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A qualitative process evaluation within a clinical trial that used healthcare technologies for children with
Louisa Lawrie1, Stephen Turner2, Seonaidh C Cotton1
1Health Services Research Unit, Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, United Kingdom.
Insights
Smart inhalers and AI-driven treatment recommendations show promise in childhood asthma management. Both healthcare staff and families found these technologies useful for monitoring adherence and guiding care, though clinical judgment remains crucial.
Area of Science:
- Pediatric Respiratory Medicine
- Health Informatics
- Digital Health
Background:
- Childhood asthma management is increasingly incorporating healthcare technologies.
- Clinical and patient perspectives on technology use in pediatric asthma care are under-explored.
- Qualitative process evaluation within a clinical trial investigated technology adoption in asthma management.
Purpose of the Study:
- To explore healthcare staff and family experiences with smart inhalers for medication adherence monitoring.
- To assess perspectives on algorithm-generated treatment recommendations in pediatric asthma care.
- To understand the integration of digital health tools in managing childhood asthma.
Main Methods:
- Qualitative process evaluation using interviews.
- Inclusion of trial staff (n=15) and families (n=6) involved in a childhood asthma clinical trial.
- Exploration of perspectives on smart inhalers and AI-driven treatment algorithms.
Main Results:
- Smart inhalers presented technical challenges but improved adherence monitoring and communication.
- Families and children reported increased motivation and responsibility with smart inhaler use.
- Staff were open to algorithm use but emphasized clinical judgment, especially for treatment step-downs; families valued clinician oversight.
Conclusions:
- Technology, including smart inhalers and algorithms, offers benefits for childhood asthma management through enhanced monitoring and education.
- Broad acceptance of algorithms as a guide, with concerns about extreme treatment adjustments and the need for contextual clinical judgment.
- Integration of digital tools requires balancing technological capabilities with essential clinical expertise and patient comfort.
Background:
Healthcare technologies are becoming more commonplace, however clinical and patient perspectives regarding the use of technology in the management of childhood asthma have yet to be investigated. Within a clinical trial of asthma management in children, we conducted a qualitative process evaluation that provided insights into the experiences and perspectives of healthcare staff and families on (i) the use of smart inhalers to monitor medication adherence and (ii) the use of algorithm generated treatment recommendations.
Methods:
We interviewed trial staff (n = 15) and families (n = 6) who were involved in the trial to gauge perspectives around the use of smart inhalers to monitor adherence and the algorithm to guide clinical decision making.
Findings:
Staff and families indicated that there were technical issues associated with the smart inhalers. While staff suggested that the smart inhalers were good for monitoring adherence and enabling communication regarding medication use, parents and children indicated that smart inhaler use increased motivation to adhere to medication and provided the patient (child) with a sense of responsibility for the management of their asthma. Staff were open-minded about the use of the algorithm to guide treatment recommendations, but some were not familiar with its' use in clinical care. There were some concerns expressed regarding treatment step-down decisions generated by the algorithm, and some staff highlighted the importance of using clinical judgement. Families perceived the algorithm to be a useful technology, but indicated that they felt comforted by the clinicians' own judgements.
Conclusion:
The use of technology and individual data within appointments was considered useful to both staff and families: closer monitoring and the educational impacts were especially highlighted. Utilising an algorithm was broadly acceptable, with caveats around clinicians using the recommendations as a guide only and wariness around extreme step-ups/downs considering contextual factors not taken into account.
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