A Method to Assess Adherence in Inhaler Use through Analysis of Acoustic Recordings of Inhaler Events

D’Arcy, Shona; MacHale, Elaine; Seheult, Jansen N.; Holmes, Martin S.; Hughes, Cian; Sulaiman, Imran; Hyland, Deirdre; O'Reilly, Conor; Glynn, Senan; Al-Zaabi, Thekra; McCourt, John; Taylor, Terence E.; Keane, F. B. V.; Killane, Isabelle; Reilly, Richard B.; Costello, Richard W.

doi:10.1371/journal.pone.0098701

Cited by 74 publications

(66 citation statements)

References 22 publications

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“…We have previously reported the development and validation of the INCA TM audio recording device in 60 patients with a total of 1200 audio recordings (13). The device contains a microphone, internal clock, battery and memory card with plastic housing.…”

Section: Electronic Adherence Monitormentioning

confidence: 99%

“…Audio raters assessed each acoustic recording for evidence of critical errors, as previously described (13)(14)(15). Critical errors in inhaler use, such as low inspiratory flow were classified as no dose.…”

Section: Extraction Of Features Of Inhaler Use and Calculating Adherencementioning

confidence: 99%

“…We developed a device, INhaler Compliance Assessment (INCA TM ), which makes a digital file each time the inhaler is used (13). Analysis of this information means that the time of use, the interval between doses and the proficiency of inhaler use can be assessed (13).…”

mentioning

confidence: 99%

“…Analysis of this information means that the time of use, the interval between doses and the proficiency of inhaler use can be assessed (13). Technique errors identified by this method include failing to prime the inhaler, dispersing the medication by exhalation into the inhaler after priming and other errors such as dose dumping (14,15).…”

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confidence: 99%

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A Method to Calculate Adherence to Inhaled Therapy that Reflects the Changes in Clinical Features of Asthma

et al. 2016

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Written permission has been obtained from all persons named in the acknowledgment.Author Contributions: EM, SOD and SR were primarily involved in patient recruitment. SD, VR, IK and RBR were primarily involved in the audio analysis required for this manuscript. FB was primarily involved in the statistical analysis for this manuscript. BC, and MCM were involved in data collection and data analysis for this manuscript. IS, JS and RWC were involved in all aspects required for this manuscript including patient recruitment, data management, data analysis and were the primary leads in the design of the work. All co-authors were involved in writing and editing this manuscript. Methods:We attached a digital audio device (INCA TM ) to a dry powder inhaler. This recorded when the inhaler was used and analysis of the audio data indicated if the inhaler had been used correctly. These aspects of inhaler use were combined to calculate adherence over time, as an AUC measure. Over a 3 month period a cohort of asthma patients were studied. Adherence to a twice-daily inhaler preventer therapy using this device and clinical measures were assessed. Measurements and Results:Recordings from 239 patients with severe asthma were analysed.Average Adherence, based on the dose counter was 84.4%, whereas the ratio of expected to observed accumulated AUC, Actual Adherence, was 61.8% (p<0.01). Of all adherence measures, only adherence calculated as AUC reflected changes in asthma quality of life, beta agonist reliever use and PEF, over the three months (p<0.05 compared to other measures of adherence). Conclusion:Adherence that incorporates the interval between doses and inhaler technique, and calculated as AUC, is more reflective of changes in quality of life and lung function than the currently used measures of adherence. Electronic monitors are considered to be the gold standard for objectively quantifying adherence (1). Most studies using electronic recording devices have reported adherence as the mean adherence or, the Mean Daily Dose, over the study period (2) (3) (4) The aim of this study was to test the hypothesis that by including the time of use, the interval between doses and accounting for inhaler technique, we could quantify adherence as an Area Under the Curve (AUC) and, furthermore, determine whether adherence calculated using AUC was more reflective of patient outcomes than current methods of assessing adherence. Some of the results of this study have been previously reported in the form of an abstract(18). Methods

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Section: Electronic Adherence Monitormentioning

confidence: 99%

Section: Extraction Of Features Of Inhaler Use and Calculating Adherencementioning

confidence: 99%

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confidence: 99%

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A Method to Calculate Adherence to Inhaled Therapy that Reflects the Changes in Clinical Features of Asthma

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“…Like other devices this data can later be uploaded to a PC via USB connection and software can be used to calculate date and time of doses [58]. The INCA device can measure both temporal adherence as well as technique [59]. Validation of this device has been carried out in 69 patients with asthma where a close correlation was found between audio recordings of dose and doses taken.…”

Section: Other Devicesmentioning

confidence: 99%

Electronic Monitoring of Adherence to Inhaled Medication in Asthma

Howard¹,

Lang²,

Patel³

et al. 2014

CRMR

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Abstract:The main treatment of asthma is inhaled corticosteroids. However adherence to these medications in asthma is often poor, with low adherence associated with excessive health care costs and an increased risk of emergency room visits and mortality. Although various methods are used to indirectly assess adherence, all have significant limitations whether used in clinical or research practice. The recent development of electronic monitoring devices (EMDs) for use with inhalers presents an exciting opportunity to easily and accurately measure inhaler adherence. This article summarises the current devices available; for each device features and limitations are considered, followed by a review of both the current clinical literature and data on reliability and accuracy. An overall summary is also provided to aid comparison of capabilities between devices and future issues pertaining to the use of EMDs are discussed, including barriers to adoption, stakeholder involvement, novel methods of communicating adherence data, recording of data and cloud storage. Finally key areas that still require investigation are highlighted.

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