Assessing adherence to inhaled therapies in asthma and the emergence of electronic monitoring devices

Hetal Dhruve, David J. Jackson
European Respiratory Review 2022 31: 210271; DOI: 10.1183/16000617.0271-2021

Abstract

Infrequent use of inhaled corticosteroids (ICS) and/or over-reliance of short-acting β-agonists (SABA) are recognised as key contributors to increased morbidity and mortality in asthma. The most frequent measures of ICS adherence and SABA use rely on patient-reported questionnaires or prescription refill records, neither of which are considered sufficiently reliable. Technological advancements in the development of electronic monitoring of inhaler devices allow for monitoring of use, as well as recording of and feedback on inhaler technique for some devices. Most electronic monitoring devices (EMDs) are paired with a smartphone application, allowing patients to set reminders and display both preventer and reliever use over time. This allows identification of intentional and unintentional ICS non-adherence as well as frequency of SABA use. This information assists clinicians in distinguishing difficult-to-control from severe asthma. Although additional evidence is required to assess the impact of EMDs on clinical outcome measures such as exacerbation rate, the introduction of EMDs into the asthma armoury is a significant step forward in asthma care with the potential to improve asthma-related outcomes.

Abstract

Technological advancements in the development of electronic monitoring devices allow for identification of intentional and unintentional ICS non-adherence in asthma. https://bit.ly/37MPYip

Introduction

It is estimated that ∼500 000 people die of asthma worldwide each year and several independent reviews have highlighted that many of these deaths are preventable [1, 2]. Infrequent use of inhaled corticosteroids (ICS) and/or over-reliance on short-acting β-agonists (SABA) are recognised as key contributors to asthma-related morbidity and mortality [1]. In a landmark study published in 2000, Suissa et al. [3] found that the number of ICS canisters used in the prior year was directly related to the risk of death from asthma. However, despite this and similar reports, adherence to ICS remains poor. Even in the context of the coronavirus disease 2019 (COVID-19) pandemic, ICS adherence rates averaged 55% during 2020, with only 42% achieving the 75% threshold of good adherence [4].

Adherence, often used synonymously with compliance and concordance, refers to the extent to which the recommendations made by a healthcare professional (HCP) regarding medication are accepted and followed by the patient [5]. The adherence process comprises three chronological phases: initiation, implementation and persistence. Initiation is a binary variable, patients either start taking their medication or do not. Implementation refers to whether the dosing corresponds to the prescribed dosing regimen. Lastly, persistence is from the time of initiation to its discontinuation [6]. Most measures of adherence reflect behaviour from a few weeks to 12 months. Persistence over 12 months has been measured in only one study thus far [7].

Non-adherence to medication is either intentional or unintentional. Intentional non-adherence usually reflects a scenario where a patient actively makes a decision to not follow the advice given and does not take their prescribed medication [8]. This may be due to concerns about side effects, the possibility of addiction or a wish to simply not rely on a medication. Another common and important intentional form of non-adherence may be due to the financial burden of the medication [9]. In contrast, unintentional non-adherence is where the patient fully intends to be adherent to their treatment, but either forgets to use it or, due to poor inhaler technique, a minimal amount of the drug reaches the desired location [5, 8].

Adherence can be assessed in a number of ways, each with their advantages and disadvantages (table 1). Critically, an ideal method of adherence monitoring should be objective, accurate and unobtrusive to minimise impact on patient behaviour [10]. The most widely used adherence measures are patient self-report upon direct questioning and written questionnaires [8]. Questionnaires can be useful in identifying barriers to non-adherence, allowing for personalised interventions to be made. Examples of these include the Medication Adherence Report Scale for asthma [11], the Morisky Medication Adherence Scale [12] and the Test of Adherence to Inhalers questionnaire [13]. However, these subjective measures are not considered particularly robust as it is well known that patients over-report their adherence [14].

View this table:
TABLE 1

Measures of adherence

The most common objective proxy is calculations of the medication possession ratio or the proportion of days covered, using medication issues as a determinant of adherence. This method has been found to be useful and reasonably accurate [15]. However, a secondary analysis of the Salford Lung Study dataset, which included >4000 asthma patients, found that over 30% of prescriptions issued were not collected from the dispensary [16]. This suggests that prescription records are likely to be an over-estimation of actual adherence. A more accurate measure of adherence may be from dispensing or prescription claim records, provided that prescriptions are redeemed from the same pharmacy each time [17]. Where available, dose counters may also be used to determine adherence as long as patients are on a fixed dose regimen; however, the accuracy of this method can be impacted by dose dumping before clinic visits [8].

The use of serum ICS concentration as a direct measure of adherence has been described with very low ICS concentration levels in patients associated with patients who have poor inhaler technique [18]. In addition, this technique only reflects a recent estimation of adherence and other measures of adherence would be required to confirm longer term ICS use [19]. Hair analysis has also been proposed as a tool for assessing ICS adherence; however, this method is unlikely to become a widely used tool given the increasing availability of electronic monitoring devices (EMDs) [20].

Finally, over the last decade, some specialist asthma centres have incorporated fractional exhaled nitric oxide (FENO) suppression testing into clinical practice to identify the clinical and biological response to directly observed therapy with ICS. This method allows differentiation between those with ICS-responsive, difficult-to-control but non-severe asthma, from patients with ICS-resistant, severe asthma [21, 22]. Although this has been a huge step forward in both adherence monitoring and improved identification of appropriate patients for biologic therapies, it is both resource- and time-intensive for the patient and clinical team alike.

Consequently, there is a genuine appetite among the clinical community caring for difficult-to-control asthma patients for a cheap, simple, robust measure that can inform the HCP about ICS and SABA use, identify inhaler technique errors, whilst also offering reminders to the patient who is unintentionally non-adherent [23].

Randomised controlled trials (RCTs) including the use of EMDs in children have demonstrated improvements in adherence to ICS, but most trials have not been adequately powered (due to sample size, study duration and/or severity of the cohort) to assess how this relates to clinical outcomes such as exacerbation rate [24, 25]. Clinical trial data including adult asthma subjects have been more promising, with evidence of both improved adherence as well as reductions in SABA use and exacerbation rates [26, 27].

In this review, we report on the new generation of inhaler EMDs (figure 1) that are currently licensed for use or undergoing clinical trial evaluation, identified through PubMed and ClinicalTrials.gov searches. Key search terms included “asthma AND electronic monitoring”.

FIGURE 1
FIGURE 1

Examples of electronic monitoring devices. All device images used with permission of the manufacturer/copyright holder. pMDI: pressurised metered-dose inhalers.

Inhaler Compliance Assessment™ (INCA) (Dublin, Ireland)

The INCA EMD is one of the most extensively evaluated devices to date [21, 28–35]. However, it is limited for use with the Diskus® inhaler only and a 60-dose memory, meaning it needs to be replaced every 30 days. The device consists of a microphone and a microprocessor that records the audio produced, initiated when the Diskus® inhaler is first opened, with the recording completed when the inhaler is closed [21, 36]. The audio recording includes the click of the Diskus® lever, and then patient exhalation and subsequent inhalation of the medication. Additionally, the amplitude of inhalation is recorded and correlates with peak inspiratory flow. A median amplitude of <0.016 AU corresponds to an inspiratory flow rate of <30 L·min−1, which is deemed insufficient for dry power inhalation [21]. As such, the device identifies critical inhaler technique errors as well as temporal use of the inhaler. This is important as errors can reoccur following an assessment of competence. For example, in one study, despite all patients being judged as initially competent in the use of their inhaler, 17% had >20% errors during the first month of assessment. The majority of patients who made errors did so intermittently [32]. Over the course of the study, the feedback provided by the INCA device led to a reduction in errors to <5%, resulting in observed improvements in quality of life. Furthermore, in an RCT, the impact of personalised biofeedback resulted in a significant improvement in adherence compared to a group receiving intensive education in which a fall in the rate of adherence was observed [30].

The usefulness of the INCA monitoring device has also facilitated the interpretation of FENO suppression testing as it allows the identification of intentional versus unintentional non-adherence in patients with apparent ICS-resistant high FENO [21, 34]. Despite being able to use the inhaler proficiently when initially shown, inadequate inhaler use over a 7-day period was evident in 67% of patients monitored with the INCA device [21]. Similarly, another study of patients with suspected severe uncontrolled asthma found only 27% to have refractory symptoms despite good ICS adherence, whilst 35% were uncontrolled in the context of suboptimal adherence and therefore could be considered difficult to control [30].

The device has a reported failure rate of <2% [21]. The algorithm has demonstrated a sensitivity of 95%, specificity of 94% and an accuracy of 89% in detecting inhalations. Analysis can be performed rapidly, presenting information in real time [21]. Importantly, use of the INCA has been shown to be acceptable to >90% of asthma patients attending a difficult asthma clinic [34].

The INCA device is currently being evaluated for its ability to improve uncontrolled asthma in the INCA device in Symptomatic Uncontrolled Asthma study [37].

Propeller sensor (Propeller Health, Wisconsin, USA)

The Propeller sensor is compatible for use with a wide range of devices, including pressurised metered-dose inhalers (pMDIs) such as Diskus®, Ellipta®, Turbohaler®, Easyhaler®, Breezhaler® and Respimat® [38]. As such, Propeller sensors can be used for both preventer and reliever inhalers to record the date, time and location of actuation [39]. The sensors record when the inhalers are opened and closed as a surrogate for drug delivery, but inhaler technique is not recorded. As well as monitoring use, electronic notifications can be enabled to alert patients and providers about omitted doses.

The sensor transmits information via Bluetooth® to a paired smartphone application and securely uploads the data to remote servers. Email notifications or text messages alert individuals and physicians about a change in asthma control based on reliever use. By providing personalised feedback, individuals are enabled to action changes and reduce the risk of an exacerbation [39, 40]. Global positioning system data obtained through a smartphone provides geospatial information with the potential to help patients and HCPs identify asthma triggers. For example, increased SABA use may occur in a certain location associated with high exposure to a particular aeroallergen. When exposed to the same set of triggers in the future, patients are warned of the risk of a possible exacerbation [41].

Propeller sensors have been used in several studies to monitor ICS adherence, including change in ICS use for patients with asthma and COPD during the first few months of the COVID-19 pandemic [26, 42, 43]. In an adult population with uncontrolled asthma, an increase in the percentage of SABA-free days was demonstrated in the group that received reminders and feedback on ICS and SABA use compared to a control group without feedback. Adherence changed minimally in the intervention group, whereas a significant decrease was seen in the control group [27]. This study also identified a positive response in younger participants and those with worse asthma control at baseline, a subset of patients who are likely to particularly benefit from EMDs [27].

The evidence supporting the impact of the propeller sensor on asthma-related emergency department (ED) visits and hospitalisations is mixed. A study of 224 participants aged 3–88 years reported a reduction in asthma-related ED visits and hospitalisations with use of the EMD; however, a Hawthorne effect could not be excluded [26]. In contrast, a paediatric study of 252 participants reported significantly higher rates of asthma-related hospitalisations and ED visits at 12 months for those using EMDs [44]. This was believed to be due to increased feedback when >4 SABA inhalations per day were used, and alerts enabling detection of loss of asthma control directing children to the ED. Additionally, increased vigilance and awareness of clinically concerning symptoms were thought to have prompted increased healthcare utilisation during the study [44].

Hailie® (Adherium, Auckland, New Zealand)

SmartTrack, SmartInhaler and SmartTurbo have been developed and rebranded as the Hailie® sensors.

Similar to the Propeller sensor, the Hailie® sensor can track both preventer and reliever use, logging the date and time of inhaler actuation. The Hailie® sensor is paired via Bluetooth® to a smartphone application and provides notifications and reminders. The application shows bar charts providing instant feedback on adherence and reliever use, which can be sent to an HCP portal through a secure cloud [25, 45]. The Hailie® sensor is currently limited to use with pMDI, Diskus® and Turbohaler® devices. The next-generation Hailie® sensor (currently only available for Symbicort® hydrofluoroalkane) also includes physiological measures that detect inspiratory flow, inhaler shaking and inhaler orientation [45].

The SmartTrack device clips around a pMDI and has been shown to improve adherence to ICS in both adult and paediatric asthma patients [46, 47]. Morton et al. [47] reported a statistically significant improvement in ICS adherence in 77 children. Although this did not translate into a significant improvement in asthma control, children in the intervention arm experienced fewer exacerbations requiring oral corticosteroids at 12 months [47]. A further study of 220 children with asthma reported significant improvements in both ICS adherence and SABA use when compared to baseline and control groups [48].

Jochmann et al. [49] have used EMDs in the setting of a tertiary paediatric asthma centre to differentiate severe therapy-resistant asthma from difficult-to-control asthma. The authors highlighted that adherence rates only improved for some patients and not for others, suggesting that EMDs may not change behaviour in individuals who are intentionally non-adherent.

The SmartTurbo, which is specifically for use with the Turbuhaler® device, is able to detect the presence or absence of the cap on the mouthpiece of the inhaler. The device records pairs of anticlockwise and clockwise turns as inhaler actuations, and data is uploaded to a database [50]. Use of the SmartTurbo has been validated by comparing actuations recorded on the EMD to paper diaries and found to be highly sensitive over a 12-week period [50].

Turbu+TM (AstraZeneca, Cambridge, UK)

The SmartTurbo/Hailie EMD has been used by AstraZeneca to launch Turbu+. The Turbu+ consists of three components, an electronic device that attaches to a Turbohaler®, an application for the patients and an online portal allowing HCPs access to the same actuation data [51]. During inhalation, the date and time of actuation is recorded, but inhaler technique is not assessed. Scheduled reminders can be set by the patients and, if a dose is not taken 30 after the scheduled inhalation, a “missed-medication” motivational message is sent automatically. Patients also receive a weekly motivational push notification in the application (e.g. “Great week. You've been following your prescription this week! Keep it up!”) [52].

In a small real-world study including 32 adult asthma patients, the number of actuations recorded by the EMD was compared to patient-reported inhalations. A total of 932 medication doses were verified by the EMD with a total of 796 doses (85.4%) registered by the patient. A false-positive rate of 3.5% was registered (patient-recorded but not EMD-recorded) as well as a false negative rate of 11.1% (EMD-recorded but not patient-recorded). The reminders and motivational messages were only found to be useful in 50% of patients; however, this study was limited in length (14–21 days) and the patient cohort reported high levels of adherence prior to the study [52].

Capmedic® (Cognita Labs, California, USA)

CapMedic® is an EMD which uses animation with lights and sounds to guide the user through correct inhaler use, recording the seven steps of inhalation, including the mean inspiratory flow rate (L·min−1). It fits onto most pMDIs and provides prompts based on the user's actions; for example, to guide the user to shake their inhaler correctly. It also detects the user's breathing and nudges the patient with audio-visual cues to press the inhaler while breathing in, followed by reminders to encourage a long inhalation. Light-emitting diode lights then provide the user with immediate feedback on how well the inhaler was used. As with many of the new EMDs, data is synced to an application providing data on both use and critical errors. The CapMedic® can also provide lung function measurements including peak inspiratory flow and spirometry. It is currently only available for use with pMDIs [53].

In a small study of 23 patients with asthma and COPD, the CapMedic® EMD identified that 100% of patients made at least one error and 74% made at least three errors in using a pMDI [54]. The CapMedic® tool was considered to be more sensitive in identifying and quantifying these errors than observation alone. Another small study of 16 patients showed improved inhaler technique in patients using CapMedic®, compared to patients who were only shown an inhaler technique video [55]. The impact of using the CapMedic® device on other clinical outcomes has not yet been evaluated.

Respiro® (Amiko Digital Health Ltd, Milan, Italy)

The Respiro® sensor records both inhaler administration and technique, and is available for use with pMDI, Ellipta®, Nexthaler® and Spiromax® devices as an add-on sensor providing digital feedback for each critical step of inhalation, including inspiratory flow and inhaler orientation. Data regarding inhaler use is stored and wirelessly exchanged with a paired smartphone or PC reporting adherence patterns and inhaler technique [56]. The Respiro® mobile application provides personalised guidance to help patients manage their condition and is accessible to the HCP [57]. The provider portal displays a dashboard of patient data, notifications about patients at risk of an exacerbation and monthly reports on patient progress, allowing the monitoring of large patient populations. A study evaluating its use is currently underway in children with uncontrolled asthma (Dutch Trial Register NL7705) [58].

Herotracker® (AptarPharma, Milton Keynes, UK, formerly Cohero Health, New York, USA)

The HeroTracker®, linked by Bluetooth® to the BreatheSmart® application, allows tracking of medication use, symptoms and triggers. The application sends daily reminders and information about environmental conditions to alert patients of any changes. The Herotracker® is designed for both controller and rescue medications and fits most pMDI and Diskus® inhalers. The next-generation pMDI add-on is called HeroTracker® Sense and is designed to detect and record co-ordination, flow rate and duration of inspiration. This is then fed back to patients via the BreatheSmart application and to the HCP portal. A sensor embedded within a pMDI, called an eMDI, has also been developed [59]. In addition, patients can be issued a linked lung function sensor to track peak expiratory flow rates and forced expiratory volume in 1 s over time. The application keeps a record of the best peak flow and reports how each measurement compares to the best value [59]. Clinical trials evaluating the HeroTracker® and BreatheSmart application are currently underway (ClinicalTrials.gov NCT03103880 and NCT0373486).

Digihaler® (TEVA, Tel Aviv, Israel)

The Digihaler® includes an imbedded inhalation flow sensor that detects inhaler use, recorded when the cap is opened or the patient inhales. Inspiratory flow rates are measured and categorised as good (>45 L·min−1), fair (30–45 L·min−1), low or no inhalation (<30 L·min−1), assisting identification of poor technique. A recent study reported a strong correlation between the peak inspiratory flow measurements by the Digihaler® and an inhalation profile recorder [60].

Patients can receive notifications and reminders from their Digihaler® application and data on inhaler use can be shared on the screen during an HCP visit or in the form of a PDF summary [61]. It is available for salbutamol (ProAir Digihaler) fluticasone/salmeterol (AirDuo Digihaler) and fluticasone (ArmonAir Digihaler).

In a 12-week, open-label study, use of the ProAir Digihaler highlighted that the strongest predictive factor during the 5 days before an asthma exacerbation was the average number of SABA inhalations per day [62]. A number of additional clinical trials to assess its use are currently underway (ClinicalTrials.gov NCT04896645 and NCT04997304). The Digihaler® is currently only available in the USA.

Limitations of EMDs

To date, mechanical issues have limited the usability of some EMDs. For example, an RCT of 89 paediatric subjects reported that 31 devices broke, with 19 damaged beyond repair [45]. In another study, only 56/102 children had a functional EMD at 12 months [44]. However, in adult studies, this seems to be less of a problem, with only 1.9% malfunctioning and 3.5% lost when assessing over 2500 monitors [63]. Battery life may additionally impact EMD usability, but newer devices now have batteries lasting up to 12 months. A second important factor to consider is the time and staffing required to monitor patients remotely and respond to any alerts if the EMD offers this capability. Lastly, as many EMDs share real-time data to HCPs, data privacy and the need to comply with General Data Protection Regulation (GDPR) requirements must be considered.

Summary

Recent years have seen an exponential growth in the number of EMDs being developed for patients with airways disease. Devices that started as simple counting tools have now been replaced by highly sophisticated inhaler attachments providing audio-visual reminders, guided inhaler use, inspiratory flow measurements and personalised feedback to patients; whilst offering HCPs detailed insights into patient behaviour. Although experience in their use is only now starting to expand from the research space into routine clinical care, EMDs have the potential to improve the quality of care an HCP is able to deliver for patients with asthma. Some EMDs can provide feedback on the elements of inhaler technique that are often difficult to objectively assess, such as whether there was sufficient co-ordination with inhalation or whether sufficient inspiratory force was generated. The combination of both temporal and inhaler technique data provides a composite account of adherence, allowing identification of both intentional and non-intentional non-adherence over time. Critically, this information can assist clinicians in distinguishing difficult-to-control from severe asthma, which will allow appropriate patient-centred interventions and may avoid inappropriate escalation of therapy to systemic corticosteroids and/or expensive biologic agents. Whilst very promising, additional research is needed to convincingly demonstrate that improvements in adherence to ICS using an EMD translate into clinical outcomes such as exacerbation rate and quality-of-life measures.

Footnotes

  • Provenance: Submitted article, peer reviewed.

  • Conflict of interest: H. Dhruve reports receiving honoraria from Asthma UK Centre for Applied Research, University College London, Pharmacy Management, and Primary Care Respiratory Society, outside the submitted work. Leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid: Pharmacy Management, Primary Care Respiratory Society, London Respiratory Network, Academic Health Science Network – Severe asthma sub-committee.

  • Conflict of interest: D.J. Jackson reports receiving grants or contracts from AstraZeneca outside the submitted work. Consulting fees from AstraZeneca, GSK, and Sanofi Regeneron, outside the submitted work. Speaker fees received from AstraZeneca, GSK, and Sanofi Regeneron, outside the submitted work.

  • Received December 14, 2021.
  • Accepted March 12, 2022.
http://creativecommons.org/licenses/by-nc/4.0/

This version is distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0. For commercial reproduction rights and permissions contact permissions{at}ersnet.org

References

  1. ↵
    1. Royal College of Physicians
    . Why Asthma Still Kills: the National Review of Asthma Deaths (NRAD) Confidential Enquiry Report. London, Royal College of Physicians, 2015. Available from: www.rcplondon.ac.uk/sites/default/files/why-asthma-still-kills-full-report.pdf.
  2. ↵
    1. GBD Chronic Respiratory Disease Collaborators
    . Prevalence and attributable health burden of chronic respiratory diseases, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Respir Med 2020; 8: 585–596. doi:10.1016/S2213-2600(20)30105-3
    OpenUrl
  3. ↵
    1. Suissa S,
    2. Ernst P,
    3. Benayoun S, et al.
    Low-dose inhaled corticosteroids and the prevention of death from asthma. N Engl J Med 2000; 343: 332–336. doi:10.1056/NEJM200008033430504
    OpenUrlCrossRefPubMed
  4. ↵
    1. Dhruve H,
    2. d'Ancona G,
    3. Holmes S, et al.
    Prescribing patterns and treatment adherence in patients with asthma during the COVID-19 pandemic. J Allergy Clin Immunol Pract 2022; 10: 100–107.e2. doi:10.1016/j.jaip.2021.09.032
    OpenUrl
  5. ↵
    1. Horne R
    . Compliance, adherence, and concordance: implications for asthma treatment. Chest 2006; 130: Suppl. 1, 65s–72s. doi:10.1378/chest.130.1_suppl.65S
    OpenUrlCrossRefPubMed
  6. ↵
    1. Jansen EM,
    2. van de Hei SJ,
    3. Dierick BJH, et al.
    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. J Thorac Dis 2021; 13: 3846–3864. doi:10.21037/jtd-20-2360
    OpenUrl
  7. ↵
    1. Vähätalo I,
    2. Ilmarinen P,
    3. Tuomisto LE, et al.
    12-year adherence to inhaled corticosteroids in adult-onset asthma. ERJ Open Res 2020; 6: 00324-2019. doi:10.1183/23120541.00324-2019
    OpenUrlAbstract/FREE Full Text
  8. ↵
    1. Holmes J,
    2. Heaney LG
    . Measuring adherence to therapy in airways disease. Breathe 2021; 17: 210037. doi:10.1183/20734735.0037-2021
    OpenUrlAbstract/FREE Full Text
  9. ↵
    1. Laba TL,
    2. Jan S,
    3. Zwar NA, et al.
    Cost-related underuse of medicines for asthma-opportunities for improving adherence. J Allergy Clin Immunol Pract 2019; 7: 2298–2306.e12. doi:10.1016/j.jaip.2019.03.024
    OpenUrl
  10. ↵
    1. Chan AHY,
    2. Harrison J,
    3. Black PN, et al.
    Using electronic monitoring devices to measure inhaler adherence: a practical guide for clinicians. J Allergy Clin Immunol Pract 2015; 3: 335–49.e1–5. doi:10.1016/j.jaip.2015.01.024
    OpenUrl
  11. ↵
    1. Horne R,
    2. Weinman J
    . Self-regulation and self-management in asthma: exploring the role of illness perceptions and treatment beliefs in explaining non-adherence to preventer medication. Psychology Health 2002; 17: 17–32. doi:10.1080/08870440290001502
    OpenUrl
  12. ↵
    1. Janežič A,
    2. Locatelli I,
    3. Kos M
    . Criterion validity of 8-item Morisky Medication Adherence Scale in patients with asthma. PLoS One 2017; 12: e0187835. doi:10.1371/journal.pone.0187835
    OpenUrl
  13. ↵
    1. Plaza V,
    2. Fernández-Rodríguez C,
    3. Melero C, et al.
    Validation of the ‘Test of the Adherence to Inhalers’ (TAI) for asthma and COPD patients. J Aerosol Med Pulm Drug Deliv 2016; 29: 142–152. doi:10.1089/jamp.2015.1212
    OpenUrlPubMed
  14. ↵
    1. Patel M,
    2. Perrin K,
    3. Pritchard A, et al.
    Accuracy of patient self-report as a measure of inhaled asthma medication use. Respirology 2013; 18: 546–552. doi:10.1111/resp.12059
    OpenUrlPubMed
  15. ↵
    1. Engelkes M,
    2. Janssens HM,
    3. de Jongste JC, et al.
    Medication adherence and the risk of severe asthma exacerbations: a systematic review. Eur Respir J 2015; 45: 396–407. doi:10.1183/09031936.00075614
    OpenUrlAbstract/FREE Full Text
  16. ↵
    1. Tibble H,
    2. Lay-Flurrie J,
    3. Sheikh A, et al.
    Linkage of primary care prescribing records and pharmacy dispensing records in the Salford Lung Study: application in asthma. BMC Med Res Methodol 2020; 20: 303. doi:10.1186/s12874-020-01184-8
    OpenUrl
  17. ↵
    1. van Boven JFM,
    2. van de Hei SJ,
    3. Sadatsafavi M
    . Making sense of cost-effectiveness analyses in respiratory medicine: a practical guide for non-health economists. Eur Respir J 2019; 53: 1801816. doi:10.1183/13993003.01816-2018
    OpenUrlAbstract/FREE Full Text
  18. ↵
    1. George KE,
    2. Ryan DM,
    3. Keevil B, et al.
    A pilot study to investigate the use of serum inhaled corticosteroid concentration as a potential marker of treatment adherence in severe asthma. J Allergy Clin Immunol 2017; 139: 1037–1039.e1. doi:10.1016/j.jaci.2016.08.037
    OpenUrl
  19. ↵
    1. Alahmadi FH,
    2. Keevil B,
    3. Elsey L, et al.
    Serum inhaled corticosteroid detection for monitoring adherence in severe asthma. J Allergy Clin Immunol Pract 2021; 9: 4279–4287.e6. doi:10.1016/j.jaip.2021.05.041
    OpenUrl
  20. ↵
    1. Hassall D,
    2. Brealey N,
    3. Wright W, et al.
    Hair analysis to monitor adherence to prescribed chronic inhaler drug therapy in patients with asthma or COPD. Pulm Pharmacol Ther 2018; 51: 59–64. doi:10.1016/j.pupt.2018.07.001
    OpenUrl
  21. ↵
    1. Heaney LG,
    2. Busby J,
    3. Bradding P, et al.
    Remotely monitored therapy and nitric oxide suppression identifies nonadherence in severe asthma. Am J Respir Crit Care Med 2019; 199: 454–464. doi:10.1164/rccm.201806-1182OC
    OpenUrlPubMed
  22. ↵
    1. Couillard S,
    2. Shrimanker R,
    3. Chaudhuri R, et al.
    Fractional exhaled nitric oxide non-suppression identifies corticosteroid-resistant type-2 signaling in severe asthma. Am J Respir Crit Care Med 2021; 204: 731–734. doi:10.1164/rccm.202104-1040LE
    OpenUrlPubMed
  23. ↵
    1. Anderson WC 3rd.,
    2. Gondalia R,
    3. Hoch HE, et al.
    Screening for inhalation technique errors with electronic medication monitors. J Allergy Clin Immunol Pract 2019; 7: 2065–2067. doi:10.1016/j.jaip.2019.02.006
    OpenUrl
  24. ↵
    1. Burgess SW,
    2. Sly PD,
    3. Devadason SG
    . Providing feedback on adherence increases use of preventive medication by asthmatic children. J Asthma 2010; 47: 198–201. doi:10.3109/02770900903483840
    OpenUrlCrossRefPubMed
  25. ↵
    1. Makhecha S,
    2. Chan A,
    3. Pearce C, et al.
    Novel electronic adherence monitoring devices in children with asthma: a mixed-methods study. BMJ Open Respir Res 2020; 7: e000589. doi:10.1136/bmjresp-2020-000589
    OpenUrlAbstract/FREE Full Text
  26. ↵
    1. Merchant R,
    2. Szefler SJ,
    3. Bender BG, et al.
    Impact of a digital health intervention on asthma resource utilization. World Allergy Organ J 2018; 11: 28. doi:10.1186/s40413-018-0209-0
    OpenUrl
  27. ↵
    1. Mosnaim GS,
    2. Stempel DA,
    3. Gonzalez C, et al.
    The impact of patient self-monitoring via electronic medication monitor and mobile app plus remote clinician feedback on adherence to inhaled corticosteroids: a randomized controlled trial. J Allergy Clin Immunol Pract 2021; 9: 1586–1594. doi:10.1016/j.jaip.2020.10.064
    OpenUrl
  28. ↵
    1. D'Arcy S,
    2. MacHale E,
    3. Seheult J, et al.
    A method to assess adherence in inhaler use through analysis of acoustic recordings of inhaler events. PLoS One 2014; 9: e98701. doi:10.1371/journal.pone.0098701
    OpenUrlPubMed
    1. Seheult JN,
    2. O'Connell P,
    3. Tee KC, et al.
    The acoustic features of inhalation can be used to quantify aerosol delivery from a Diskus™ dry powder inhaler. Pharm Res 2014; 31: 2735–2747. doi:10.1007/s11095-014-1371-x
    OpenUrlCrossRefPubMed
  30. ↵
    1. Sulaiman I,
    2. Greene G,
    3. MacHale E, et al.
    A randomised clinical trial of feedback on inhaler adherence and technique in patients with severe uncontrolled asthma. Eur Respir J 2018; 51: 1701126. doi:10.1183/13993003.01126-2017
    OpenUrlAbstract/FREE Full Text
    1. Sulaiman I,
    2. Seheult J,
    3. MacHale E, et al.
    A method to calculate adherence to inhaled therapy that reflects the changes in clinical features of asthma. Ann Am Thorac Soc 2016; 13: 1894–1903. doi:10.1513/AnnalsATS.201603-222OC
    OpenUrl
  32. ↵
    1. Sulaiman I,
    2. Seheult J,
    3. MacHale E, et al.
    Irregular and ineffective: a quantitative observational study of the time and technique of inhaler use. J Allergy Clin Immunol Pract 2016; 4: 900–909.e2. doi:10.1016/j.jaip.2016.07.009
    OpenUrl
    1. Taylor TE,
    2. Zigel Y,
    3. Egan C, et al.
    Objective assessment of patient inhaler user technique using an audio-based classification approach. Sci Rep 2018; 8: 2164. doi:10.1038/s41598-018-20523-w
    OpenUrl
  34. ↵
    1. Boddy CE,
    2. Naveed S,
    3. Craner M, et al.
    Clinical outcomes in people with difficult-to-control asthma using electronic monitoring to support medication adherence. J Allergy Clin Immunol Pract 2021; 9: 1529–1538.e2. doi:10.1016/j.jaip.2020.10.059
    OpenUrl
  35. ↵
    1. Greene G,
    2. Costello RW,
    3. Cushen B, et al.
    A novel statistical method for assessing effective adherence to medication and calculating optimal drug dosages. PLoS One 2018; 13: e0195663. doi:10.1371/journal.pone.0195663
    OpenUrl
  36. ↵
    INCA. www.incadevice.com Date last accessed: 26 October 2021
  37. ↵
    1. Mokoka MC,
    2. Lombard L,
    3. MacHale EM, et al.
    In patients with severe uncontrolled asthma, does knowledge of adherence and inhaler technique using electronic monitoring improve clinical decision making? A protocol for a randomised controlled trial. BMJ Open 2017; 7: e015367. doi:10.1136/bmjopen-2016-015367
    OpenUrl
  38. ↵
    Propeller Health. www.propellerhealth.com Date last accessed: 26 October 2021
  39. ↵
    1. Merchant RK,
    2. Inamdar R,
    3. Quade RC
    . Effectiveness of population health management using the Propeller Health asthma platform: a randomized clinical trial. J Allergy Clin Immunol Pract 2016; 4: 455–463. doi:10.1016/j.jaip.2015.11.022
    OpenUrl
  40. ↵
    1. Barrett MA,
    2. Humblet O,
    3. Marcus JE, et al.
    Effect of a mobile health, sensor-driven asthma management platform on asthma control. Ann Allergy Asthma Immunol 2017; 119: 415–421.e1. doi:10.1016/j.anai.2017.08.002
    OpenUrl
  41. ↵
    1. Williams AM,
    2. Phaneuf DJ,
    3. Barrett MA, et al.
    Short-term impact of PM2.5 on contemporaneous asthma medication use: behavior and the value of pollution reductions. Proc Natl Acad Sci USA 2019; 116: 5246–5253. doi:10.1073/pnas.1805647115
    OpenUrlAbstract/FREE Full Text
  42. ↵
    1. De Keyser HEH,
    2. Kaye L,
    3. Anderson WC, et al.
    Electronic medication monitors help determine adherence subgroups in asthma. Respir Med 2020; 164: 105914. doi:10.1016/j.rmed.2020.105914
    OpenUrl
  43. ↵
    1. Kaye L,
    2. Theye B,
    3. Smeenk I, et al.
    Changes in medication adherence among patients with asthma and COPD during the COVID-19 pandemic. J Allergy Clin Immunol Pract 2020; 8: 2384–2385. doi:10.1016/j.jaip.2020.04.053
    OpenUrl
  44. ↵
    1. Gupta RS,
    2. Fierstein JL,
    3. Boon KL, et al.
    Sensor-based electronic monitoring for asthma: a randomized controlled trial. Pediatrics 2021; 147: e20201330. doi:10.1542/peds.2020-1330
    OpenUrlAbstract/FREE Full Text
  45. ↵
    Hailie. www.hailie.com Date last accessed: 26 October 2021
  46. ↵
    1. Foster JM,
    2. Usherwood T,
    3. Smith L, et al.
    Inhaler reminders improve adherence with controller treatment in primary care patients with asthma. J Allergy Clin Immunol 2014; 134: 1260–8.e3. doi:10.1016/j.jaci.2014.05.041
    OpenUrlCrossRef
  47. ↵
    1. Morton RW,
    2. Elphick HE,
    3. Rigby AS, et al.
    STAAR: a randomised controlled trial of electronic adherence monitoring with reminder alarms and feedback to improve clinical outcomes for children with asthma. Thorax 2017; 72: 347–354. doi:10.1136/thoraxjnl-2015-208171
    OpenUrlAbstract/FREE Full Text
  48. ↵
    1. Chan AHY,
    2. Stewart AW,
    3. Harrison J, et al.
    The effect of an electronic monitoring device with audiovisual reminder function on adherence to inhaled corticosteroids and school attendance in children with asthma: a randomised controlled trial. Lancet Respir Med 2015; 3: 210–219. doi:10.1016/S2213-2600(15)00008-9
    OpenUrl
  49. ↵
    1. Jochmann A,
    2. Artusio L,
    3. Jamalzadeh A, et al.
    Electronic monitoring of adherence to inhaled corticosteroids: an essential tool in identifying severe asthma in children. Eur Respir J 2017; 50: 1700910. doi:10.1183/13993003.00910-2017
    OpenUrlAbstract/FREE Full Text
  50. ↵
    1. Pilcher J,
    2. Shirtcliffe P,
    3. Patel M, et al.
    Three-month validation of a turbuhaler electronic monitoring device: implications for asthma clinical trial use. BMJ Open Respir Res 2015; 2: e000097. doi:10.1136/bmjresp-2015-000097
    OpenUrlAbstract/FREE Full Text
  51. ↵
    Turbuplus. www.turbuplusinfo.co.uk Date last accessed: 26 October 2021
  52. ↵
    1. Kuipers E,
    2. Poot CC,
    3. Wensing M, et al.
    Self-Management Maintenance Inhalation Therapy With eHealth (SELFIE): observational study on the use of an electronic monitoring device in respiratory patient care and research. J Med Internet Res 2019; 21: e13551. doi:10.2196/13551
    OpenUrl
  53. ↵
    CapMedic. www.capmedicinhaler.com Date last accessed: 26 October 2021
  54. ↵
    1. Biswas R,
    2. Patel G,
    3. Mohsin A, et al.
    Measuring competence in metered dose inhaler use using CapMedic electronic inhaler monitoring tool. Chest 2016; 150: Suppl., 14A. doi:10.1016/j.chest.2016.08.017
    OpenUrl
  55. ↵
    1. Paronyan E,
    2. Landon C,
    3. Biswas R, et al.
    Utilizing CapMedic electronic device to measure and improve inhaler technique in clinic. Am J Respir Crit Care Med 2020; 201: A4786. doi:10.1164/ajrccm-conference.2020.201.1_MeetingAbstracts.A4786
    OpenUrl
  56. ↵
    1. Braido F,
    2. Paa F,
    3. Ponti L, et al.
    A new tool for inhalers’ use and adherence monitoring: the Amiko® validation trial. Int J Eng Res Sci 2016; 2: 159–166.
    OpenUrl
  57. ↵
    Respiro Amiko. www.amiko.io Date last accessed: 26 October 2021
  58. ↵
    1. Sportel ET,
    2. Oude Wolcherink MJ,
    3. van der Palen J, et al.
    Does immediate smart feedback on therapy adherence and inhalation technique improve asthma control in children with uncontrolled asthma? A study protocol of the IMAGINE I study. Trials 2020; 21: 801. doi:10.1186/s13063-020-04694-4
    OpenUrl
  59. ↵
    HeroTracker. www.coherohealth.com Date last accessed: 26 October 2021
  60. ↵
    1. Chrystyn H,
    2. Saralaya D,
    3. Shenoy A, et al.
    Investigating the accuracy of the Digihaler, a new electronic multidose dry-powder inhaler, in measuring inhalation parameters. J Aerosol Med Pulm Drug Deliv 2021; in press [https://doi.org/10.1089/jamp.2021.0031].
  61. ↵
    Digihaler. www.digihalerhcp.com Date last accessed: 26 October 2021
  62. ↵
    1. Granovsky L,
    2. Li T,
    3. Reich M, et al.
    A predictive model for clinical asthma exacerbations using albuterol eMDPI (ProAir Digihaler): a 12-week, open-label study. Am J Respir Crit Care Med 2019; 199: A7309. doi:10.1164/ajrccm-conference.2019.199.1_MeetingAbstracts.A7307
    OpenUrl
    1. Patel M,
    2. Pilcher J,
    3. Travers J, et al.
    Use of metered-dose inhaler electronic monitoring in a real-world asthma randomized controlled trial. J Allergy Clin Immunol Pract 2013; 1: 83–91. doi:10.1016/j.jaip.2012.08.004
    OpenUrl
Back to top
View this article with LENS
Email
Print
Citation Tools

Assessing adherence to inhaled therapies in asthma and the emergence of electronic monitoring devices
Hetal Dhruve, David J. Jackson
European Respiratory Review Jun 2022, 31 (164) 210271; DOI: 10.1183/16000617.0271-2021
del.icio.us logo Technorati logo Twitter logo Connotea logo Facebook logo Mendeley logo
Full Text (PDF)

Jump To

Subjects