The effect of providing feedback on inhaler technique and adherence from an electronic audio recording device, INCA®, in a community pharmacy setting: study protocol for a randomised controlled trial.

BACKGROUND: Poor adherence to inhaled medication may lead to inadequate symptom control in patients with respiratory disease. In practice it can be difficult to identify poor adherence. We designed an acoustic recording device, the INCA® (INhaler Compliance Assessment) device, which, when attached to an inhaler, identifies and records the time and technique of inhaler use, thereby providing objective longitudinal data on an individual's adherence to inhaled medication. This study will test the hypothesis that providing objective, personalised, visual feedback on adherence to patients in combination with a tailored educational intervention in a community pharmacy setting, improves adherence more effectively than education alone. METHODS/DESIGN: The study is a prospective, cluster randomised, parallel-group, multi-site study conducted over 6 months. The study is designed to compare current best practice in care (i.e. routine inhaler technique training) with the use of the INCA® device for respiratory patients in a community pharmacy setting. Pharmacies are the unit of randomisation and on enrolment to the study they will be allocated by the lead researcher to one of the three study groups (intervention, comparator or control groups) using a computer-generated list of random numbers. Given the nature of the intervention neither pharmacists nor participants can be blinded. The intervention group will receive feedback from the acoustic recording device on inhaler technique and adherence three times over a 6-month period along with inhaler technique training at each of these times. The comparator group will also receive training in inhaler use three times over the 6-month study period but no feedback on their habitual performance. The control group will receive usual care (i.e. the safe supply of medicines and advice on their use). The primary outcome is the rate of participant adherence to their inhaled medication, defined as the proportion of correctly taken doses of medication at the correct time relative to the prescribed interval. Secondary outcomes include exacerbation rates and quality of life measures. Differences in the timing and technique of inhaler use as altered by the interventions will also be assessed. Data will be analysed on an intention-to-treat and a per-protocol basis. Sample size has been calculated with reference to comparisons to be made between the intervention and comparator clusters and indicates 75 participants per cluster. With an estimated 10 % loss to follow-up we will be able to show a 20 % difference between the population means of the intervention and comparator groups with a power of 0.8. The Type I error probability associated with the test of the null hypothesis is 0.05. DISCUSSION: This clinical trial will establish whether providing personalised feedback to individuals on their inhaler use improves adherence. It may also be possible to enhance the role of pharmacists in clinical care by identifying patients in whom alteration of either therapy or inhaler device is appropriate. REGISTRATION: ClinicalTrials.gov NCT02203266 .

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

RATIONALE: Currently, studies on adherence to inhaled medications report average adherence over time. This measure does not account for variations in the interval between doses, nor for errors in inhaler use. OBJECTIVES: To investigate whether adherence calculated as a single area under the (concentration-time) curve (AUC) measure, incorporating the interval between doses and inhaler technique, was more reflective of patient outcomes than were current methods of assessing adherence. METHODS: We attached a digital audio device (INhaler Compliance Assessment) 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 patients with asthma was studied. Adherence to a twice-daily inhaler preventer therapy using this device and clinical measures were assessed. MEASUREMENTS AND MAIN RESULTS: Recordings from 239 patients with severe asthma were analyzed. Average adherence that was 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 the adherence measures, only adherence calculated as AUC reflected changes in asthma quality of life, ß-agonist reliever use, and peak expiratory flow over the 3 months (P < 0.05 compared with other measures of adherence). CONCLUSIONS: 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 are the currently used measures of adherence. Clinical trial registered with www.clinicaltrials.gov (NCT 01529697).

A protocol for a randomised clinical trial of the effect of providing feedback on inhaler technique and adherence from an electronic device in patients with poorly controlled severe asthma.

INTRODUCTION: In clinical practice, it is difficult to distinguish between patients with refractory asthma from those with poorly controlled asthma, where symptoms persist due to poor adherence, inadequate inhaler technique or comorbid diseases. We designed an audio recording device which, when attached to an inhaler, objectively identifies the time and technique of inhaler use, thereby assessing both aspects of adherence. This study will test the hypothesis that feedback on these two aspects of adherence when passed on to patients improves adherence and helps clinicians distinguish refractory from difficult-to-control asthma. METHODS: This is a single, blind, prospective, randomised, clinical trial performed at 5 research centres. Patients with partially controlled or uncontrolled severe asthma who have also had at least one severe asthma exacerbation in the prior year are eligible to participate. The effect of two types of nurse-delivered education interventions to promote adherence and inhaler technique will be assessed. The active group will receive feedback on their inhaler technique and adherence from the new device over a 3-month period. The control group will also receive training in inhaler technique and strategies to promote adherence, but no feedback from the device. The primary outcome is the difference in actual adherence, a measure that incorporates time and technique of inhaler use between groups at the end of the third month. Secondary outcomes include the number of patients who remain refractory despite good adherence, and differences in the components of adherence after the intervention. Data will be analysed on an intention-to-treat and a per-protocol basis. The sample size is 220 subjects (110 in each group), and loss to follow-up is estimated at 10% which will allow results to show a 10% difference (0.8 power) in adherence between group means with a type I error probability of 0.05. TRIAL REGISTRATION NUMBER: NCT01529697; Pre-results.

Reliability and validity of the Automatic Cognitive Assessment Delivery (ACAD).

IN THIS STUDY WE EVALUATED RELIABILITY AND VALIDITY OF THE AUTOMATIC COGNITIVE ASSESSMENT DELIVERY (ACAD): a short computerized battery composed by memory and attention tests, delivered online, and designed primarily for the elderly. Reliability was examined with a test-retest design and validity was assessed by means of comparison with standard neuropsychological tests. Older (N = 32) and young adult participants (N = 21) were involved. We found that the ACAD is free from any practice effect. Test-retest reliability was confirmed via significant correlations and high percentage agreements between the scores of three repeated assessments. ACAD scores were lower for older than for young adult participants and correlated significantly with the standardized measures of memory and attention. Results demonstrate that the ACAD battery provides a reliable and valid measure of both immediate and delayed recognition memory and sustained attention, and may be useful for convenient and efficient cognitive assessment and monitoring in older adults.

A study into the automation of cognitive assessment tasks for delivery via the telephone: lessons for developing remote monitoring applications for the elderly.

BACKGROUND: Cognitive assessments are valuable tools in assessing neurological conditions. They are critical in measuring deficits in cognitive function in an array of neurological disorders and during the ageing process. Automation of cognitive assessments is one way to address the increasing burden on medical resources for an ever increasing ageing population. OBJECTIVE: This study investigated the suitability of using automated Interactive Voice Response (IVR) technology to deliver a suite of cognitive assessments to older adults using speech as the input modality. METHODS: Several clinically valid and gold-standard cognitive assessments were selected for implementation in the IVR application. The IVR application was designed using human centred design principles to ensure the experience was as user friendly as possible. Sixty one participants completed two IVR assessments and one face to face (FF) assessment with a neuropsychologist. Completion rates for individual tests were inspected to identify those tests that are most suitable for administration via IVR technology. Interclass correlations were calculated to assess the reliability of the automated administration of the cognitive assessments across delivery modes. RESULTS: While all participants successfully completed all automated assessments, variability in the completion rates for different cognitive tests was observed. Statistical analysis found significant interclass correlations for certain cognitive tests between the different modes of administration. Analysis also suggests that an initial FF assessment reduces the variability in cognitive test scores when introducing automation into such an assessment. CONCLUSION: [corrected] This study has demonstrated the functional and cognitive reliability of administering specific cognitive tests using an automated, speech driven application. This study has defined the characteristics of existing cognitive tests that are suitable for such an automated delivery system and also informs on the limitations of other cognitive tests for this modality. This study presents recommendations for developing future large scale cognitive assessments.

Dynamic minimum pause threshold estimation for speech analysis in studies of cognitive function in ageing.

Cognitive decline represents the biggest limiting factor to independence in older adults. Speech analysis has emerged as an alternative to standard cognitive assessment tools. Temporal segmentation of speech is reported in many studies and typically employs a static threshold to define a pause. This study investigated the effect of using pause and utterance duration distribution data in differentiating between cognitively healthy and impaired older adults. Three sets of features were extracted from 187 speech recordings: temporal features using a static 250ms threshold; temporal features using a dynamic threshold; and pause and utterance duration distribution parameters. The ability of each of these sets to differentiate between cognitively healthy and cognitively impaired participants was investigated using a Linear Discriminant Analysis (LDA) classifier. Improvements of 0.22% (to 64.20%) in sensitivity, 6.33% (73.12%) in specificity, and 3.27% (68.66%) in overall accuracy were observed in the performance of the classifier using the pause and utterance duration distribution parameters when compared to the static temporal features. The use of the dynamic threshold had a negative impact on the classifier performance, with a decrease of 5.73% (to 58.25%) in sensitivity, 1.10% (65.69%) in specificity, and 3.42% (61.97%) in accuracy.

Automatic identification and accurate temporal detection of inhalations in asthma inhaler recordings.

Asthma is chronic airways disease characterized by recurrent attacks of breathlessness and wheezing. Adherence to medication regimes is a common failing for asthmatic patients and there exists a requirement to monitor such patients' adherence. The detection of inhalations from recordings of inhaler use can provide empirical evidence about patients' adherence to their asthma medication regime. Manually listening to recordings of inhaler use is a tedious and time consuming process and thus an algorithm which can automatically and accurately carry out this task would be of great value. This study employs a recording device attached to a commonly used dry powder inhaler to record the acoustic signals of patients taking their prescribed medication. An algorithm was developed to automatically detect and accurately demarcate inhalations from the acoustic signals. This algorithm was tested on a dataset of 255 separate recordings of inhaler use in real world environments. The dataset was obtained from 12 asthma outpatients who attended a respiratory clinic over a three month period. Evaluation of the algorithm on this dataset achieved sensitivity of 95%, specificity of 94% and an accuracy of 89% in detecting inhalations compared to manual inhalation detection.

Acoustic and temporal analysis of speech: A potential biomarker for schizophrenia.

Currently, there are no established objective biomarkers for the diagnosis or monitoring of schizophrenia. It has been previously reported that there are notable qualitative differences in the speech of schizophrenics. The objective of this study was to determine whether a quantitative acoustic and temporal analysis of speech may be a potential biomarker for schizophrenia. In this study, 39 schizophrenic patients and 18 controls were digitally recorded reading aloud an emotionally neutral text passage from a children's story. Temporal, energy and vocal pitch features were automatically extracted from the recordings. A classifier based on linear discriminant analysis was employed to differentiate between controls and schizophrenic subjects. Processing the recordings with the algorithm developed demonstrated that it is possible to differentiate schizophrenic patients and controls with a classification accuracy of 79.4% (specificity=83.6%, sensitivity=75.2%) based on speech pause related parameters extracted from recordings carried out in standard office (non-studio) environments. Acoustic and temporal analysis of speech may represent a potential tool for the objective analysis in schizophrenia.