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  1. AU="Ambade, Preshit Nemdas"
  2. AU="Sarmah, Deepraj"
  3. AU="Little, James W."
  4. AU="Templin, Zoe"
  5. AU="Levick, Samantha"
  6. AU="Tatakis, Fotis"
  7. AU="de Vries, Florentine R"
  8. AU="Tsai, Y-T" AU="Tsai, Y-T"
  9. AU="Gonakoti, Sriram"
  10. AU="Wulf, J"
  11. AU="Mardsen, D"
  12. AU="James, David B A"
  13. AU="Montabone, Erika"
  14. AU="Susan J. Burke"
  15. AU="Chen, Yuguang"
  16. AU="Zhao, Zhenghuan"
  17. AU="De Chiara, Anna Rosaria"
  18. AU="Savage, Anne"
  19. AU="Salamanca, Albert"
  20. AU="Zhong, Xiao-Song"
  21. AU="Deguchi, Masashi"
  22. AU="Żmuda, J"
  23. AU="Liao, Yanyan"
  24. AU="Zhu, Jin-Wei"
  25. AU="Khan, Azkia"
  26. AU="Folkman, Judah"
  27. AU=Bhatia Rajesh
  28. AU="Thobois, Stéphane"
  29. AU="Lai, Chien-Chih"
  30. AU="Ahn, Bo Young"
  31. AU="Jeje, Olamide"
  32. AU="Fine, Samson W"
  33. AU="Riemann, Burkhard"
  34. AU="Nazir, Ahsan"
  35. AU="Kawakita, Emi"
  36. AU="Wang, Junnian"
  37. AU="Nie, Chong"

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  1. Artikel: Wealth Status and Health Insurance Enrollment in India: An Empirical Analysis.

    Ambade, Preshit Nemdas / Gerald, Joe / Rahman, Tauhidur

    Healthcare (Basel, Switzerland)

    2023  Band 11, Heft 9

    Abstract: Since 2005, health insurance (HI) coverage in India has significantly increased, largely because of the introduction of government-funded pro-poor insurance programs. As a result, the determinants of HI enrollment and their relative importance may have ... ...

    Abstract Since 2005, health insurance (HI) coverage in India has significantly increased, largely because of the introduction of government-funded pro-poor insurance programs. As a result, the determinants of HI enrollment and their relative importance may have changed. Using National Family Health Survey (NFHS)-4 data, collected in 2015-2016, and employing a Probit regression model, we re-examine the determinants of household HI enrollment. Then, using a multinomial logistic regression model, we estimate the relative risk ratio for enrollment in different HI schemes. In comparison to the results on the determinants of HI enrollment using the NFHS data collected in 2005-2006, we find a decrease in the wealth gap in public HI enrollment. Nonetheless, disparities in enrollment remain, with some changes in those patterns. Households with low assets have lower enrollments in private and community-based health insurance (CBHI) programs. Households with a higher number of dependents have a higher likelihood of HI enrollment, especially in rural areas. In rural areas, poor Scheduled Caste and Scheduled Tribe households are more likely to be enrolled in public HI than the general Caste households. In urban areas, Muslim households have a lower likelihood of enrollment in any HI. The educational attainment of household heads is positively associated with enrollment in private HI, but it is negatively associated with enrollment in public HI. Since 2005-2006, while HI coverage has improved, disparities across social groups remain.
    Sprache Englisch
    Erscheinungsdatum 2023-05-07
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2721009-1
    ISSN 2227-9032
    ISSN 2227-9032
    DOI 10.3390/healthcare11091343
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel: COVID-19 Pandemic: Did Strict Mobility Restrictions Save Lives and Healthcare Costs in Maharashtra, India?

    Ambade, Preshit Nemdas / Thavorn, Kednapa / Pakhale, Smita

    Healthcare (Basel, Switzerland)

    2023  Band 11, Heft 14

    Abstract: Introduction: Maharashtra, India, remained a hotspot during the COVID-19 pandemic. After the initial complete lockdown, the state slowly relaxed restrictions. We aim to estimate the lockdown's impact on COVID-19 cases and associated healthcare costs.: ...

    Abstract Introduction: Maharashtra, India, remained a hotspot during the COVID-19 pandemic. After the initial complete lockdown, the state slowly relaxed restrictions. We aim to estimate the lockdown's impact on COVID-19 cases and associated healthcare costs.
    Methods: Using daily case data for 84 days (9 March-31 May 2020), we modeled the epidemic's trajectory and predicted new cases for different phases of lockdown. We fitted log-linear models to estimate the growth rate, basic (R
    Results: The estimated median R
    Conclusion: Maharashtra's early public health response delayed the pandemic and averted new cases and deaths during the first wave of the pandemic. However, we recommend that such restrictions be carefully used while considering the local socio-economic realities in countries like India.
    Sprache Englisch
    Erscheinungsdatum 2023-07-24
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2721009-1
    ISSN 2227-9032
    ISSN 2227-9032
    DOI 10.3390/healthcare11142112
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Explaining Caste-Based Disparities in Enrollment for National Health Insurance Program in India: a Decomposition Analysis.

    Ambade, Preshit Nemdas / Pakhale, Smita / Rahman, Tauhidur

    Journal of racial and ethnic health disparities

    2022  Band 10, Heft 4, Seite(n) 1918–1932

    Abstract: Background: Caste plays a significant role in individual healthcare access and health outcomes in India. Discrimination against low-caste communities contributes to their poverty and poor health outcomes. The Rashtriya Swasthya Bima Yojana (RSBY), a ... ...

    Abstract Background: Caste plays a significant role in individual healthcare access and health outcomes in India. Discrimination against low-caste communities contributes to their poverty and poor health outcomes. The Rashtriya Swasthya Bima Yojana (RSBY), a national health insurance program, was created to improve healthcare access for the poor. This study accounts for caste-based disparities in RSBY enrollment in India by decomposing the contributions of relevant factors.
    Methods: Using the data from the 2015-2016 round of the National Family Health Survey, we compare RSBY enrollment rates of low-caste and high-caste households. We use a non-linear extension of Oaxaca-Blinder decomposition and estimate two models by pooling coefficients across the comparison groups and all caste groups. Enrollment differentials are decomposed into individual- and household-level characteristics, media access, and state-level fixed effects, allowing 2000 replications and random ordering of variables.
    Results: The analysis of 480,766 households show that scheduled tribe households have the highest enrollment (18.85%), followed by 14.13% for scheduled caste, 10.67% for other backward caste, and 9.33% for high caste. Household factors, family head's characteristics, media access, and state-level fixed effects account for a 32% to 52% gap in enrollment. More specifically, the enrollment gaps are attributable to differences in wealth status, educational attainment, residence, family size, dependency ratio, media access, and occupational activities of the households.
    Conclusions: Weaker socio-economic status of low-caste households explains their high RSBY enrollments.
    Mesh-Begriff(e) Humans ; Social Class ; Insurance, Health ; Health Services Accessibility ; India ; National Health Programs ; Socioeconomic Factors
    Sprache Englisch
    Erscheinungsdatum 2022-08-22
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2760524-3
    ISSN 2196-8837 ; 2197-3792
    ISSN (online) 2196-8837
    ISSN 2197-3792
    DOI 10.1007/s40615-022-01374-8
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel ; Online: Why health policies should be transnational: A case for East Asia Pacific countries.

    Ambade, Preshit Nemdas / Katragadda, Chinmayee / Sun, Diana / Bootman, J Lyle / Abraham, Ivo

    The International journal of risk & safety in medicine

    2019  Band 30, Heft 2, Seite(n) 101–125

    Abstract: This paper argues that health policies should transcend national boundaries yet should not reach the supranational level. Along with multinational global health efforts, such cross-national health policies are essential to leverage joint efforts by ... ...

    Abstract This paper argues that health policies should transcend national boundaries yet should not reach the supranational level. Along with multinational global health efforts, such cross-national health policies are essential to leverage joint efforts by countries learning from their peers that experience similar health system challenges. In our analysis, we used World Bank Health, Nutrition, and Population (HNP) data from 1995 to 2014 for East Asia Pacific (EAP) countries to explore health system comparability across member nations. We applied a hierarchical cluster analysis using Ward's method and a squared Euclidean distance approach to classify 24 EAP countries into four relatively stable clusters based on their (dis)similarities over nine selected health expenditure and health system performance related indicators. One-way analysis of variance (ANOVA) was used to assess the discreteness of the formed clusters. Each cluster had unique characteristics based on the included indicators and health system performance of the member countries. We present transnational health policy recommendations for the EAP region based on both our use of robust methodology and the resulting comparative clusters.
    Mesh-Begriff(e) Analysis of Variance ; Cluster Analysis ; Cross-Cultural Comparison ; Far East/epidemiology ; Global Health/statistics & numerical data ; Health Policy ; Health Services Research ; Humans ; International Cooperation ; Policy Making
    Sprache Englisch
    Erscheinungsdatum 2019-07-07
    Erscheinungsland Netherlands
    Dokumenttyp Journal Article
    ZDB-ID 1055458-0
    ISSN 1878-6847 ; 0924-6479
    ISSN (online) 1878-6847
    ISSN 0924-6479
    DOI 10.3233/JRS-199001
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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