Entete 3

Monthly Archives: May 2019

Multimorbidity methods

The measurement of multimorbidity

May 17, 2019 – 8:36 am

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.
.
1. Nicholson K, Almirall J, Fortin M: The measurement of multimorbidity. Health Psychol 2019. Apr 25. doi: 10.1037/hea0000739. [Epub ahead of print]
Comments (2)
Epidemiology and outcomes research

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

May 3, 2019 – 8:42 am

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
.
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].
.
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.
Comment (0)