Health system performance evaluation

Multimorbidity and Complex Multimorbidity in India: Findings from the 2017–2018 Longitudinal Ageing Study in India (LASI)Complex multimorbidity refers to the co-occurrence of three or more chronic illnesses across >2 body systems, which may identify persons in need of additional medical support and treatment. There is a scarcity of evidence on the differences in patient outcomes between non-complex (≥2 conditions) and complex multimorbidity groups. We evaluated the prevalence and patient outcomes of complex multimorbidity and compared them to non-complex multimorbidity. We included 30,489 multimorbid individuals aged ≥45 years from the Longitudinal Ageing Study in India (LASI) from wave-1 conducted in 2017–2018. We employed a log link in generalised linear models (GLM) to identify possible risk factors presenting the adjusted prevalence–risk ratio (APRR) and adjusted prevalence–risk difference (APRD) with 95% confidence interval. The prevalence of complex multimorbidity was 34.5% among multimorbid individuals. Participants residing in urban areas [APRR: 1.10 (1.02, 1.20)], [APRD: 0.04 (0.006, 0.07)] were more likely to report complex multimorbidity. Participants with complex multimorbidity availed significantly higher inpatient department services and had higher expenditure as compared to the non-complex multimorbidity group. Our findings have major implications for healthcare systems in terms of meeting the requirements of people with complicated multimorbidity, as they have significantly higher inpatient health service utilisation, higher medical costs, and poorer self-rated health.

Frontiers | Provincial heterogeneity in the management of care cascade for hypertension, diabetes, and dyslipidaemia in China: Analysis of nationally representative population-based surveyBackgroundThis study aims to examine (1) province-level variations in the levels of cardiovascular disease (CVD) risk and behavioral risk for CVDs, (2) provi...

Rural and urban differences in health system performance among older Chinese adults: cross-sectional analysis of a national sample - BMC Health Services ResearchBackground Despite improvement in health outcomes over the past few decades, China still experiences striking rural-urban health inequalities. There is limited research on the rural-urban differences in health system performance in China. Method We conducted a cross-sectional analysis to compare health system performance between rural and urban areas in five key domains of the health system: effectiveness, cost, access, patient-centredness and equity, using data from the WHO Study on Global AGEing and adult health (SAGE), China. Multiple logistic and linear regression models were used to assess the first four domains, adjusting for individual characteristics, and a relative index of inequality (RII) was used to measure the equity domain. Findings Compared to urban areas, rural areas had poorer performance in the management and control of hypertension and diabetes, with more than 50% lower odds of having breast (AOR = 0.44; 95% CI: 0.30, 0.64) and cervical cancer screening (AOR = 0.49; 95% CI: 0.29, 0.83). There was better performance in rural areas in the patient-centredness domain, with more than twice higher odds of getting prompt attention, respect, clarity of the communication with health provider and involvement in decision making of the treatment in inpatient care (AOR = 2.56, 2.15, 2.28, 2.28). Although rural residents incurred relatively less out-of-pocket expenditures (OOPE) for outpatient and inpatient services than urban residents, they were more likely to incur catastrophic expenditures on health (AOR = 1.30; 95% CI 1.16, 1.44). Wealth inequality was found in many indicators related to the effectiveness, costs and access domains in both rural and urban areas. Rural areas had greater inequalities in the management of hypertension and coverage of cervical cancer (RII = 7.45 vs 1.64). Conclusion Our findings suggest that urban areas have achieved better prevention and management of non-communicable disease than rural areas, but access to healthcare was equivalent. A better understanding of the causes of the observed variations is needed to develop appropriate policy interventions which address these disparities.

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