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

Application of e-Health tools in the assessment of inhalation therapy adherence in patients with chronic obstructive pulmonary disease: Scoping review coupled with bibliometric analysis

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a common respiratory disorder, and the assessment of inhalation therapy adherence is an important component of management in COPD patients. The emergence of e-Health tools provides new prospects for the assessment of inhalation therapy adherence. However, there is no comprehensive summary of the application of e-Health tools in assessing inhalation therapy adherence in COPD patients.

OBJECTIVES

This review aims to clarify the current state, effects, benefits, and limitations of using e-Health tools in assessing inhalation therapy adherence in COPD patients and provide future directions and recommendations for development in this field.

METHODS

This scoping review follows the 5-step framework developed by Arksey and O'Malley. Literature on the practical application of e-Health tools was systematically searched from PubMed, Embase, Web of Science, CINAHL, and Cochrane Library, spanning from inception to April 2024. Additionally, VOSviewer (version 1.6.20) was used to construct visualization maps of countries, institutions, authors, and keywords to investigate the internal relations of included literature and to explore research hotspots.

RESULTS

A total of 26 studies were included. The e-Health tools mainly include electronic monitoring devices (EMDs), smartphone app, electronic prescription, and web-based tool. e-Health tools can assess inhalation therapy adherence in COPD patients in real-time and objectively, and improve inhalation therapy adherence and clinical outcomes. Bibliometric analysis indicates that there is no network of co-authorship between countries or academic organizations. Two collaborative networks have been formed centered on Greene G. EMDs and disease exacerbations are the popular research directions.

CONCLUSIONS

e-Health tools have a wide range of applications and promising prospects in the assessment of inhalation therapy adherence in COPD patients. In the future, it is necessary to strengthen the cooperation between countries or research institutions, explore the cost-effectiveness of e-Health tools, and improve their accessibility and usability while adopting integrated design and combining artificial intelligence to improve the effectiveness of e-Health tools in the management of COPD.

The Turkish adaptation of the Adherence to Asthma Medication Questionnaire

BACKGROUND

This study was conducted to adapt the Adherence to Asthma Medication Questionnaire (AAMQ-13) into Turkish.

METHODS

The research was conducted in the pulmonology outpatient clinic of a state hospital in Nigde/Turkey. The sample consisted of 229 volunteers with asthma for at least one year. First, language and content validity were assessed. After evaluating the language validity and content validity of the questionnaire, internal consistency, split-half reliability, and construct validity were examined. Questionnaire and demographic data were analyzed using numbers, percentages, dependent and independent groups t-tests, correlation analysis.

RESULTS

The AAMQ-13-TR has a Cronbach's alpha (α) score of 0.90 (p < 0.001). It has a split-half reliability coefficient of 0.86. The confirmatory factor analysis (CFA) shows that the factor structure of the AAMQ-13-TR agrees well with the two-factor model of the original questionnaire.

CONCLUSIONS

This study presented sources of evidence of validity of AAMQ-13-TR in Turkish population.

Errors in Metered Dose Inhaler Use Amongst Pediatric Asthma Patients

Purpose

The aim of this paper is to use easily accessible smartphones as a straightforward means for physicians to objectively check Medical Device Inhaler (MDI) technique, without the need for additional devices. Additionally, we seek to assess the frequency of inhaler technique errors and their impact on asthma control.

Patients and Methods

Thirty-two children between the ages of 5 and 18 receiving asthma therapy through MDIs were included. Three surveys were administered to all participants to gauge device history, asthma control, and patient characteristics. Patient technique was scored using inhaler audio signals recorded with a smartphone. For subjects that were able, forced oscillation technique (FOT) was performed during tidal breathing conditions before and after corticosteroid administration.

Results

81% (25/31) of participants used their MDIs incorrectly with the most common errors being rapid shallow breathing, inadequate breath-holding, and excessive actuations. Poor inhaler technique correlated with poorly controlled asthma symptoms.

Conclusion

The use of smartphone recordings can a convenient way to evaluate technique errors and could allow patients to demonstrate and refine their technique and usage without a doctor's visit, ensuring proper technique and enhancing treatment effectiveness.

Use of digital measurement of medication adherence and lung function to guide the management of uncontrolled asthma (INCA Sun): a multicentre, single-blinded, randomised clinical trial

BACKGROUND

The clinical value of using digital tools to assess adherence and lung function in uncontrolled asthma is not known. We aimed to compare treatment decisions guided by digitally acquired data on adherence, inhaler technique, and peak flow with existing methods.

METHODS

A 32-week prospective, multicentre, single-blinded, parallel, randomly controlled trial was done in ten severe asthma clinics across Ireland, Northern Ireland, and England. Participants were 18 years or older, had uncontrolled asthma, asthma control test (ACT) score of 19 or less, despite treatment with high-dose inhaled corticosteroids, and had at least one severe exacerbation in the past year despite high-dose inhaled corticosteroids. Patients were randomly assigned in a 1:1 ratio to the active group or the control group, by means of a computer-generated randomisation sequence of permuted blocks of varying sizes (2, 4, and 6) stratified by fractional exhaled nitric oxide (FeNO) concentration and recruitment site. In the control group, participants were masked to their adherence and errors in inhaler technique data. A statistician masked to study allocation did the statistical analysis. After a 1-week run-in period, both groups attended three nurse-led education visits over 8 weeks (day 7, week 4, and week 8) and three physician-led treatment adjustment visits at weeks 8, 20, and 32. In the active group, treatment adjustments during the physician visits were informed by digital data on inhaler adherence, twice daily digital peak expiratory flow (ePEF), patient-reported asthma control, and exacerbation history. Treatment was adjusted in the control group on the basis of pharmacy refill rates (a measure of adherence), asthma control by ACT questionnaire, and history of exacerbations and visual management of inhaler technique. Both groups used a digitally enabled Inhaler Compliance Assessment (INCA) and PEF. The primary outcomes were asthma medication burden measured as proportion of patients who required a net increase in treatment at the end of 32 weeks and adherence rate measured in the last 12 weeks by area under the curve in the intention-to-treat population. The safety analyses included all patients who consented for the trial. The trial is registered with ClinicalTrials.gov, NCT02307669 and is complete.

FINDINGS

Between Oct 25, 2015, and Jan 26, 2020, of 425 patients assessed for eligibility, 220 consented to participate in the study, 213 were randomly assigned (n=108 in the active group; n=105 in the control group) and 200 completed the study (n=102 in the active group; n=98 in the control group). In the intention-to-treat analysis at week 32, 14 (14%) active and 31 (32%) control patients had a net increase in treatment compared with baseline (odds ratio [OR] 0·31 [95% CI 0·15-0·64], p=0·0015) and 11 (11%) active and 21 (21%) controls required add-on biological therapy (0·42 [0·19-0·95], p=0·038) adjusted for study site, age, sex, and baseline FeNO. Three (16%) of 19 active and 11 (44%) of 25 control patients increased their medication from fluticasone propionate 500 μg daily to 1000 μg daily (500 μg twice a day; adjusted OR 0·23 [0·06-0·87], p=0·026). 26 (31%) of 83 active and 13 (18%) of 73 controls reduced their medication from fluticasone propionate 1000 μg once daily to 500 μg once daily (adjusted OR 2·43 [1·13-5·20], p=0·022. Week 20-32 actual mean adherence was 64·9% (SD 23·5) in the active group and 55·5% (26·8) in the control group (between-group difference 11·1% [95% CI 4·4-17·9], p=0·0012). A total of 29 serious adverse events were recorded (16 [55%] in the active group, and 13 [45%] in the control group), 11 of which were confirmed as respiratory. None of the adverse events reported were causally linked to the study intervention, to the use of salmeterol-fluticasone inhalers, or the use of the digital PEF or INCA.

INTERPRETATION

Evidence-based care informed by digital data led to a modest improvement in medication adherence and a significantly lower treatment burden.

FUNDING

Health Research Board of Ireland, Medical Research Council, INTEREG Europe, and an investigator-initiated project grant from GlaxoSmithKline.

Electronic Monitoring Devices to Support Inhalation Technique in Patients with Asthma: a Narrative Review

Purpose of Review

Improper inhaling technique is common and is associated with poor patient outcomes. However, digital e-health devices may offer novel opportunities for educational support. This narrative review provides an overview of electronic monitoring devices (EMDs) measuring patient inhalation technique. We summarise their technical features, capabilities and limitations and discuss the steps necessary for implementation in clinical practice.

Recent Findings

Six EMDs measuring inhalation were identified. The quality of published evidence varied widely. Devices differed in the inhalation technique steps measured, the feedback provided and the type of sensor employed. Sustainability and battery life differed according to whether devices were built into inhalers or add-ons. Nevertheless, all EMDs could reliably capture diverse inhaler technique errors, and some can guide educational interventions and follow-up treatment. In addition, some EMDs may serve as an early warning system for exacerbations.

Summary

New-generation EMDs can measure patient inhalation technique, yet there is limited data on patient preferences, acceptability of inhaler technique monitoring, cost-effectiveness and the influence of inhaler technique monitoring on clinical outcomes, all representing areas for further research.

Assessing adherence to medications: Is there a difference between a subjective method and an objective method, or between using them concurrently?

Background

Patients' adherence to medication can be assessed by several subjective or objective methods. The Global Initiative for Asthma (GINA) has recommended the use of both measures simultaneously.

Objective

To assess patients' adherence to medication using a subjective or an objective method separately, and via using a combination of both methods. As well as identifying the degree of agreement between the two methods.

Methods

Participants who met the study inclusion criteria completed the Adherence to Asthma Medication Questionnaire (AAMQ). A retrospective audit was conducted in order to extract pharmacy refill records for the previous twelve months. The patients' pharmacy refill records were expressed using the Medication Possession Ratio (MPR). Data were analyzed using the Statistical Package for Social Science. The degree of agreement was determined by Cohen's kappa coefficient (κ).

Results

In terms of the difference in the ability of each method to identify non-adherent patients, a higher percentage of non-adherent patients were identified using the self-reported AAMQ (61.4%) compared to the pharmacy refill records (34.3%). When both methods, in combination, were used to assess adherence, the percentage of non-adherent patients was 80.0%, which is higher than each method when used separately. Twenty percent of the patients were considered adherent on both assessment methods, while 15.7% were considered non-adherent via both methods. Consequently, the AAMQ and pharmacy refill records agreed on 35.7% of the patients. The degree of agreement analysis showed a low correlation between the two methods.

Conclusion

The combination strategy resulted in a higher percentage of non-adherent patients, compared to using a subjective (the AAMQ) or an objective (the pharmacy refill records) method. The GINA guideline proposition may be supported by the present study's findings.

The Contribution of Oral and Inhaled Glucocorticoids to Adrenal Insufficiency in Asthma

BACKGROUND

Exposure to any form of glucocorticoid preparation is associated with a risk of adrenal insufficiency (AI).

OBJECTIVE

To establish the contribution of oral corticosteroid (OCS) and inhaled corticosteroid (ICS) exposure to the risk of AI in a cohort of patients (n = 80) with severe, uncontrolled asthma.

METHODS

We compiled individualized cumulative OCS and ICS exposure data using a combination of health care records and electronic inhaler monitoring using an Inhaler Compliance Assessment device and estimated the risk of AI for each participant using a morning serum cortisol concentration.

RESULTS

The predicted prevalence of AI based on morning cortisol concentrations was 25% (20 of 80). Participants on maintenance OCS therapy had the highest risk of AI at 60% (6 of 10) compared with 17% (11 of 65) in those with no recent OCS exposure. Morning serum cortisol correlated negatively with both OCS exposure (mg/kg prednisolone) (r = -0.4; P < .0002) and ICS exposure (mg/kg fluticasone propionate) (r = -0.26; P = .019). Logistic regression of risk of AI against the number of standard treatment courses of OCS demonstrated a positive relationship although this did not reach statistical significance (odds ratio, 1.41; 95% CI, 0.97-2.05; P = .073). Logistic regression analysis, categorizing patients as high-risk AI (cortisol <130 nmol/L) or not (cortisol >130 nmol/L), showed that cumulative ICS exposure remained a significant predictor of AI, even when exposure to OCS was controlled for (odds ratio, 2.17 per 1 mg/kg increase in cumulative fluticasone propionate exposure; 95% CI, 1.06-4.42; P = .033).

CONCLUSIONS

Our data suggest that AI is common among patients with asthma and highlights that the risk of AI is associated with both high-dose ICS therapy and intermittent treatment courses of OCS.

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.

The future of dry powder inhaled therapy: Promising or Discouraging for systemic disorders?

Dry powder inhalation therapy has been shown to be an effective method for treating respiratory diseases like asthma, Chronic Obstructive Pulmonary Diseases and Cystic Fibrosis. It has also been widely accepted and used in clinical practices. Such success has led to great interest in inhaled therapy on treating systemic diseases in the past two decades. The current coronavirus (COVID-19) pandemic also has increased such interest and is triggering more potential applications of dry powder inhalation therapy in vaccines and antivirus drugs. Would the inhaled dry powder therapy on systemic disorders be as encouraging as expected? This paper reviews the marketed and in-development dry powder inhaler (DPI) products on the treatment of systemic diseases, their status in clinical trials, as well as the potential for COVID-19 treatment. The advancements and unmet problems on DPI systems are also summarized. With countless attempts behind and more challenges ahead, it is believed that the dry powder inhaled therapy for the treatment of systemic disorders still holds great potential and promise.

Exploring Validated Self-Reported Instruments to Assess Adherence to Medications Used: A Review Comparing Existing Instruments

OBJECTIVE

To provide an overview of instruments that measure adherence to medications to facilitate selection of an instrument and to provide a summary of some published adherence assessment tools tailored to be used by the healthcare team, especially the pharmacists.

DATA SOURCES

Studies were identified via PubMed, Medline, Embase, and Google Scholar using the search terms medication adherence, compliance, persistence, combined with the terms questionnaire, scale, survey, self-report, and instrument.

STUDY SELECTION

Articles written in English, describing questionnaire instruments that were psychometrically evaluated (reporting a good coefficient of internal consistency, reliability assessed through Cronbach's alpha, and had been validated against a subjective or objective measure), and containing 30 or fewer items were included.

DATA SYNTHESIS

Twelve instruments were identified and included in this review. Instruments were reviewed by evaluating specific characteristics (number of items, sample size, reliability, sensitivity, specificity, questionnaire completion time, criterion validity, and component analysis).

CONCLUSION

Various instruments are used to assess patient adherence to medications; however, no single one performs well on all criteria. Every instrument has different advantages and unique properties. A particular instrument can be chosen after considering certain factors, such as the specific requirements, population, the needed time to complete the questionnaire, the sensitivity, and the specificity of the questionnaire. Moreover, there is a recognized need to provide primary care medication adherence services customized to patient's needs. A link for teamwork between healthcare providers such as pharmacists and patients is needed. This link can be a validated instrument to assess patient's adherence to medication.

Measuring adherence to therapy in airways disease

Non-adherence to medication is one of the most significant issues in all airways disease and can have a major impact on disease control as well as on unscheduled healthcare utilisation. It is vital that clinicians can accurately determine a patient's level of adherence in order to ensure they are gaining the maximal benefit from their therapy and also to avoid any potential for unnecessary increases in therapy. It is essential that measurements of adherence are interpreted alongside biomarkers of mechanistic pathways to identify if improvements in medication adherence can influence disease control. In this review, the most common methods of measuring adherence are discussed. These include patient self-report, prescription record checks, canister weighing, dose counting, monitoring drug levels and electronic monitoring. We describe the uses and benefits of each method as well as potential shortcomings. The practical use of adherence measures with measurable markers of disease control is also discussed.

Educational aims

To understand the various methods available to measure adherence in airways disease.To learn how to apply these adherence measures in conjunction with clinical biomarkers in routine clinical 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.

Remote health diagnosis and monitoring in the time of COVID-19

Coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is rapidly spreading across the globe. The clinical spectrum of SARS-CoV-2 pneumonia requires early detection and monitoring, within a clinical environment for critical cases and remotely for mild cases, with a large spectrum of symptoms. The fear of contamination in clinical environments has led to a dramatic reduction in on-site referrals for routine care. There has also been a perceived need to continuously monitor non-severe COVID-19 patients, either from their quarantine site at home, or dedicated quarantine locations (e.g. hotels). In particular, facilitating contact tracing with proximity and location tracing apps was adopted in many countries very rapidly. Thus, the pandemic has driven incentives to innovate and enhance or create new routes for providing healthcare services at distance. In particular, this has created a dramatic impetus to find innovative ways to remotely and effectively monitor patient health status. In this paper, we present a review of remote health monitoring initiatives taken in 20 states during the time of the pandemic. We emphasize in the discussion particular aspects that are common ground for the reviewed states, in particular the future impact of the pandemic on remote health monitoring and consideration on data privacy.

Medication adherence among patients with chronic obstructive pulmonary disease treated in a primary general hospital during the COVID-19 pandemic

Background

The objective of this study was to investigate medication adherence and the associated influencing factors in patients with chronic obstructive pulmonary disease (COPD) who were treated in a primary general hospital in Shanghai China during the 2019 novel coronavirus (COVID-19) pandemic.

Methods

From March to April 2020, all of the COPD patients treated in our department in the last 7 years were interviewed by telephone. The basic patient data and each questionnaire item were collected, and influencing factors were analyzed by the Chi-square test, U test, and univariate and multivariate logistic regression analyses.

Results

A total of 191 patients with COPD were queried, and 84 (44.0%) valid questionnaires were obtained. Among them, individuals with group B symptoms were most represented (45.2%); 53.6% had Medical Research Council (MRC) dyspnea levels of 2 or above. Chronic obstructive pulmonary disease assessment test (CAT) had an average of 9 [3, 13], and 52.4% of patients used two-drug combination therapy. Medication adherence was both good in ordinary times and over the past 2 months of the pandemic, and 88.8% of patients had no acute exacerbation during the pandemic. The CAT scores of male patients <70 years old, and patients with general outpatient follow-up and regular gargling were reduced (P<0.05). Drug combination and doctor’s supervision were favorable factors affecting medication adherence during the 2 months of the pandemic, while possible depression was an unfavorable factor (P<0.05).

Conclusions

During the pandemic, medication adherence in patients with COPD was similar to that in regular times, and was significantly related to drug combination, doctor’s supervision, and accompanying mood disorders. An effective way to improve patient adherence and disease control could be strengthening follow-up education and diagnosing and treating depression and other complications.

Measuring and reporting treatment adherence: What can we learn by comparing two respiratory conditions?

Medication non-adherence, defined as any deviation from the regimen recommended by their healthcare provider, can increase morbidity, mortality and side effects, while reducing effectiveness. Through studying two respiratory conditions, asthma and tuberculosis (TB), we thoroughly review the current understanding of the measurement and reporting of medication adherence. In this paper, we identify major methodological issues in the standard ways that adherence has been conceptualised, defined and studied in asthma and TB. Between and within the two diseases there are substantial variations in adherence reporting, linked to differences in dosing intervals and treatment duration. Critically, the communicable nature of TB has resulted in dose-by-dose monitoring becoming a recommended treatment standard. Through the lens of these similarities and contrasts, we highlight contemporary shortcomings in the generalised conceptualisation of medication adherence. Furthermore, we outline elements in which knowledge could be directly transferred from one condition to the other, such as the application of large-scale cost-effective monitoring methods in TB to resource-poor settings in asthma. To develop a more robust evidence-based approach, we recommend the use of standard taxonomies detailed in the ABC taxonomy when measuring and discussing adherence. Regimen and intervention development and use should be based on sufficient evidence of the commonality and type of adherence behaviours displayed by patients with the relevant condition. A systematic approach to the measurement and reporting of adherence could improve the value and generalisability of research across all health conditions.

Automatic Audio-Based Classification of Patient Inhaler Use: A Pharmacy Based Study

Chronic respiratory diseases may be controlled through the delivery of medication to the airways and lungs using an inhaler. However, adherence to correct inhaler technique is poor, which impedes patients from receiving maximum clinical benefit from their medication. In this study, the Inhaler Compliance Assessment device was employed to record audio of patients using a Diskus dry powder inhaler. An algorithm that classifies inhaler sounds (blister, inhalation, interference) was developed to automatically assess patient adherence from these inhaler audio recordings. The presented algorithm employed audio-based signal processing methods and statistical modeling in the form of quadratic discriminant analysis (QDA). A total of 350 audio recordings were obtained from 70 patients. The acquired audio dataset was split evenly for training and testing. A total accuracy of 85.35% was obtained (testing dataset) for this 3-class classification system. A sensitivity of 89.22% and 70% was obtained for inhalation and blister detection respectively. This approach may have significant clinical impact by providing healthcare professionals with an efficient, objective method of monitoring patient adherence to inhaler treatment.

Deep CNN Sparse Coding for Real Time Inhaler Sounds Classification

Effective management of chronic constrictive pulmonary conditions lies in proper and timely administration of medication. As a series of studies indicates, medication adherence can effectively be monitored by successfully identifying actions performed by patients during inhaler usage. This study focuses on the recognition of inhaler audio events during usage of pressurized metered dose inhalers (pMDI). Aiming at real-time performance, we investigate deep sparse coding techniques including convolutional filter pruning, scalar pruning and vector quantization, for different convolutional neural network (CNN) architectures. The recognition performance has been assessed on three healthy subjects following both within and across subjects modeling strategies. The selected CNN architecture classified drug actuation, inhalation and exhalation events, with 100%, 92.6% and 97.9% accuracy, respectively, when assessed in a leave-one-subject-out cross-validation setting. Moreover, sparse coding of the same architecture with an increasing compression rate from 1 to 7 resulted in only a small decrease in classification accuracy (from 95.7% to 94.5%), obtained by random (subject-agnostic) cross-validation. A more thorough assessment on a larger dataset, including recordings of subjects with multiple respiratory disease manifestations, is still required in order to better evaluate the method’s generalization ability and robustness.

The Utility of Electronic Inhaler Monitoring in COPD Management: Promises and Challenges

COPD is a common respiratory disorder that poses a major health-care burden with societal and financial ramifications. Although effective inhaled therapies are available, nonadherence is common among patients with COPD and potentially contributes to the burden of this disease. Electronic inhaler monitoring (EIM) is a novel modality that enables real-time assessment of adherence to inhaled therapy and informs the assessment of treatment effectiveness. EIM can be combined with physician feedback, automated audiovisual reminders, and text messaging to bolster adherence. Clinical studies have suggested that EIM can diagnose nonadherence, improve adherence, and predict exacerbations. Using an EIM-guided protocol has the potential to avoid treatment escalation in the nonadherent. Coupling EIM to behavioral intervention is an area of ongoing research with mixed results, with some studies showing benefit and others showing minimal or no significant change in clinical outcomes. Further investigation is necessary to understand the incremental benefits of EIM features, delineate optimal program implementation, and target patient populations that would benefit the most from monitoring.

The role of inspiratory flow in selection and use of inhaled therapy for patients with chronic obstructive pulmonary disease

Inhalation therapy is the mainstay of chronic obstructive pulmonary disease management, and inhaler selection can have a profound impact on drug delivery and medication adherence, as well as on treatment outcomes. Although multiple delivery systems, such as pressurized metered-dose inhalers, dry powder inhalers, slow-mist inhalers, and nebulizers, are available, clinical benefits achieved by patients rely on effective delivery of the inhaled medication to the airways. Among several factors influencing drug deposition, inspiratory flow is one of the most important. Inspiratory flow impacts drug delivery and subsequent clinical efficacy, making it necessary to adequately train patients to ensure correct inhaler use. Peak inspiratory flow is the maximal airflow generated during a forced inspiratory maneuver. Health care professionals need to select the appropriate delivery system after carefully considering patient characteristics, including lung function, optimal inspiratory flow, manual dexterity, and cognitive function. Herein, the role of inspiratory flow in the selection and use of inhaled therapy in patients with COPD is reviewed.

Errors in inhaler use related to devices and to inhalation technique among patients with chronic obstructive pulmonary disease in primary health care

AIM

The aim of this study was to describe inhaler use in primary health care patients with chronic obstructive pulmonary disease (COPD) and to categorize these patients into those making errors related to devices, those making errors related to inhalation technique and those making errors related to both.

DESIGN

Observational study.

METHODS

COPD nurses used a checklist to assess the use of inhalers by patients with spirometry-verified COPD (N = 183) from primary healthcare centres. The STROBE checklist has been used.

RESULTS

The mean age of the patients was 71 (SD 9) years. Almost half of them (45%) made at least one error; of these, 50% made errors related to devices, 31% made errors related to inhalation technique and 19% made errors related both to devices and to inhalation technique.

Personalized Biofeedback on Inhaler Adherence and Technique by Community Pharmacists: A Cluster Randomized Clinical Trial

BACKGROUND

Guidelines recommend that patients treated with inhalers receive adherence counseling and device training. Digital technologies that assess both inhaler adherence and technique have been developed. Using these technologies community pharmacists, who have regular contact with patients, are well placed to deliver personalized inhaler education.

OBJECTIVE

To determine the impact of a pharmacist intervention, informed by digital technology, on inhaler technique and adherence of patients with asthma in the community.

METHODS

A cluster randomized, parallel-group, multisite pharmacy study was conducted over 6 months. All study groups had an electronic device (inhaler compliance assessment device) attached to their maintenance inhaler. A biofeedback group received personalized inhaler training informed by data recorded by the device. The demonstration group received inhaler training, by physical demonstration with a placebo inhaler. The control group received usual care. The primary outcome was inhaler adherence, which was classified as "actual adherence" and expressed as the proportion of expected drug accumulation if adherence and technique had been perfect. Secondary outcomes were quality-of-life scores as measured by the St George's Respiratory Questionnaire, symptoms, and exacerbations.

RESULTS

A total of 152 participants (n = 74 biofeedback, n = 56 demonstration, and n = 22 control) were recruited. Asthma was the predominant condition among participants (n = 83), with chronic obstructive pulmonary disease (n = 55) and asthma/chronic obstructive pulmonary disease overlap also reported (n = 8). In intention-to-treat analysis, adherence in the biofeedback group during month 2 was 62%, 18% higher (95% CI, 6 to 30) than that in the demonstration group (P = .004) and 24% higher (95% CI, 9 to 40) than that in the control group (P = .003). During month 6, adherence was 14% higher (95% CI, -1 to 30; P = .07) in the biofeedback group than in the demonstration group and 31% higher (95% CI, 13 to 48; P = .001) than in the control group. At the end of the study, the biofeedback group had a sustained fall in St George's Respiratory Questionnaire from baseline, -6.1 (95% CI, -9 to -0.4; P = .04) and had significantly improved daily respiratory symptoms.

CONCLUSIONS

Community pharmacist-delivered inhaler training informed by a digital technology improved adherence and health status.

Inhalation technique and asthma outcomes with different corticosteroid-containing inhaler devices

Objective: Inhaler devices must be used correctly to ensure the effectiveness of the asthma treatment. This study evaluated inhalation technique across different types of corticosteroid-containing inhaler devices as well as health outcomes in patients with asthma. Methods: In a cross-sectional study, we evaluated inhaler technique by observing patients' handling of the inhaler devices and using checklists for four inhaler types, namely Diskus (n = 52), pressure metered dose inhalers (pMDIs; n = 41), Turbuhaler (n = 36) and Twisthaler (n = 16). We also collected data on patients' characteristics, asthma therapy, exacerbations, medication adherence (8-item Morisky Medication Adherence Scale), asthma control (Asthma Control Test) and quality of life (Saint George Respiratory Questionnaire). Results: In total, we included 145 patients. The mean (SD) age of the patients was 54.5 (18.9) years and 57% were female. The majority of the patients (70%) made at least one error in their inhalation technique. Patients using Turbuhaler performed the highest number of elements correctly, followed by pMDIs, Twisthaler and Diskus. Patients with Diskus or Twisthaler had better adherence compared with patients using pMDIs or Turbuhaler. Patients using Twisthaler had better asthma outcomes than patients using the other device types. Conclusions: Most patients with asthma made mistakes when handling their inhaler devices, especially those using Diskus. However, in addition to the device type being used, patients' characteristics, asthma therapy and medication adherence also played an important role in achieving good health outcomes.

Does knowledge of patient non-compliance change prescribing behavior in the real world? A claims-based analysis of patients with serious mental illness

Background

New digital technologies offer providers the promise of more accurately tracking patients’ medication adherence. It is unclear, however, whether access to such information will affect provider treatment decisions in the real world.

Methods

Using prescriber-reported information on patient non-compliance from health insurance claims data between 2008 and 2014, we examined whether prescribers’ knowledge of non-compliance was associated with different prescribing patterns for patients with serious mental illness (SMI). We examined patients who initiated an oral atypical antipsychotic, but were later objectively non-adherent to this treatment, defined as proportion of days covered (PDC) <0.8. We examined how a physician’s awareness of patient non-compliance (ICD-9 diagnosis code: V15.81) was correlated with the physician’s real-world treatment decisions for that patient. Treatment decisions studied included the share of patients who increased antipsychotic dose, augmented treatment, switched their antipsychotic, or used a long-acting injectable (LAI).

Results

Among the 286,249 patients with SMI who initiated an antipsychotic and had PDC <0.8, 4,033 (1.4%) had documented non-compliance. When prescribers documented non-compliance, patients were more likely to be switched to another antipsychotic (32.8% vs 24.7%, P<0.001), have their dose increased (24.4% vs 22.1%, P=0.004), or receive an LAI (0.09% vs 0.04%, P=0.008), but were less likely to have augmented therapy with another antipsychotic (1.1% vs 1.3%, P=0.035) than patients without documented non-compliance.

Conclusion

Among SMI patients with documented non-compliance, the frequency of dose, medication switches, and LAI use were higher and augmentation was lower compared to patients without documented non-compliance. Access to adherence information may help prescribers more rapidly switch ineffective medications as well as avoid unnecessary medication augmentation.

Adherence to Inhaled Medications and its Effect on Healthcare Utilization and Costs Among High-Grade Chronic Obstructive Pulmonary Disease Patients

BACKGROUND

Adherence to inhaled medication regimens affects chronic obstructive pulmonary disease (COPD) prognosis and quality of life, and reduces the use of healthcare services, resulting in cost savings.

OBJECTIVES

To examine the effects of adherence to inhaled medication regimens on healthcare utilization and costs in high-grade COPD patients.

METHODS

We performed an observational retrospective cohort study using a longitudinal data set from the Korean Health Insurance Review and Assessment Service (2008-2013) containing healthcare services' information for 50 million beneficiaries. The study population was high-grade COPD patients. "Adherent" was defined as a patient attaining a medication possession ratio (MPR) ≥ 80%. We estimated the effects of adherence on the use of intensive care units (ICUs) and emergency rooms (ERs) using a multivariate logistic regression, and estimated the effects on costs (all-cause and COPD-related) using a generalized linear model, with adjustment for patient sociodemographic characteristics, health status, and comorbidities.

RESULTS

Of 9086 high-grade COPD patients, adherence declined from 34.7 to 22.3% over 4 years. Adherence was inversely associated with use of ICUs and costs, and this association got stronger as the adherence period lengthened. Over the 4-year period, the adherent group had a lower likelihood of using ICUs [odds ratio (OR) = 0.74, 95% confidence interval (CI) 0.60-0.91] than the non-adherent group. Similarly, the adherent group had a 10.4% lower all-cause cost (p < 0.001) and an 11.7% lower COPD-related cost (p < 0.0001) versus the non-adherent group.

CONCLUSIONS

Adherence reduces healthcare utilization and costs, so adherence is not only clinically effective but also economically efficient. However, less than one-quarter of this population remained adherent over the 4-year period, suggesting that strategies are needed to improve adherence.

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.