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1.
Health Policy Plan ; 38(4): 454-463, 2023 Apr 11.
Artículo en Inglés | MEDLINE | ID: mdl-36744622

RESUMEN

In 2018, the Government of Madhya Pradesh initiated the feasibility testing of integrating an algorithmic approach (assess, give, counsel, treat) to strengthen antenatal nutrition services in routine government-funded programmes coupled with a health system thinking approach to strengthen the health service delivery platform. Implementation phases included (1) an evidence review and stakeholder consultations (April 2018) and (2) a health systems strengthening preparedness phase (May-December 2018), including pilot testing in Vidisha district (January-December 2019) covering ∼54 100 pregnant women with 237 antenatal contact points through 241 government auxiliary nurse midwives/staff nurses. During 2020-21, feasibility testing was expanded to an additional 7 districts. We used programme registers of the Auxiliary Nurse Midwives Registers (2019-21) and National Family Health Survey data for 2016 and 2021 to show changes in the Vidisha district and 7 expansion districts. We compare the performance of Vidisha district with Ashok Nagar district, where no such intervention occurred. Comparing 2016 and 2021 data, the Vidisha district showed improvements in receipt of antenatal care in the first trimester (29 to 85%) and in four antenatal visits (17 to 54%). Using the difference-in-difference approach, a 42% net increase in first-trimester antenatal check-ups in Vidisha as compared to Ashok Nagar is observed. There was also an improvement in the maternal nutrition budget of the state from USD 8.5 million to USD 17.8 million during this period. The Vidisha initiative offers several lessons in time-effective workflow to deliver all constituents of nutrition services at various antenatal contact points through and via routine government health systems. Continued execution of the algorithm for screening, with longitudinal data on the management of all nutrition risks, will be critical to show its long-term impact on maternal morbidities and birth outcomes.


Asunto(s)
Accesibilidad a los Servicios de Salud , Atención Prenatal , Femenino , Embarazo , Humanos , Fenómenos Fisiologicos de la Nutrición Prenatal , Gobierno , Análisis de Sistemas
2.
Matern Child Nutr ; 18(2): e13253, 2022 04.
Artículo en Inglés | MEDLINE | ID: mdl-35231160

RESUMEN

In India, 15 nutrition interventions are delivered and financed through the National Health Mission (NHM). Programmatic know-how, however, on tracking nutrition budgets in health sector plans is limited. Following the four phases of the budget cycle-planning, allocations, disbursements and expenditure, this paper presents a new method developed by the authors to track nutrition budgets within health sector plans. Using the example of the Anemia Mukt Bharat (AMB) or Anemia Free India strategy, it reports preliminary findings on the application of the first two phases of the method, that is, to track and act for improved planning and allocations, covering 12 states. The paper lists out the budget heads, cost norms and developed tools to plan adequately. Supportive action was undertaken through sharing trends and trainings for AMB's budgeting to create opportunities for improvements. It was observed that the AMB budget increased over 3 years despite the COVID situation. It increased from INR 6184 million in FY 2019-2020 to INR 6293 million, a 2% increase in FY 2020-2021, and to INR 7433 million, an 18% increase in FY 2021-2022. The difference in allocations and planned budgets were low (16%, 4% and 11%, respectively) while the difference in required budgets and planned budgets were significant but reduced consistently (41%, 31% and 22%, respectively). The paper concludes that the methods adopted for tracking and acting for improved nutrition budgets helped in informing national and state governments regarding yearly trends. Such methods can be effective and be developed for other nutrition interventions.


Asunto(s)
Anemia , COVID-19 , Presupuestos , Planificación en Salud , Humanos , India , Estado Nutricional
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