Internet-of-Things systems can be trusted to support a range of asthma self-management tasks, research suggests
Artificial intelligence can be trusted to help patients manage their asthma at home, but more confidence in these systems is needed
A study published in JMIR mHealth and uHealth has explored patient and clinician trust in the functionality, helpfulness and reliability of Internet-of-Things (IoT) systems to deliver asthma self-management support.
Researchers from the Asthma UK Centre for Applied Research wanted to find out the level of trust that patients and clinicians have in IoT systems to deliver supported asthma self-management.
IoT devices such as smart peak flow meters, smart inhalers and smart watches have been used previously in supporting the clinical management of conditions such as asthma, diabetes and hypertension, but this is the first study to explore the trust that patients’ and healthcare professionals’ place (or not) in IoT connected systems with artificial intelligence (AI) to support asthma self-management.
The research used semi-structure interviews to explore patients’ and clinicians’ trust in using IoT systems to support asthma self-management. In particular, they focused on functionality, helpfulness and reliability of the technology. 12 adult patients with active asthma, and 12 clinicians who provide routine asthma care in primary, secondary and tertiary care were interviewed.
Interviews with patients
The researchers wanted to understand the perceived use of self-management support features and their trust in using IoT systems. They asked patients to design a personalised IoT system incorporating the features they thought would help them live with asthma
Interviews with clinicians
The team asked clinicians to formulate IoT systems that would support asthma self-management and the care they provide for people with asthma. The interviews also explored their trust in the features and the IoT system itself.
Most patients perceived that the IoT had functionality that could support a range of self-management tasks. Typically this was based on past experiences with technology. Some patients believed that the features that would support them to live with asthma did not yet exist.
Some clinicians believed that IoT had the functionality to engage patients to look after their asthma and support self-management. They thought future systems could provide clinicians with the manual or auto logs for review. Other doubted that technology could change patients’ behaviour.
Most patients perceived IoT systems to have useful services to log data about their asthma symptoms. Helpful customised alerts and advice they would welcome included:
- identifying unusual asthma symptoms and automatically providing customised information and advice on medication adjustments and follow-up actions
- alerting them if their inhaler technique was incorrect
- detecting unusual use of rescue inhalers
- reminding them to comply with their preventer inhaler
Patients also believed that IoT systems would help them in supporting their communication with clinicians. They thought it would help them ask quick questions or arrange follow-up consultations via text, WhatsApp or email. They could also share their data with clinicians to assess their asthma status.
Most clinicians agreed that receiving data about peak flow and symptoms would help them assess asthma status in reviews. They also thought the objective data on incorrect or correct inhaler use would help them assess adherence and suitability of the inhaler device.
Some patients observed that a system that logged data in the background would reduce missing data. They believed that smart peak flow meters and smart inhalers could reliably capture data, but there were some limitations. Some patients did not always carry these devices with them, or they had one reliever inhaler at home, one in the car and one at work.
Most patients believed that the system could offer advice on an agreed action plan, but had doubts that the system could safely generate new advice. All patients preferred their clinician to interpret the data and decide on new advice,
Most clinicians agreed that automatic logs are more accurate, as they reduce human error. They were also comfortable with an early warning system to alert patients to seek further assistance when their condition worsened.
Both patients and clinicians emphasised the importance of personal relationships.
Patients and clinicians do agree that IoT systems have the potential to provide a range of customised support for asthma self-management. They think that IoT systems can be trusted to learn about an individual’s asthma throughout time and provide advice on a set of rules.
However, neither group of participants in this study trusted the IoT system over the clinicians’ intelligence to create new self-management advice.
Users need to increase their level of trust in the reliability of IoT systems before they accept the advice they generate. The participants in this study are not yet ready for this step.
This publication is part of the Asthma UK Centre for Applied Research study A4A (App for Asthma) Connected+.
Dr Io Chi-Yan Hui, who is a Research Fellow on the A4A+ study, was the lead author on this paper. She thinks this paper is an important step in understanding how patients and clinicians trust IoT systems to support asthma self-management. She said:
Internet-of-Things with artificial intelligence could support patient self-management in many ways but it is not a panacea. It is vital to understand what features are trusted by users to encourage adoption and substantial use in real life. We conclude that research is needed to ensure that technological capability does not outstrip the trust of the individuals using it. We hope our findings will be of interest to healthcare services providers, technology developers and researchers developing intelligent technological approaches to support people living with long-term conditions such as asthma.
Read the paper
Hui CY, McKinstry B, Fulton O, Buchner M, Pinnock H, Patients’ and Clinicians’ Perceived Trust in Internet-of-Things Systems to Support Asthma Self-management: Qualitative Interview Study, JMIR Mhealth Uhealth 2021;9(7):e24127 doi: 10.2196/24127
Read more about the A4A Connected+ study