key: cord-0881769-do2ftee0 authors: Saini, Avi; Shukla, Ritwik; Joe, William; Kapur, Avani title: Improving nutrition budgeting in health sector plans: Evidence from India's anaemia control strategy date: 2022-03-01 journal: Matern Child Nutr DOI: 10.1111/mcn.13253 sha: 8964a721ffeeff5d5c029f27458b8dd9c91564db doc_id: 881769 cord_uid: do2ftee0 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. Evidence on effective public finance management for nutrition (Picanyol et al., 2015) suggests following the funds through the policy cycle-planning or resource cost estimations, budgeting at scale, ensuring funds reach the last mile, and finally, that they are utilized effectively. Funds for health programmes, notably NHM, have been tracked by various authors (Ghai et al., 2016; Srivastava et al., 2017) . There are two notable differences from previous work. First, the Tract and Act method tracks all components of the budget cycle from resource requirements to expenditures in real time providing insights for course corrections during the budget cycle. Second, it integrates supportive action measures like training and tools parallel to tracking budgets to create opportunities for improvement in the budgeting of specific strategies like AMB within the health sector. The method was based on NHM's planning and budgeting system. As First, referring to the interventions mentioned in AMB guidelines, a list of AMB budget line items was collated. State-wise planned and approved budgets were calculated against the major and minor budget heads identified. This was compared to the estimated budget required for 100% coverage to calculate differences in planning and • Tracking budgets and timely action can improve planning and allocation efficiency. • Support to states in planning budgets is essential. No major gaps were found in approvals. • Technical partners can assist in supporting governments for improving financial efficiency. allocations. This tracking was completed by July to enable funds requests via supplementary budgets proposed by states, that is, a midcourse correction. The second phase involves supportive action including sharing information on planning gaps and through meetings, training and sharing budget tracking tools. This was completed by November to allow revisions in state-level planning for the next financial year. The third phase requires assessing the disbursement of approved funds for timeliness and equity. Suggestions to improve the timeliness and equity of disbursements are shared in the fourth phase, along with developing tools for the same. Finally, the fifth stage tracks expenditures (Figure 3 ). This paper reports the application of the first two phases of the method-the planning and allocation of funds for AMB. This has been done due to a lack of publicly available data on disbursements Steps in planning and approval of NHM financial plans. Given the lack of a consolidated AMB budget, a first step was to identify the strategy-specific FMR codes. Based on this assessment, a total of 11 major and 46 minor eligible budget heads under the purview of AMB were identified in PIPs. Budget heads were selected based on their relevance to each of the six interventions mentioned earlier that AMB focuses on. All budget heads related to IFA supplementation were included. For deworming and nonnutritional causes of anaemia, separate national-level programmes are operational. Hence, only selected budget heads related to these strategies were included. For deworming, intervention budgets related to procurement, capacity building, and Information, Education, Communication/Behaviour Change Communication (IEC/BCC) were included. Similarly, for haemoglobinopathies, budgets for procurement and capacity building were included. For malaria, only the cost of insecticide-treated bed nets was included, as it is a focus activity under AMB. For fluorosis, no budget heads which directly affect the AMB programme were found, and hence it was excluded. Further, any anaemia-related research, innovation, human resource, drug warehouse and logistics, and programme management that was proposed or approved were included. The list of identified major and minor budget heads is presented as Appendix Table S1 . Second, the required budget was calculated by using denominators (e.g., population figures, the number of community health workers), unit costs and calculation norms for each budget head. Information on category-wise population was sourced from the publicly available data in the AMB dashboard (an online portal for AMB, MoHFW). States report the number of target beneficiaries, and these were multiplied with unit costs to arrive at the state level budget requirements under AMB. Further, information on unit costs of drugs (IFA, albendazole, iron, sucrose, etc.), AMB training, the number of ASHAs, the number of health subcenters, the number of school health teams, details of IEC/BCC campaigns, research and innovation projects, and so forth were obtained from state-specific PIPs and ROPs. A tool (available in Supporting Information) was developed to automatically calculate the required budget for each sample state with prefilled cost norms. Third, the required budget was benchmarked against the planned budget and approved budget to observe differences in these. Unbudgeted components were also identified. Contribution of each major budget head in the total AMB budget, 12 states, India, FY 2021-2022. Others involve program management, drug and warehouse logistics, human resources, research and innovation. Source: Authors based on NHM PIP and RoP documents This process was conducted for 12 states accounting for 76% of India's AMB target population in the first phase (July to August, FY 2019). These were Assam, Bihar, Chhattisgarh, Gujarat, Jharkhand, Madhya Pradesh, Maharashtra, Odisha, Rajasthan, Telangana, Uttar Pradesh and West Bengal. These states were selected as UNICEF state teams were involved in the state planning process, providing feedback and conducting state-level in-depth technical analytical guidance which was integral to the method. Fourth, the Track and Act method focused on supportive action based on insights from tracking budgets using a nonfault-finding approach. The objective was to list out areas that needed attention and enable planners to cover components comprehensively. Therefore, an important step was to share findings with state-level NHM officials and enable data-based budgetary decisions. Supportive action included union and state level dissemination of the findings, the inclusion of training on financial planning using the tracker in AMB cascade trainings and national reviews, and the preparation of costing templates to support state programme managers to appropriately plan for upcoming budget cycles. Building trust and coordinating with governments was key. Other development partners were also involved in training and necessary materials were shared with them. In particular, state-wise factsheets that highlighted gaps, items missed and items under-budgeted were discussed/considered by MoHFW and states to ensure that these were addressed during PIP submissions and NPCC meetings for next year. Lastly, changes in planning and allocation over the period of three financial years, namely FY 2019-2020, FY 2020-2021 and FY 2021-2022 were studied. This section describes the preliminary results of using the Track and Act method in observing changes in required, planned and allocated budgets across three years namely FY 2019-2020, FY 2020-2021 and FY 2021-2022, following training and supportive actions done with government stakeholders. Although the change is assessed to observe the difference in budgets across years, we are not implying causality or conducting a statistical evaluation of impact. Budgets may have changed as budgeting involves many political and administrative factors and not just the application of the track and act method. In FY 2019-2020, the states required INR 12,432 million for universal coverage of AMB. States proposed INR 7377 million or 41% of the required budget. From this, INR 6184 million or 84% of the proposed amount was approved. Thus, overall, 50% of the required budget was available in FY 2019-2020 for programme implementation (Table 1) . Interestingly, as compared to FY 2019-2020, planned budgets for FY 2020-2021 all states were closer to required budgets resulting in a reduction in the gap between estimated requirements and planned budgets. For instance, the difference in planned and required budget was reduced to 31%, a decrease of 10 percentage points, which further reduced to 22% in FY 2021-2022. In FY 2019-2020, (Table 2) the maximum difference in estimated requirement and planned budget was in West Bengal (69%), Gujarat (59%) and Telangana (49%). In FY 2020-21, this difference was maximum in West Bengal (58%), Bihar (55%) and Uttar Pradesh (42%). In FY 2021-2022, this difference was maximum in the same states but the percentage points reduced namely West Bengal (47%), Bihar (37%) and Uttar Pradesh (39%). In FY 2019-2020, a total of INR 6184 million was allocated for AMB in 12 study states. In FY 2020-2021, INR 6293 million was allocated, a 2% increase. Out of 12 states, the budget increased in seven states with the highest increase in Telangana (419%), followed by Assam (48%) and Chhattisgarh (33%). Five states were allocated lower budgets than the previous year with the highest decreases observed in Uttar Pradesh (36%), followed by Maharashtra (28%) and Odisha (22%). In FY 2021-2022, INR 7433 million was allocated, 18% more than the previous year. Out of 12 states, the budget increased in 8 states with the highest in Madhya Pradesh (82%), followed by Odisha (75%) and Maharashtra (51%). Four states were allocated a lower budget against the previous year. This included in descending order Telangana (46%), followed by Rajasthan (28%) and Chhattisgarh (24%). Coincidentally, FY 2019-2020 preceded the COVID-19 pandemic, and FY 2020-2021 and FY 2021-2022 were during the pandemic. This perspective has been used in the "Discussion" section. Out of 11 major budget heads or components of AMB, procurement remains the biggest component (79%) in the overall AMB budget, followed by incentives for community workers (9%). The contribution of critical components like capacity building, IEC/BCC, printing and strengthening of services were low, that is, 3%, 1%, T A B L E 1 Estimated required, planned and allocated budget for Anemia Mukt Bharat, 12 states, India, FY 2019-2020, FY 2020-2021 and FY 2021-2022, INR in million 3% and 5%, respectively. Research and Innovation remain negligible in the AMB budget (Table 3) . (Table 4) . Planned and allocated budgets were compared to understand the possible reasons for any significant differences. In FY 2019-2020, states had planned for INR 7377 million and had been allocated 84% of the planned budget. The highest difference in the planned and T A B L E 2 Change in estimated required budget and percentage change in planned against required for AMB, 12 states, India, FY 2019 -2020 , FY 2020 and FY 2021 -2022 Assam 13 2 2 1 2 2 0 0 0 2 0 24 27 19 Bihar 6 2 2 1 3 2 0 0 0 0 0 16 15 has also been accounted for while estimating requirements. Third, for some major heads, such as programme management, drug and warehousing, human resources, states spend from the budget for routine NHM activities. Since demarcating such funds is difficult, these heads were included only when any explicit reference was made in the RoPs. Fourth, norms and standards for some major heads such as IEC/BCC, printing and strengthening of service delivery were unavailable. Therefore, the amounts proposed by states have been treated as required amounts. The same is true for research and innovation. By choosing the proposed amount as a proxy for the required amount, we may potentially underestimate planning and approval gaps. However, these components account for only 7% of the required amount, and therefore any underestimations are small. Fifth, the Track and Act methodology may not necessarily have a causal association with improvements in budgeting practices and increased budgets. There are several other parameters such as interest, motivation and focus of various stakeholders as well as the broader policy attention on anaemia prevalence that may shape budgets. Lastly, while the present findings only speak to the first two phases, there may also be differences between approvals and disbursements, and disbursements and expenditures. Challenges in analysing public expenditure for nutrition in Bihar, public financing for nutrition in Bihar Nutrition financing in Rajasthan: Trends and gaps in 2016-17 Rajasthan-Nutrition-Financing-Policy-Brief-2016-17.pdf International Institute of Population Sciences Public finance management and data availability for nutrition financing in India Financing nutrition in India: Cost implications of the new nutrition policy landscape, 2019-20. Accountability Initiative. Centre for Policy Research and International Food Policy Research Institute Optimizing the multisectoral nutrition policy cycle: A systems perspective. Food and nutrition bulletin Estimating the cost of delivering direct nutrition interventions at scale: National and subnational level insights from India. Maternal and Child Nutrition Anemia Mukt Bharat operational guidelines. Government of India. https:// anemiamuktbharat.info/resource/amb-operational-guidelinesenglish/ Ministry of Health and Family Welfare Trends and drivers of change in the prevalence of anemia among one million women and children in India From stumbling block to enabler: The role of public financial management in health service delivery in Tanzania and Zambia Tracking investments in nutrition in Africa: Experience from four countries Budgeting for health, strategizing national health in the 21st century: A handbook World Bank, Results for Development Institute (R4D), and 1000 days with support from the Bill & Melinda Gates Foundation and the Children's Investment Fund Foundation (CIFF Budgeting for nutrition specific interventions in Bihar in 2014-18: Outlays, adequacy and expenditure. Working Paper, Centre for Budget and Governance Accountability and UNICEF Strengthening health systems to improve health outcomes. WHO's Method of Action Hemoglobin concentrations for the diagnosis of anemia and assessment of severity. Vitamin and Mineral Nutrition Information System The authors declare that there are no conflict of interests. No ethical approval required as the data were sourced from an open access website. AS and WJ visualized, conceptualized and designed the study. AS performed the research and analysed the data. RS and AS wrote the paper. AK and WJ reviewed and edited the paper.