Rethinking the patient: using Burden of Treatment Theory to understand the changing dynamics of illness

By Carl R May, D. Eton, Kasey R. Boehmer, K. Gallacher, Katherine J Hunt, S. Macdonald, F. Mair, C. May, Victor M. Montori, A. Richardson and 2 more. BMC Health Services Research, 2014

618 citations recorded by the source corpus.

BackgroundIn this article we outline Burden of Treatment Theory, a new model of the relationship between sick people, their social networks, and healthcare services. Health services face the challenge of growing populations with long-term and life-limiting conditions, they have responded to this by delegating to sick people and their networks routine work aimed at managing symptoms, and at retarding – and sometimes preventing – disease progression. This is the new proactive work of patient-hood for which patients are increasingly accountable: founded on ideas about self-care, self-empowerment, and self-actualization, and on new technologies and treatment modalities which can be shifted from the clinic into the community. These place new demands on sick people, which they may experience as burdens of treatment.DiscussionAs the burdens accumulate some patients are overwhelmed, and the consequences are likely to be poor healthcare outcomes for individual patients, increasing strain on caregivers, and rising demand and costs of healthcare services. In the face of these challenges we need to better understand the resources that patients draw upon as they respond to the demands of both burdens of illness and burdens of treatment, and the ways that resources interact with healthcare utilization.SummaryBurden of Treatment Theory is oriented to understanding how capacity for action interacts with the work that stems from healthcare. Burden of Treatment Theory is a structural model that focuses on the work that patients and their networks do. It thus helps us understand variations in healthcare utilization and adherence in different healthcare settings and clinical contexts.

Subfields: Epidemiology, General Health Professions, Philosophy

View Paper: https://www.semanticscholar.org/paper/6261f16ddd268168320c429396470b65928ec081

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In Epidemiology

Carl R. May

In General Health Professions

Citations in the corpus

Systematic review of smartphone-based passive sensing for health and wellbeing (2017, background): “Passive sensing can ease — or, minimally, not add to —“ work that is delegated to patients and their families ” [67], by facilitating or automating di ﬃ cult tasks such as self-monitoring or daily logging [68].”
Implementation, context and complexity (2016, background): “[58], for example, applies NPT to situations in the home and outside of formal healthcare organisations, where ‘contexts’ are not so much organisational as organising and are distributed across informal social networks [59, 60].”
2017 National Standards for Diabetes Self-Management Education and Support (2012, neutral): “health beliefs and attitudes, diabetes knowledge, diabetes self-management skills and behaviors, emotional response to diabetes, disease burden, ability, readiness to learn, literacy level (including health literacy and numeracy), physical limitations, family support, peer support (in person or via ”
Analysing the role of complexity in explaining the fortunes of technology programmes: empirical application of the NASSS framework (2018, methodology): “We drew in particular on published technology implementation frameworks and key theoretical work on diffusion of innovations [17, 18], technological entrepreneurship [6, 19], the patient experience of chronic illness [20], clinician resistance to technologies [21], the social processes of ‘normalisi”
Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies (2017, background): “But as May et al have pointed out in their burden of treatment theory, shifting the work of care from clinic to community places new demands on the sick (and hence raises ethical questions) [75].”
Understanding factors affecting patient and public engagement and recruitment to digital health interventions: a systematic review of qualitative studies (2016, positive): “Drawing on BOTT’s relational networks [38] to direct engagement with digital health we suggest that:”