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Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models
Published on: November 11, 2020
Determinants of Inhaler Choice at Hospital Discharge
Myriam Calle Rubio1,2,3,4, Soha Esmaili1,5,6, Iman Esmaili7
1Department of Medicine, School of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Abstract:
Background: Inhaler device changes at hospital discharge should address patient capacity yet often reflect routine. We evaluated the appropriateness of these decisions and their impact on clinical outcomes. Methods: In this prospective observational study (N = 480), we assessed patient technical capacity using a composite of critical errors, inspiratory flow, adherence, and knowledge. We stratified patients into 'Need-Positive' and 'Need-Negative' cohorts to quantify patterns of clinical inertia and over-adjustment. Multivariable models identified predictors of decision-making and associations with 30-day outcomes. Results: Device changes were primarily determined by the pre-admission device class (spacers: aOR 0.52; 95% CI 0.28-0.96; p = 0.037) and by the patient's treatment pathway rather than by clinical need. This disconnect generated two types of errors: 38.3% of Need-Positive patients (n = 214) experienced clinical inertia (no corrective action), while 36.8% of Need-Negative patients (n = 266) underwent over-adjustment (unnecessary switching). Inertia perpetuated errors in patients with need, whereas over-adjustment was associated with the emergence of new errors in patients without need. Successful mismatch resolution was associated with a significantly lower 30-day readmission rate (12.1% vs. 32.5%; OR 0.48; 95% CI 0.26-0.88; p = 0.017). Conclusions: Discharge prescribing is driven more by habit than by objective assessment, leading to widespread missed opportunities for correction. Implementing evidence-based protocols to identify and resolve patient-device mismatches may represent a high-impact strategy to reduce readmissions and associated healthcare use.
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