- Minimally disruptive medicine
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Minimally Disruptive Medicine[1] is an approach to patient care in chronic illness proposed by Carl R May, Victor Montori, and Frances Mair. In a 2009 article in the British Medical Journal[1] they argued that the burden of illness (the pathophysiological and psychosocial impact of disease on the sufferer) has its counterpart in the burden of treatment (the workload delegated to the patient by health professionals, which may include self care and self-monitoring, managing therapeutic regimens, organizing doctors’ visits, tests, and insurance). As medical responses to illness have become more sophisticated, the burden of treatment has grown, and includes increasingly complex techniques and health technologies (such as telecare) that must be routinely incorporated in everyday life by their users. Minimally Disruptive Medicine is an approach to designing patient care that seeks to consider the effects of treatment work, and in particular to prevent overburdening patients[2]. Overburdening leads, May. Montori and Mair argued, to structurally induced non-compliance with treatment, in which it becomes progressively more difficult for patients – especially older patients with multiple co-morbidities – to meet the demands that therapeutic regimens place upon them. Minimally Disruptive Medicine has a theoretical basis in Normalization Process Theory[3], which explains the processes by which treatment regimens and other ensembles of cognitive, behavioural and technical practices are routinely incorporated in everyday life[2][3].
REFERENCES
- ^ May C, Montori VM, Mair FS. We need minimally disruptive medicine. BMJ 2009;339:b2803
- ^ May C, Finch T. Implementation, embedding, and integration: an outline of Normalization Process Theory. Sociology 2009;43:535-54
- ^ May C, Mair FS, Finch T, MacFarlane A, Dowrick C, Treweek S, Rapley T, Ballini L, Ong BN, Rogers A, Murray E, Elwyn G, Legare F, Gunn J, Montori VM. Development of a theory of implementation and integration: Normalization Process Theory. Implementation Science 2009;4.
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