| Literature DB >> 28439076 |
Elizabeth Azzi1, Pamela Srour2, Carol Armour2,3, Cynthia Rand4, Sinthia Bosnic-Anticevich2,3.
Abstract
Poor inhaler technique and non-adherence to treatment are major problems in the management of asthma. Patients can be taught how to achieve good inhaler technique, however maintenance remains problematic, with 50% of patients unable to demonstrate correct technique. The aim of this study was to determine the clinical, patient-related and/or device-related factors that predict inhaler technique maintenance. Data from a quality-controlled longitudinal community care dataset was utilized. 238 patients using preventer medications where included. Data consisted of patient demographics, clinical data, medication-related factors and patient-reported outcomes. Mixed effects logistic regression was used to identify predictors of inhaler technique maintenance at 1 month. The variables found to be independently associated with inhaler technique maintenance using logistic regression (Χ 2 (3,n = 238) = 33.24, p < 0.000) were inhaler technique at Visit 1 (OR 7.1), device type (metered dose inhaler and dry powder inhalers) (OR 2.2) and self-reported adherent behavior in the prior 7 days (OR 1.3). This research is the first to unequivocally establish a predictive relationship between inhaler technique maintenance and actual patient adherence, reinforcing the notion that inhaler technique maintenance is more than just a physical skill. Inhaler technique maintenance has an underlying behavioral component, which future studies need to investigate. ASTHMA: BEHAVIORAL ELEMENT TO CORRECT LONG-TERM INHALER TECHNIQUES: Patients who consciously make an effort to perfect asthma inhaler technique will maintain their skills long-term. Elizabeth Azzi at the University of Sydney, Australia, and co-workers further add evidence that there is a strong behavioral component to patients retaining correct inhaler technique over time. Poor inhaler technique can limit asthma control, affecting quality of life and increasing the chances of severe exacerbations. Azzi's team followed 238 patients to determine the key predictors of inhaler technique maintenance from factors including age, asthma knowledge and perceived future risks. Correct inhaler technique at initial assessment was the strongest predictor of long-term success, but this was strengthened further when patients reported good adherence to their own medication regimen. This suggests that maintaining correct inhaler technique is more than just a physical skill. Careful guidance towards this 'practice makes perfect' approach may improve patients' long-term technique maintenance.Entities:
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Year: 2017 PMID: 28439076 PMCID: PMC5435088 DOI: 10.1038/s41533-017-0031-0
Source DB: PubMed Journal: NPJ Prim Care Respir Med ISSN: 2055-1010 Impact factor: 2.871
Fig. 1Consort diagram of patients recruited and completing the study
Proportion of patients with correct inhaler technique per device
| Visit 1a | Visit 2 | |
|---|---|---|
| Correct technique ( | 24% (56/238) | 50% (118/238) |
| Correct technique per device | ||
| pMDI technique ( | 25% (18/71) | 40% (28/71) |
| DPI technique ( | 23% (38/167) | 54% (90/167) |
| TH technique ( | 17% (15/90) | 52% (47/90) |
| ACC Technique ( | 30% (23/77) | 56% (43/77) |
a All patients who demonstrated incorrect technique at Visit 1 were trained to mastery
Independent variables with significant bivariate association with ‘correct inhaler technique maintenance’
| Variable/characteristic | Maintained | Did not maintain | Pearson co-efficient |
|
|---|---|---|---|---|
| Inhaler technique at Visit 1 | ||||
| Correct inhaler technique ( | 44 | 12 | 24.622 | 0 |
| Incorrect inhaler technique ( | 74 | 108 | ||
| Regimen Score | ||||
| Adherent (scores <1) | 47 | 29 | 12.557 | 0.028 |
| Future risk of non-adherence (scores ≥1) | 71 | 91 | ||
| Device type DPI/MDI | ||||
| DPI | 90 | 77 | 4.164 | 0.041 |
| MDI | 28a | 43b | ||
a 9 patients using a MDI with a spacer maintained correct technique
b 6 patients using a MDI with a spacer did not maintain correct technique
Logistic regression model variables showing significant predictive likelihood for correct inhaler technique maintenance
| Predictor | Coding | B | SE | Deviance | df |
| Odds ratio | 95% CI for odds ratio | |
|---|---|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||||
| Inhaler technique at VISIT 1 | 0 = Correct technique ( | 1.965 | .455 | 17.431 | 1 | .000 | 7.131 | 3.104 | 18.922 |
| 1 = Incorrect technique ( | |||||||||
| Regimen Score | Score range 1–7 | .275 | .127 | 4.498 | 1 | .031 | 1.317 | 1.027 | 1.701 |
| Device type | 0 = DPI ( | .791 | .355 | 5.344 | 1 | .026 | 2.205 | 1.116 | 4.554 |
| 1 = pMDI ( | |||||||||
Outcome variable coding for inhaler technique maintenance: 0 = maintained correct inhaler technique, 1 = did not maintain correct inhaler technique.
a MDI and MDI with a spacer groups were combined under pMDI to achieve sufficient group size for logistic regression analysis
Data measures and collection points
| Measure | Visit 1 | Visit 2 | |
|---|---|---|---|
| Clinical | |||
| Asthma control | ✓ | ✓ | |
| Medication profile | ✓ | ✓ | |
| Future risk of medication non-adherence | ✓ | ||
| Inhaler technique | ✓ | ✓ | |
| Asthma knowledge | ✓ | ||
| Hospital emergency department visits and admissions | ✓ | ||
| Patient-related | |||
| Asthma quality of Life | ✓ | ||
| Asthma perceived control | ✓ | ||