Challenges of managing people with multimorbidity in today’s healthcare systems

Multimorbidity is a growing issue and poses a major challenge to health care systems around the world. Multimorbidity is related to ageing but many studies have now shown that it is also socially patterned, being more common and occurring at an earlier age in areas of high socioeconomic deprivation. There is lack of research on patients with multimorbidity, and thus guidelines are based on single-conditions. Polypharmacy is common in multimorbidity, increasing drug-disease and drug-drug interactions. Multimorbid patients need holistic care, but secondary care services are highly specialised and thus are often duplicative and fragmented and thus increase treatment burden in multimorbid patients. The cost of care is high in multimorbidity, due to high rates of primary and secondary care consultations and unplanned hospital admissions. The combination of mental and physical conditions increases complexity of care, and costs. Mental-physical multimorbidity is especially common in deprived areas. General practitioners and primary care teams have a key role in managing patients with multimorbidity, using a patient-centred generalist approach. Consultation length and continuity of care may need to be substantially enhanced in order to enable such patients. This will require a radical change in how health care systems are organised and funded in order to effectively meet the challenges of multimorbidity

The association between perceived stress and mortality among people with multimorbidity: a prospective population-based cohort study

Multimorbidity is common and is associated with poor mental health and high mortality. Nevertheless, no studies have evaluated whether mental health may affect the survival of people with multimorbidity. We investigated the association between perceived stress and mortality in people with multimorbidity by following a population-based cohort of 118,410 participants from the Danish National Health Survey 2010 for up to 4 years. Information on perceived stress and lifestyle was obtained from the survey. We assessed multimorbidity using nationwide register data on 39 conditions and identified 4,229 deaths for the 453,648 person-years at risk. Mortality rates rose with increasing levels of stress in a dose-response relationship (P-trend < 0.0001), independently of multimorbidity status. Mortality hazard ratios (highest stress quintile vs. lowest) were 1.51 (95% confidence interval (CI): 1.25, 1.84) among persons without multimorbidity, 1.39 (95% CI: 1.18, 1.64) among those with 2 or 3 conditions, and 1.43 (95% CI: 1.18, 1.73) among those with 4 or more conditions, when adjusted for disease severities, lifestyle, and socioeconomic status. The numbers of excess deaths associated with high stress were 69 among persons without multimorbidity, 128 among those with 2 or 3 conditions, and 255 among those with 4 or more conditions. Our findings suggested that perceived stress contributes significantly to higher mortality rates in a dose-response pattern, and more stress-associated deaths occurred in people with multimorbidity

Secondary analysis of data on comorbidity/multimorbidity: a call for papers

Despite the high proportion and growing number of people with comorbidity/multimorbidity, clinical trials often exclude this group, leading to a limited evidence base to guide policy and practice for these individuals [1–5]. This evidence gap can potentially be addressed by secondary analysis of studies that were not originally designed to specifically examine comorbidity/multimorbidity, but have collected information from participants on co-occurring conditions. For example, secondary data analysis from randomized controlled trials may shed light on whether there is a differential impact of interventions on people with comorbidity/multimorbidity. Furthermore, data regarding comorbidity/multimorbidity can often be obtained from registration networks or administrative data sets

Adapting clinical guidelines to take account of multimorbidity

Most people with a chronic condition have multimorbidity, but clinical guidelines almost entirely focus on single conditions. It will never be possible to have good evidence for every possible combination of conditions, but guidelines could be made more useful for people with multimorbidity if they were delivered in a format that brought together relevant recommendations for different chronic conditions and identified synergies, cautions, and outright contradictions. We highlight the problem that multimorbidity poses to clinicians and patients using guidelines for single conditions and propose ways of making them more useful for people with multimorbidity

The coexistence of terms to describe the presence of multiple concurrent diseases

Background: Consensus on terminology for multiple diseases is lacking. Because of the clinical relevance and social impact of multiple concurrent diseases, it is important that concepts are clear. Objective: To highlight the diversity of terms in the literature referring to the presence of multiple concurrent diseases/conditions and make recommendations. Design: A bibliometric analysis of English-language publications indexed in the MEDLINE database from 1970 to 2012 for the terms comorbidity, multimorbidity, polymorbidity, polypathology, pluripathology, multipathology, and multicondition, and a review of definitions of multimorbidity found in English-language publications indexed from 1970 to 2012 in the MEDLINE and SCOPUS databases. Results: Comorbidity was used in 67,557 publications, multimorbidity in 434, and the other terms in three to 31 publications. At least 144 publications used the term comorbidity without referring to an index disease. Thirteen general definitions of multimorbidity were identified, but only two were frequently used (91% of publications). The most frequently used definition (48% of publications) was “more than one or multiple chronic or long-term diseases/conditions”. Multimorbidity was not defined in 51% of the publications using the term. Conclusions: Comorbidity was overwhelmingly used to describe any clinical entity coexisting with an index disease under study. Multimorbidity was the term most frequently used when no index disease was designated. Several definitions of multimorbidity were found. However, most authors using the term did not define it. The use of clearly defined terms in the literature is recommended until a general consensus on the terminology of multiple coexistent diseases is reached.Journal of Comorbidity 2013;3(1):4–9 

Multimorbidity as an important issue among women: results of gender difference investigation in a large population-based cross-sectional study in West Asia

Objectives: To investigate the impact of gender on multimorbidity in northern Iran. Design: A cross-sectional analysis of the Golestan cohort data. Setting: Golestan Province, Iran. Study population: 49 946 residents (age 40–75 years) of Golestan Province, Iran. Main outcome measures: Researchers collected data related to multimorbidity, defined as co-existence of two or more chronic diseases in an individual, at the beginning of a representative cohort study which recruited its participants from 2004 to 2008. The researchers utilised simple and multiple Poisson regression models with robust variances to examine the simultaneous effects of multiple factors. Results: Women had a 25.0% prevalence of multimorbidity, whereas men had a 13.4% prevalence (p<0.001). Women of all age-groups had a higher prevalence of multimorbidity. Of note, multimorbidity began at a lower age (40–49 years) in women (17.3%) compared with men (8.6%) of the same age (p<0.001). This study identified significant interactions between gender as well as socioeconomic status, ethnicity, physical activity, marital status, education level and smoking (p<0.01). Conclusion: Prevention and control of multimorbidity requires health promotion programmes to increase public awareness about the modifiable risk factors, particularly among women

The Challenges of Multimorbidity from the Patient Perspective

BACKGROUND Although multiple co-occurring chronic illnesses within the same individual are increasingly common, few studies have examined the challenges of multimorbidity from the patient perspective. OBJECTIVE The aim of this study is to examine the self-management learning needs and willingness to see non-physician providers of patients with multimorbidity compared to patients with single chronic illnesses. DESIGN. This research is designed as a cross-sectional survey. PARTICIPANTS Based upon ICD-9 codes, patients from a single VHA healthcare system were stratified into multimorbidity clusters or groups with a single chronic illness from the corresponding cluster. Nonproportional sampling was used to randomly select 720 patients. MEASUREMENTS Demographic characteristics, functional status, number of contacts with healthcare providers, components of primary care, self-management learning needs, and willingness to see nonphysician providers. RESULTS Four hundred twenty-two patients returned surveys. A higher percentage of multimorbidity patients compared to single morbidity patients were "definitely" willing to learn all 22 self-management skills, of these only 2 were not significant. Compared to patients with single morbidity, a significantly higher percentage of patients with multimorbidity also reported that they were "definitely" willing to see 6 of 11 non-physician healthcare providers. CONCLUSIONS Self-management learning needs of multimorbidity patients are extensive, and their preferences are consistent with team-based primary care. Alternative methods of providing support and chronic illness care may be needed to meet the needs of these complex patients.US Department of Veterans Affairs (01-110, 02-197); Agency for Healthcare Research and Quality (K08 HS013008-02

Health-related preferences of older patients with multimorbidity: the protocol for an evidence map

Introduction: Interaction of conditions and treatments, complicated care needs and substantial treatment burden make patient–physician encounters involving multimorbid older patients highly complex. To optimally integrate patients’ preferences, define and prioritise realistic treatment goals and individualise care, a patient-centred approach is recommended. However, the preferences of older patients, who are especially vulnerable and frequently multimorbid, have not been systematically investigated with regard to their health status. The purpose of this evidence map is to explore current research addressing health-related preferences of older patients with multimorbidity, and to identify the knowledge clusters and research gaps. Methods and analysis: To identify relevant research, we will conduct searches in the electronic databases MEDLINE, EMBASE, PsycINFO, PSYNDEX, CINAHL, Social Science Citation Index, Social Science Citation Index Expanded and the Cochrane library from their inception. We will check reference lists of relevant articles and carry out cited reference research (forward citation tracking). Two independent reviewers will screen titles and abstracts, check full texts for eligibility and extract the data. Any disagreement will be resolved and consensus reached with the help of a third reviewer. We will include both qualitative and quantitative studies, and address preferences from the patients’ perspectives in a multimorbid population of 60 years or older. There will be no restrictions on the publication language. Data extraction tables will present study and patient characteristics, aim of study, methods used to identify preferences and outcomes (ie, type of preferences). We will summarise the data using tables and figures (ie, bubble plot) to present the research landscape and to describe clusters and gaps. Ethics and dissemination: Due to the nature of the proposed evidence map, ethics approval will not be required. Results from our research will be disseminated by means of specifically prepared materials for patients, at relevant (inter)national conferences and via publication in peer-reviewed journals

Coping with complexity: working beyond the guidelines for patients with multimorbidities

Primary care physicians believe they are delivering evidence-based care, understanding that adherence to evidence-based clinical guidelines results in tangible benefits in the populations for which they were developed. Unfortunately, most clinical guidelines are based on trial populations which are very different to primary care populations [1], and do not reflect the reality of multimorbidity in general practice [2–6]. Since patients with multimorbidity account for around eight in every 10 primary care consultations [7], it is unsurprising that many primary care physicians find managing these patients challenging. Additionally, current clinical guidelines do not provide guidance on how best to prioritize recommendations for individuals with multimorbidity, and may therefore result in over-treatment and polypharmacy, and a risk of overlooking patient preferences [2,8]. Journal of Comorbidity 2015;5(1):11–1

Religious Activity Participation and Self-Rated Health Among Older Population in Indonesia

A number of studies have documented a positive and robust relationship between religious activity and health outcomes. The purpose of the study was to examine the relationship between religious activity participation and self-rated health (SRH) among older population in Indonesia. Data were obtained from 2,915 respondents 60 years and older from the Indonesian Family Life Survey 4 (2007). SRH was assessed by a single-item health measure with four options: “very healthy,” “somewhat healthy,” “somewhat unhealthy,” and “unhealthy”. Logistic regression were used to examine the relationship of the religious activity participation and SRH. Bivariate analysis revealed that religious activity participation was significantly associated with SRH. Multivariate analysis shows that among participants who participated in religious activity, the likehood of a better SRH is increased (OR = 1.422; 95% CI = 1.203 to 1.682) after controlling for sociodemographic variables, socio-economic status (SES), health behaviour and number of Non Communicable Diseases (NCDs). This findings suggest that religious activity participation has an important effect on self-rated health status. Longitudinal studies are needed to help elucidate mechanisms and the order and direction of effects