Entete 3

Publications on multimorbidity January-April 2019


By Martin Fortin

Our search for papers on multimorbidity that were published during the period January-April 2019 has been completed. As in previous searches, we have prepared a PDF file that can be accessed following this link.

Probably, there are some publications that were not detected by our search strategy using the terms “multimorbidity”, “multi-morbidity” and the expression “multiple chronic diseases” in PubMed (https://www.ncbi.nlm.nih.gov/pubmed), but we are sure that most publications on the subject are included in the list.

All references are also included in our library. Feel free to share with anyone interested in multimorbidity.

Middle-aged men with multimorbidity at greatest risk of death

By Bhautesh Jani and Frances Mair

Our study published in BMC Medicine [1], found that multimorbidity is associated with a higher risk of death from cancer, vascular conditions and all causes of death – even after accounting for lifestyle or demographic factors. The effect of multiple long-term conditions (LTCs) on higher mortality risk was largest among men between 37-49 years.

The study used the UK Biobank cohort (approx. half million adults) and found that the type of LTC, as opposed to the number of LTC, may have an important role to play in understanding the relationship between multimorbidity and death.

This is the first study to examine the relationship of multimorbidity with cancer mortality and we have shown a dose-response relationship between number of LTCs and cancer mortality.

Younger participants, especially men, were observed to have a relatively higher risk of mortality with increasing number of LTCs, and that certain combinations of conditions were associated with a particularly higher risk of death. Going forward, further research is needed to study the impact and management of multimorbidity in middle aged adults, as they may be at higher risk of early death.

1. Jani BD, Hanlon P, Nicholl BI, et al. Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank cohort. BMC Med 2019;17(1):74. doi: 10.1186/s12916-019-1305-x

The measurement of multimorbidity

By Kathryn Nicholson
Answering an invitation to contribute with an article to a special issue of the journal Health Psychology, we wrote the article entitled “The measurement of multimorbidity” that was recently published [1]. The article was written with the purpose of providing a review of the literature published between 1974 and 2018 that have utilized measures for multimorbidity and to provide guidance on measures to consider when conducting a research study on multimorbidity. The article introduces the reader to the two main groups of measures of multimorbidity that can be distinguished. The first group of measures is constituted by a simple count from various lists of chronic conditions. The second group of measures introduces weighting for included chronic conditions thus creating a “weighted index” of multimorbidity. These two main groups are not mutually exclusive as the list of medical conditions in some weighted indexes can be used as a list of conditions without weighting. This classification does not include measures of multimorbidity which are not based on lists of medical conditions, such as the Cumulative Illness Rating Scale, which includes areas or domains that are grouped under body systems instead of medical conditions. The article shows the variety of existing measurements, highlighting their differences, to provide an overview of the possibilities that are available to a researcher intending to measure multimorbidity. Finally, the article outlines some guidelines for the choice of a measurement of multimorbidity for research studies. We hope that this review of the existing literature will help inform the careful use of these tools by researchers moving forward. In addition to this review, it is advised that readers attempt to keep updated on the ever-increasing multimorbidity literature.
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1. Nicholson K, Almirall J, Fortin M: The measurement of multimorbidity. Health Psychol 2019. Apr 25. doi: 10.1037/hea0000739. [Epub ahead of print]

Socio-economic inequalities in life expectancy of older adults with and without multimorbidity

By Madhavi Bajekal, on behalf of the UCL Multimorbidity Project Team
New paper by @ucl_dahr and colleagues [1]: https://doi.org/10.1093/ije/dyz052
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Using linked electronic health data for a cohort followed up from 2001 to 2010, we have been able to quantify socio-economic differences in the age of onset of multimorbidity (MM) and, with subsequent mortality, how much of remaining life after age 65 are years lived with and without multiple chronic diseases.
A seminal study by Barnett et al [2] reported a 10y gap in the cross-sectional prevalence of MM at younger ages between the most and least deprived populations in Scotland in 2007.  Our study shows that in England the difference in MM incidence was again about 10y between the most deprived (Q5) and the least deprived (Q1) groups in middle-age (Fig 3), with rates converging at successively older ages.  Health- and life expectancy measures are based on incidence rates (of diseases and of subsequent death); we modelled these to estimate and partition remaining life into years with and without MM.
At age 65, men spend 6.9y without MM and 9.9y with MM; and women, 7.6 y and 11.7y respectively. Overall, men and women spend about 60% of their remaining life in old age with two or more chronic diseases, although this proportion varies by up to 5 percentage points above and below between the two ends of the deprivation spectrum (Tables 2 and 3).
We show that the most deprived groups live, on average, fewer years in total than the least deprived groups, but spend almost the same number of years with MM. In terms of healthcare costs this implies that, although average lifetime resource-spend for both groups might be of a similar magnitude, it is shifted to younger ages for the most deprived groups. The evidence adds weight to the argument calling for a shift to the standard age-cost curve used in the national resource allocation formula to younger ages in deprived areas to reflect greater need earlier in the life course [3].
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1. Chan MS, van den Hout A, Pujades-Rodriguez M, Jones MM, Matthews FE, Jagger C, Raine R, Bajekal M: Socio-economic inequalities in life expectancy of older adults with and without multimorbidity: a record linkage study of 1.1 million people in England. Int J Epidemiol 2019.
2. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B: Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 2012, 380(9836):37–43.
3. Brilleman SL, Gravelle H, Hollinghurst S, Purdy S, Salisbury C, Windmeijer F: Keep it simple? Predicting primary health care costs with clinical morbidity measures. J Health Econ 2014, 35:109-122.

A multidisciplinary self-management intervention among patients with multimorbidity: Impact of socioeconomic factors

By Martin Fortin
The objective of this study was to analyze the effect of a multidisciplinary self-management intervention among patients with multimorbidity and the impact of socioeconomic factors on the results.
Participants of this study were multimorbid patients from of a pragmatic randomized trial evaluating an intervention that included patients (18 to 75 yrs.) from eight primary care practices in Quebec, Canada. The intervention included self-management support and patient-centered motivational approaches.
Self-management was evaluated using the Health Education Impact Questionnaire (heiQ) which measures eight different domains.
The effect of the intervention on the likelihood of an improvement in self-management was significant in six heiQ domains in the univariate analysis: Health-directed behavior, Emotional well-being, Self-monitoring and insight, Constructive attitudes and approaches, Skill and technique acquisition, and Health services navigation. After controlling for age and gender the results remained essentially the same.
After additional adjustments for family income, education and self-perceived financial status, the likelihood of an improvement was no longer significant in the domains Emotional well-being and Self-monitoring and insight.
It was concluded that the intervention produced significant improvements in multimorbid patients for most domains of self-management but socioeconomic factors had a minor impact on the results.
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The complete article can be accessed at the following link:

Improving patient-centred care for multimorbidity

By Chris Salisbury, University of Bristol, on behalf of the 3D trial team.
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Full report of the 3D study helps us interpret the findings
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The 3D approach was designed to improve care for patients with multimorbidity. Based on a patient-centred care approach, it promotes continuity of care, offers a comprehensive holistic review which focuses on problems that most matter to the patient, and seeks to reduce inappropriate polypharmacy. The reviews involve a six-monthly multi-disciplinary review from a nurse, pharmacist and GP, leading to a health plan with specific goals agreed between the patient and GP. The 3D model incorporates most of the strategies recommended in international guidelines on multimorbidity.
We conducted a large cluster randomised controlled trial comparing the 3D approach and usual care, and the main trial results were published in the Lancet in July 2018 [1]. We found that the 3D intervention was effective at improving patient centred care, but did not result in improvements in patient’s quality of life, health outcomes or polypharmacy.
How should we make sense of these counter-intuitive results? Are the current international guidelines misconceived?  Perhaps the 3D approach was the wrong intervention, perhaps it was not effectively implemented or not provided for the long enough to make a difference. Or maybe we chose the wrong outcome measures. Interestingly, the conclusion that the 3D approaches improves patient-centred care but not quality of life is consisent with most previous trials of interventions for multimorbidity.
The Lancet paper has generally been interpreted as reporting a negative trial. The full report of the 3D study has now been published [2], and provides a more rounded perspective on the findings. It includes a process evaluation based on interviews with patients and staff, along with direct observation in case-study practices to help us understand how the 3D approach was implemented and how it might be improved. The full report also includes an economic evaluation of cost-effectiveness.
Through the process evaluation we found that practices were strongly supportive of the principles underlying the 3D approach, but they found implementing it logistically difficult. Many patients in the trial did not receive the full ‘dose’ of the intervention. Only half of the patients received two 3D reviews over 15 months as intended, while three-quarters received at least one review. This incomplete implementation was related to the pressures that general practices in the UK currently face, which made introducing any kind of change very difficult. Trying to do so within the context of a trial made it even more difficult. Introducing a new way of working for a limited period for a sub-set of patients, within practices which had well-established systems for offering single-disease care designed to meet the requirements of the Quality and Outcomes Framework, meant that not everything worked as planned. For example, some practices offered 3D reviews as well as, rather than instead of, single-disease reviews. However, practices did identify ways in which the 3D model might be improved, for example by more selectively targeting patients with the most complex problems, more training for staff and tailoring the frequency of reviews according to patients’ needs.
The economic evaluation showed that the 3D intervention was associated with small improvements in quality-adjusted life years (QALYs) along with small increases in NHS costs. The cost per QALY was £18,499, just below the threshold of £20,000 commonly used to justify new interventions in the NHS. Therefore the economic case for introducing 3D is arguable, and could be justified given that it provided care in a way that patient’s preferred and which they felt met their needs.
In summary, the report describes the advantages and limitations of the 3D approach, and ways in which it might be improved. There doesn’t appear to be a simple magic bullet to improve care for multimorbidity and no model of care has yet been convincingly shown to be effective in randomised trials. Paradoxically, one key finding from the report is that the 3D approach would probably need to become normal practice and offered over several years before the benefits became apparent, but testing this hypothesis in an affordable randomised trial would almost certainly be impossible.
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This project was funded by the National Institute for Health Research Health Services and Delivery Research Programme (project number 12/130/15). The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the HS&DR Programme, NIHR, NHS or the Department of Health.
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Publications on multimorbidity September – December 2018

By Martin Fortin
Our search for papers on multimorbidity that were published during the period September – December 2018 has been completed. As in previous searches, we have prepared a PDF file that can be accessed following this link.
Probably, there are some publications that were not detected by our search strategy using the terms “multimorbidity”, “multi-morbidity” and the expression “multiple chronic diseases” in PubMed (https://www.ncbi.nlm.nih.gov/pubmed), but we are sure that most publications on the subject are included in the list.
All references are also included in our library. Feel free to share with anyone interested in multimorbidity.

Articles from a special edition of the Journal of Internal Medicine

By Martin Roland
Following an international symposium on multimorbidity held in Stockholm in 2018, the following papers have been published this month in a special edition of the Journal of Internal Medicine. They’re excellent reviews and worth a read.
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Calderón‐Larrañaga A & L. Fratiglioni L  Multimorbidity research at the crossroads: developing the scientific evidence for clinical practice and health policy  https://onlinelibrary.wiley.com/doi/full/10.1111/joim.12872
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Calderón‐Larrañaga A et al Multimorbidity and functional impairment–bidirectional interplay, synergistic effects and common pathways  https://onlinelibrary.wiley.com/doi/full/10.1111/joim.12843
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Muth C et al. Evidence supporting the best clinical management of patients with multimorbidity and polypharmacy: a systematic guideline review and expert consensus  https://onlinelibrary.wiley.com/doi/full/10.1111/joim.12842
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Valderas JM et al Quality of care assessment for people with multimorbidity  https://onlinelibrary.wiley.com/doi/full/10.1111/joim.12881

Joint workshop on multimorbidity in the UK and in low-and middle-income countries

By Martin Fortin
On 20 and 21 June 2018, the Academy of Medical Sciences (UK) organized a two-day workshop together with the Medical Research Council, the National Institute for Health Research, and Wellcome.
The primary objective of the workshop was to provide a platform to discuss key priorities for multimorbidity research, with the aim of identifying:
• Areas where research can have the most impact in addressing multimorbidity.
• Current barriers to performing and funding research, and ways in which they can be overcome.
• The methodological approaches needed to better enable multimorbidity research.
• The best mechanisms with which research funders can support research activity in this area.
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The report of this workshop is now available to download, along with the agenda and copies of the presentations at:

Publications on multimorbidity May – August 2018

By Martin Fortin
Our search for papers on multimorbidity that were published during the period May – Agust 2018 has been completed. As in previous searches, we have prepared a PDF file that can be accessed following this link.
Probably, there are some publications that were not detected by our search strategy using the terms “multimorbidity”, “multi-morbidity” and the expression “multiple chronic diseases” in PubMed (https://www.ncbi.nlm.nih.gov/pubmed), but we are sure that most publications on the subject are included in the list.
All references are also included in our library. Feel free to share with anyone interested in multimorbidity.