| Publons ID | (not set) |
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| Wos ID | WOS:000612476300140 |
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| Doi | 10.7189/jogh.10.020428 |
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| Title | The contribution of service density and proximity to geographical inequalities in health care utilisation in Indonesia: A nation-wide multilevel analysis |
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| First Author | |
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| Last Author | |
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| Authors | Mulyanto, J; Kunst, AE; Kringos, DS; |
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| Publish Date | DEC 2020 |
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| Journal Name | JOURNAL OF GLOBAL HEALTH |
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| Citation | 4 |
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| Abstract | a:4:{i:0;s:364:"Background Geographical inequalities in access to health care have only recently become a global health issue. Little evidence is available about their determinants. This study investigates the associations of service density and service proximity with health care utilisation in Indonesia and the parts they may play in geographic inequalities in health care use.";i:1;s:529:"Methods Using data from a nationally representative survey (N = 649625), we conducted a cross-sectional study and employed multilevel logistic regression to assess whether supply-side factors relating to service density and service proximity affect the variability of outpatient and inpatient care utilisation across 497 Indonesian districts. We used median odds ratios (MORs) to estimate the extent of geographical inequalities. Changes in the MOR values indicated the role played by the supply-side factors in the inequalities.";i:2;s:726:"Results Wide variations in the density and proximity of health care services were observed between districts. Outpatient care utilisation was associated with travel costs (odds ratio (OR) = 0.82, 95% confidence interval (CI) = 0.70-0.97). Inpatient care utilisation was associated with ratios of hospital beds to district population (OR= 1.23, 95% CI = 1.05-1.43) and with travel times (OR = 0.72 95% CI = 0.61-0.86). All in all, service density and proximity provided little explanation for district-level geographic inequalities in either outpatient (MOR = 1.65, 95% Crl = 1.59-1.70 decreasing to 1.61, 95% Crl = 1.56-1.67) or inpatient care utilisation (MOR= 1.63, 95% Crl =1.55-1.69 decreasing to 1.60 95% Crl =1.54-1.66).";i:3;s:485:"Conclusions Supply-side factors play important roles in individual health care utilisation but do not explain geographical inequalities. Variations in other factors, such as the price and responsiveness of services, may also contribute to the inequalities. Further efforts to address geographical inequalities in health care should go beyond the physical presence of health care infrastructures to target issues such as regional variations in the prices and responsiveness of services.";} |
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| Publish Type | Journal |
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| Publish Year | 2020 |
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| Page Begin | (not set) |
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| Page End | (not set) |
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| Issn | 2047-2978 |
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| Eissn | 2047-2986 |
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| Url | https://www.webofscience.com/wos/woscc/full-record/WOS:000612476300140 |
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| Author | dr. JOKO MULYANTO, S.Ked, M.Sc., PhD |
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| File | 123970.pdf |
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