Better guidelines for better care: accounting for multimorbidity in clinical guidelines - structured examination of exemplar guidelines and health economic modelling

Background: Multimorbidity is common but most clinical guidelines focus on single diseases. Aim: To test the feasibility of new approaches to developing single-disease guidelines to better account for multimorbidity. Design: Literature-based and economic modelling project focused on areas where mult...

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Main Authors: Bruce Guthrie (Author), Alexander Thompson (Author), Siobhan Dumbreck (Author), Angela Flynn (Author), Phil Alderson (Author), Moray Nairn (Author), Shaun Treweek (Author), Katherine Payne (Author)
Format: Book
Published: National Institute for Health Research, 2017-04-01T00:00:00Z.
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100 1 0 |a Bruce Guthrie  |e author 
700 1 0 |a Alexander Thompson  |e author 
700 1 0 |a Siobhan Dumbreck  |e author 
700 1 0 |a Angela Flynn  |e author 
700 1 0 |a Phil Alderson  |e author 
700 1 0 |a Moray Nairn  |e author 
700 1 0 |a Shaun Treweek  |e author 
700 1 0 |a Katherine Payne  |e author 
245 0 0 |a Better guidelines for better care: accounting for multimorbidity in clinical guidelines - structured examination of exemplar guidelines and health economic modelling 
260 |b National Institute for Health Research,   |c 2017-04-01T00:00:00Z. 
500 |a 2050-4349 
500 |a 2050-4357 
500 |a 10.3310/hsdr05160 
520 |a Background: Multimorbidity is common but most clinical guidelines focus on single diseases. Aim: To test the feasibility of new approaches to developing single-disease guidelines to better account for multimorbidity. Design: Literature-based and economic modelling project focused on areas where multimorbidity makes guideline application problematic. Methods: (1) Examination of accounting for multimorbidity in three exemplar National Institute for Health and Care Excellence guidelines (type 2 diabetes, depression, heart failure); (2) examination of the applicability of evidence in multimorbidity for the exemplar conditions; (3) exploration of methods for comparing absolute benefit of treatment; (4) incorporation of treatment pay-off time and competing risk of death in an exemplar economic model for long-term preventative treatments with slowly accruing benefit; and (5) development of a discrete event simulation model-based cost-effectiveness analysis for people with both depression and coronary heart disease. Results: (1) Comorbidity was rarely accounted for in the clinical research questions that framed the development of the exemplar guidelines, and was rarely accounted for in treatment recommendations. Drug-disease interactions were common only for comorbid chronic kidney disease, but potentially serious drug-drug interactions between recommended drugs were common and rarely accounted for in guidelines. (2) For all three conditions, the trials underpinning treatment recommendations largely excluded older, more comorbid and more coprescribed patients. The implications of low applicability varied by condition, with type 2 diabetes having large differences in comorbidity, whereas potentially serious drug-drug interactions were more important for depression. (3) Comparing absolute benefit of treatments for different conditions was shown to be technically feasible, but only if guideline developers are willing to make a number of significant assumptions. (4) The lifetime absolute benefit of statins for primary prevention is highly sensitive to the presence of both the direct treatment disutility of taking a daily tablet and competing risk of death. (5) It was feasible to use a discrete event simulation-based model to represent the relevant care pathways to estimate the relative cost-effectiveness of pharmacological treatments of major depressive disorder in primary care for patients who are also likely to go on and receive treatment for coronary heart disease but the analysis was reliant on eliciting some parameter values from experts, which increases the inherent uncertainty in the results. The key limitation was that real-life use in guideline development was not examined. Conclusions: Guideline developers could feasibly (1) use epidemiological data characterising the guideline population to inform consideration of applicability and interactions; (2) systematically compare the absolute benefit of long-term preventative treatments to inform decision-making in people with multimorbidity and high treatment burden; and (3) modify the output from economic models used in guideline development to examine time to benefit in terms of the pay-off time and varying competing risk of death from other conditions. Future work: Further research is needed to optimise presentation of comparative absolute benefit information to clinicians and patients, to evaluate the use of epidemiological and time-to-benefit data in guideline development, to better quantify direct treatment disutility and to better quantify benefit and harm in people with multimorbidity. Funding: The National Institute for Health Research Health Services and Delivery Research programme. 
546 |a EN 
690 |a multimorbidity 
690 |a comorbidity 
690 |a guidelines 
690 |a quality of health-care 
690 |a models economic 
690 |a cost-effectiveness analysis 
690 |a drug interactions 
690 |a depression 
690 |a diabetes mellitus type 2 
690 |a heart failure 
690 |a Public aspects of medicine 
690 |a RA1-1270 
690 |a Medicine (General) 
690 |a R5-920 
655 7 |a article  |2 local 
786 0 |n Health Services and Delivery Research, Vol 5, Iss 16 (2017) 
787 0 |n https://doi.org/10.3310/hsdr05160 
787 0 |n https://doaj.org/toc/2050-4349 
787 0 |n https://doaj.org/toc/2050-4357 
856 4 1 |u https://doaj.org/article/8b186f1f4bc848caaf25c3d9fecaa09b  |z Connect to this object online.