Author Year, Country | Aim | Design Measurements | Statistical Analysis | Conclusion |
1. Bähler et al. (2015) SWITZERLAND | To examine the association between multi-morbidity, healthcare utilization and costs in the community. | Quantitative, cross-sectional. PCG. | Descriptive statistics. | The burden of multi-morbidity is a fundamental aspect the management of patients in health service delivery systems and for healthcare policy debates about resource allocation. Strategies for better coordination of multi-morbid patients are urgently needed. |
2. Glynn et al. (2011) IRELAND | To examine the prevalence and associated healthcare utilization and cost of patients with multimorbidity. | Quantitative ICPC-2, HSU, HCC. | Binary Logistic regression. | Multi-morbidity is common in primary care and in a system with strong gate-keeping is associated with high healthcare utilization and cost. Interventions to address quality and cost associated with multi-morbidity must focus on primary as well as secondary care. |
3. Holzhausen et al. (2011) GERMANY | To develop a conceptual framework and a set of standardized instruments and indicators for continuous monitoring of multi-morbidity and associated healthcare needs in the population. | Quantitative, longitudinal. ADL, BSSS, DSST, CAPI, CATI, IPANAS, OMAHA, MILVA, PCI, PHQ, SWLS, QoL, FLQM. Self-administered questionnaire. | Not reported. | This study added methodological and content-specific discourses on human resources for maintaining quality of life and autonomy throughout old age, even in the face of multiple health complaints. |
4. Jowsey et al. (2013) AUSTRALIA | To identify how much time people with multiple chronic conditions spend managing their health that will help policy makers and health service providers make decisions about areas in which patients need support. | Quantitative, cross sectional survey. Recall questionnaire COPD, NDSS, NSA. | Descriptive analyses. | Multi-morbidity imposes considerable time burdens on patients. Ageing is associated with increasing rates of multi-morbidity. Many older adults experience high demands on their time to manage their health in the face of decreasing energy and mobility. Their time use must be considered in health service delivery and health system reform. |
5. Nunes et al. (2015) BRAZIL | To verify the prevalence and distribution of multi-morbidity in Brazilian older adults. | Quantitative. Cross-sectional. Face-to-face interviews. Structured self-reported questionnaires. | Stat version 12. | Multimorbidity frequency was high in the sample studied. The social inequities identified increased the challenges faced by the health system in the management of multimorbidity, requiring comprehensive and multidimensional care. The combinations of diseases can provide an initial reason for including multimorbidity in Brazilian clinical protocols. |
6. Orueta et al. (2014) USA | To present an overview of the prevalence and costs of multi-morbidity by socio-economic levels in the whole Basque population. | Quantitative cross-sectional. | Descriptive statistics. | Multi-morbidity is common and its prevalence increases with age and an unfavorable socio-economic environment. The costs of care for patients with several chronic conditions cannot be described as the average sum of their individual pathologies. Given the ageing population, multi-morbidity and its consequences should be taken into account in healthcare policy, the organization of care and medical research. |
7. Perruccio et al. (2012) CANADA | To investigate the association between multi-morbidity―a construct comprising several health domains―and overall self-rated health (SRH), an important chronic disease health outcome. | Quantitative survey. SRH. | Bivariate analyses. | The findings suggested that focus on one domain in health research may limit the researchers’ ability to understand health outcomes for which SRH is a predictor. |