Evidence map›Paper›PMID 31256565›Full record

ArticleInternational journal of health policy and management2019

The Challenge of Additionality: The Impact of Central Grants for Primary Healthcare on State-Level Spending on Primary Healthcare in India.

Diana M Bowser, Rajesh Jha, Manjiri Bhawalkar, Peter Berman

Abstract read
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Article in International journal of health policy and management, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Diana M BowserThe Heller School for Social Policy and Management, Brandeis University, Waltham, MA, USA.
Rajesh JhaIndependent Consultant, Delhi, India.
Manjiri BhawalkarHealth Financing Team, The Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.
Peter BermanDepartment of Global Health and Population, International Health Systems Program, Harvard School of Public Health, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn planning for universal health coverage, many countries have been examining their fiscal decentralization policies with the goal of increasing efficiency and equity via "additionalities." The concept of "additionality," when the government of a lower administrative level increases the funding allocated to a particular issue when extra funds are present, is often used in these contexts. Although the definition of "additionality" can be used more broadly, for the purposes of this paper we focus narrowly on the additional allocation of primary healthcare expenditures. This paper explores this idea by examining the impact of central level primary healthcare expenditure, on individual state level contributions to primary healthcare expenditure within 16 Indian states between 2005 and 2013.

methodsIn examining 5 main variables, we compared differences between government expenditures, contributions, and revenues for Empowered Action Group (EAG) states, and non-EAG states. EAG states are normally larger states that have weaker public health infrastructure and hence qualify for additional funding. Finally, using a model that captured the quantity of central level primary healthcare expenditure distributions to these states, we measured its impact on each state's own contributions to primary healthcare spending.

resultsOur results show that, at the state level, growth in per capita central level primary healthcare expenditure has increased by 110% from 2005-2013, while state's own contributions to primary healthcare expenditure per capita increased by 32%. Further analyses show that a 1% change disbursement from the central level leads to a -0.132%, although not significant, change by states in their own expenditure. The effect for wealthier states is -0.151% and significant and for poorer states the effect is smaller at -0.096% and not significant.

conclusionThis analysis suggests that increases in central level primary healthcare expenditure to states have an inverse relationship with primary healthcare expenditures by the state level. Furthermore, this effect is more pronounced in wealthier Indian states. This finding has policy implications on India's decision to increase block grants to states in place of targeted program expenditures.

Indexed as

Financing, OrganizedHealth ExpendituresHealth ResourcesHealth Services AccessibilityHumansIndiaPrimary Health CarePublic HealthSocioeconomic FactorsUniversal Health InsuranceFungibilityHealth SystemsIndiaPrimary HealthcareSpending and Financing

Identifiers

PMID31256565
PMCPMC6600018

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.