Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Jun 26, 2019
Date Accepted: Dec 15, 2019
Measuring what matters to patients: a qualitative analysis of clinical endpoint priorities for remote measurement technologies to aid chronic health conditions
ABSTRACT
Background:
Remote measurement technology (RMT), including the use of smartphone apps and wearable devices, may provide the opportunity for ‘real-world’ assessment and intervention that will streamline clinical input in years to come. In order establish the benefits of this approach we need to operationalize what is expected in terms of a ‘successful outcome’. We focus on three clinical long-term conditions where a novel case has been made for the benefits of RMT: major depressive disorder (MDD), multiple sclerosis and epilepsy.
Objective:
The aim of the present study was to conduct a consultation exercise on the clinical end point or outcome measurement priorities for RMT studies, drawing on the experiences of people with chronic health conditions.
Methods:
Participants (N24; 67% women; ages ranging from 28 to 65) with a diagnosis of one of three chronic health conditions (MDD, multiple sclerosis – MS, or epilepsy), took part in six focus groups. A systematic thematic analysis was used to extract themes and subthemes of clinical endpoint or measurement priorities.
Results:
The views of people with MDD, epilepsy and MS differed. Each group highlighted unique outcomes of importance, relevant to their specific needs. Although there was agreement that remote measurement could be useful for tracking symptoms of illness, some symptoms were specific to the individual groups. Measuring signs of wellness were discussed more by people with MDD than people with MS and epilepsy. However, overlap did emerge when considering contextual factors, such as life events and availability of support (MDD and epilepsy) as well as ways of coping (epilepsy and MS).
Conclusions:
This is a unique study that puts patients’ views at the forefront of the design of a clinical study employing novel digital resources. In all cases, measuring symptoms severity is key; people want to know when their health is getting worse. Second, symptom severity needs to be placed in context. A holistic approach that, in some cases, considers signs of wellness as well as illness, should be the aim of studies employing RMT to understand the health of people with chronic conditions.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.