Adherence measure Advantages Disadvantages Least Objective Most Objective Non– judgemental questioning by clinician  Easy to perform in clinic  Cheap  Inaccurate  Over-estimates adherence Self-report questionnaires  Easy to perform in clinic  Cheap  Inaccurate  Recall inaccuracy  Susceptible to self- desirability bias  Over-estimates adherence Daily diary cards   Reduces recall inaccuracy  Amenable to technological advances  Inaccurate  Susceptible to self- desirability bias  Over-estimates adherence Prescription– refill data  Cheap  Reduces self– desirability bias  Inaccurate  Over-estimates adherence  Susceptible to dose “dumping”  No guarantee dispensed medication is taken Canister weight/ dose counters  Cheap  Reduces self- desirability bias  Not time-sensitive  Over-estimates adherence  Susceptible to dose “dumping” Drug assays  Objective  Accurate  Impractical in clinical setting  Short term adherence monitoring Electronic Monitoring Devices (EMDs)  Most Objective  Accurate  Continuous adherence monitoring  Expensive  Device malfunctions • Detect device actuation, not inhalation
2.7 Adherence levels to inhaled steroids in children with asthma when recorded electronically As described above, when many studies have recorded adherence levels to preventer inhalers in children, the methods used are often subjective, and therefore potentially inaccurate. Recent studies which have recorded adherence electronically can give us an objective indication of adherence levels in the paediatric asthma population. Table 2 pools the adherence data from these studies. Trials were found by searching the Pubmed database for the period January 1980 to October 2013 with the terms adherence/compliance and asthma and electronic and monitoring. The search was repeated with the same terms and the table updated in May 2016. Other studies were identified from reference lists from these studies. Studies were included if they were monitoring adherence only in children (aged <18). Where the trials involve an adherence intervention, only the control arm rates or rates at baseline are quoted. Studies were rejected if they looked at rates in populations which were already shown to be non-adherent. The mean rate of adherence is the overall rate of adherence for the whole duration of the respective studies. If multiple adherence rates were recorded over time, the mean of these rates has been calculated. Table 2 Adherence rates to inhaled corticosteroids when measured electronically
Study Population Age Medication Duration EMD Mean Funder () 33 children, USA 6-19 yrs Multivitamins 3 months MEMS 64% CF Foundation Traineeship () 36 children, USA 6-13 yrs Pancreatic Enzymes 3 months MEMS* 43% Agency for Healthcare & Research Quality () 28 children, UK 2-15 yrs Nebulised Antibiotics 1 year I-Neb 67% RLCH R&D fund () 24 children, UK 11-17 yrs Nebulised Antibiotics 1 year I I-Neb 65% Not declared Table 3 – Mean adherence rates to therapy in children with CF when measured electronically * MEMS- Medication Event Monitoring System – Aardex, Union City, California, USA Philips Respironics, UK 2.9 Trends in adherence for children with asthma and CF Data from these studies show that adherence rates are lower in older children and adolescents in asthma and CF (, , ), with the highest rates seen in children under the age of 6. In asthma, rates are lower in children from a poor socioeconomic background (, , , , ). The populations where adherence rates are highest are developed western countries such as the UK, the Netherlands, Australia & the USA, although these rates are often still below 75%. These studies with more adherent populations in developed countries also only included younger children (, , , , ). Adult studies have reported that adherence rates are higher in males than in females in both asthma() and CF (), but this has not been shown in paediatric populations. The studies which have reported this trend in adults have used prescription
either underpowered, methodologically flawed, or with too short follow – up periods to demonstrate an improvement in clinical outcome. Studies have shown that direct medication reminders are effective at improving adherence rates, but have also failed to show an improvement in clinical outcome. 2.16 - Evidence Deficit The literature review has shown there have been no studies in either children or adults, with asthma or CF which have demonstrated an effective and clinically feasible adherence intervention, which has achieved a significant and sustained improvement in adherence and clinical outcomes. Previous studies have either been underpowered, or had methodological flaws when measuring adherence rates which have potentially reduced the validity of their results. 2.17 - Research Hypothesis 2.17.1 Adherence Conceptual Framework As demonstrated in the review of literature, non-adherence is likely to be a combination of intentional and non-intentional factors, and in order to improve adherence, both factors need to be addressed. Previous interventions have potentially failed because they have only addressed one of these factors. In order for a patient to achieve full adherence, they and their parents need to have a positive view of asthma/ CF and inhaled medication, and have the capability and opportunity to take the medication regularly. Once this has been achieved, the regular behaviour of taking medication can become a habit, and on-going adherence will be more routine. Based on this premise, a conceptual framework for adherence and habit formation has been proposed by Martin Wildman and colleagues,
4.3.4 Secondary Outcomes 4.3.4.1 Lung Function – Rosenthal 1993 data FEV1% predicted increased in both groups, but was no significant difference between baseline and visit values for either group, or between groups (table 10). The Rosenthal data are the % predicted FEV values as compared to the 1993 Rosenthal data reference ranges. These were the original data collected. The Global Lung Initiative (GLI, 2012) data were calculated later (and shown afterwards). Baseline Mean (SD) 3 months 6 months 9 months 12 months Combined mean Mean (SD) [95% CI] Mean (SD) [95% CI] Mean (SD) [95% CI] Mean (SD) [95% CI] Mean (SD) [95% CI] A 87.0 (18.0) [82.0-91.1] 90.4 (17.7) [84.1-96.6] 89.8 (17.0) [82.8-96.7] 90.9 (14.6) [85.7-96.1] 89.9 (14.3) [85.5-94.2] 91.5 (14.2) [87.1-95.9] B 83.3 (16.4) [78.4-88.3] 87.1 (13.3) [82.4-91.9] 85.2 (21.1) [77.7-92.7] 86.0 (13.8) [81.1-91.0] 87.3 (16.2) [81.8-92.7] 86.7 (13.4) [82.6-90.9] A vs. B P value 0.31 0.43 0.38 0.11 0.48 1.27 Table 10 – Mean (SD) FEV1% predicted (Rosenthal 1993) scores for each study visit for groups A and B.
[4.2-5.0] [5.2-6.0] P = 0.53 MBQ A 2.5 (0.5) [2.4-2.6] 2.3 (0.5) [1.9-2.8] MBQ B 2.6 (0.4) [2.5-2.8] 2.5 (0.4) [2.3-2.7] P = 0.56 IPQ Group A 5.6 (1.3) [5.2-6.0] 4.4 (1.4) [3.7-5.5] IPQ Group B 5.3 (0.9) [5.0-5.6] 4.8 (0.9) [4.3-5.2] P = 0.21 Table 17 – Between group comparisons for secondary outcomes for Groups A and B. BTS = British Thoracic Society. PQL = Paediatric quality of life questionnaire. Inhaled steroid dose is beclometasone equivalent dose. 4.3.4.10 Clinic Visits Table 18 shows the rates of did not attend (DNA) and cancelled clinic appointments in groups A and B. Wherever possible, appointments were re-scheduled. However as some patients were not scheduled a clinic appointment at or around a 3 month interval, or had cancelled an appointment without the possibility of obtaining a replacement appointment, 35 non-clinical study visits (15 intervention, 20 control) were performed. Despite these visits, the high number of cancelled or missed appointments impacted on the ability to provide feedback at each of the three scheduled time points (3,6 & 9 months). Table 19 shows the number of successful feedback visits for group A (total number of participants randomised to group A, n = 47). Total no. study visits Mean no. visits per participant DNA Cancelled Total (DNA +cancelled) Group A 136 2.9 38 37 75 B 124 3.0 33 35 68 Total 260 71 72 143
4.4.5 Weekend/ Weekday/ Holiday adherence There was no overall difference between the pre- text and text periods for weekday adherence, weekend adherence, school holiday adherence and mean missed days (table 27). 4.4.6 Missed days & There were fewer missed doses during the text period, but the difference was not significant (table 27). Mean (SD) [95% CI] weekday adherence Median (IQR) weekday adherence Mean (SD) [95% CI] weekend adherence Median (IQR) weekend adherence Mean (SD) [95% CI] school holiday adherence Median (IQR) school holiday adherence Mean(SD) [95% CI] missed doses Mean (SD) [95% CI] missed days Pre-text period 79.5 (25.7) [65.0-94.0] 94.1 (73-96) [ 79.5 (25.8) 95.4 (64-98) 80.6 (27.6) 93.5 (73-97) 75.9 (104.0) 20.2 (38.2) [0.0-40.9] Text period 78.5 (29.8) [61.7-95.4] 91.5 (77-98) [ 80.5 (30.6) 95.2 (82-98) 77.4 (32.8) 92.5 (81-95) 58.1 (71.4) 26.2 (51.0) [0.0-54.0] P 1.0 1.0 0.43 0.42 0.21 Table 27 – Other outcome results for the pre-text and text periods. Adherence rates are percentages Participant Mean adherence (overall) Pre-text Mean adherence (overall) Text Mean weekday adherence Pre-text Mean weekday adherence Text Mean weekend adherence Pre-text Mean weekend adherence Text Mean school holiday Mean school holiday
combination had no overall effect on the adherence of the small group of children in this study, who had existing high baseline rates. This was the first study to use reminder text messages on children with CF, whilst electronically monitoring adherence rates. The data from this study can be used to design future research studies, or this approach can be used in clinical practice and the patient outcomes audited at a departmental level. 7.4 Recommendations and policy change This thesis has shown that sub-optimal adherence to inhaled medication in childhood asthma and CF is a common and significant problem, resulting in detrimental consequences for both the patient and healthcare provider. Subjective methods of adherence monitoring are flawed, and therefore electronic monitoring is essential to record the most accurate rates possible. When guidelines written by the BTS, ICON, and the UK CF registry are updated, they should therefore emphasize the importance of electronic adherence monitoring. For children with poorly controlled asthma, we have shown that the use of these monitors with regular feedback in clinic can significantly reduce the rate of severe exacerbations. These outcomes have been achieved despite the realistic use and misuse of the devices by children in the clinical setting. The BTS has questioned the use of these devices due to their cost, but we have demonstrated that they are likely to be cost effective, even at current prices. With increased use and commercial competition, devices will become cheaper and make them even more financially viable. To optimise the effect and economic benefit of these devices, they should only be used in children with poorly controlled asthma, and if they are found to be ineffective due to breakage or increased patient non-attendance at clinic, they should be removed.
The existing technology available to electronically monitor both asthma and CF is now well established, and with an increased evidence base for its efficacy, should be utilised more widely in clinical practice. Future studies should investigate how to optimise and refine this approach, and incorporate emerging technology using remote monitoring and smartphone applications. With rapid technological advances in current devices and software available, it’s an intriguing time for electronic adherence monitoring, and its potential to significantly improve the lives of children with asthma and cystic fibrosis. 7.5 Summary The STAAR study was the first study using electronic adherence monitoring with feedback and alarms to demonstrate a sustained improvement in adherence and clinical outcomes in children with asthma. The Nebtext study showed it is feasible to use regular reminder text messages to children with CF, and whilst they are amenable to this approach, the reminders have a limited effect when used on a group of patients with high baseline adherence rates.