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The multimorbidity epidemic: challenges for real-world research

Published online by Cambridge University Press:  06 March 2020

Muna Adan*
Pharmacoepidemiologist, Department of Health Sciences, University of Leicester, Leicester, UK
Clare Gillies
Lecturer in Medical Statistics, Department of Health Sciences, University of Leicester, Leicester, UK
Freya Tyrer
Researcher in Epidemiology, Department of Health Sciences, University of Leicester, Leicester, UK
Kamlesh Khunti
Professor of Primary Care Diabetes and Vascular Medicine, University of Leicester, Leicester, UK Director, Leicester Diabetes Research Centre, Leicester, UK
Author for correspondence: Muna Adan, Department of Health Sciences, Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, Gwendolyn Road, LeicesterLE5 4PW, UK. E-mail:
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Multimorbidity, defined as the co-occurrence of two or more long-term medical conditions in the same individual, continues to be a major health and social care challenge. Evidence shows that in England, multimorbidity accounts for 50% of general practice (GP) appointments, 64% of outpatient appointments, 70% of inpatient bed days and 70% of the total healthcare expenditure (Department of Health, 2012). From an individual perspective, multimorbidity reduces quality of life, physical functioning and life expectancy and increases the risk of psychological distress and the risk of adverse drug events from polypharmacy (Calderón-Larrañaga et al., Reference Calderón-larrañaga, Poblador-Plou, González-Rubio, Gimeno-Feliu, Abad-Díez and Prados-Torres2012; Brettschneider et al., Reference Brettschneider, Leicht, Bickel, Dahlhaus, Fuchs, Gensichen, Maier, Riedel-Heller, Schäfer, Schön, Weyerer, Wiese, van den Bussche, Scherer and König2013; DuGoff et al., Reference DuGoff, Canudas-Romo, Buttorff, Bruce and Gerard2014).

The prevalence of multimorbidity is known to be increasing in the general population and is more common in the elderly population, in females and in individuals from low socioeconomic status (Barnett et al., Reference Barnett, Mercer, Norbury, Watt, Wyke and Guthrie2012). Published prevalence studies have generally been few and have varied greatly in methodology. In observational studies, multiple morbidities have typically been determined using either health-based questionnaires/surveys or, more frequently, using electronic health records with the application of disease-specific medical codes. The main peril with the use of electronic health records is that there is no single standardized ‘correct’ code list that has been consistently used to ascertain any given morbidity and that a standard method of measuring multimorbidity does not exist (Barnett et al., Reference Barnett, Mercer, Norbury, Watt, Wyke and Guthrie2012; Dhalwani et al., Reference Dhalwani, Zaccardi, O’Donovan, Carter, Hamer, Yates, Davies and Khunti2017). The codes, therefore, remain subjective and at the discretion of the researcher and clinical team involved in a study, meaning that they differ from one study to another and, inadvertently, affect the derived prevalence rates. In addition, multimorbidity is often defined in light of the number of conditions with little account of disease severity. Some morbidities are associated with worse disease outcomes than others, and certain clusters of morbidities occurring together may present more than an additive effect on future risk of complications or death (Dhalwani et al., Reference Dhalwani, O’Donovan, Zaccardi, Hamer, Yates, Davies and Khunti2016; Reference Dhalwani, Zaccardi, O’Donovan, Carter, Hamer, Yates, Davies and Khunti2017).

Patients with multiple long-term morbidities have traditionally been managed interchangeably between primary and secondary care, with diagnosis and treatment often instigated in secondary care, and patients’ follow-up conducted in primary care. However, over time and with the publication of a sequence of healthcare policies related to the management of long-term conditions, responsibility for chronic morbidities has increasingly shifted to primary care (Department of Health, 2006; 2008; Lester and Campbell, Reference Lester and Campbell2010). Conversely, this presents two immediate key obstacles. First, although as it currently stands, the GP contract in the UK sets consultation duration at 10 min, irrespective of the patient’s clinical profile, the national consultation average time has been estimated as being 8.86 min (Hobbs et al., Reference Hobbs, Bankhead, Mukhtar, Stevens, Perera-Salazar, Holt and Salisbury2016). Research conducted in England has highlighted that consultation times are compromised by the number of patients’ co-existing long-term conditions, showing a linear relationship of an average of 2 min for each extra problem (Salisbury et al., Reference Salisbury, Procter, Stewart, Bowen, Purdey, Ridd, Valderas, Blakeman and Reeves2013). Therefore, it seems apparent that individuals with a greater number of long-term conditions need longer consultation times to cover the scope of care of each of the presenting complaints (inclusive of any therapeutic management), which could place an undue strain on general practitioners’ workload and resource use.

Secondly, the evidence base for delivering services for patients with multiple chronic long-term conditions in primary care is relatively sparse. A large systematic review identified only 10 studies that evaluated clinical interventions for improving outcomes in patients with multimorbidity. The review concluded that the evidence was limited, with many studies focusing on the effects of multimorbidity on patients and the healthcare system, as opposed to assessing interventions (Smith et al., Reference Smith, Soubhi, Fortin, Hudon and O’Dowd2012). Furthermore, despite the inception of several National Service Frameworks [of which the Quality Outcomes Framework is key], which have outlined the standards of primary care for specific numbers of long-term conditions, the management frameworks remain predominantly focused on ‘single-disease’ guidelines. This may limit the applicability of the recommendations to patients with multiple co-existing chronic conditions.

In addition, the use of multiple ‘single-disease’ guidelines could, unwittingly, increase unwarranted drug interactions, drug–disease interactions and drug–food interactions. For example, consider the clinical management of elderly patients with several co-existing chronic conditions such as osteoporosis, diabetes, hypertension, chronic obstructive pulmonary disorder and osteoarthritis. For patients to be compliant with all of the management recommendations from relevant guidelines, patients’ therapeutic and nontherapeutic treatment would consist of 12 pharmacological and 14 nonpharmacological regimens. Individually, this may seem rational and evidence-based, but the sum recommendation is not (Zulman et al., Reference Zulman, Asch, Martins, Kerr, Hoffman and Goldstein2014). In light of this, the National Institute for Health and Care Excellence recently published recommendations on the assessment and management of patients with multimorbidity (The National Institute for Health and Care Excellence, 2016). However, given the dearth of research in this area of care, the recommendation remains markedly generic.

For example, the guideline has a general introduction and discussion on the importance of tailoring treatment and management to patients’ needs and preferences; however, there is little practical guidance on what this specifically entails or looks like. In addition, there is an emphasis on involving patients in the management decision-making process to ensure adherence of treatment; however, given the complex context of treatment-combinations, risks and benefit is not accounted for in the guidance nor is there a discussion on issues related to treatment failures.

It is apparent that a more integrated care response may be needed for people with multimorbidity. The concept, broadly defined and described in the literature, refers to an integration of interdisciplinary care across specializations that is incorporated into patients’ routine primary care with shared decision-making that results in a single combined long-term treatment plan adapted to address patients (complex) multitude of health problem (Trivedi, Reference Trivedi2017; Rijken et al., Reference Rijken, Hujala, van Ginneken, Melchiorre, Groenewegen and Schellevis2018). The care builds in different working dimensions such as the type of integration, the extent of services involved and the level of integration needed.

It has further been argued that service users’ needs should be at the center of integrated care, under the rationale that patients with higher levels of needs as measured by degree of instability, chronicity of the condition, duality and complexity of treatments, and the general impact of the condition(s) would require a more comprehensive integrated health and, perhaps, social care approach than patients with lower levels of health needs (Rijken et al., Reference Rijken, Hujala, van Ginneken, Melchiorre, Groenewegen and Schellevis2018). Currently, at the service delivery level, the model that closely resembles the theoretical aspects of integrated care in practice is ‘case management’. This involves the identification of ‘at risk’ patients (typically defined in terms of at risk of hospital admission), assessment of their health needs and organizing and coordinating care between different healthcare professionals. However, although its delivery has been encouraged in the recent modifications to the National Health Service (NHS) (five-year framework) GP contract, its provision is purported to vary across the country and details of its practical application, particularly in patients with higher needs remain unclear (NHS England and British Medical Association, 2019).

NHS England’s ‘Long Term Plan’ report has outlined a pressing need to reshape the current delivery of care to improve national health outcomes (NHS England, 2019). We emphasize the importance of the healthcare system’s inclusion of a more holistic multidisciplinary model for patients with multimorbidity and further research to evaluate the outcomes.


Barnett, K, Mercer, SW, Norbury, M, Watt, G, Wyke, S and Guthrie, B (2012) Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 380, 3743.CrossRefGoogle ScholarPubMed
Brettschneider, C, Leicht, H, Bickel, H, Dahlhaus, A, Fuchs, A, Gensichen, J, Maier, W, Riedel-Heller, S, Schäfer, I, Schön, G, Weyerer, S, Wiese, B, van den Bussche, H, Scherer, M and König, HH (2013) MultiCare Study Group. Relative impact of multimorbid chronic conditions on health-related quality of life: results from the MultiCare Cohort Study. PLoS One 8, e66742.CrossRefGoogle Scholar
Calderón-larrañaga, A, Poblador-Plou, B, González-Rubio, F, Gimeno-Feliu, LA, Abad-Díez, JM and Prados-Torres, A (2012) Multimorbidity, polypharmacy, referrals, and adverse drug events: are we doing things well? British Journal of General Practice 62, 821926.CrossRefGoogle ScholarPubMed
Department of Health (2006) Health reform in England: update and commissioning framework. London: Department of Health.Google Scholar
Department of Health (2008) High Quality Care for All: NHS next stage review final report. London: Department of Health.Google Scholar
Department of Health (2012) Long-term conditions compendium of information: third edition. London: Department of Health.Google Scholar
Dhalwani, NN, O’Donovan, G, Zaccardi, F, Hamer, M, Yates, T, Davies, M and Khunti, K (2016) Long terms trends of multimorbidity and association with physical activity in older English population. International Journal of Behavioral Nutrition and Physical Activity 13, 8.CrossRefGoogle ScholarPubMed
Dhalwani, NN, Zaccardi, F, O’Donovan, G, Carter, P, Hamer, M, Yates, T, Davies, M and Khunti, K (2017) Association between lifestyle factors and the incidence of multimorbidity in an older English population. Journals of Gerontology 72, 528534.Google Scholar
DuGoff, EH, Canudas-Romo, V, Buttorff, C, Bruce, L and Gerard, FA (2014) Multiple chronic conditions and life expectancy: a life table analysis. Medical Care 52, 688694.CrossRefGoogle ScholarPubMed
Hobbs, FD, Bankhead, C, Mukhtar, T, Stevens, S, Perera-Salazar, R, Holt, T and Salisbury, C (2016) Workload in UK primary care: a retrospective analysis of 100 million consultations in England, 2007–14. Lancet 387, 23232330.CrossRefGoogle Scholar
Lester, H and Campbell, S (2010) Developing Quality and Outcomes Framework (QOF) indicators and the concept of ‘QOFability’. Quality of Primary Care 18, 103109.Google Scholar
NHS England (2019) The NHS Long Term Plan. London: NHS England.Google Scholar
NHS England and British Medical Association (2019) Investment and evolution: a five-year framework for GP contract reform to implement The NHS Long Term Plan. London: NHS England.Google Scholar
Rijken, M, Hujala, A, van Ginneken, E, Melchiorre, MG, Groenewegen, P and Schellevis, F (2018) Managing multimorbidity: profiles of integrated care approaches targeting people with multiple chronic conditions in Europe. Health Policy. Special issue: Integrated care for people living with multimorbidity 122, 4452.CrossRefGoogle Scholar
Salisbury, C, Procter, S, Stewart, K, Bowen, L, Purdey, S, Ridd, M, Valderas, J, Blakeman, T and Reeves, D (2013) The content of general practice consultations: cross-sectional study based on video recordings. British Journal of General Practice 63, e751e759.CrossRefGoogle ScholarPubMed
Smith, SM, Soubhi, H, Fortin, M, Hudon, C and O’Dowd, T (2012) Interventions for improving outcomes in patients with multimorbidity in primary care and community settings. Cochrane Database of Systematic Reviews CD006560.CrossRefGoogle ScholarPubMed
The National Institute for Health and Care Excellence (2016) Multimorbidity: clinical assessment and management. London: The National Institute for Health and Care Excellence.Google Scholar
Trivedi, D. (2017) Cochrane Review Summary: interventions for improving outcomes in patients with multimorbidity in primary care and community settings. Primary Health Care Research & Development 18, 109111.CrossRefGoogle ScholarPubMed
Zulman, DM, Asch, SM, Martins, SB, Kerr, EA, Hoffman, BB and Goldstein, MK (2014) Quality of care for patients with multiple chronic conditions: the role of comorbidity interrelatedness. Journal of General Internal Medicine 29, 529537.CrossRefGoogle ScholarPubMed