Identifying multimorbidity clusters with the highest primary care use: 15 years of evidence from a multi-ethnic metropolitan population.
TL;DR: In this paper, the authors assess the association between multimorbidity clusters and primary care consultations over time, using a retrospective longitudinal (panel) study design, using data from 826 166 patients registered at GP practices in London between 2005 and 2020.
Abstract: Background People with multimorbidity have complex healthcare needs. Some co-occurring diseases interact with each other to a larger extent than others and may have a different impact on primary care use. Aim To assess the association between multimorbidity clusters and primary care consultations over time. Design and setting A retrospective longitudinal (panel) study design was used. Data comprised electronic primary care health records of 826 166 patients registered at GP practices in an ethnically diverse, urban setting in London between 2005 and 2020. Method Primary care consultation rates were modelled using generalised estimating equations. Key controls included the total number of long-term conditions, five multimorbidity clusters, and their interaction effects, ethnic group, and polypharmacy (proxy for disease severity). Models were also calibrated by consultation type and ethnic group. Results Individuals with multimorbidity used two to three times more primary care services than those without multimorbidity (incidence rate ratio 2.30, 95% confidence interval = 2.29 to 2.32). Patients in the alcohol dependence, substance dependence, and HIV cluster (Dependence+) had the highest rate of increase in primary care consultations as additional long-term conditions accumulated, followed by the mental health cluster (anxiety and depression). Differences by ethnic group were observed, with the largest impact in the chronic liver disease and viral hepatitis cluster for individuals of Black or Asian ethnicity. Conclusion This study identified multimorbidity clusters with the highest primary care demand over time as additional long-term conditions developed, differentiating by consultation type and ethnicity. Targeting clinical practice to prevent multimorbidity progression for these groups may lessen future pressures on primary care demand by improving health outcomes.
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TL;DR: A retrospective cohort analysis based on hospital discharge records of about 5.0 million individuals of all ages from 2015 to 2019 in a megacity in southwest China identified specific differences in the co-occurrence of chronic diagnoses by sex and age, which could help in the design of clinical interventions for inpatient multimorbidity.
Abstract: Background Multimorbidity represents a global health challenge, which requires a more global understanding of multimorbidity patterns and trends. However, the majority of studies completed to date have often relied on self-reported conditions, and a simultaneous assessment of the entire spectrum of chronic disease co-occurrence, especially in developing regions, has not yet been performed. Objective We attempted to provide a multidimensional approach to understand the full spectrum of chronic disease co-occurrence among general inpatients in southwest China, in order to investigate multimorbidity patterns and temporal trends, and assess their age and sex differences. Methods We conducted a retrospective cohort analysis based on 8.8 million hospital discharge records of about 5.0 million individuals of all ages from 2015 to 2019 in a megacity in southwest China. We examined all chronic diagnoses using the ICD-10 (International Classification of Diseases, 10th revision) codes at 3 digits and focused on chronic diseases with ≥1% prevalence for each of the age and sex strata, which resulted in a total of 149 and 145 chronic diseases in males and females, respectively. We constructed multimorbidity networks in the general population based on sex and age, and used the cosine index to measure the co-occurrence of chronic diseases. Then, we divided the networks into communities and assessed their temporal trends. Results The results showed complex interactions among chronic diseases, with more intensive connections among males and inpatients ≥40 years old. A total of 9 chronic diseases were simultaneously classified as central diseases, hubs, and bursts in the multimorbidity networks. Among them, 5 diseases were common to both males and females, including hypertension, chronic ischemic heart disease, cerebral infarction, other cerebrovascular diseases, and atherosclerosis. The earliest leaps (degree leaps ≥6) appeared at a disorder of glycoprotein metabolism that happened at 25-29 years in males, about 15 years earlier than in females. The number of chronic diseases in the community increased over time, but the new entrants did not replace the root of the community. Conclusions Our multimorbidity network analysis identified specific differences in the co-occurrence of chronic diagnoses by sex and age, which could help in the design of clinical interventions for inpatient multimorbidity.
5 citations
TL;DR: Kuan et al. as discussed by the authors examined frequencies of common combinations of diseases and identified non-random disease associations in people of all ages and multiple ethnicities in an observational population-based study including nearly four million participants.
Abstract: In an observational population-based study including nearly four million participants, Kuan et al. examined frequencies of common combinations of diseases and identified non-random disease associations in people of all ages and multiple ethnicities.
1 citations
TL;DR: It is found that the prevalence and the severity of multimorbidity, as quantified by the number of co-occurring chronic conditions, increase progressively with age, and people living in more deprived areas are more likely to be multimOrbid compared to those living inMore affluent areas at all ages.
Abstract: Background With multimorbidity becoming the norm rather than the exception, the management of multiple chronic diseases is a major challenge facing healthcare systems worldwide. Methods Using a large, nationally representative database of electronic medical records from the United Kingdom spanning the years 2005–2016 and consisting over 4.5 million patients, we apply statistical methods and network analysis to identify comorbid pairs and triads of diseases and identify clusters of chronic conditions across different demographic groups. Unlike many previous studies, which generally adopt cross-sectional designs based on single snapshots of closed cohorts, we adopt a longitudinal approach to examine temporal changes in the patterns of multimorbidity. In addition, we perform survival analysis to examine the impact of multimorbidity on mortality. Results The proportion of the population with multimorbidity has increased by approximately 2.5 percentage points over the last decade, with more than 17% having at least two chronic morbidities. We find that the prevalence and the severity of multimorbidity, as quantified by the number of co-occurring chronic conditions, increase progressively with age. Stratifying by socioeconomic status, we find that people living in more deprived areas are more likely to be multimorbid compared to those living in more affluent areas at all ages. The same trend holds consistently for all years in our data. In general, hypertension, diabetes, and respiratory-related diseases demonstrate high in-degree centrality and eigencentrality, while cardiac disorders show high out-degree centrality. Conclusions We use data-driven methods to characterize multimorbidity patterns in different demographic groups and their evolution over the past decade. In addition to a number of strongly associated comorbid pairs (e.g., cardiac-vascular and cardiac-metabolic disorders), we identify three principal clusters: a respiratory cluster, a cardiovascular cluster, and a mixed cardiovascular-renal-metabolic cluster. These are supported by established pathophysiological mechanisms and shared risk factors, and largely confirm and expand on the results of existing studies in the medical literature. Our findings contribute to a more quantitative understanding of the epidemiology of multimorbidity, an important pre-requisite for developing more effective medical care and policy for multimorbid patients.
1 citations
TL;DR: In this paper , a systematic review and meta-analysis is conducted to estimate the prevalence of polypharmacy in patients with chronic liver disease and to comprehensively synthesize the socio-demographic factors that drive this.
27 Jun 2023-Journal of stroke and cerebrovascular diseases : official publication of the National Stroke Association
TL;DR: The South London Stroke Register (SLSR) is a population-based cohort study, which was established in 1995 to study the causes, incidence, and outcomes of stroke as mentioned in this paper .
Abstract: PurposeThe South London Stroke Register (SLSR) is a population-based cohort study, which was established in 1995 to study the causes, incidence, and outcomes of stroke. The SLSR aims to estimate incidence, and acute and long term needs in a multi-ethnic inner-city population, with follow-up durations for some participants exceeding 20 years.ParticipantsThe SLSR aims to recruit residents of a defined area within Lambeth and Southwark who experience a first stroke. More than 7700 people have been registered since inception, and >2750 people continue to be followed up. At the 2011 census, the source population was 357,308.Findings to dateThe SLSR was instrumental in highlighting the inequalities in risk and outcomes in the UK, and demonstrating the dramatic improvements in care quality and outcomes in recent decades. Data from the SLSR informed the UK National Audit Office in its 2005 report criticising the poor state of stroke care in England. For people living in the SLSR area the likelihood of being treated in a stroke unit increased from 19% in 1995–7 to 75% in 2007–9. The SLSR has investigated health inequalities in stroke incidence and outcome. SLSR analyses have demonstrated that lower socioeconomic status was associated with poorer outcome, and that Black people and younger people have not experienced the same improvements in stroke incidence as other groups.Future plansAs part of an NIHR Programme Grant for Applied Research, from April 2022 the SLSR has expanded to recruit ICD-11 defined stroke (including those with <24 h symptoms where there are neuroimaging findings), and have expanded the follow up interviews to collect more detailed information on quality of life, cognition, and care needs. Additional data items will be added over the Programme based on feedback from patients and other stakeholders.
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TL;DR: The Behavioral Model of Health Services Use was initially developed over 25 years ago and is reviewed and assessed for continued relevance.
Abstract: The Behavioral Model of Health Services Use was initially developed over 25 years ago. In the interim it has been subject to considerable application, reprobation, and alteration. I review its development and assess its continued relevance.
8,261 citations
TL;DR: The findings challenge the single-disease framework by which most health care, medical research, and medical education is configured, and a complementary strategy is needed, supporting generalist clinicians to provide personalised, comprehensive continuity of care, especially in socioeconomically deprived areas.
4,839 citations
01 Jan 2007
Abstract: The Index of Multiple Deprivation 2007 (IMD 2007) is a measure of multiple deprivation at the small area level. The model of multiple deprivation which underpins the IMD 2007 is the same as that which underpinned its predecessor – the IMD 2004 (Noble et al., 2004) and is based on the idea of distinct dimensions of deprivation which can be recognised and measured separately. These are experienced by individuals living in an area. People may be counted as deprived in one or more of the domains, depending on the number of types of deprivation that they experience. The overall IMD is conceptualised as a weighted area level aggregation of these specifi c dimensions of deprivation. This chapter, which draws from the ID 2004 Report, elaborates on the model of multiple deprivation that has been used and addresses issues relating to it.
1,081 citations
TL;DR: Multimorbidity is common in the population and most consultations in primary care involve people with multi- chronic conditions, but these people are less likely to receive continuity of care, although they may be more likely to gain from it.
Abstract: Background In developed countries, primary health care increasingly involves the care of patients with multiple chronic conditions, referred to as multimorbidity. Aim To describe the epidemiology of multimorbidity and relationships between multimorbidity and primary care consultation rates and continuity of care. Design of study Retrospective cohort study. Setting Random sample of 99 997 people aged 18 years or over registered with 182 general practices in England contributing data to the General Practice Research Database. Method Multimorbidity was defined using two approaches: people with multiple chronic conditions included in the Quality and Outcomes Framework, and people identified using the Johns Hopkins University Adjusted Clinical Groups (ACG®) Case-Mix System. The determinants of multimorbidity (age, sex, area deprivation) and relationships with consultation rate and continuity of care were examined using regression models. Results Sixteen per cent of patients had more than one chronic condition included in the Quality and Outcomes Framework, but these people accounted for 32% of all consultations. Using the wider ACG list of conditions, 58% of people had multimorbidity and they accounted for 78% of consultations. Multimorbidity was strongly related to age and deprivation. People with multimorbidity had higher consultation rates and less continuity of care compared with people without multimorbidity. Conclusion Multimorbidity is common in the population and most consultations in primary care involve people with multimorbidity. These people are less likely to receive continuity of care, although they may be more likely to gain from it.
719 citations
TL;DR: This systematic literature review identified and summarized 35 studies that investigated the relationship between multiple chronic conditions (MCCs) and health care utilization outcomes (i.e. physician use, hospital use, medication use) andhealth care cost outcomes (medication costs, out-of-pocket costs, total health care costs) for elderly general populations.
Abstract: This systematic literature review identified and summarized 35 studies that investigated the relationship between multiple chronic conditions (MCCs) and health care utilization outcomes (i.e. physi...
594 citations