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Pinch Analysis as a Quantitative Decision Framework for Determining Gaps in Health Care Delivery Systems

handle: 1721.1/114424
With ‘good health and well-being’ being set as one of the targets of the Sustainable Development Goal (SDG), this paper proposes the application of Pinch Analysis, a quantitative method originally applied to conserve scarce resources in source-demand allocation networks, for identifying gaps in health care service delivery. This method is also found to be useful for health care infrastructure capacity planning and policy testing. The major contribution of this method in this context is identification of marginalized sections and testing specific policies targeted towards them, which will justify release of financial aid and infrastructure development for appropriate sections. We explored this concept for investigating the in-patient health care delivery system in the context of developing nations, where the health care facilities (both public and private) thrive by offering services at drastically different prices. A novel framework is developed in this paper, supported by a case study of Kolkata, India where both the gaps and surplus faced by different sections of population are identified. In order to offset these gaps, we offer recommendations for possible policy implementation. A few hypothetical scenarios are also examined in order to understand the importance of Pinch Analysis for policy testing. We conclude by proving that Pinch Analysis can be a robust integrated decision-making framework for the health care sector, especially in resource-constrained communities.
- Norwegian Institute for Cultural Heritage Research Norway
- Massachusetts Institute of Technology United States
- Indian Institute of Technology Bombay India
- University of Cambridge United Kingdom
360, Developing countries, Quantitative framework, Pinch analysis, Decision-making tool, Health care service delivery
360, Developing countries, Quantitative framework, Pinch analysis, Decision-making tool, Health care service delivery
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).19 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
