Informing the Design of “Lifestyle Monitoring” Technology for the Detection of Health Deterioration in Long-Term Conditions: A Qualitative Study of People Living With Heart Failure

Abstract

BackgroundHealth technologies are being developed to help people living at home manage long-term conditions. One such technology is “lifestyle monitoring” (LM), a telecare technology based on the idea that home activities may be monitored unobtrusively via sensors to give an indication of changes in health-state. However, questions remain about LM technology: how home activities change when participants experience differing health-states; and how sensors might capture clinically important changes to inform timely interventions.ObjectiveThe objective of this paper was to report the findings of a study aimed at identifying changes in activity indicative of important changes in health in people with long-term conditions, particularly changes indicative of exacerbation, by exploring the relationship between home activities and health among people with heart failure (HF). We aimed to add to the knowledge base informing the development of home monitoring technologies designed to detect health deterioration in order to facilitate early intervention and avoid hospital admissions.MethodsThis qualitative study utilized semistructured interviews to explore everyday activities undertaken during the three health-states of HF: normal days, bad days, and exacerbations. Potential recruits were identified by specialist nurses and attendees at an HF support group. The sample was purposively selected to include a range of experience of living with HF.ResultsThe sample comprised a total of 20 people with HF aged 50 years and above, and 11 spouses or partners of the individuals with HF. All resided in Northern England. Participant accounts revealed that home activities are in part shaped by the degree of intrusion from HF symptoms. During an exacerbation, participants undertook activities specifically to ease symptoms, and detailed activity changes were identified. Everyday activity was also influenced by a range of factors other than health.ConclusionsThe study highlights the importance of careful development of LM technology to identify changes in activities that occur during clinically important changes in health. These detailed activity changes need to be considered by developers of LM sensors, platforms, and algorithms intended to detect early signs of deterioration. Results suggest that for LM to move forward, sensor set-up should be personalized to individual circumstances and targeted at individual health conditions. LM needs to take account of the uncertainties that arise from placing technology within the home, in order to inform sensor set-up and data interpretation. This targeted approach is likely to yield more clinically meaningful data and address some of the ethical issues of remote monitoring.

Symptom perception in heart failure: a scoping review on definition, factors and instruments

“…Manuscript types included 46 observational studies, 2, 7, 14, 21–63 27 qualitative studies, 4, 64–89 12 literature reviews, 16, 17,…”

“…115 Some of the 106 references related to more than one of the research questions. Twelve included references related to HF symptom perception definition, 1, 8, 17, 27, 34, 43, 54, 75, 80, 100, 102, 106 68 to description, 2–4, 7, 10, 16, 17, 21–42, 49, 64–74, 76–79, 81–87, 89…”

“…Some responses are more active in nature and may include resting, relaxing or changing their daily routine. 25, 31, 38, 80, 82 Other responses are more avoidant in nature such as ignoring symptoms 68, 74, 81 or adopting a ‘wait and see’ strategy 102 in hopes that symptoms will resolve spontaneously. 3, 4, 72, 81 These strategies can delay help-seeking, 38, 97 or patients may only seek medical support if symptoms do not resolve, 82 or symptoms escalate interfering with daily life activities, 27 or become unmanageable, 76, 80 leading to emergency situations 67, 79, 115 and hospitalisation.…”

The Management of Diabetes with Hyperuricemia: Can We Hit Two Birds with One Stone?

“…Lifestyle monitoring technology for the detection of health deterioration in long-term conditions has been applied in diseases such as heart failure 88 and dementia, 89 as well as in diabetes. A 3-month follow-up study, including 1354 participants, showed that the higher the levels of patient activation and engagement with remote patient monitoring technology, the better the outcomes of glycemic control.…”

Characteristics of Future Models of Integrated Outpatient Care

“…We use the terms ‘remote surveillance’ and ‘remote monitoring’ for the collection of information from the patient when she/he is not in the office/clinic or in the hospital. Others use such terms as ‘remote patient monitoring’ [174], ‘remote monitoring of patient self-care’ [175], and ‘lifestyle monitoring’ [176].…”