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dc.contributor.advisorStan N. Finkelstein and Jarrod Goentzel.en_US
dc.contributor.authorZhang, Biao, S.M. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Technology and Policy Program.en_US
dc.coverage.spatiald------en_US
dc.date.accessioned2015-07-31T19:13:26Z
dc.date.available2015-07-31T19:13:26Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/98001
dc.descriptionThesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2015.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 94-99).en_US
dc.description.abstractPediatric Pneumonia (PNA) is the single leading cause of death in children under five, accounting for 19% of all childhood deaths worldwide. Due to severe resource constraints on healthcare, the global burden of the disease in children is disproportionately shared by developing countries. In particular, India, having the highest incidence rate of PNA, accounts for more than 30% of the world's neonatal deaths from pneumonia every year. The three-tier referral systems, shared by many other developing countries, has introduced inefficiencies into delivering appropriate healthcare to patients in need. Point-of-care (POC) diagnostics is a type of tool used to assist physicians to make clinical decisions. Its key advantage include the quick turnaround of results, low cost and high diagnostic power could potentially improve India's pressing situation due to pneumonia. Since the disease progresses quickly in infants and babies and transportation of patients within the healthcare system is time consuming, POC diagnostic is crucial in lowering both the mortality of children with pneumonia and the cost of treating PNA. To this effect, we investigate the potential impact of POC diagnostics when implemented in a three-tier referral system. Using India as a case country, I construct a decision tree model that evaluates cost, mortality, and the combined cost-effectiveness in Tree-Age software as a framework which evaluates five implementation strategies of a POC diagnostic for PNA within the Indian public healthcare system. The strategies reflect various prescription decisions and referral patterns in current medical practice in India. I concluded that (1) the diagnostic will result in both higher cost and mortality in areas where the practice is to provide all patients antibiotics and thus not recommended, (2) the diagnostic is very likely to achieve lower cost and mortality when patients do not always receive antibiotics and sometimes are given only symptom-relieving drugs and thus recommended, (3) the diagnostic has great potential in generating savings by limiting patients from being transported to urban hospitals, (4) when dual diagnostic is employed combining POC diagnostics and X-ray, confirming positive cases from the diagnostic by X-ray results in lower cost and confirming negative cases results in lower mortality and (5) the diagnostic can save resources and benefit health outcomes and should be implemented in places where X-ray is not available.en_US
dc.description.statementofresponsibilityby Biao Zhang.en_US
dc.format.extent103 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectTechnology and Policy Program.en_US
dc.titleDecision analysis of novel point-of-care diagnostics for Pediatric Pneumonia : implementation in Developing countries with tiered healthcare systemsen_US
dc.title.alternativeDecision analysis of novel POC diagnostics for PNA : implementation in Developing countries with tiered healthcare systemsen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Technology and Policyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Technology and Policy Program.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentMassachusetts Institute of Technology. Technology and Policy Program
dc.identifier.oclc914481706en_US


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