accuracy of the synthetic data by comparing it to the real data recorded by the sensors. The results obtained demonstrate how synthetic datasets created through a well-structured GAN are comparable with a real dataset, as validated by a novel approach based on machine learning.

Integrating hospital and community care: using a community virtual ward model to deliver combined specialist and generalist care to patients with severe chronic respiratory disease in their homes

Background

Chronic respiratory diseases are responsible for significant patient morbidity, mortality, and healthcare use. Community virtual ward (CVW) models of care have been successfully implemented to manage patients with complex medical conditions.

Aims

To explore the feasibility and clinical outcomes of a CVW model of care in patients with chronic respiratory disease.

Methods

Patients known to specialist respiratory services with Chronic Obstructive Pulmonary Disease (COPD) and/or asthma were admitted to the CVW for disease optimisation and exacerbation management. Individualised management plans were delivered in the patients’ home by hospital-based respiratory and community nursing teams, incorporating remote technology to monitor vital signs. Symptoms and health status at admission and discharge were compared.

Results

Twenty patients were admitted. One-quarter of patients had asthma, 50% COPD, and 25% combined asthma/COPD. Patients had severe disease, mean (SD) FEV₁ 50(20) % predicted, and an average 6.4(5.7) exacerbations of disease in the previous 12 months. Patients received personalised disease and self-management education. All acute exacerbations (n = 11) were successfully treated in the community. The average length of CVW admission was 10(4) days. By discharge, 60% of COPD and 66% of asthma patients recorded improvements in symptoms score exceeding the minimal clinically important difference. Fifty percent had clinically meaningful improvements in health status.

Conclusion

A CVW model facilitates the delivery of combined specialist and generalist care to patients with chronic respiratory disease in the community and improves symptoms and health status. The principles of the model are transferable to other conditions to improve overall health and reduce emergency hospital care.

A Clinical Perspective on the Role of Electronic Devices in Monitoring and Promoting Adherence in Airways Disease

Poor adherence to treatment is a common reason why patients with chronic disease have worse outcomes than might be expected. Poor treatment adherence is of particular concern among people with airways disease because, apart from not taking treatment as prescribed, inhaled medication can also be administered incorrectly. Recently, a number of technological advances that accurately document when an inhaled treatment has been used and, in certain instances, how it was used have been developed. There is good evidence from a number of research groups that these devices, either by patient reminders or physician feedback, promote adherence to inhaled treatments. What is less certain is how, in a real-world setting, these devices change outcomes. In this perspective article, the role of electronic devices in quantifying treatment use and addressing poor treatment adherence and their potential role in clinical practice outside of clinical validation trials are described.

Peak Inspiratory Flow as a Predictive Therapeutic Biomarker in COPD

Biomarkers in COPD may be clinical (prior exacerbation history), physiologic (FEV₁), or blood based (eosinophil count or fibrinogen level). Recent interest in using biomarkers to predict response to therapy in clinical practice has emerged. The benefits of inhaled therapy depend on the correct use of the inhaler, including an appropriate inspiratory flow. Of the available delivery systems, dry powder inhalers are unique because they have an internal resistance, are breath actuated, and are flow dependent. Ideally, the user inhales "forcefully" to generate turbulent energy (determined by an individual's inspiratory flow and the resistance of the device) within the device that disaggregates the powder so that the individual inhales the medication particles into the lower respiratory tract. Because of specific features of dry powder inhalers and the required optimal inspiratory flow, an unmet need exists to identify individuals who are likely or unlikely to benefit from dry powder medications. Peak inspiratory flow, defined as the maximum airflow generated during inhalation against the simulated resistance of a dry powder inhaler, is a physiologic measure that has biological plausibility, has good test characteristics (repeatability and reliability), and is generalizable. Current evidence supports peak inspiratory flow as a predictive therapeutic biomarker to optimize therapy in both outpatients with COPD as well as those hospitalized for an exacerbation before discharge. This approach is consistent with the precepts of precision medicine, which considers differences in a person's biological features, exposure, and lifestyle to prevent and treat disease.

Economic evaluations of chronic obstructive pulmonary disease pharmacotherapy: how well are the real-world issues of medication adherence, comorbidities and adverse drug-reactions addressed?

INTRODUCTION

When estimating the cost-effectiveness or budget impact of chronic obstructive pulmonary disease (COPD) medication, it is common practice to use trial data for clinical inputs. However, such inputs do not always reflect the real-world situation. Previous reviews recognized the need for taking real-world data (medication adherence, comorbidity and adverse drug reactions [ADRs]) into account. Whether recent cost-effectiveness analyses of COPD medication implemented those recommendations is unknown.

AREAS COVERED

The authors reviewed recent economic evaluations of COPD-maintenance treatments focusing on medication adherence, comorbidity and ADRs.

EXPERT OPINION

In most registration trials of COPD treatment, strict inclusion and exclusion criteria are applied. During trials, patient monitoring is well controlled. As such, medication adherence is often higher than seen in less controlled, real-world environments with more heterogeneous characteristics. Additionally, safety data collected in trials may not be widely generalizable due to more comorbidity and polypharmacy in the real-world. Consequently, when merely relying on trial data, the impact of adherence, comorbidity and ADRs on the cost-effectiveness can be underestimated. To overcome these real-world data gaps, use of pragmatic trials and observational studies in addition to strictly controlled trial data is recommended. To catalyze implementation of these real-world issues, reporting checklists should be updated.

Delivery and adherence with inhaled therapy in asthma

The benefits of inhaled medication for the treatment of respiratory diseases are immense. Inhalers are unquestionably the most important medical devices for the treatment of asthma and in Europe today there are more than 230 different device and drug combinations of inhaled therapies many of which are available for the treatment of asthma. They are designed to alleviate the symptoms of asthma by controlling inflammation and minimising exacerbations and are intended to be simple enough to operate by all patients regardless of their age and education. However, it is still a huge challenge for patients to use their inhaler correctly and consistently and achieving asthma control continues to be an elusive goal for most patients worldwide. The reality is that despite advances in the diagnosis of asthma, the availability of comprehensive asthma management guidelines and potent asthma medications combined with efficient delivery systems, uncontrolled disease is still linked to substantial morbidity and mortality. Despite the enormous benefits of delivering topically acting medication directly to the site of disease in the lungs adherence to treatment still remains one of the biggest challenges in asthma control. This current review looks at why patients have difficulty in using their inhalers and why adherence is so poor and how this may be improved through the use of innovation in inhaler design.

Interventions to standardise hospital care at presentation, admission or discharge or to reduce unnecessary admissions or readmissions for patients with acute exacerbation of chronic obstructive pulmonary disease: a scoping review

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is a chronic respiratory disease that may be punctuated by episodes of worsening symptoms, called exacerbations. Acute exacerbations of COPD (AECOPD) are detrimental to clinical outcomes, reduce patient quality of life and often result in hospitalisation and cost for the health system. Improved diagnosis and management of COPD may reduce the incidence of hospitalisation and death among this population. This scoping review aims to identify improvement interventions designed to standardise the hospital care of patients with AECOPD at presentation, admission and discharge, and/or aim to reduce unnecessary admissions/readmissions.

METHODS

The review followed a published protocol based on methodology set out by Arksey and O'Malley and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Electronic database searches for peer-reviewed primary evidence were conducted in Web of Science, EMBASE (Elsevier) and PubMed. Abstract, full-text screening and data extraction were completed independently by a panel of expert reviewers. Data on type of intervention, implementation supports and clinical outcomes were extracted. Findings were grouped by theme and are presented descriptively.

RESULTS

21 articles met the inclusion criteria. Eight implemented a clinical intervention bundle at admission and/or discharge; six used a multidisciplinary care pathway; five used coordinated case management and two ran a health coaching intervention with patients.

CONCLUSION

The findings indicate that when executed reliably, improvement initiatives are associated with positive outcomes, such as reduction in length of stay, readmissions or use of health resources. Most of the studies reported an improvement in staff compliance with the initiatives and in the patient's understanding of their disease. Implementation supports varied and included quality improvement methodology, multidisciplinary team engagement, staff education and development of written or in-person delivery of patient information. Consideration of the implementation strategy and methods of support will be necessary to enhance the likelihood of success in any future intervention.

Determinants of self-reported adherence to inhaler therapy in patients with chronic obstructive pulmonary disease

Background

Adherence to therapy is crucial for COPD patients, since non-adherence leads to worse quality of life, increased health-care expenditure and poor clinical outcome. The aim of this study was to identify the main determinants of suboptimal adherence to therapy in a cohort of COPD patients.

Methods

General information (age, BMI, smoking, comorbidities, education, life style), lung function, exacerbations, symptoms and COPD treatment were collected. Adherence to therapy was assessed by self-reported 4-item Morisky Medication Adherence Scale (MMAS-4), and was related to anthropometric, socio/economic and health status data, obtained by questionnaires (COPD Assessment Test, CAT; Treatment Satisfaction Questionnaire, HRQoL; Katz Index of Independence of Daily Living Activities, Lawton Instrumental Activities of Daily Living Scale).

Results

136 COPD patients were studied (age 72±8 yrs; 73.5% men; BMI 28.5±7.4 kg/m²; FEV¹ 53.5±19.0 % predicted). Nearly half of the patients (46.3%) had suboptimal adherence to therapy (score >0) and, as compared to those with optimal adherence, had higher prevalence of women and coronary artery disease, heavier smoking history and worse CCQ overall score. The results of multivariate analysis showed that the determinants of suboptimal adherence were female sex (OR 4.339, 95%CI 1.509-12.474, p=0.006), amount of pack/years smoked (OR 1.947, 95%CI 1.141-3.323, p=0.015), higher CCQ overall score (OR 3.318, 95%CI 1.050-9.892, p=0.049) and higher education (OR 2.758, 95%CI 1.083-7.022, p=0.033). Adherence was better in patients assuming triple inhaler therapy.

Conclusions

Suboptimal adherence is frequent among COPD patients, particularly in women, heavy smokers and subjects with high educational level. Interventions to improve adherence should be especially addressed to patients with these characteristics.

Does a tailored intervention to promote adherence in patients with chronic lung disease affect exacerbations? A randomized controlled trial

BACKGROUND

Poor medication-adherence is common in chronic lung patients, resulting in reduced health-outcomes and increased healthcare-costs. This study aimed to investigate the impact of an acoustic reminder and support calls on adherence to inhaled therapy in asthma and COPD patients and to determine their effect on exacerbations.

METHODS

This single-blinded randomized controlled trial investigated asthma and COPD patients during 6 months in an ambulatory setting. The intervention consisted of daily alarm clock and support phone calls, whenever use of rescue medication doubled or inhaled medication was not taken as prescribed. Primary outcome was time to next exacerbation. Frequency of exacerbations, adherence to inhaled medication and quality of life scores were secondary outcomes. Cox and Poisson regression were used to determine intervention effect on time to exacerbation and frequency of exacerbations, respectively.

RESULTS

Seventy-five participants were assigned to the intervention group and 74 to usual follow-up care. During a median follow-up of 6.2 months, 22 and 28% in the intervention and control groups respectively, experienced at least one exacerbation. Intervention had no effect on time to first exacerbation (HR 0.65, 95% CI 0.21 to 2.07, P = .24), but showed a trend toward a 39% decreased frequency of exacerbations (RR = 0.61, 95% CI 0.35 to 1.03, P = .070) for the adjusted models, respectively. The intervention group had significantly more days with 80-100% taking adherence regarding puff inhalers (82 ± 14% vs. 60 ± 30%, P < .001) and dry powder capsules (90 ± .10% vs. 80 ± 21%, P = .01). Timing adherence in participants using puff inhalers was higher in the intervention group (69 ± 25% vs. 51 ± 33%, P < .001). No significant differences in QoL were found between the two groups.

CONCLUSION

Participants assigned to the intervention group had significantly better taking and timing adherence of inhaled medication resulting in a trend towards a decreased frequency of exacerbations. However, no effect on time to next exacerbation was observed.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02386722, Registered 14 February 2014.

Electronic inhaler monitoring and healthcare utilization in chronic obstructive pulmonary disease

INTRODUCTION

The effect of electronic inhaler monitoring (EIM) on healthcare utilization in chronic obstructive pulmonary disease (COPD) has not been studied. We hypothesized that the use of EIM in conjunction with a disease management program reduces healthcare utilization in patients with COPD.

METHODS

This is a retrospective pre- and post-analysis of a quality improvement project. Patients with COPD and high healthcare utilization (≥one hospitalization or emergency room visit during the year prior to enrolment) were provided with electronic monitoring devices for monitoring controller and rescue inhaler utilization for one year. Patients were contacted when alerts were triggered, indicating suboptimal adherence to controller inhaler or increased use of rescue inhalers, potentially signalling an impending exacerbation. Healthcare utilization was assessed pre- and post-monitoring, with each subject serving as his/her own control.

RESULTS

Patients with COPD and high healthcare utilization (n = 39) were recruited. Mean EIM duration was 280.5 (±120.6) days. The mean age was 68.6 (±9.9) years, FEV1 (mean forced expiratory volume in one second) was 1.1 (±0.4) L, and mean Charlson Comorbidity index was 5.6 (±2.7). Average adherence was 44.4% (28.4%). Compared with the year prior to enrolment, EIM was associated with a reduction in COPD-related healthcare utilization per year (2.2 (±2.3) versus 3.4 (±3.2), p = 0.01). Although there was a reduction in all-cause healthcare utilization, this was not statistically significant (3.4 (±2.6) versus 4.7 (±4.1), p = 0.06).

DISCUSSION

EIM in conjunction with a disease management program may play a role in reducing healthcare utilization in COPD patients with a history of high healthcare utilization.

The Importance of Inhaler Adherence to Prevent COPD Exacerbations

It has been shown that the better outcomes of chronic obstructive pulmonary disease (COPD) are closely associated with adherence to drug therapy, independent of the treatment administered. The clinical trial Towards a Revolution in COPD Health (TORCH) study clearly showed in a three year follow up that patients with good adherence to their inhaler treatment presented a longer time before the first exacerbation, a lower susceptibility to exacerbation and lower all-cause mortality. The Latin American Study of 24-hour Symptoms in Chronic Obstructive Pulmonary Disease (LASSYC), a real-life study, evaluated the self-reported inhaler adherence in COPD patients in seven countries in a cross-sectional non-interventional study and found that approximately 50% of the patients had good adherence, 30% moderate adherence and 20% poor adherence. Adherence to inhaler may be evaluated by the specific inhaler adherence questionnaire, the Test of Adherence to Inhalers (TAI). Several factors may predict the incorrect use of inhalers or adherence in COPD outpatient, including the number of devices and the daily dosing frequency. Ideally, patient education, simplicity of the device operation, the use of just one device for multiple medications and the best adaptation of the patient to the inhaler should guide the physician in prescribing the device.

Adherence to inhaled therapy and its impact on chronic obstructive pulmonary disease (COPD)

Background

COPD is a treatable disease with increasing prevalence worldwide. Treatment aims to stop disease progression, to improve quality of life, and to reduce exacerbations. We aimed to evaluate the association of the stage of COPD on adherence to inhaled therapy and the relationship between adherence and COPD exacerbations.

Methods

A retrospective analysis of patients hospitalized for acute exacerbation of COPD in a tertiary care hospital in Upper Austria and discharged with a guideline conform inhaled therapy was performed. Follow-up data on medical utilization was recorded for the subsequent 24 months. Adherence to inhaled therapy was defined according to the percentage of prescribed inhalers dispensed to the patient and classified as complete (> 80%), partial (50–80%) or low (< 50%).

Results

Out of 357 patients, 65.8% were male with a mean age of 66.5 years and a mean FEV₁ of 55.0%pred. Overall, 35.3% were current smokers, and only 3.9% were never-smokers. In 77.0% inhaled triple therapy (LAMA + LABA + ICS) was prescribed. 33.6% showed complete adherence to their therapy (33.2% in men, 34.4% in women), with a mean age of 67.0 years. Mean medication possession ratio by GOLD spirometry class I – IV were 0.486, 0.534, 0.609 and 0.755, respectively (p = 0.002). Hence, subjects with complete adherence to therapy had a significantly lower FEV₁ compared to those with low adherence (49.2%pred. vs 59.2%pred., respectively; p <  0.001).

The risk of exacerbations leading to hospitalization was 10-fold higher in GOLD spirometry class IV compared to GOLD spirometry class I, which was even more evident in multivariate analysis (OR 13.62).

Conclusion

Complete adherence to inhaled therapy was only seen in 33.6% and was higher among those with more severe COPD.

Trial registration

Not applicable.

Personalising adherence-enhancing interventions using a smart inhaler in patients with COPD: an exploratory cost-effectiveness analysis

Four inhaler adherence clusters have been identified using the INCA audio device in COPD patients: (1) regular use/good technique, (2) regular use/frequent technique errors, (3) irregular use/good technique, and (4) irregular use/frequent technique errors. Their relationship with healthcare utilization and mortality was established, but the cost-effectiveness of adherence-enhancing interventions is unknown. In this exploratory study, we aimed to estimate the potential cost-effectiveness of reaching optimal adherence in the three suboptimal adherence clusters, i.e., a theoretical shift of clusters 2, 3, and 4 to cluster 1. Cost-effectiveness was estimated over a 5-year time horizon using the Irish healthcare payer perspective. We used a previously developed COPD health-economic model that was updated with INCA trial data and Irish national economic and epidemiological data. For each cluster, interventions would result in additional quality-adjusted life years gained at reasonable investment. Cost-effectiveness was most favorable in cluster 3, with possible cost savings of €845/annum/person.