Multimorbidity: The need for a consensus on its operational definition

Global population aging and the ever-rising incidence of non-communicable disease has led to an upward epidemiological trend of multimorbidity in the past two decades. Defined as the presence of more than one chronic condition, a systematic review showed that the overall global prevalence of multimorbidity among adults in community settings was 37.2%, with the figure rising to over 50% among adults aged 60 or over (Chowdhury et al., 2023). Among countries worldwide, the population in South America is most affected, followed by those in North America, Europe and Asia (Chowdhury et al., 2023). Multimorbidity is highly undesirable because the negative impact of each contributing morbidity is multiplicative rather than additive on one's well-being (Skou et al., 2022). Substantial evidence indicates that multimorbidity was associated with increased risk of poorer quality of life (Makovski et al., 2019), more functional decline (Pengpid et al., 2022), greater depression (Read et al., 2017), higher rate of hospitalization (Rodrigues et al., 2022) and even mortality (Nunes et al., 2016). The financial implications to the society and healthcare system are tremendous (Soley-Bori et al., 2021). Therefore, to ensure person-centred and holistic care, nurses play a key role to pioneer strategies for effective prevention, early identification and prompt management of multimorbidity. Despite the growing research in multimorbidity, there is a lack of consensus on how to operationally define the condition. Even though the Academy of Medical Sciences define multimorbidity as coexistence of two or more chronic conditions (The Academy of Medical Sciences, 2018), previous research on this topic adopted varied operational definitions in terms of the cut-off number of chronic conditions, the number and types of chronic diseases being included, and the method of aggregating the chronic condition. Such variations would cause great confusion in interpreting the global burden resulting from multimorbidity, the associated negative health impact and the predictive risk profile. All of which would hinder effective health resource allocation and nursing care model development to cope with this ever-rising health challenge. The overall aim of this editorial is to discuss the debate about the operational definition of multimorbidity, so as to derive insights to advance nursing research and the inter-professional management of multimorbidity. Multimorbidity is different from the concept of comorbidity, which refers to the combined effects of additional conditions in relation to the index condition in an individual (Harrison et al., 2021). Although some guidelines and professional consensus have provided definitions of multimorbidity, there is no consensus in the operational definition of multimorbidity. Subsequently, the World Health Organization (WHO) in 2008 defined multimorbidity as the coexistence of two or more chronic conditions in the same individual (World Health Organization, 2008). This definition was also adopted by the National Institute for Health and Care Excellence (NICE; Farmer et al., 2016), the Academy of Medical Sciences (The Academy of Medical Sciences, 2018) and a consensus among Chinese experts (Tang et al., 2022). However, the European General Practice Research Network defined multimorbidity more broadly as 'any combination of chronic disease with at least one other disease (acute or chronic), biopsychosocial factor (associated or not), or somatic risk factor' (Le Reste et al., 2013). Despite the appearance of a consensus in how different professional bodies define multimorbidity, a large-scale systematic review of 566 studies published more recently identified the great variations in the operational definition of this condition in the research context (Ho et al., 2021). Firstly, there is no agreement on the cut-off number of chronic conditions to define multimorbidity. The review found that 47.3% (n = 268) of studies defined multimorbidity as the presence of two or more chronic conditions, while 4.9% (n = 28) and 0.7% (n = 4) defined multimorbidity as the presence of three or more and five or more chronic conditions, respectively. Secondly, there is a lack of consensus regarding the types of diseases to be included in multimorbidity. Among the reviewed studies, the types of chronic conditions included ranged from 3 to 285, with 1 study only included two chronic conditions as the research focused on a very specific type of multimorbidity. However, nearly 80% of studies did not precisely capture such conditions but just categorized them into cardiovascular, metabolic and endocrine, respiratory, musculoskeletal or mental health conditions. No attention was paid to the great heterogeneity in the candidate diseases being represented by these chronic disease categories which may greatly affect the findings on the prognostic impact of multimorbidity. A closer scrutiny of these studies also indicated that more than half of studies only include eight more prevalent chronic conditions in defining multimorbidity, including diabetes, stroke, cancer, chronic obstructive pulmonary disease, hypertension, coronary heart disease, chronic kidney disease and heart failure. On the other hand, mental health conditions are under-represented as disease candidates in measuring multimorbidity. Some other conditions including chronic infections, haematological conditions, ophthalmic and oto-rhinnological conditions, dermatological disease, oral and congenital pathology were even not considered as the contributing candidate to multimorbidity. Thirdly, there is no consensus on the method of aggregating chronic conditions. Whereas most of the studies simply count the number of chronic conditions, some others used algorithms to assign weighting to the chronic condition according to the pathological risk or treatment-related burden (e.g. medication-based indices) to better address the research objectives. As the included conditions are heterogeneous in terms of pathological progression, disease burden on patients and healthcare systems and treatment-related burden, most of the measurement models have suppressed such important information in considering the impact of multimorbidity. The lack of consensus on the operational definition of multimorbidity undermines the comparability of findings across studies and makes it difficult to draw conclusive insights on its evolving pattern, prognostic impact and the boarder global burden. In views of the urge to develop sensitive preventive and management care for multimorbidity, it is imperative to identify a standardized approach to operationalize multimorbidity. Referring to the current state, the limitations of the operational definition of multimorbidity rest on the inadequacy in the representativeness of the attributing chronic conditions and comprehensiveness to capture the multimorbidity severity. Considering the representativeness of the attributing chronic conditions, a standardized list of chronic conditions in measuring multimorbidity is important to control the bias in identifying the burden and prognostic impact of multimorbidity. In defining the attributing candidates, considerations should be given to the chronicity of the condition, the pathogenic impact on triggering other chronic disease, the treatment burden, the prognostic impact on a wider scope of patient-reported outcomes, functional status, healthcare system and mortality. In formulating this standardized list of the chronic conditions, a critical analysis of the studies which identified the burden of a wide range of chronic conditions from the pathophysiological, functional and economical perspective is needed. With the advancement of big data analytics in the past decade (Shi, 2022), it is also possible to derive the insights on defining the list of attributing chronic conditions for multimorbidity from the available national and international healthcare datasets. Considering the severity of multimorbidity, it is an important dimension of multimorbidity in the context of both research and practice. To our knowledge, there are only a few algorithms to capture multimorbidity severity in a two-dimensional approach considering the number of chronic conditions and respective prognostic risk or treatment burden. This approach of measuring multimorbidity should be adopted as good practice in order to better reflect the impact of this complex pathological condition. Yet, further advancement of the algorithm to capture multimorbidity is imperative. First, a more integrative approach is needed to define the weight to be assigned to each chronic condition. The weighting should be carefully operationalized to capture the 'meaningful' disease impact. The debate on whether different systems of weighting should be developed depending on the purpose of use or a standardized weighting system which captures a consensual impact of various chronic conditions is needed to advance the measurement of multimorbidity severity. In fact, patient-centred factors may also be considered as many chronic diseases such as diabetes, cardiac arrythmia and dementia and even cancer may have somehow different pathophysiological manifestation, treatment burden and impact on quality of life. With the increase in the recognition of how social determinants shape the prognostic impact of chronic disease (Istilli et al., 2020), it is equally important to include the social context which influences the disease trajectory when capturing multimorbidity severity. Multimorbidity presents a significant challenge to healthcare systems and families worldwide, resulting in significant financial and healthcare burdens. To address this challenge, a consensus operational definition of multimorbidity is necessary. The current operational definition of multimorbidity has certain limitations, including the inadequacy in the representativeness of the attributing chronic conditions and the comprehensiveness in capturing the severity of multimorbidity. It is imperative to develop a standardized list of chronic conditions for measuring multimorbidity. Additionally, it is necessary to adopt a more integrative approach to determine the weight assigned to each chronic condition, and to consider patient-centred factors and the social context to capture the severity of multimorbidity. None.