Abstract
Introduction:
Inhaler therapy is paramount in asthma management, yet non-adherence poses a significant challenge. This study investigates inhaler adherence patterns among adult asthma patients, employing the Test of Adherence to Inhalers (TAIs) questionnaire.
Methods:
This cross-sectional study recruited 99 eligible patients from a specialist outpatient clinic over six months. The TAI questionnaire was administered to the patients. Data on asthma control test scores, medication possession ratio, and healthcare utilisation were collected. Statistical analyses were performed to examine the associations between adherence, patient characteristics, and clinical outcomes.
Results:
More than half of the patients (68.7%) exhibited intermediate (n = 23) or poor (n = 45) adherence, with younger age associated with poorer adherence. Different patterns of non-compliance were identified; 38.8% (n = 19) of patients with poor adherence showed deliberate non-compliance, whereas only 7.3% (n = 3) with good adherence showed unconscious non-compliance. Surprisingly, patients with intermediate and poor adherence often achieved good asthma control, revealing potential challenges in outcome-based adherence assessments. A relatively higher but statistically non-significant proportion of patients with poor adherence had at least one hospitalisation or emergency department attendance due to asthma (42.2% with poor adherence vs. 35.5% with good adherence) or at least one asthma exacerbation requiring oral corticosteroid (64.4% with poor adherence vs. 48.4% with good adherence) in the past 12 months.
Conclusion:
This study provides insights into inhaler adherence among local adult asthma patients, identifying distinct adherence patterns and recognising potential complacency issues associated with traditional adherence assessments. Despite these limitations, our findings contribute to the optimisation of asthma care through a nuanced understanding of inhaler adherence.
Keywords: Adherence, asthma, inhaler, TAI questionnaire
INTRODUCTION
Asthma, a chronic respiratory condition affecting millions worldwide, necessitates effective management strategies for optimal outcomes. In this context, inhaled corticosteroids (ICS) serve as the cornerstone of asthma treatment, endorsed by international guidelines such as the Global Initiative for Asthma.[1] This was also echoed by British Thoracic Society/Scottish Intercollegiate Guidelines Network guidelines on asthma management and a local guideline on asthma management published by Agency for Care Effectiveness, Singapore.[2,3] Notably, these guidelines emphasise the critical assessment of inhaler technique and adherence, along with the evaluation of asthma control and comorbidities. The significance of adherence to inhaler therapy lies in its direct correlation with symptom control, and poor adherence may inadvertently lead to the misjudgement of asthma severity and unwarranted treatment escalation.[4]
Studies have unveiled a wide range of inhaler adherence rates, underscoring the multifaceted challenges in ensuring consistent and optimal adherence to prescribed inhaler regimens.[5,6] The findings by Lindsay and Heaney further illuminate the stark consequences of poor inhaler adherence, including increased asthma-related hospital admissions, heightened asthma-related mortality, and subsequent escalation of healthcare costs.[4]
SUMMARY BOX
What is known?
Adherence to inhaler therapy is crucial for asthma control and prevention of exacerbations. Traditional methods such as verbal assessments often overestimate adherence.
What is new?
This study is among the first to objectively measure inhaler adherence in a local adult asthma population using the Test of Adherence to Inhalers questionnaire a reliable, and easy-to-administer tool.
What is the impact?
The study shows that identifying risk factors for non-adherence enables the development of targeted interventions to improve adherence and asthma outcomes for patients.
Despite the pivotal role of inhaler adherence, practical assessment in clinical settings often relies on subjective methods, such as patient recall, which has been shown to overestimate actual adherence rates.[5] The discrepancy between recommended guidelines and real-world assessments prompts the need for an objective evaluation of inhaler adherence, particularly within the adult asthma population in Singapore.
The primary aim of this study was to objectively investigate inhaler adherence among adult asthma patients in Singapore, utilising the Test of Adherence to Inhalers (TAI) questionnaire developed by Plaza et al.[7] Specifically, we aimed to (a) employ the TAI questionnaire to assess adherence objectively, categorising patients into distinct adherence levels (good, intermediate or partial, poor), (b) analyse responses to specific items in the TAI questionnaire, focusing on factors such as forgetfulness, poor understanding of the disease, patient attitudes and beliefs, emotional factors, and financial difficulties, and (c) utilise the Asthma Control Test (ACT) and healthcare utilisation data from the past 12 months to assess the impact of adherence on asthma control and resource utilisation.
METHODS
This study adopted a cross-sectional design to investigate inhaler adherence among adult asthma patients, including the utilisation of the TAI questionnaire, which is validated for its reliability in assessing adherence levels and patterns.[8] The TAI questionnaire is available in English and has validated translation in other languages, including Chinese. A licence was obtained to utilise both the English and Chinese versions for the study. The study was conducted at the Respiratory Specialist Outpatient Clinic (Clinic 4A), Tan Tock Seng Hospital, Singapore. Ethics approval was obtained from National Healthcare Group Domain Specific Review Board (2022/00718).
Recruitment and data collection occurred over six months. All adult asthma patients aged ≥21 years who were actively following up at Clinic 4A were screened for eligibility. Exclusion criteria included patients with diagnoses other than asthma (e.g., chronic obstructive pulmonary disease (COPD) or asthma–COPD overlap), illiteracy or inability to fill out the questionnaire, individuals diagnosed with lung cancer, pregnant patients, and those who are inhaler-naive. Eligible patients were handed the TAI questionnaire during their clinic visit. The 12-item questionnaire allowed patients to self-rate their level of adherence, with specific questions addressing various aspects of inhaler usage. Type or pattern of non-compliance was assessed based on the sum of scores of the respective questions, with Q1 to Q5 assessing ‘sporadic’ non-compliance (score of 5 to 25), Q6 to Q10 assessing ‘deliberate’ non-compliance (score of 5 to 25), and Q11 to Q12 assessing ‘unconscious’ non-compliance. The level of adherence was interpreted using the sum of the scores of Q1 to Q10 — good adherence (50), intermediate adherence (46–49), and poor adherence (≤45). Non-compliance was interpreted as sporadic when the sum of scores of Q1 to Q5 was <25, deliberate when the sum of scores of Q5 to Q10 was <25, and unconscious when the sum of scores of Q11 to Q12 was <4. Additionally, study team members assessed responses to Q11 and Q12 during the clinic visit by comparing inhaler use frequency against prescription lists and by evaluating asthma nurse- or pharmacist-led assessment of inhaler technique using a placebo inhaler. Retrospective medical records review was conducted for the 12 months preceding the study commencement to retrieve baseline demographic and clinical characteristics, including age, race, gender, body mass index (BMI), education level, comorbidities, type of inhalers prescribed, asthma severity and past healthcare utilisation. Asthma control of the patients was assessed using ACT scores, which ranged from 5 (poor control) to 25 (complete control), with higher scores reflecting greater asthma control and score >19 indicating well-controlled asthma.[9,10] The medication possession ratio (MPR) of the inhalers (up to 12 months prior) was calculated as follows: Medication possession ratio (MPR) = (number of days of medication supplied)/(number of days between the first and the last refill) × 100% (capped at 100%).[11]
When estimating the true population prevalence of non-adherence or poor adherence, a sample size of 50 patients would yield a precision of approximately 15% (margin of error) around the estimated prevalence at a 95% confidence level (CI). Given the number of eligible patients at our specialist outpatient clinic, we aimed to recruit up to 100 eligible patients to meet the objectives of our study, ensuring adequate statistical power and generalisability of findings.
Statistical analysis of baseline and study-related characteristics, TAIs scores, and associated risk factors and outcomes, was conducted using IBM SPSS Statistics version 27 (IBM Corp, Armonk, NY, USA). Distribution of baseline demographic and clinical data, inhaler adherence, and outcomes were summarised using appropriate descriptive statistics. Univariate statistical tests were used to identify factors associated with different levels of adherence. Groups were compared using t-tests (for two independent groups) or ANOVA (for three or more independent groups), and chi-square tests or Fisher’s exact test (accounting for small cell size). Agreement between adherence rates calculated from the TAI test and MPR was estimated using the weighted kappa coefficient to evaluate the accuracy of patient self-reporting. The risk of outcomes, such as the number of exacerbations leading to hospitalisation and emergency department (ED) attendance, oral corticosteroid (OCS) use or any near-fatal events (defined as intensive care unit/high dependency admission, intubation, or non-invasive ventilation) in the last 12 months, was compared across varying levels of inhaler adherence using chi-square tests. All statistical analyses were performed at a two-sided 5% significance level.
RESULTS
A total of 99 asthma subjects were recruited from the Respiratory Specialist Outpatient Clinic (Clinic 4A) over 6 months (February 2023 to July 2023), contributing to a dataset of 118 completed TAI questionnaires, as a single subject may have more than one controller in the treatment regime. On interpretation of the TAI scores, 31 (31.3%) subjects with 41 TAI questionnaires were categorised as having good adherence, 23 (23.2%) subjects with 28 TAI questionnaires as having intermediate adherence, and 45 (45.5%) subjects with 49 TAI questionnaires as having poor adherence.Significant associations were found between age and degree of adherence groups, revealing that younger subjects tended to exhibit intermediate or poor adherence, with mean ages of 64, 58, and 48 years in good, intermediate, and poor adherence groups, respectively (P < 0.001). Other baseline demographics showed no statistical differences in associations between degree of adherence and gender, ethnic groups, BMI, marital status, living arrangement, or most comorbidities, except for hypertension. A higher proportion of patients with good to intermediate adherence had hypertension compared to those with poor adherence (P = 0.009) [Table 1].
Table 1.
Baseline characteristics and their associations with degree of adherence.
| Baseline characteristic | Degree of adherence, n (%) | P | ||
|---|---|---|---|---|
|
| ||||
| Good (n=31, 31.3%) | Intermediate (n=23, 23.2%) | Poor (n=45, 45.5%) | ||
| Age, mean±SD (yr) | 63.9±12.1 | 57.9±17.6 | 48.4±16.5 | <0.001 |
|
| ||||
| Female gender | 24 (77.4) | 15 (65.2) | 33 (73.3) | 0.605 |
|
| ||||
| Ethnicity | 0.455 | |||
|
| ||||
| Chinese | 16 (51.6) | 13 (56.5) | 26 (57.8) | |
|
| ||||
| Malay | 7 (22.6) | 2 (8.7) | 11 (24.4) | |
|
| ||||
| Indian | 7 (22.6) | 8 (34.8) | 7 (15.6) | |
|
| ||||
| Others | 1 (3.2) | 0 | 1 (2.2) | |
|
| ||||
| Body mass index (kg/m2), mean±SD | 26.2±4.1 | 23.4±13.2 | 26.2±8.5 | 0.564 |
|
| ||||
| Marital status | 0.249 | |||
|
| ||||
| Single | 9 (29.0) | 3 (13.0) | 8 (17.8) | |
|
| ||||
| Married | 18 (58.1) | 11 (47.8) | 24 (53.3) | |
|
| ||||
| Divorced | 1 (3.2) | 4 (17.4) | 4 (8.9) | |
|
| ||||
| Widowed | 1 (3.2) | 3 (13.0) | 1 (2.2) | |
|
| ||||
| Separated | 9 (29.0) | 3 (13.0) | 8 (17.8) | |
|
| ||||
| Living arrangement | 0.874 | |||
|
| ||||
| Lives alone | 2 (6.5) | 2 (8.7) | 1 (2.2) | |
|
| ||||
| Lives with family | 25 (80.6) | 18 (78.3) | 35 (77.8) | |
|
| ||||
| Lives with unrelated persons | 1 (3.2) | 1 (4.3) | 2 (4.4) | |
|
| ||||
| Lives in institution | 2 (6.5) | 2 (8.7) | 1 (2.2) | |
|
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| Comorbidity | ||||
|
| ||||
| Allergic rhinitis | 15 (48.4) | 9 (39.1) | 19 (42.2) | 0.775 |
|
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| Chronic rhinosinusitis | 0 | 1 (4.3) | 0 | 0.232 |
|
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| Nasal polyps | 0 | 1 (4.3) | 0 | 0.232 |
|
| ||||
| Eczema | 0 | 0 | 4 (8.9) | 0.145 |
|
| ||||
| Obstructive sleep apnoea | 2 (6.5) | 0 | 0 | 0.148 |
|
| ||||
| Gastroesophageal reflux disease | 3 (9.7) | 5 (21.7) | 7 (15.6) | 0.418 |
|
| ||||
| Diabetes mellitus | 7 (22.6) | 4 (17.4) | 8 (17.8) | 0.849 |
|
| ||||
| Hypertension | 13 (41.9) | 9 (39.1) | 5 (11.1) | 0.009 |
|
| ||||
| Osteoporosis | 2 (6.5) | 1 (4.3) | 0 | 0.158 |
|
| ||||
| Ischaemic heart disease | 3 (9.7) | 2 (8.7) | 2 (4.4) | 0.601 |
More than half (n = 77, 65%) of the recruited subjects demonstrated intermediate or poor adherence with TAI scores below 50, and non-mutually exclusive pattern of non-compliance was analysed. The predominant pattern of non-compliance was sporadic (n = 75, 63.6%), followed by deliberate (n = 19, 16.1%) and unconscious (n = 20, 16.9%) [Table 2]. The association between degree of adherence and pattern of non-compliance was statistically significant, particularly for sporadic and deliberate non-compliance [Table 2]. Notably, the poor adherence group had a higher proportion of subjects with sporadic non-compliance (n = 48, 98%) compared to the intermediate (n = 27, 96%) and good (n = 0) adherence groups. Sporadic non-compliance is often associated with forgetfulness. Among patients with good, intermediate and poor adherence, 41 (100%), 18 (64.3%), and 12 (24.5%), respectively, denied forgetting to use their regular inhaler in the past seven days (P < 0.0001). Deliberate non-compliance occurs when patients refuse to use their inhalers due to reasons such as fear of potential side effects (Q6) or poor understanding of their condition (Q7). Among patients with good, intermediate, and poor adherence, 41 (100%), 25 (89.3%), and 23 (46.9%), respectively, denied discontinuing inhaler use due to fear of potential side effects (P < 0.0001). Similarly, 41 (100%), 26 (92.9%), and 30 (61.2%), respectively, denied discontinuing inhaler use because they believed the inhalers were of little help in treating their condition (P < 0.0001). Unconscious non-compliance occurs when patients do not know the therapeutic regimen or how to use their inhalers. Among patients with good, intermediate, and poor adherence, 40 (97.6%), 27 (96.4%) and 44 (89.8%), respectively, reported being aware of their prescribed regimen (P = 0.249). In addition, 39 (95.1%), 23 (82.1%) and 41 (83.7%), respectively, were observed not to have critical error in their inhaler technique (P = 0.173).
Table 2.
Association of degree of adherence with pattern of non-compliance.
| Variable | Degree of adherence, n (%) | P | ||
|---|---|---|---|---|
|
| ||||
| Good | Intermediate | Poor | ||
| Pattern of non-compliance | ||||
|
| ||||
| Sporadic | 0 | 27 (96.4) | 48 (98.0) | <0.0001 |
|
| ||||
| Deliberate | 0 | 0 | 19 (38.8) | <0.0001 |
|
| ||||
| Unconscious | 3 (7.3) | 6 (21.4) | 11 (22.4) | 0.125 |
A comparison of the TAI questionnaire results with the subjects’ ACT scores revealed no statistical difference (P > 0.05) in association between the degree of adherence and ACT scores [Table 3]. However, there was a higher proportion of subjects with poor asthma control (ACT < 20) in the poor adherence group (n = 21) compared to the intermediate (n = 5) and good (n = 8) adherence groups. Interestingly, 61% (n = 41) of subjects with intermediate and poor adherence reported good asthma control (ACT ≥ 20). The Cramer’s V correlation coefficient for this association was 0.245 (95% CI 0.085–0.451).
Table 3.
Association of degree of adherence with asthma control test (ACT) scores.
| Variable | Degree of adherence, n (%) | P | ||
|---|---|---|---|---|
|
| ||||
| Good | Intermediate | Poor | ||
| ACT score, mean±SD | 20.60±4.11 | 21.83±3.17 | 19.18±4.83 | 0.052 |
|
| ||||
| ACT score | 0.054 | |||
|
| ||||
| ≥20 | 22 (73.3) | 18 (78.3) | 23 (52.3) | |
|
| ||||
| <20 | 8 (26.7) | 5 (21.7) | 21 (47.7) | |
There was a strong correlation between the degree of adherence and self-reported adherence (P < 0.0001), with the majority of subjects categorised as having good adherence on the TAI questionnaire also self-reporting good adherence (n = 24, 92.3%) [Table 4]. Conversely, most subjects categorised as having poor adherence on the TAI questionnaire also self-reported poor adherence (n = 17, 41.5%). Comparison of TAI questionnaire results with subjects’ MPR revealed a statistical difference (P = 0.018), indicating that subjects with poor adherence (69.40%) had a lower MPR compared to those with intermediate (84.61%) and good (84.49%) adherence [Table 4]. Notably, a higher proportion of subjects with poor adherence (n = 22, 45.8%) scored MPR < 80% compared to those with intermediate (n = 9, 32.1%) and good (n = 12; 29.3%) adherence. We observed a poor level of agreement between TAI and MPR measured adherence, with concordance found for half of the patients (weighted kappa = 0.215 [95% CI 0.074–0.355]).
Table 4.
Association of the degree of adherence with baseline reported adherence and MPR.a
| Variable | Degree of adherence, n (%) | P | ||
|---|---|---|---|---|
|
| ||||
| Good | Intermediate | Poor | ||
| Baseline reported adherenceb | <0.0001 | |||
|
| ||||
| Good | 24 (92.3) | 16 (80.0) | 12 (29.3) | |
|
| ||||
| Suboptimal | 1 (3.8) | 4 (20.0) | 12 (29.3) | |
|
| ||||
| Poor | 1 (3.8) | 0 | 17 (41.5) | |
|
| ||||
| MPR, mean±SD | 84.49±24.17 | 84.61±22.32 | 69.40±33.26 | 0.018 |
|
| ||||
| MPR | 0.229 | |||
|
| ||||
| ≥80% | 29 (70.7) | 19 (67.9) | 26 (54.2) | |
|
| ||||
| <80% | 12 (29.3) | 9 (32.1) | 22 (45.8) | |
aMedication possession ratio (MPR) = (number of days of medication supplied)/(number of days between the first and the last refill) × 100% (capped at 100%). bGood = never misses, suboptimal = misses less than half of the time, poor = misses more than half of the time.
There was no significant association between the degree of adherence and the type of inhaler device used [Table 5]. However, there was a higher prevalence of poor adherence among patients using metered dose inhalers (MDIs) (n = 27, 55.1%) compared to those using dry powder inhalers (DPIs) (n = 18, 36.7%) and soft mist inhalers (SMIs) (n = 4, 8.2%). Additionally, a statistically significant association (P = 0.046) was observed between the dosing regimen and adherence, with patients on more than once-daily dosing more likely to demonstrate poor adherence (n = 43, 87.8%) compared to those on a once-daily regimen (n = 6, 12.2%).
Table 5.
Association of the degree of adherence with device type, and dosing frequency.
| Variable | Degree of adherence, n (%) | P | ||
|---|---|---|---|---|
|
| ||||
| Good | Intermediate | Poor | ||
| Device type | 0.338 | |||
|
| ||||
| Metered dose inhaler | 16 (39.0) | 14 (50.0) | 27 (55.1) | |
|
| ||||
| Dry-powdered inhaler | 17 (41.5) | 12 (42.9) | 18 (36.7) | |
|
| ||||
| Soft mist inhaler | 8 (19.5) | 2 (7.1) | 4 (8.2) | |
|
| ||||
| Dosing frequency | 0.046 | |||
|
| ||||
| Once daily | 14 (34.1) | 7 (25.0) | 6 (12.2) | |
|
| ||||
| More than once daily | 27 (65.9) | 21 (75.0) | 43 (87.8) | |
Analysis of healthcare utilisation in the preceding 12 months showed no clinically or statistically significant differences between the degree of adherence and asthma hospitalisation or ED attendance, OCS use, or near-fatal events [Figure 1]. There was a non-significant higher proportion of poorly adherent subjects (n = 19, 42.2%) who had at least one hospitalisation or ED attendance due to asthma in the past 12 months as compared to those with good adherence (n = 11, 35.5%) and intermediate (n = 5, 21.7%) adherence. Similarly, there was a non-significant higher proportion of poorly adherent subjects (n = 19, 64.4%) who had at least one asthma exacerbation requiring OCS in the past 12 months as compared to those with good (n = 15, 48.4%) and intermediate (n = 13, 56.5%) adherence.
Figure 1.
Graph shows the distribution of healthcare utilisation/clinical outcomes by degree of adherence. ED: emergency department, OCS: oral corticosteroid
DISCUSSION
Inhaler therapy, especially ICS, remains the cornerstone of treatment in asthma management. Adherence to inhaler therapy is therefore imperative for controlling asthma symptoms and preventing asthma exacerbations. Previous overseas studies have estimated the inhaler therapy non-adherence rates to be 30%–70% with multifactorial reasons for non-adherence, which are often displayed as variable and inconsistent behaviour traits.[4] Patients have traditionally been subjectively assessed for their adherence to inhaler therapy during each clinic consult or admission episode through verbal questioning, which has been shown in previous studies to overestimate adherence.[5] This is one of the first studies conducted on the local adult asthma population to objectively measure inhaler adherence rates using a self-reported questionnaire that is easy to administer, thus offering healthcare providers a clearer scope of the problem.
In our study of 99 subjects, 19 received an add-on long-acting muscarinic antagonist therapy alongside ICS-containing inhalers, with two TAI questionnaires administered per subject. However, our statistical analyses for associations between degree of adherence and baseline demographics, ACT scores, baseline reported adherence, and healthcare utilisation focused solely on TAI questionnaires about ICS-containing inhalers.
Our study revealed that more than half of the recruited subjects (n = 77, 65%) demonstrated intermediate or poor adherence, which is in line with findings from Ethiopia, Bangladesh, and Malaysia.[12,13,14] Tailored strategies may be essential for different patterns of non-compliance. Notably, clinicians should be vigilant in identifying deliberate non-compliance when patients exhibit poor adherence on the TAI questionnaire. Surprisingly, 61% (n = 41) of subjects with intermediate and poor adherence achieved good asthma control (ACT ≥ 20). This suggests potential complacency, over-treatment, or inadequate awareness of asthma symptoms, resulting in overestimation of control, with the latter being more consistent with our literature review. Bereznicki et al. found that almost half of the Australian population in their study over-reported well-controlled asthma using validated tools, and this was consistent with the findings of a large multinational observational study, where a significant proportion of the participants tended to overestimate their asthma control.[15,16] Similarly, a large European study by Kritikos et al. found that most of the participants rated their asthma as well-controlled using validated tools, although close to half had required steroid bursts within the last year, and almost a quarter had visited the ED.[17]
While MPR can serve as a surrogate marker for adherence, it is not without limitations. First, MPR reflects medication possession but does not guarantee administration. Second, it may overlook medications obtained from private practitioners or other sources not captured by the National Electronic Health Records (NEHR). Additionally, assessing adherence over short intervals (<90 days) using MPR may be imprecise and could potentially overestimate adherence.
Our study did not find a significant association between the degree of adherence and the type of inhaler device used; however, poor adherence was more prevalent among patients using MDIs compared to those using DPIs and SMIs. This observation is consistent with findings from Roy et al.,[18] which reported higher adherence rates among DPI users compared to MDI users. The higher adherence among DPI users may be attributed to its greater ease of use, as compared with MDI, whose users often experienced difficulty coordinating canister actuation with inhalation.[19] Furthermore, our study revealed a significant association between dosing regimens and adherence, with patients on more than once-daily dosing being more likely to exhibit poor adherence, suggesting the importance of simplifying dosing regimens to enhance adherence.[20]
Although our study showed no statistical significance between the degree of adherence and asthma hospitalisation or ED attendance, OCS use or near-fatal events, good adherence may potentially reduce annual healthcare utilisation costs by up to SGD 346 per hospital admission per patient.[21]
Examples of evidence-based interventions to improve inhaler adherence in asthma patients include shared decision-making in selecting medications and dosages, which has been demonstrated to significantly improve adherence and clinical outcomes.[22] Additionally, inhaler reminders have been effective in primary care settings to improve adherence, although this did not consistently translate into day-to-day asthma control improvements.[23] Moreover, using electronic monitoring devices with audiovisual reminders significantly enhanced adherence to ICS in paediatric patients, suggesting potential benefits in asthma control for patients with poor adherence.[24] Lastly, prescribing a once-daily low-dose ICS regimen, rather than a twice-daily regimen, has been associated with higher adherence rates and improved health-related quality of life.[20]
Our study has inherent limitations, including the observational nature of the study design and the lack of multivariate analysis of risk factors due to the limited sample size. Furthermore, the unavailability of follow-up data on ED attendance or hospitalisations at external institutions, due to restrictions in accessing patient data through the NEHR, poses a constraint in tracking comprehensive healthcare utilisation and calculation of MPR. While acknowledging these limitations, they do not diminish the study’s significance in contributing to the understanding of inhaler adherence among local adult asthma patients. Rather, these limitations highlight avenues for future research enhancements and emphasise the need for a nuanced interpretation of our results.
In conclusion, our study sheds light on inhaler adherence patterns among local adult asthma patients. We observed a significant prevalence of intermediate or poor adherence, emphasising the importance of targeted interventions. The identification of diverse patterns of non-compliance underscores the need for tailored strategies in clinical management. Surprisingly, a substantial proportion of subjects with intermediate and poor adherence demonstrated good asthma control, suggesting potential challenges in assessing adherence solely based on clinical outcomes. While MPR offers insights, its limitations warrant careful consideration.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
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