Kress DH, Wang H, Su Y. An Application of the RTM Framework to UnderstandPrimary Health Care in Nigeria. In: Tracking Resources for Primary Health Care: A Framework and Practices in Low- and Middle-Income Countries. Vol. 8. World Scientific ; 2020. nigeria_rtm_kress_wang_su.pdf
Su Y, Kress DH, Wang H. Productivity of Health Workers in Primary HealthcareFacilities in Nigeria: Why is the Average CaseloadEstimated to be Low?. In: Tracking Resources for Primary Health Care: A Framework and Practices in Low- and Middle-Income Countries. Vol. 8. World Scientific ; 2020. nigeria_phc_su_kress_wang.pdf
Zhou Z, Su Y, Heitner J, Si Y, Wang D, Zhou Z, Yuan C. The Effects on Inappropriate Weight for Gestational Age of an SMS Based Educational Intervention for Pregnant Women in Xi’an China: A Quasi-Randomized Controlled Trial. International Journal of Environmental Research and Public Health. 2020;17 (5) :1482. Publisher's VersionAbstract
Background: The aim of this study was to estimate the effects of maternal text messages on inappropriate weight for gestational age (IWGA) in newborns in rural China. Methods: Participants were pregnant women presenting for antenatal care at a Maternal and Child Health Center in Xi’an, China during the 2013–2015 period. In total, 2115 women completed the program with follow-up information included in the final analyses. All mothers were divided into four groups, including (1) a control group that received only a few “Basic” messages, (2) a Care-Seeking (CS) message group, (3) Good Household Prenatal Practices (GHPP) message group, and (4) a group receiving all 148 text messages. The primary outcome was IWGA, including small for gestational age (SGA) and macrosomia (weighing ≥4000g at birth). Multivariable logistic regression using an intent-to-treat estimate was utilized. Results: In total, 19.5% of newborns were IWGA. The risk of IWGA was 23.0% in the control group, 19.6% in the CS group, 18.9% in the GHPP group, and 16.5% in the group with All Texts. Compared to the control group, the odds ratio of IWGA was 0.65 (0.48–0.89) for the group receiving All Texts, which remained statistically significant after performing the Holm-Bonferroni correction. The odds ratio of macrosomia was 0.54 (0.34–0.87) and 0.57 (0.36–0.49) for the Care Seeking message group and the All Texts group, respectively, with statistical significance. Conclusion: A package of free informational text messages, including advice for good household prenatal practices and care seeking, may prevent the inappropriate weight for gestational age through a protective effect on macrosomia. Advice to encourage care seeking in pregnancy may prevent macrosomia among neonates in rural China as well.
Micah AE, Su Y, Bachmeier SD, Chapin A, Cogswell IE, Crosby SW, Cunningham B, Harle AC, Maddison ER, Moitra M, et al. Health sector spending and spending on HIV/AIDS, tuberculosis, and malaria, and development assistance for health: progress towards Sustainable Development Goal 3. The Lancet. 2020. Publisher's VersionAbstract
\textlessh2\textgreaterSummary\textless/h2\textgreater\textlessh3\textgreaterBackground\textless/h3\textgreater\textlessp\textgreaterSustainable Development Goal (SDG) 3 aims to "ensure healthy lives and promote well-being for all at all ages". While a substantial effort has been made to quantify progress towards SDG3, less research has focused on tracking spending towards this goal. We used spending estimates to measure progress in financing the priority areas of SDG3, examine the association between outcomes and financing, and identify where resource gains are most needed to achieve the SDG3 indicators for which data are available.\textless/p\textgreater\textlessh3\textgreaterMethods\textless/h3\textgreater\textlessp\textgreaterWe estimated domestic health spending, disaggregated by source (government, out-of-pocket, and prepaid private) from 1995 to 2017 for 195 countries and territories. For disease-specific health spending, we estimated spending for HIV/AIDS and tuberculosis for 135 low-income and middle-income countries, and malaria in 106 malaria-endemic countries, from 2000 to 2017. We also estimated development assistance for health (DAH) from 1990 to 2019, by source, disbursing development agency, recipient, and health focus area, including DAH for pandemic preparedness. Finally, we estimated future health spending for 195 countries and territories from 2018 until 2030. We report all spending estimates in inflation-adjusted 2019 US\$, unless otherwise stated.\textless/p\textgreater\textlessh3\textgreaterFindings\textless/h3\textgreater\textlessp\textgreaterSince the development and implementation of the SDGs in 2015, global health spending has increased, reaching \$7·9 trillion (95% uncertainty interval 7·8–8·0) in 2017 and is expected to increase to \$11·0 trillion (10·7–11·2) by 2030. In 2017, in low-income and middle-income countries spending on HIV/AIDS was \$20·2 billion (17·0–25·0) and on tuberculosis it was \$10·9 billion (10·3–11·8), and in malaria-endemic countries spending on malaria was \$5·1 billion (4·9–5·4). Development assistance for health was \$40·6 billion in 2019 and HIV/AIDS has been the health focus area to receive the highest contribution since 2004. In 2019, \$374 million of DAH was provided for pandemic preparedness, less than 1% of DAH. Although spending has increased across HIV/AIDS, tuberculosis, and malaria since 2015, spending has not increased in all countries, and outcomes in terms of prevalence, incidence, and per-capita spending have been mixed. The proportion of health spending from pooled sources is expected to increase from 81·6% (81·6–81·7) in 2015 to 83·1% (82·8–83·3) in 2030.\textless/p\textgreater\textlessh3\textgreaterInterpretation\textless/h3\textgreater\textlessp\textgreaterHealth spending on SDG3 priority areas has increased, but not in all countries, and progress towards meeting the SDG3 targets has been mixed and has varied by country and by target. The evidence on the scale-up of spending and improvements in health outcomes suggest a nuanced relationship, such that increases in spending do not always results in improvements in outcomes. Although countries will probably need more resources to achieve SDG3, other constraints in the broader health system such as inefficient allocation of resources across interventions and populations, weak governance systems, human resource shortages, and drug shortages, will also need to be addressed.\textless/p\textgreater\textlessh3\textgreaterFunding\textless/h3\textgreater\textlessp\textgreaterThe Bill & Melinda Gates Foundation.\textless/p\textgreater
Su Y, Baena IG, Harle AC, Crosby SW, Micah AE, Siroka A, Sahu M, Tsakalos G, Murray CJL, Floyd K, et al. Tracking total spending on tuberculosis by source and function in 135 low-income and middle-income countries, 2000–17: a financial modelling study. The Lancet Infectious Diseases. 2020. Publisher's VersionAbstract
\textlessh2\textgreaterSummary\textless/h2\textgreater\textlessh3\textgreaterBackground\textless/h3\textgreater\textlessp\textgreaterEstimates of government spending and development assistance for tuberculosis exist, but less is known about out-of-pocket and prepaid private spending. We aimed to provide comprehensive estimates of total spending on tuberculosis in low-income and middle-income countries for 2000–17.\textless/p\textgreater\textlessh3\textgreaterMethods\textless/h3\textgreater\textlessp\textgreaterWe extracted data on tuberculosis spending, unit costs, and health-care use from the WHO global tuberculosis database, Global Fund proposals and reports, National Health Accounts, the WHO-Choosing Interventions that are Cost-Effective project database, and the Institute for Health Metrics and Evaluation Development Assistance for Health Database. We extracted data from at least one of these sources for all 135 low-income and middle-income countries using the World Bank 2019 definitions. We estimated tuberculosis spending by source and function for notified (officially reported) and non-notified tuberculosis cases separately and combined, using spatiotemporal Gaussian process regression to fill in for missing data and estimate uncertainty. We aggregated estimates of government, out-of-pocket, prepaid private, and development assistance spending on tuberculosis to estimate total spending in 2019 US\$.\textless/p\textgreater\textlessh3\textgreaterFindings\textless/h3\textgreater\textlessp\textgreaterTotal spending on tuberculosis in 135 low-income and middle-income countries increased annually by 3·9% (95% CI 3·0 to 4·6), from \$5·7 billion (5·2 to 6·5) in 2000 to \$10·9 billion (10·3 to 11·8) in 2017. Government spending increased annually by 5·1% (4·4 to 5·7) between 2000 and 2017, and reached \$6·9 billion (6·5 to 7·5) or 63·5% (59·2 to 66·8) of all tuberculosis spending in 2017. Of government spending, \$5·8 billion (5·6 to 6·1) was spent on notified cases. Out-of-pocket spending decreased annually by 0·8% (−2·9 to 1·3), from \$2·4 billion (1·9 to 3·1) in 2000 to \$2·1 billion (1·6 to 2·7) in 2017. Development assistance for country-specific spending on tuberculosis increased from \$54·6 million in 2000 to \$1·1 billion in 2017. Administrative costs and development assistance for global projects related to tuberculosis care increased from \$85·3 million in 2000 to \$576·2 million in 2017. 30 high tuberculosis burden countries of low and middle income accounted for 73·7% (71·8–75·8) of tuberculosis spending in 2017.\textless/p\textgreater\textlessh3\textgreaterInterpretation\textless/h3\textgreater\textlessp\textgreaterDespite substantial increases since 2000, funding for tuberculosis is still far short of global financing targets and out-of-pocket spending remains high in resource-constrained countries, posing a barrier to patient's access to care and treatment adherence. Of the 30 countries with a high-burden of tuberculosis, just over half were primarily funded by government, while others, especially lower-middle-income and low-income countries, were still primarily dependent on development assistance for tuberculosis or out-of-pocket health spending.\textless/p\textgreater\textlessh3\textgreaterFunding\textless/h3\textgreater\textlessp\textgreaterBill & Melinda Gates Foundation.\textless/p\textgreater
tlid2020.pdf tlid2020_appendix.pdf
Su Y, Hsiao W. Improving Health Measures: Evidence from a List Experiment, Cognitive Interviews, and a Vignette Study. Global Health and Population. 2015;Doctor of Science. su_dissertation_abstract.pdf
Su Y. Direct Questioning or List-based Questioning: Evidence from a Survey Experiment on Intravenous Infusion Use and Smoking in China, in 12th Midwest International Economic Development Conference. Madison, Wisconsin ; 2015. list_experiment_yanfang_su_harvard_2015.pdf
Zhou Z, Su Y, Campbell B, Zhou Z, Gao J, Yu Q, Chen J, Pan Y. The Financial Impact of the ‘Zero-Markup Policy for Essential Drugs’ on Patients in County Hospitals in Western Rural China. PLoS OnePLoS One. 2015;10 :e0121630. 2_zhou_su_drug_policy_plos_one.pdf
Zhou Z, Su Y, Campbell B, Zhou Z, ianmin Gao, Yu Q, Chen J, Pan Y. The impact of China's Zero-Markup Drug Policy on county hospital revenue and government subsidy levels. Journal of Asian Public PolicyJournal of Asian Public Policy. 2015. zhou_su_drug_policy_original_manuscript.pdf
Su Y. An Inverted Pyramid: Three-tier Public Financing for Health in Nigeria. Harvard College Global Health ReviewHarvard College Global Health Review. 2012;IV. nigeria_yanfang_2012.pdf
周忠良, 苏延芳, 高建民, 周志英, 徐玲, 张耀光. 农村居民卫生服务需求弹性研究. 中国卫生经济. 2012;30 (12) :14-16. nong_cun_ju_min_wei_sheng_fu_wu_xu_qiu_dan_xing_yan_jiu_.pdf