Measuring multimorbidity in research: Delphi consensus study

Ho, Iris; Azcoaga-Lorenzo, Amaya; Akbari, Ashley; Davies, Jim; Khunti, Kamlesh; Kadam, Umesh; Lyons, Ronan A.; McCowan, Colin; Mercer, Stewart W; Nirantharakumar, Krishnarajah; Staniszewska, Sophie; Guthrie, Bruce

doi:10.1136/bmjmed-2022-000247

Cited by 80 publications

(97 citation statements)

References 38 publications

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“…For every individual, the authors of the current study defined the presence of 80 LTCs (10 of which were mental health conditions), categorised into ICD-10 chapters (Supplementary Table S1). The 80 conditions were chosen because they featured in phenotyping algorithms in the HDR-UK Phenotype Library, 18 and/or were recommended by a recent Delphi consensus study 19 and deemed to be relevant by the clinical authors (the first, second, and final authors). Codes used to identify individuals with each condition were mutually exclusive, therefore double counting of conditions was not possible.…”

Section: Methodsmentioning

confidence: 99%

Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis

MacRae

Mercer²,

Henderson³

et al. 2022

Br J Gen Pract

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Background: Multimorbidity poses major challenges to healthcare systems worldwide. Definitions with cut-offs of more than ≥2 long-term conditions (LTCs) might better capture populations with complexity but are not standardised. Aim: This study examined variation in prevalence using different definitions of multimorbidity. Design and setting: Cross-sectional study of 1168620 people in England. Methods: Comparison of multimorbidity prevalence using four definitions: MM2+ (≥2 LTCs), MM3+ (≥3 LTCs), MM3+ from 3+ (≥3 LTCs from ≥3 ICD-10 chapters), and mental-physical MM (≥2 LTCs where ≥1 mental and ≥1 physical). Logistic regression was used to examine patient characteristics associated with multimorbidity under all four definitions. Results: MM2+ was most common (40.4%) followed by MM3+ (27.5%), MM3+ from 3+ (22.6%), and mental-physical MM (18.9%). MM2+, MM3+, and MM3+ from 3+ were strongly associated with oldest age (aOR 58.09 [56.13-60.14]), aOR 77.69 [75.33-80.12]), and aOR 102.06 [98.61-105.65] respectively), but mental-physical MM was much less strongly associated (aOR 4.32 [4.21-4.43]). People in the most deprived decile had equivalent rates of multimorbidity at a younger age than those in the least deprived. This was most marked in mental-physical MM at 40-45 years younger, followed by MM2+ at 15-20 years, and MM3+ and MM3+ from 3+ at 10-15 years. Women had higher prevalence of multimorbidity under all definitions, which was most marked for mental-physical MM. Conclusion: Estimated prevalence of multimorbidity depends on the definition used, and associations with age, sex, and socioeconomic position vary between definitions. Applicable multimorbidity research requires consistency of definitions across studies.

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Section: Methodsmentioning

confidence: 99%

Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis

MacRae

Mercer²,

Henderson³

et al. 2022

Br J Gen Pract

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“…In this study, consensus was reached among professionals and people with chronic conditions that multimorbidity should be defined as two or more chronic conditions. Furthermore, consensus was also reached on a list of conditions to always include and usually include in multimorbidity measures 63 .…”

Section: Epidemiologymentioning

confidence: 99%

Multimorbidity

Skou

Mair

Fortin

et al. 2022

Nat Rev Dis Primers

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Interest in multimorbidity -commonly defined as the co-occurrence of at least two chronic conditions in the same individual 1 -has increased in the past few years owing to its substantial effect on the individual and the individual's family, as well as on health systems and on society, particularly in resource-poor settings 2-4 . Multimorbidity is distinct from the related concept of comorbidity, which refers to the combined effects of additional conditions in relation to the index condition in an individual [5][6][7][8] . By contrast, care for multimorbidity is patient-centred and does not routinely give priority to any single condition, although in clinical care, patients and clinicians will usually focus on the most pressing problems that the patient is experiencing.People with multimorbidity are more likely to die prematurely, be admitted to hospital and have an increased length of stay than people with a single chronic condition 9,10 . Multimorbidity is also associated with poorer function and health-related quality of life (HRQOL), depression and intake of multiple drugs (polypharmacy) and greater socioeconomic costs [11][12][13][14][15][16][17][18] . Most health care is designed to treat individual conditions rather than providing comprehensive, person-centred care 2,19,20 , which often leads to fragmented and sometimes contradictory care for people with multimorbidity and increases their treatment burden 21 Moreover, treating one condition at a time is inefficient and unsatisfactory for both people with multimorbidity and their health-care providers [22][23][24] .Multimorbidity is increasingly common owing to changes in lifestyle risk factors, notably physical inactivity and obesity, and population ageing that in part reflects improvements in survival from acute and chronic conditions 2,19,25,26 . Multimorbidity is associated with socioeconomic status and age 3,19,25,27 . However, although age is the strongest driver of multimorbidity, in absolute numbers, more people <65 years of age have multimorbidity than people ≥65 years of age, partly because more people in the general population are in that age group. Moreover, this emphasizes that multimorbidity is not just a feature of ageing 19,26 .Multimorbidity is further complicated in low-income and middle-income countries (LMICs) by the overlap of compounding factors, including adverse environmental and early life stressors linked to poverty, limited social infrastructure and poorer family coping mechanisms, that translate into chronic diseases occurring at earlier ages [28][29][30][31] . LMICs also have a higher prevalence of multimorbidity-related financial burden 32,33 and have weaknesses in health systems including a greater focus Treatment burdenThe workload associated with managing treatments and health-care recommendations and the impact of this on an individual and their supporters.

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“…At a basic level, it would certainly be beneficial to differentiate between cardiovascular multimorbidity and non-cardiovascular multimorbidity as proposed by Déruaz-Luyet et al ( 22 ). A recent Delphi-consensus study also proposed to use weighted measures of multimorbidity when focusing on risk adjustment ( 6 ).…”

Section: Discussionmentioning

confidence: 99%

“…The World Health Organization defines multimorbidity as an association of two or more diseases that can impact a person's health status. Since many people consider this definition insufficient to summarize multimorbidity, numerous definitions can be found in the literature (4)(5)(6). Cardiovascular diseases and metabolic diseases, such as diabetes mellitus or obesity, are among the most represented health issues in patients with multimorbidity (7,8).…”

Section: Introductionmentioning

confidence: 99%

Multimorbidity and statin prescription for primary prevention of cardiovascular diseases: A cross-sectional study in general practice in France

et al. 2023

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BackgroundStatins are a first line, evidence-based yet underprescribed treatment for cardiovascular primary prevention. In primary care settings, multimorbidity is a complex situation which makes it difficult to apply prevention guidelines.AimTo assess the associations between multimorbidity and prescription of statins in accordance with the 2016 ESC recommendations (“appropriate prescription”), and to identify the factors and conditions associated with these prescriptions.Design and settingCross-sectional prospective study in the French region of Rhône-Alpes among 40 general practitioners and their patients.MethodsWe examined the association between appropriate statin prescription and several patient characteristics, including multimorbidity, using multivariate logistic regression models.ResultsBetween August 2017 and February 2019, 327 patients were included in the study. Seventy-four (22.6%) were on statin medication and 199 (60.9%) exhibited multimorbidity, defined as ≥2 diseases. Only 22.5% of eligible patients were prescribed statins for primary prevention. Diabetes was most strongly associated with appropriate statin prescription (aOR 8.10, CI 95: 3.81–17.80). Multimorbidity was not associated with appropriate statin prescription (aOR 1.31, CI 95: 0.54–3.26), except in the presence of diabetes which defined diabetic multimorbidity (aOR 10.46, CI 95: 4.87–23.35). Conversely, non-diabetic multimorbidity was associated with lower odds of being appropriately prescribed a statin (aOR 0.26, CI 95: 0.12–0.56).ConclusionMultimorbidity, in itself, does not seem to be a determinant factor for appropriate statin prescription. The latter appears to be determined by a patient’s type of multimorbidity, especially the presence or not of diabetes. Differentiating between diabetic and non-diabetic multimorbidity may be a pragmatic way for GPs to improve primary prevention in a patient-centered and shared decision-making approach.

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Measuring multimorbidity in research: Delphi consensus study

Cited by 80 publications

References 38 publications

Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis

Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis

Multimorbidity

Multimorbidity and statin prescription for primary prevention of cardiovascular diseases: A cross-sectional study in general practice in France

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