Many patients with several concurrent medical conditions (multimorbidity) are seen in the primary care setting. A thorough understanding of outcomes associated with multimorbidity would benefit primary care workers of all disciplines. The purpose of this systematic review was to clarify the relationship between the presence of multimorbidity and the quality of life (QOL) or health-related quality of life (HRQOL) of patients seen, or likely to be seen, in the primary care setting.
Medline and Embase electronic databases were screened using the following search terms for the reference period 1990 to 2003: multimorbidity, comorbidity, chronic disease, and their spelling variations, along with quality of life and health-related quality of life. Only descriptive studies relevant to primary care were selected.
Of 753 articles screened, 108 were critically assessed for compliance with study inclusion and exclusion criteria. Thirty of these studies were ultimately selected for this review, including 7 in which the relationship between multimorbidity or comorbidity and QOL or HRQOL was the main outcome measure. Major limitations of these studies include the lack of a uniform definition for multimorbidity or comorbidity and the absence of assessment of disease severity. The use of self-reported diagnoses may also be a weakness. The frequent exclusion of psychiatric diagnoses and presence of potential confounding variables are other limitations. Nonetheless, we did find an inverse relationship between the number of medical conditions and QOL related to physical domains. For social and psychological dimensions of QOL, some studies reveal a similar inverse relationship in patients with 4 or more diagnoses.
Our findings confirm the existence of an inverse relationship between multimorbidity or comorbidy and QOL. However, additional studies are needed to clarify this relationship, including the various dimensions of QOL affected. Those studies must employ a clear definition of multimorbidity or comorbidity and valid ways to measure these concepts in a primary care setting. Pursuit of this research will help to better understand the impact of chronic diseases on patients.
Objective To determine the effectiveness of interventions designed to improve outcomes in patients with multimorbidity in primary care and community settings.
Design Systematic review.
Data sources Medline, Embase, CINAHL, CAB Health, Cochrane central register of controlled trials, the database of abstracts of reviews of effectiveness, and the Cochrane EPOC (effective practice and organisation of care) register (searches updated in April 2011).
Eligibility criteria Randomised controlled trials, controlled clinical trials, controlled before and after studies, and interrupted time series analyses reporting on interventions to improve outcomes for people with multimorbidity in primary care and community settings. Multimorbidity was defined as two or more chronic conditions in the same individual. Outcomes included any validated measure of physical or mental health and psychosocial status, including quality of life outcomes, wellbeing, and measures of disability or functional status. Also included were measures of patient and provider behaviour, including drug adherence, utilisation of health services, acceptability of services, and costs.
Data selection Two reviewers independently assessed studies for eligibility, extracted data, and assessed study quality. As meta-analysis of results was not possible owing to heterogeneity in participants and interventions, a narrative synthesis of the results from the included studies was carried out.
Results 10 studies examining a range of complex interventions totalling 3407 patients with multimorbidity were identified. All were randomised controlled trials with a low risk of bias. Two studies described interventions for patients with specific comorbidities. The remaining eight studies focused on multimorbidity, generally in older patients. Consideration of the impact of socioeconomic deprivation was minimal. All studies involved complex interventions with multiple components. In six of the 10 studies the predominant component was a change to the organisation of care delivery, usually through case management or enhanced multidisciplinary team work. In the remaining four studies, intervention components were predominantly patient oriented. Overall the results were mixed, with a trend towards improved prescribing and drug adherence. The results indicated that it is difficult to improve outcomes in this population but that interventions focusing on particular risk factors in comorbid conditions or functional difficulties in multimorbidity may be more effective. No economic analyses were included, although the improvements in prescribing and risk factor management in some studies could provide potentially important cost savings.
Conclusions Evidence on the care of patients with multimorbidity is limited, despite the prevalence of multimorbidity and its impact on patients and healthcare systems. Interventions to date have had mixed effects, although are likely to be more effective if targeted at risk factors or specific functional difficulties. A need exists to clearly identify patients with multimorbidity and to develop cost effective and specifically targeted interventions that can improve health outcomes.
Obstructive sleep apnea (OSA) is becoming increasingly prevalent in North America and has been described in association with specific chronic diseases, particularly cardiovascular diseases. In primary care, where the prevalence of co-occurring chronic conditions is very high, the potential association with OSA is unknown. The purpose of this study was to explore the association between OSA and 1) the presence and severity of multimorbidity (multiple co-occurring chronic conditions), and 2) subcategories of multimorbidity.
A cluster sampling technique was used to recruit 120 patients presenting with OSA of various severities from the records of a sleep laboratory in 2008. Severity of OSA was based on the results of the polysomnography. Patients invited to participate received a mail questionnaire including questions on sociodemographic characteristics and the Disease Burden Morbidity Assessment (DBMA). They also consented to give access to their medical records. The DBMA was used to provide an overall multimorbidity score and sub-score of diseases affecting various systems.
Bivariate analysis did not demonstrate an association between OSA and multimorbidity (r = 0.117; p = 0.205). However, severe OSA was associated with multimorbidity (adjusted odds ratio = 7.33 [1.67-32.23], p = 0.05). OSA was moderately correlated with vascular (r = 0.26, p = 0.01) and metabolic syndrome (r = 0.26, p = 0.01) multimorbidity sub-scores.
This study showed that severe OSA is associated with severe multimorbidity and sub-scores of multimorbidity. These results do not allow any causal inference. More research is required to confirm these associations. However, primary care providers should be aware of these potential associations and investigate OSA when deemed appropriate.
Obstructive sleep apnea; Multimorbidity; Disease Burden Morbidity Assessment; Chronic disease; Severity
Multimorbidity is a major concern in primary care. Nevertheless, evidence of prevalence and patterns of multimorbidity, and their determinants, are scarce. The aim of this study is to systematically review studies of the prevalence, patterns and determinants of multimorbidity in primary care.
Systematic review of literature published between 1961 and 2013 and indexed in Ovid (CINAHL, PsychINFO, Medline and Embase) and Web of Knowledge. Studies were selected according to eligibility criteria of addressing prevalence, determinants, and patterns of multimorbidity and using a pretested proforma in primary care. The quality and risk of bias were assessed using STROBE criteria. Two researchers assessed the eligibility of studies for inclusion (Kappa = 0.86).
We identified 39 eligible publications describing studies that included a total of 70,057,611 patients in 12 countries. The number of health conditions analysed per study ranged from 5 to 335, with multimorbidity prevalence ranging from 12.9% to 95.1%. All studies observed a significant positive association between multimorbidity and age (odds ratio [OR], 1.26 to 227.46), and lower socioeconomic status (OR, 1.20 to 1.91). Positive associations with female gender and mental disorders were also observed. The most frequent patterns of multimorbidity included osteoarthritis together with cardiovascular and/or metabolic conditions.
Well-established determinants of multimorbidity include age, lower socioeconomic status and gender. The most prevalent conditions shape the patterns of multimorbidity. However, the limitations of the current evidence base means that further and better designed studies are needed to inform policy, research and clinical practice, with the goal of improving health-related quality of life for patients with multimorbidity. Standardization of the definition and assessment of multimorbidity is essential in order to better understand this phenomenon, and is a necessary immediate step.
Multimorbidity is a growing concern worldwide, with approximately 1 in 4 adults affected. Most of the evidence on multimorbidity, its prevalence and effects, comes from high income countries. Not much is known about multimorbidity in low income countries, particularly in sub-Saharan Africa. The aim of this study was to determine the prevalence of multimorbidity and examine its association with various social determinants of health in South Africa.
The data used in this study are taken from the South Africa National Income Dynamic Survey (SA-NIDS) of 2008. Multimorbidity was defined as the coexistence of two or more chronic diseases in an individual. Multinomial logistic regression models were constructed to analyse the relationship between multimorbidity and several indicators including socioeconomic status, area of residence and obesity.
The prevalence of multimorbidity in South Africa was 4% in the adult population. Over 70% of adults with multimorbidity were females. Factors associated with multimorbidity were social assistance (Odds ratio (OR) 2.35; Confidence Interval (CI) 1.59-3.49), residence (0.65; 0.46-0.93), smoking (0.61; 0.38-0.96); obesity (2.33; 1.60-3.39), depression (1.07; 1.02-1.11) and health facility visits (5.14; 3.75-7.05). Additionally, income was strongly positively associated with multimorbidity. The findings are similar to observations made in studies conducted in developed countries.
The findings point to a potential difference in the factors associated with single chronic disease and multimorbidity. Income was consistently significantly associated with multimorbidity, but not single chronic diseases. This should be investigated further in future research on the factors affecting multimorbidity.
Multimorbidity; South Africa; Social determinants of health
The consequences of multimorbidity include polypharmacy and repeated referrals for specialised care, which may increase the risk of adverse drug events (ADEs).
The objective of this study was to analyse the influence of multimorbidity, polypharmacy, and multiple referrals on the frequency of ADEs, as an indicator of therapeutic safety, in the context of a national healthcare system.
Design and setting
This was a multicentre, retrospective, observational study of 79 089 adult patients treated during 2008 in primary care centres.
The explanatory patient variables sex, age, level of multimorbidity, polypharmacy, number of primary care physician visits, and number of different specialties attended were analysed. The response variable was the occurrence of ADEs. Logistic regression models were used to identify associations among the analysed variables.
The prevalence of individuals with at least one ADE was 0.88%. Multivariate analysis identified the following variables as risk factors for the occurrence of ADE in descending order of effect size: multimorbidity level (odds ratio [OR]Veryhigh/Low = 45.26; ORHigh/Low = 17.58; ORModerate/Low = 4.25), polypharmacy (OR = 1.34), female sex (OR = 1.31), number of different specialties (OR = 1.20), and number of primary care physician visits (OR = 1.01). Age, however, did not show statistical significance (OR = 1.00; 95% confidence interval = 0.996 to 1.005).
The results of this study demonstrate that multimorbidity is strongly related to the occurrence of ADEs, insofar as it requires the intervention of multiple specialties and the prescription of multiple medications. Further research should shed light on the causal pathway between multimorbidity and increased risk of adverse events.
adverse drug event; healthcare system, national; multimorbidity, multiple; polypharmacy; referral, hospital
Very little is known about multimorbidity and chronic diseases in low and middle income countries, particularly Sub-Saharan Africa, and more information is needed to guide the process of adapting the health systems in these countries to respond adequately to the increasing burden of chronic diseases. We conducted a hospital-based survey in an urban setting in Ghana to determine the prevalence of multimorbidity and its associated risk factors among adult patients presenting to an inner city clinic.
Between May and June 2012, we interviewed adult patients (aged 18 years and above) attending a routine outpatient clinic at an inner-city hospital in Accra using a structured questionnaire. We supplemented the information obtained from the interviews with information obtained from respondents’ health records. We used logistic regression analyses to explore the risk factors for multimorbidity.
We interviewed 1,527 patients and retrieved matching medical records for 1,399 (91.6%). The median age of participants was 52.1 years (37–64 years). While the prevalence of multimorbidity was 38.8%, around half (48.6%) of the patients with multimorbidity were aged between 18–59 years old. The most common combination of conditions was hypertension and diabetes mellitus (36.6%), hypertension and musculoskeletal conditions (19.9%), and hypertension and other cardiovascular conditions (11.4%). Compared with patients aged 18–39 years, those aged 40–49 years (OR 4.68, 95% CI: 2.98–7.34), 50–59 years (OR 12.48, 95% CI: 8.23–18.92) and 60 years or older (OR 15.80, 95% CI: 10.66–23.42) were increasingly likely to present with multimorbidity. While men were less likely to present with multimorbidity, (OR 0.71, 95% CI: 0.45–0.94, p = 0.015), having a family history of any chronic disease was predictive of multimorbidity (OR 1.43, 95% CI: 1.03–1.68, p = 0.027).
Multimorbidity is a significant problem in this population. By identifying the risk factors for multimorbidity, the results of the present study provide further evidence for informing future policies aimed at improving clinical case management, health education and medical training in Ghana.
Comorbidity; Chronic disease; Non-communicable conditions; Ghana; Africa
The burden of chronic conditions and multimorbidity is a growing health problem in developed countries. The study aimed to determine the estimated prevalence and patterns of multimorbidity in urban areas of Catalonia, stratified by sex and adult age groups, and to assess whether socioeconomic status and use of primary health care services were associated with multimorbidity.
A cross-sectional study was conducted in Catalonia. Participants were adults (19+ years) living in urban areas, assigned to 251 primary care teams. Main outcome: multimorbidity (≥2 chronic conditions). Other variables: sex (male/female), age (19–24; 25–44; 45–64; 65–79; 80+ years), socioeconomic status (quintiles), number of health care visits during the study.
We included 1,356,761 patients; mean age, 47.4 years (SD: 17.8), 51.0% women. Multimorbidity was present in 47.6% (95% CI 47.5-47.7) of the sample, increasing with age in both sexes but significantly higher in women (53.3%) than in men (41.7%). Prevalence of multimorbidity in each quintile of the deprivation index was higher in women than in men (except oldest group). In women, multimorbidity prevalence increased with quintile of the deprivation index. Overall, the median (interquartile range) number of primary care visits was 8 (4–14) in multimorbidity vs 1 (0–4) in non-multimorbidity patients. The most prevalent multimorbidity pattern beyond 45 years of age was uncomplicated hypertension and lipid disorder. Compared with the least deprived group, women in other quintiles of the deprivation index were more likely to have multimorbidity than men until 65 years of age. The odds of multimorbidity increased with number of visits in all strata.
When all chronic conditions were included in the analysis, almost 50% of the adult urban population had multimorbidity. The prevalence of multimorbidity differed by sex, age group and socioeconomic status. Multimorbidity patterns varied by life-stage and sex; however, circulatory-endocrine-metabolic patterns were the most prevalent multimorbidity pattern after 45 years of age. Women younger than 80 years had greater prevalence of multimorbidity than men, and women’s multimorbidity prevalence increased as socioeconomic status declined in all age groups. Identifying multimorbidity patterns associated with specific age-related life-stages allows health systems to prioritize and to adapt clinical management efforts by age group.
Multimorbidity; Chronic conditions; Socioeconomic status; Use of health services; Life-stage; Urban area; Inequalities
Multimorbidity, the simultaneous occurrence of two or more chronic conditions, is usually associated with older persons. This research assessed multimorbidity across a range of ages so that planners are informed and appropriate prevention programs, management strategies and health service/health care planning can be implemented.
Multimorbidity was assessed across three age groups from data collected in a major biomedical cohort study (North West Adelaide Health Study). Using randomly selected adults, diabetes, asthma, and chronic obstructive pulmonary disease were determined clinically and cardio-vascular disease, osteoporosis, arthritis and mental health by self-report (ever been told by a doctor). A range of demographic, social, risk and protective factors including high blood pressure and high cholesterol (assessed bio-medically), health service use, quality of life and medication use (linked to government records) were included in the multivariate modelling.
Overall 4.4% of the 20-39 year age group, 15.0% of the 40-59 age group and 39.2% of those aged 60 years of age or older had multimorbidity (17.1% of the total). Of those with multimorbidity, 42.1% were aged less than 60 years of age. A variety of variables were included in the final logistic regression models for the three age groups including family structure, marital status, education attainment, country of birth, smoking status, obesity measurements, medication use, health service utilisation and overall health status.
Multimorbidity is not just associated with older persons and flexible care management support systems, appropriate guidelines and care-coordination programs are required across a broader age range. Issues such as health literacy and polypharamacy are also important considerations. Future research is required into assessing multimorbidity across the life course, prevention of complications and assessment of appropriate self-care strategies.
Multimorbidity is a phenomenon with high burden and high prevalence in the elderly. Our previous research has shown that multimorbidity can be divided into the multimorbidity patterns of 1) anxiety, depression, somatoform disorders (ADS) and pain, and 2) cardiovascular and metabolic disorders. However, it is not yet known, how these patterns are influenced by patient characteristics. The objective of this paper is to analyze the association of socio-demographic variables, and especially socio-economic status with multimorbidity in general and with each multimorbidity pattern.
The MultiCare Cohort Study is a multicentre, prospective, observational cohort study of 3.189 multimorbid patients aged 65+ randomly selected from 158 GP practices. Data were collected in GP interviews and comprehensive patient interviews. Missing values have been imputed by hot deck imputation based on Gower distance in morbidity and other variables. The association of patient characteristics with the number of chronic conditions is analysed by multilevel mixed-effects linear regression analyses.
Multimorbidity in general is associated with age (+0.07 chronic conditions per year), gender (-0.27 conditions for female), education (-0.26 conditions for medium and -0.29 conditions for high level vs. low level) and income (-0.27 conditions per logarithmic unit). The pattern of cardiovascular and metabolic disorders shows comparable associations with a higher coefficient for gender (-1.29 conditions for female), while multimorbidity within the pattern of ADS and pain correlates with gender (+0.79 conditions for female), but not with age or socioeconomic status.
Our study confirms that the morbidity load of multimorbid patients is associated with age, gender and the socioeconomic status of the patients, but there were no effects of living arrangements and marital status. We could also show that the influence of patient characteristics is dependent on the multimorbidity pattern concerned, i.e. there seem to be at least two types of elderly multimorbid patients. First, there are patients with mainly cardiovascular and metabolic disorders, who are more often male, have an older age and a lower socio-economic status. Second, there are patients mainly with ADS and pain-related morbidity, who are more often female and equally distributed across age and socio-economic groups.
General practitioners often care for patients with several concurrent chronic medical conditions (multimorbidity). Recent data suggest that multimorbidity might be observed more often than isolated diseases in primary care. We explored the age- and gender-related prevalence of multimorbidity and compared these estimates to the prevalence estimates of other common specific diseases found in Swiss primary care.
We analyzed data from the Swiss FIRE (Family Medicine ICPC Research using Electronic Medical Record) project database, representing a total of 509,656 primary care encounters in 98,152 adult patients between January 1, 2009 and July 31, 2011. For each encounter, medical problems were encoded using the second version of the International Classification of primary Care (ICPC-2). We defined chronic health conditions using 147 pre-specified ICPC-2 codes and defined multimorbidity as 1) two or more chronic health conditions from different ICPC-2 rubrics, 2) two or more chronic health conditions from different ICPC-2 chapters, and 3) two or more medical specialties involved in patient care. We compared the prevalence estimates of multimorbidity defined by the three methodologies with the prevalence estimates of common diseases encountered in primary care.
Overall, the prevalence estimates of multimorbidity were similar for the three different definitions (15% [95%CI 11-18%], 13% [95%CI 10-16%], and 14% [95%CI 11-17%], respectively), and were higher than the prevalence estimates of any specific chronic health condition (hypertension, uncomplicated 9% [95%CI 7-11%], back syndrome with and without radiating pain 6% [95%CI 5-7%], non-insulin dependent diabetes mellitus 3% [95%CI 3-4%]), and degenerative joint disease 3% [95%CI 2%-4%]). The prevalence estimates of multimorbidity rose more than 20-fold with age, from 2% (95%CI 1-2%) in those aged 20–29 years, to 38% (95%CI 31-44%) in those aged 80 or more years. The prevalence estimates of multimorbidity were similar for men and women (15% vs. 14%, p=0.288).
In primary care, prevalence estimates of multimorbidity are higher than those of isolated diseases. Among the elderly, more than one out of three patients suffer from multimorbidity. Management of multimorbidity is a principal concern in this vulnerable patient population.
Multimorbidity; Chronic medical conditions; Prevalence; Primary care; Age; Gender; Swiss; FIRE
In developed countries, primary health care increasingly involves the care of patients with multiple chronic conditions, referred to as multimorbidity.
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.
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.
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.
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.
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.
chronic disease; comorbidity; family practice; primary health care; outcome and process assessment (healthcare); prevalence
Data on multimorbidity among the elderly people in Bangladesh are lacking. This paper reports the prevalence and distribution patterns of multimorbidity among the elderly people in rural Bangladesh. This cross-sectional study was conducted among persons aged ≥60 years in Matlab, Bangladesh. Information on their demographics and literacy was collected through interview in the home. Information about their assets was obtained from a surveillance database. Physicians conducted clinical examinations at a local health centre. Two physicians diagnosed medical conditions, and two senior geriatricians then evaluated the same separately. Multimorbidity was defined as suffering from two or more of nine chronic medical conditions, such as arthritis, stroke, obesity, signs of thyroid hypofunction, obstructive pulmonary symptoms, symptoms of heart failure, impaired vision, hearing impairment, and high blood pressure. The overall prevalence of multimorbidity among the study population was 53.8%, and it was significantly higher among women, illiterates, persons who were single, and persons in the non-poorest quintile. In multivariable logistic regression analyses, female sex and belonging to the non-poorest quintile were independently associated with an increased odds ratio of multimorbidity. The results suggest that the prevalence of multimorbidity is high among the elderly people in rural Bangladesh. Women and the non-poorest group of the elderly people are more likely than men and the poorest people to be affected by multimorbidity. The study sheds new light on the need of primary care for the elderly people with multimorbidity in rural Bangladesh.
Cross-sectional studies; Elderly; Morbidity; Multimorbidity; Bangladesh
Studies on the prevalence of multimorbidity, defined as having two or more chronic conditions, have predominantly focused on the elderly. We estimated the prevalence and specific patterns of multimorbidity across different adult age groups. Furthermore, we examined the associations of multimorbidity with socio-demographic factors.
Using data from the Health Quality Council of Alberta (HQCA) 2010 Patient Experience Survey, the prevalence of self reported multimorbidity was assessed by telephone interview among a sample of 5010 adults (18 years and over) from the general population. Logistic regression analyses were performed to determine the association between a range of socio-demographic factors and multimorbidity.
The overall age- and sex-standardized prevalence of multimorbidity was 19.0% in the surveyed general population. Of those with multimorbidity, 70.2% were aged less than 65 years. The most common pairing of chronic conditions was chronic pain and arthritis. Age, sex, income and family structure were independently associated with multimorbidity.
Multimorbidity is a common occurrence in the general adult population, and is not limited to the elderly. Future prevention programs and practice guidelines should take into account the common patterns of multimorbidity.
Family physicians often have to care for patients with several concurrent
chronic conditions (multimorbidity or comorbidity). Consequently, they need
to inform themselves by reading indexed publications on multimorbidity. This
study aimed to assess how well the concept of multimorbidity was covered in
the medical literature. Objectives were first, to quantify the literature on
multimorbidity (or comorbidity) and to compare the number of publications on
it with the number of publications on three common chronic conditions
(asthma, hypertension, and diabetes), and second, to describe the articles
We consulted MEDLINE for the reference period 1990 to the end of 2002. The
term “multimorbidity” and its various spellings was used as the search term.
Comorbidity, asthma, hypertension, and diabetes were searched for using
their respective MeSH terms. For comparison purposes, prevalence data were
taken from published sources. Abstracts of articles relating to
multimorbidity were reviewed and their content analyzed.
MAIN OUTCOME MEASURES
Number and type of articles.
Multimorbidity has a prevalence of 60% among people aged 55 to 74. This
prevalence is much higher than that of asthma (6.5%), hypertension (29.6%),
and diabetes (8.7%). Few articles in the medical literature deal
specifically with multimorbidity (or comorbidity), however. For each article
on multimorbidity, there are 74 on asthma, 94 on hypertension, and 38 on
diabetes. Content analysis of abstracts of articles on multimorbidity
revealed a high proportion of epidemiologic studies (50.0%) followed by
validation studies (22.4%) and opinion pieces (11.8%). The few experimental
studies on multimorbidity were not done in primary care settings.
This study shows that the prevalence of multimorbidity is not matched by the
number of indexed publications on it in the medical literature. To date, the
number and diversity of articles on multimorbidity are both insufficient to
provide scientific background for strong evidence-based care of patients
affected by multiple concurrent chronic conditions. Research is needed to
increase knowledge and understanding of this important clinical topic.
Chronic conditions and multimorbidity have become one of the main challenges in health care worldwide. However, data on the burden of multimorbidity are still scarce. The purpose of this study is to examine the association between multimorbidity and the health care utilization and costs in the Swiss community-dwelling population, taking into account several sociodemographic factors.
The study population consists of 229'493 individuals aged 65 or older who were insured in 2013 by the Helsana Group, the leading health insurer in Switzerland, covering all 26 Swiss cantons. Multimorbidity was defined as the presence of two or more chronic conditions of a list of 22 conditions that were identified using an updated measure of the Pharmacy-based Cost Group model. The number of consultations (total and divided by primary care physicians and specialists), the number of different physicians contacted, the type of physician contact (face-to-face, phone, and home visits), the number of hospitalisations and the length of stay were assessed separately for the multimorbid and non-multimorbid sample. The costs (total and divided by inpatient and outpatient costs) covered by the compulsory health insurance were calculated for both samples. Multiple linear regression modelling was conducted to adjust for influencing factors: age, sex, linguistic region, purchasing power, insurance plan, and nursing dependency.
Prevalence of multimorbidity was 76.6%. The mean number of consultations per year was 15.7 in the multimorbid compared to 4.4 in the non-multimorbid sample. Total costs were 5.5 times higher in multimorbid patients. Each additional chronic condition was associated with an increase of 3.2 consultations and increased costs of 33%. Strong positive associations with utilization and costs were also found for nursing dependency. Multimorbid patients were 5.6 times more likely to be hospitalised. Furthermore, results revealed a significant age-gender interaction and a socioeconomic gradient.
Multimorbidity is associated with substantial higher health care utilization and costs in Switzerland. Quantified data on the current burden of multimorbidity are fundamental for the management of patients in health service delivery systems and for health care policy debates about resource allocation. Strategies for a better coordination of multimorbid patients are urgently needed.
Electronic supplementary material
The online version of this article (doi:10.1186/s12913-015-0698-2) contains supplementary material, which is available to authorized users.
Health care utilization; Health care costs; Multimorbidity; Claims data
Multimorbidity is a common phenomenon in primary care. Until now, no clinical guidelines for multimorbidity exist. For the development of these guidelines, it is necessary to know whether or not patients are aware of their diseases and to what extent they agree with their doctor. The objectives of this paper are to analyze the agreement of self-reported and general practitioner-reported chronic conditions among multimorbid patients in primary care, and to discover which patient characteristics are associated with positive agreement.
The MultiCare Cohort Study is a multicenter, prospective, observational cohort study of 3,189 multimorbid patients, ages 65 to 85. Data was collected in personal interviews with patients and GPs. The prevalence proportions for 32 diagnosis groups, kappa coefficients and proportions of specific agreement were calculated in order to examine the agreement of patient self-reported and general practitioner-reported chronic conditions. Logistic regression models were calculated to analyze which patient characteristics can be associated with positive agreement.
We identified four chronic conditions with good agreement (e.g. diabetes mellitus κ = 0.80;PA = 0,87), seven with moderate agreement (e.g. cerebral ischemia/chronic stroke κ = 0.55;PA = 0.60), seventeen with fair agreement (e.g. cardiac insufficiency κ = 0.24;PA = 0.36) and four with poor agreement (e.g. gynecological problems κ = 0.05;PA = 0.10).
Factors associated with positive agreement concerning different chronic diseases were sex, age, education, income, disease count, depression, EQ VAS score and nursing care dependency. For example: Women had higher odds ratios for positive agreement with their GP regarding osteoporosis (OR = 7.16). The odds ratios for positive agreement increase with increasing multimorbidity in almost all of the observed chronic conditions (OR = 1.22-2.41).
For multimorbidity research, the knowledge of diseases with high disagreement levels between the patients’ perceived illnesses and their physicians’ reports is important. The analysis shows that different patient characteristics have an impact on the agreement. Findings from this study should be included in the development of clinical guidelines for multimorbidity aiming to optimize health care. Further research is needed to identify more reasons for disagreement and their consequences in health care.
Agreement; Self-report; Physician report; Chronic diseases; Primary care; Multimorbidity
In the context of population aging, multimorbidity has emerged as a growing concern in public health. However, little is known about multimorbidity patterns and other issues surrounding chronic diseases. The aim of our study was to examine multimorbidity patterns, the relationship between physical and mental conditions and the distribution of multimorbidity in the Spanish adult population.
Data from this cross-sectional study was collected from the COURAGE study. A total of 4,583 participants from Spain were included, 3,625 aged over 50. An exploratory factor analysis was conducted to detect multimorbidity patterns in the population over 50 years of age. Crude and adjusted binary logistic regressions were performed to identify individual associations between physical and mental conditions.
Three multimorbidity patterns rose: ‘cardio-respiratory’ (angina, asthma, chronic lung disease), ‘mental-arthritis’ (arthritis, depression, anxiety) and the ‘aggregated pattern’ (angina, hypertension, stroke, diabetes, cataracts, edentulism, arthritis). After adjusting for covariates, asthma, chronic lung disease, arthritis and the number of physical conditions were associated with depression. Angina and the number of physical conditions were associated with a higher risk of anxiety. With regard to multimorbidity distribution, women over 65 years suffered from the highest rate of multimorbidity (67.3%).
Multimorbidity prevalence occurs in a high percentage of the Spanish population, especially in the elderly. There are specific multimorbidity patterns and individual associations between physical and mental conditions, which bring new insights into the complexity of chronic patients. There is need to implement patient-centered care which involves these interactions rather than merely paying attention to individual diseases.
We sought to examine the relationship between literacy and heart failure-related quality of life (HFQOL), and to explore whether literacy-related differences in knowledge, self-efficacy and/or self-care behavior explained the relationship.
We recruited patients with symptomatic heart failure (HF) from four academic medical centers. Patients completed the short version of the Test of Functional Health Literacy in Adults (TOFHLA) and questions on HF-related knowledge, HF-related self-efficacy, and self-care behaviors. We assessed HFQOL with the Heart Failure Symptom Scale (HFSS) (range 0–100), with higher scores denoting better quality of life. We used bivariate (t-tests and chi-square) and multivariate linear regression analyses to estimate the associations between literacy and HF knowledge, self-efficacy, self-care behaviors, and HFQOL, controlling for demographic characteristics. Structural equation modeling was conducted to assess whether general HF knowledge, salt knowledge, self-care behaviors, and self-efficacy mediated the relationship between literacy and HFQOL.
We enrolled 605 patients with mean age of 60.7 years; 52% were male; 38% were African-American and 16% Latino; 26% had less than a high school education; and 67% had annual incomes under $25,000. Overall, 37% had low literacy (marginal or inadequate on TOFHLA). Patients with adequate literacy had higher general HF knowledge than those with low literacy (mean 6.6 vs. 5.5, adjusted difference 0.63, p < 0.01), higher self-efficacy (5.0 vs. 4.1 ,adjusted difference 0.99, p < 0.01), and higher prevalence of key self-care behaviors (p < 0.001). Those with adequate literacy had better HFQOL scores compared to those with low literacy (63.9 vs. 55.4, adjusted difference 7.20, p < 0.01), but differences in knowledge, self-efficacy, and self-care did not mediate this difference in HFQOL.
Low literacy was associated with worse HFQOL and lower HF-related knowledge, self-efficacy, and self-care behaviors, but differences in knowledge, self-efficacy and self-care did not explain the relationship between low literacy and worse HFQOL.
literacy; self-care; quality of life; heart failure
With increasing life expectancy the number of people affected by multimorbidity rises. Knowledge of factors associated with health-related quality of life in multimorbid people is scarce. We aimed to identify the factors that are associated with self-rated health (SRH) in aged multimorbid primary care patients.
Cross-sectional study with 3,189 multimorbid primary care patients aged from 65 to 85 years recruited in 158 general practices in 8 study centers in Germany. Information about morbidity, risk factors, resources, functional status and socio-economic data were collected in face-to-face interviews. Factors associated with SRH were identified by multivariable regression analyses.
Depression, somatization, pain, limitations of instrumental activities (iADL), age, distress and Body Mass Index (BMI) were inversely related with SRH. Higher levels of physical activity, income and self-efficacy expectation had a positive association with SRH. The only chronic diseases remaining in the final model were Parkinson’s disease and neuropathies. The final model accounted for 35% variance of SRH. Separate analyses for men and women detected some similarities; however, gender specific variation existed for several factors.
In multimorbid patients symptoms and consequences of diseases such as pain and activity limitations, as well as depression, seem to be far stronger associated with SRH than the diseases themselves. High income and self-efficacy expectation are independently associated with better SRH and high BMI and age with low SRH.
MultiCare Cohort study registration:ISRCTN89818205.
Quality of life; Self-assessment; Chronic disease; Depression; Pain; Functionally- impaired elderly; General practice
Concurrent diseases, multiple pathologies and multimorbidity patterns are topics of increased interest as the world’s population ages. To explore the impact of multimorbidity on affected patients and the consequences for health services, we designed a study to describe multimorbidity by sex and life-stage in a large population sample and to assess the association with acute morbidity, area of residency and use of health services.
A cross-sectional study was conducted in Catalonia (Spain). Participants were 1,749,710 patients aged 19+ years (251 primary care teams). Primary outcome: Multimorbidity (≥2 chronic diseases). Secondary outcome: Number of new events of each acute disease. Other variables: number of acute diseases per patient, sex, age group (19–24, 25–44, 45–64, 65–79, and 80+ years), urban/rural residence, and number of visits during 2010.
Multimorbidity was present in 46.8% (95% CI, 46.7%-46.8%) of the sample, and increased as age increased, being higher in women and in rural areas. The most prevalent pair of chronic diseases was hypertension and lipid disorders in patients older than 45 years. Infections (mainly upper respiratory infection) were the most common acute diagnoses. In women, the highest significant RR of multimorbidity vs. non-multimorbidity was found for teeth/gum disease (aged 19–24) and acute upper respiratory infection. In men, this RR was only positive and significant for teeth/gum disease (aged 65–79). The adjusted analysis showed a strongly positive association with multimorbidity for the oldest women (80+ years) with acute diseases and women aged 65–79 with 3 or more acute diseases, compared to patients with no acute diseases (OR ranged from 1.16 to 1.99, p < 0.001). Living in a rural area was significantly associated with lower probability of having multimorbidity. The odds of multimorbidity increased sharply as the number of visits increased, reaching the highest probability in those aged 65–79 years.
Multimorbidity is related to greater use of health care services and higher incidence of acute diseases, increasing the burden on primary care services. The differences related to sex and life-stage observed for multimorbidity and acute diseases suggest that further research on multimorbidity should be stratified according to these factors.
Multimorbidity; Chronic disease; Acute disease; Life-stage
Multimorbidity has been linked to elevated healthcare utilization and previous studies have found that socioeconomic status is an important factor associated with multimorbidity. Nonetheless, little is known regarding the impact of multimorbidity and socioeconomic status on healthcare costs and whether inequities in healthcare exist between socioeconomic classes within a universal healthcare system.
This longitudinal study employed the claims database of the National Health Insurance of Taiwan (959 990 enrolees), adopting medication-based Rx-defined morbidity groups (Rx-MG) as a measurement of multimorbidity. Mixed linear models were used to estimate the effects of multimorbidity and socioeconomic characteristics on annual healthcare costs between 2005 and 2010.
The distribution of Rx-MGs and total costs presented statistically significant differences among gender, age groups, occupation, and income class (p < .001). Nearly 80% of the enrolees were classified as multimorbid and low income earners presented the highest prevalence of multimorbidity. After controlling for age and gender, increases in the number of Rx-MG assignments were associated with higher total healthcare costs. After controlling for the effects of Rx-MG assignment and demographic characteristics, physicians, paramedical personnel, and public servant were found to generate higher total costs than typical employees/self-employed enrolees, while low-income earners generated lower costs. High income levels were also found to be associated with lower total costs. It was also revealed that occupation and multimorbidity have a moderating effect on healthcare cost.
Increases in the prevalence of multimorbidity are associated with higher health care costs. This study determined that instances of multimorbidity varied according to socioeconomic class; likewise there were inequities in healthcare utilization among individuals of various occupations and income levels, even when demographic characteristics and multimorbidity were controlled for. This highlights the importance of socioeconomic status with regard to healthcare utilization. These results indicate that socioeconomic factors should not be discounted when discussing the utilization of healthcare by patients with multimorbidity.
Due to technological progress and improvements in medical care and health policy the average age of patients in primary care is continuously growing. In equal measure, an increasing proportion of mostly elderly primary care patients presents with multiple coexisting medical conditions. To properly assess the current situation of co- and multimorbidity, valid scientific data based on an appropriate data structure are indispensable. CONTENT (CONTinuous morbidity registration Epidemiologic NeTwork) is an ambitious project in Germany to establish a system for adequate record keeping and analysis in primary care based on episodes of care. An episode is defined as health problem from its first presentation by a patient to a doctor until the completion of the last encounter for it. The study aims to describe co- and multimorbidity as well as health care utilization based on episodes of care for the study population of the first participating general practices.
The analyses were based on a total of 39,699 patients in a yearly contact group (YCG) out of 17 general practices in Germany for which data entry based on episodes of care using the International Classification of Primary Care (ICPC) was performed between 1.1.2006 and 31.12.2006. In order to model the relationship between the explanatory variables (age, gender, number of chronic conditions) and the response variables of interest (number of different prescriptions, number of referrals, number of encounters) that were applied to measure health care utilization, we used multiple linear regression.
In comparison to gender, patients' age had a manifestly stronger impact on the number of different prescriptions, the number of referrals and number of encounters. In comparison to age (β = 0.043, p < 0.0001), multimorbidity measured by the number of patients' chronic conditions (β = 0.51, p < 0.0001) had a manifestly stronger impact the number of encounters for the observation period. Moreover, we could observe that the number of patients' chronic conditions had a significant impact on the number of different prescriptions (β = 0.226, p < 0.0001) as well as on the number of referrals (β = 0.3, p < 0.0001).
Documentation in primary care on the basis of episodes of care facilitates an insight to concurrently existing health problems and related medical procedures. Therefore, the resulting data provide a basis to obtain co- and multimorbidity patterns and corresponding health care utilization issues in order to understand the particular complex needs caused by multimorbidity.
Multimorbidity occurs at a younger age in individuals in areas of high socioeconomic deprivation but little is known about the ‘typology’ of multimorbidity in different age groups and its association with socioeconomic status.
To characterise multimorbidity type and most common conditions in a large nationally representative primary care dataset in terms of age and deprivation.
Design and setting
Cross-sectional analysis of 1 272 685 adults in Scotland.
Multimorbidity type of participants (physical-only, mental-only, mixed physical, and mental) and most common conditions were analysed according to age and deprivation.
Multimorbidity increased with age, ranging from 8.1% in those aged 25–34 to 76.1% for those aged ≥75 years. Physical-only (56% of all multimorbidity) was the most common type of multimorbidity in those aged ≥55 years, and did not vary substantially with deprivation. Mental-only was uncommon (4% of all multimorbidity), whereas mixed physical and mental (40% of all multimorbidity) was the most common type of multimorbidity in those aged <55 years and was two- to threefold more common in the most deprived compared with the least deprived in most age groups. Ten conditions (seven physical and three mental) accounted for the top five most common conditions in people with multimorbidity in all age groups. Depression and pain featured in the top five conditions across all age groups. Deprivation was associated with a higher prevalence of depression, drugs misuse, anxiety, dyspepsia, pain, coronary heart disease, and diabetes in multimorbid patients at different ages.
Mixed physical and mental multimorbidity is common across the life-span and is exacerbated by deprivation from early adulthood onwards.
chronic disease; mental health; multimorbidity; primary health care; socioeconomic status
Risk factors for hip fracture are well studied because of the negative impact on patients and the community, with mortality in the first year being almost 30% in the elderly. Age, gender and fall risk-increasing drugs, identified by the National Board of Health and Welfare in Sweden, are well known risk factors for hip fracture, but how multimorbidity level affects the risk of hip fracture during use of fall risk-increasing drugs is to our knowledge not as well studied. This study explored the relationship between use of fall risk-increasing drugs in combination with multimorbidity level and risk of hip fracture in an elderly population.
Data were from Östergötland County, Sweden, and comprised the total population in the county aged 75 years and older during 2006. The odds ratio (OR) for hip fracture during use of fall risk-increasing drugs was calculated by multivariate logistic regression, adjusted for age, gender and individual multimorbidity level. Multimorbidity level was estimated with the Johns Hopkins ACG Case-Mix System and grouped into six Resource Utilization Bands (RUBs 0–5).
2.07% of the study population (N = 38,407) had a hip fracture during 2007. Patients using opioids (OR 1.56, 95% CI 1.34-1.82), dopaminergic agents (OR 1.78, 95% CI 1.24-2.55), anxiolytics (OR 1.31, 95% CI 1.11-1.54), antidepressants (OR 1.66, 95% CI 1.42-1.95) or hypnotics/sedatives (OR 1.31, 95% CI 1.13-1.52) had increased ORs for hip fracture after adjustment for age, gender and multimorbidity level. Vasodilators used in cardiac diseases, antihypertensive agents, diuretics, beta-blocking agents, calcium channel blockers and renin-angiotensin system inhibitors were not associated with an increased OR for hip fracture after adjustment for age, gender and multimorbidity level.
Use of fall risk-increasing drugs such as opioids, dopaminergic agents, anxiolytics, antidepressants and hypnotics/sedatives increases the risk of hip fracture after adjustment for age, gender and multimorbidity level. Fall risk-increasing drugs, high age, female gender and multimorbidity level, can be used to identify high-risk patients who could benefit from a medication review to reduce the risk of hip fracture.
Hip fracture; Multimorbidity level; Fall risk-increasing drugs; Elderly; Medication review; Sweden