The incidence of multimorbidity and patterns in accumulation of chronic conditions: A systematic review.
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SUBMITTER: Kudesia P
PROVIDER: S-EPMC8287424 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDespite the growing utilization of data-driven methods to investigate multimorbidity patterns, there is currently no consensus or guidance on the conditions to include when identifying patterns. This scoping review aims to systematically examine the nature of conditions included in existing studies using data-driven techniques.MethodsA comprehensive search of three electronic databases (MEDLINE, Web of Science and Scopus) was conducted to identify relevant publications from inception to 28 February 2022 using predefined search terms and inclusion/exclusion criteria. The reference lists and citations of relevant papers were also searched.ResultsAmong 7326 search results, 5444 relevant articles were identified. After screening against the eligibility criteria, 60 articles were included in the review. Half of the reviewed studies reported selection criteria for conditions, with prevalence in the population of interest being the most common criterion (40%). Most studies included at least one neurological [59 (98.3%)], musculoskeletal [58 (96.7%)], respiratory [57 (95.0%)] or mental health [56 (93.3%)] condition. In contrast, only a small proportion of studies included skin [17 (28.3%)], infections [14 (23.3%)] or autoimmune conditions [10 (16.7%)]. Nine conditions (hypertension, diabetes, cancer, arthritis, COPD, asthma, depression, stroke and osteoporosis) were included by more than half of the studies.ConclusionsThis review highlights the considerable heterogeneity among the conditions included in analyses of multimorbidity patterns. Researchers should provide a clear rationale for the selection of conditions to facilitate comparisons across studies and ensure reproducibility, as well as consider selecting a diverse range of conditions to capture the complexity of multimorbidity.
| S-EPMC10843942 | biostudies-literature
Project description:BackgroundOlder populations often suffer from multimorbidity and guidelines for each condition are often associated with recommended drug therapy management. Yet, how different and specific multimorbidity is associated with number and type of multi-drug therapies in general populations is unknown.AimThe aim of this systematic review was to synthesize the current evidence on patterns of multi-drug prescribing in family practice.MethodsA systematic review on six common chronic conditions: diabetes mellitus, cardiovascular disease, cerebrovascular disease, chronic obstructive pulmonary disease (COPD), osteoarthritis and depression was conducted, with a focus on studies which looked at any potential combination of two or more multimorbidity. Studies were identified from searches of MEDLINE, EMBASE, PsychINFO, the Allied and Complementary Medicine Database (AMED) and the Health Management Information Consortium (HMIC) databases from 1960 to 2013.ResultsA total of eleven articles were selected based on study criteria. Our review identified very few specific studies which had explicitly investigated the association between multimorbidity and multi-drug therapy. Relevant chronic conditions literature showed nine observational studies and two reviews of comorbid depression drug treatment. Most (seven) of the articles had focused on the chronic condition and comorbid depression and whether antidepressant management had been optimal or not, while four studies focused on other multimorbidities mainly heart failure, COPD and diabetes.ConclusionsVery few studies have investigated associations between specific multimorbidity and multi-drug therapy, and most currently focus on chronic disease comorbid depression outcomes. Further research needs to identify this area as key priority for older populations who are prescribed high levels of multiple drug therapy.
| S-EPMC5942538 | biostudies-literature
Project description:Patients with multimorbidity are commonly seen in primary care. An increasing number of multimorbidity patterns are being reported in the Western literature with a few from Asia. The main objective of this systematic review was to describe patterns of associative multimorbidity, defined as associations beyond chance or patterns of diseases, in the Asian population. We searched Medical Literature Analysis and Retrieval System Online (MEDLINE (Ovid)), Excerpta Medica Database (EMBASE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science (Clarivate Analytics), and Scopus (Elsevier) databases from their inception to April 22, 2019 using medical subject headings, keywords in titles, abstracts, and text. We used the Modified Newcastle-Ottawa Scale for risk-of-bias assessment. Eight articles from China, India, Indonesia, and Japan met the inclusion criteria. Patterns of associative multimorbidity were reported as dyadic/triadic disease combinations or disease clusters. The most common multimorbidity pattern, "cardiovascular and metabolic diseases," was identified in six of eight articles. The other four multimorbidity patterns are comprised of "mental health problems," "degenerative diseases," pulmonary diseases," and "cancer diseases." The eight articles showed methodological heterogeneity in terms of the list of chronic diseases, ascertainment of multimorbidity, statistical methods, and study populations. This systematic review identified five common patterns of associative multimorbidity in Asia. "Cardiovascular and metabolic diseases" and "mental diseases" were two patterns that were similarly reported in the Western world. Alignment of the definition of multimorbidity and the statistical methodology are needed to identify the unique patterns of multimorbidity in Asia so that clinical practice guidelines on multimorbidity can be developed for the Asian population.
| S-EPMC8277911 | biostudies-literature
Project description:To describe the potential workload for patients with multimorbidity when applying existing clinical practice guidelines.Systematic analysis of clinical practice guidelines for chronic conditions and simulation modelling approach.National Guideline Clearinghouse index of US clinical practice guidelines.We identified the most recent guidelines for adults with 1 of 6 prevalent chronic conditions in primary care (ie hypertension, diabetes, coronary heart disease (CHD), chronic obstructive pulmonary disease (COPD), osteoarthritis and depression).From the guidelines, we extracted all recommended health-related activities (HRAs) such as drug management, self-monitoring, visits to the doctor, laboratory tests and changes of lifestyle for a patient aged 45-64 years with moderate severity of conditions.For each HRA identified, we performed a literature review to determine the potential workload in terms of time spent on this HRA. Then, we used a simulation modelling approach to estimate the potential workload needed to comply with these recommended HRAs for patients with several of these chronic conditions.Depending on the concomitant chronic condition, patients with 3 chronic conditions complying with all the guidelines would have to take a minimum of 6 to a maximum of 13 medications per day, visit a health caregiver a minimum of 1.2 to a maximum of 5.9 times per month and spend a mean (SD) of 49.6 (27.3) to 71.0 (34.5) h/month in HRAs. The potential workload increased greatly with increasing number of concomitant conditions, rising to 18 medications per day, 6.6 visits per month and 80.7 (35.8) h/month in HRAs for patients with 6 chronic conditions.
| S-EPMC4809109 | biostudies-other
Project description:ObjectiveTo characterise in details a random sample of multimorbid patients in Switzerland and to evaluate the clustering of chronic conditions in that sample.Methods100 general practitioners (GPs) each enrolled 10 randomly selected multimorbid patients aged ?18 years old and suffering from at least three chronic conditions. The prevalence of 75 separate chronic conditions from the International Classification of Primary Care-2 (ICPC-2) was evaluated in these patients. Clusters of chronic conditions were studied in parallel.ResultsThe final database included 888 patients. Mean (SD) patient age was 73.0 (12.0) years old. They suffered from 5.5 (2.2) chronic conditions and were prescribed 7.7 (3.5) drugs; 25.7% suffered from depression. Psychological conditions were more prevalent among younger individuals (?66 years old). Cluster analysis of chronic conditions with a prevalence ?5% in the sample revealed four main groups of conditions: (1) cardiovascular risk factors and conditions, (2) general age-related and metabolic conditions, (3) tobacco and alcohol dependencies, and (4) pain, musculoskeletal and psychological conditions.ConclusionGiven the emerging epidemic of multimorbidity in industrialised countries, accurately depicting the multiple expressions of multimorbidity in family practices' patients is a high priority. Indeed, even in a setting where patients have direct access to medical specialists, GPs nevertheless retain a key role as coordinators and often as the sole medical reference for multimorbid patients.
| S-EPMC5734197 | biostudies-literature
Project description:ObjectivesTo estimate the frequency of chronic conditions and geriatric syndromes in older patients admitted to hospital because of an exacerbation of their chronic conditions, and to identify multimorbidity clusters in these patients.DesignMulticentre, prospective cohort study.SettingInternal medicine or geriatric services of five general teaching hospitals in Spain.Participants740 patients aged 65 and older, hospitalised because of an exacerbation of their chronic conditions between September 2016 and December 2018.Primary and secondary outcome measuresActive chronic conditions and geriatric syndromes (including risk factors) of the patient, a score about clinical management of chronic conditions during admission, and destination at discharge were collected, among other variables. Multimorbidity patterns were identified using fuzzy c-means cluster analysis, taking into account the clinical management score. Prevalence, observed/expected ratio and exclusivity of each chronic condition and geriatric syndrome were calculated for each cluster, and the final solution was approved after clinical revision and discussion among the research team.Results740 patients were included (mean age 84.12 years, SD 7.01; 53.24% female). Almost all patients had two or more chronic conditions (98.65%; 95% CI 98.23% to 99.07%), the most frequent were hypertension (81.49%, 95% CI 78.53% to 84.12%) and heart failure (59.86%, 95% CI 56.29% to 63.34%). The most prevalent geriatric syndrome was polypharmacy (79.86%, 95% CI 76.82% to 82.60%). Four statistically and clinically significant multimorbidity clusters were identified: osteoarticular, psychogeriatric, cardiorespiratory and minor chronic disease. Patient-level variables such as sex, Barthel Index, number of chronic conditions or geriatric syndromes, chronic disease exacerbation 3 months prior to admission or destination at discharge differed between clusters.ConclusionsIn older patients admitted to hospital because of the exacerbation of chronic health problems, it is possible to define multimorbidity clusters using soft clustering techniques. These clusters are clinically relevant and could be the basis to reorganise healthcare circuits or processes to tackle the increasing number of older, multimorbid patients.Trial registration numberNCT02830425.
| S-EPMC8593730 | biostudies-literature
Project description:BackgroundIt is challenging to use shared decision-making with patients who have a chronic health condition or, especially, multimorbidity. A patient-goal-oriented approach can thus be beneficial. This study aims to identify and evaluate studies on the effects of interventions that support collaborative goal setting or health priority setting compared to usual care for elderly people with a chronic health condition or multimorbidity.MethodsThis systematic review was based on EPOC, PRISMA and MOOSE guidelines. Pubmed, PsychInfo, CINAHL, Web of Science, Embase and the Cochrane Central Register of Controlled Trials were searched systematically. The following eligibility criteria were applied: 1. Randomised (cluster) controlled trials, non-randomised controlled trials, controlled before-after studies, interrupted time series or repeated measures study design; 2. Single intervention directed specifically at collaborative goal setting or health priority setting or a multifactorial intervention including these elements; 3. Study population of patients with multimorbidity or at least one chronic disease (mean age ± standard deviation (SD) incl. age 65). 4. Studies reporting on outcome measures reducible to outcomes for collaborative goal setting or health priority setting.ResultsA narrative analysis was performed. Eight articles describing five unique interventions, including four cluster randomised controlled trials and one randomised controlled trial, were identified. Four intervention studies, representing 904, 183, 387 and 1921 patients respectively, were multifactorial and showed statistically significant effects on the application of goal setting (Patient Assessment of Chronic Illness Care (PACIC) goal setting subscale), the number of advance directives or the inclusion of goals in care plans. Explicit attention for goal setting or priority setting by a professional was a common element in these multifactorial interventions. One study, which implemented a single-factor intervention on 322 patients, did not have significant effects on doctor-patient agreement. All the studies had methodological concerns in varying degrees.ConclusionsCollaborative goal setting and/or priority setting can probably best be integrated in complex care interventions. Further research should determine the mix of essential elements in a multifactorial intervention to provide recommendations for daily practice. In addition, the necessity of methodological innovation and the application of mixed evaluation models must be highlighted to deal with the complexity of goal setting and/or priority setting intervention studies.
| S-EPMC5537926 | biostudies-literature
Project description:IntroductionMultimorbidity 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.MethodsSystematic 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).ResultsWe 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.ConclusionsWell-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.
| S-EPMC4105594 | biostudies-literature
Project description:Background: Psychological functioning plays an important role in medical conditions and impacts patients' quality of life. Previously, many studies have highlighted the association of metacognition to both the development and maintenance of emotional disorders. Recently, several researchers pointed out the relevant role of dysfunctional metacognitive beliefs in the context of chronic diseases. Hence, dysfunctional metacognitive beliefs could be directly related to anxiety and depression, regardless of the medical condition's expression. The aim of this systematic review was to summarize the available evidence regarding the association of metacognition with anxiety, depression, and perceived quality of life, in the context of medical conditions, according to Wells' theory. Methods: A systematic review based on electronic bibliographic databases (PsycINFO, PubMed, Scopus, Web of Science, and Web of Knowledge) of scientific literature was carried out. Studies involving patients evaluated in clinical settings were included in the analysis. Results: Our findings indicated that metacognition appears to be related to anxiety, depression, and quality of life in patients with medical chronic conditions. Therefore, dysfunctional metacognitive beliefs might be a relevant factor associated with the process of adapting to illness. Conclusions: The additional evaluation of metacognitive factors in the context of several medical chronic conditions appears valuable. Due to the rising interest in the study of metacognition, suggestions for future research have also been provided.
| S-EPMC6965316 | biostudies-literature
Project description:A person's beliefs about their chronic condition (illness representations) influence health and treatment outcomes. Recently, researchers have used clustering approaches to identify subgroups with different patterns of beliefs about their illness, with some subgroups having more favorable health outcomes than others. To date, these findings have not been synthesized. The purpose of this systematic review of the literature was to synthesize results of studies that used clustering approaches to analyze illness representation in chronic disease populations, in order to characterize the clusters and their relationship to health outcomes. Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines we searched CINAHL, PsycInfo, and PubMed. To be included, studies had to be (a) peer reviewed, (b) in English, (c) performing a cluster analysis (CA), latent class analysis (LCA), or latent profile analysis (LPA), (d) using only illness representation (IR) subscales to form clusters, (e) measuring illness representation with the Illness Perception Questionnaire (IPQ-R), (f) in a chronic condition sample, and (g) measuring health-related outcomes. Twelve studies were included. Across studies, the number of clusters found ranged from two to three. In all studies, an association was found between illness representation group and at least one of their health outcomes. Illness representation clusters associated with favorable outcomes usually included lower disease-related consequences, fewer symptoms, less negative emotion, and a more stable disease pattern. The results of this review indicate that the relationship between the patterns of the illness representation profiles and health outcomes transcend diseases. Additionally, some dimensions of illness representation may be more important drivers of group membership than others.
| S-EPMC7186157 | biostudies-literature