# Determinants of Inhaler Choice at Hospital Discharge

## TL;DR

This study finds that inhaler choices at hospital discharge are often based on routine rather than patient needs, leading to errors and higher readmission rates.

## Contribution

The study introduces a framework to assess inhaler choice appropriateness and identifies clinical inertia and over-adjustment as key issues.

## Key findings

- Device changes were mainly influenced by pre-admission device class and treatment pathway, not clinical need.
- Clinical inertia affected 38.3% of Need-Positive patients, while over-adjustment affected 36.8% of Need-Negative patients.
- Resolving device mismatches was linked to a 48% lower 30-day readmission rate.

## 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.