<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T20:41:55Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/118533" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/118533</identifier><datestamp>2022-01-13T07:55:19Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Juanjuan Zhang.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Nohria, Kanishka</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Integrated Design and Management Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Massachusetts Institute of Technology. Engineering and Management Program</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Massachusetts Institute of Technology. Integrated Design and Management Program.</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2018-10-15T20:24:07Z</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2018</dim:field>
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   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1054926960</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2018.</dim:field>
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   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 45-47).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The US healthcare system is looked at from the point of view of various stakeholders and how its current structure has emerged over the years. With the shifting demographics, change in disease mix, ICT revolution and other factors at play, the system is in a state of flux. Sensor technology on the other hand has also progressed over the years to reach a point where low-cost mass-produced smart sensors are becoming omnipresent. A variety of such sensors are now available, and new ones are being developed for specific needs, like for continuous health monitoring systems. New wireless sensing technologies are redefining the care services, processes and customer expectations. This is especially true for chronic disease management and eldercare. We develop a view point to understand at a broad level how the US healthcare system is currently evolving and what role could new technologies, like wireless sensing, play in shaping its near future. These new technologies are slowly gaining foothold in the market and could possibly reach a point of inflection soon where the population starts to adopt them in masses. By creating a new mental model of how various parts in the system interact with each other, we try and develop an understanding of which factors might affect the speed of adoption of these new technologies into the system.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Kanishka Nohria.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M. in Engineering and Management</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">47 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.</dim:field>
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   <dim:field mdschema="dc" element="subject" lang="en_US">Integrated Design and Management Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Transformation of the US healthcare system with the advent of wireless sensing technologies</dim:field>
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   	&lt;Title>Transformation of the US healthcare system with the advent of wireless sensing technologies&lt;/Title>
   	&lt;Subtitle>Transformation of the United States healthcare system with the advent of wireless sensing technologies&lt;/Subtitle>
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   	&lt;Abstract>The US healthcare system is looked at from the point of view of various stakeholders and how its current structure has emerged over the years. With the shifting demographics, change in disease mix, ICT revolution and other factors at play, the system is in a state of flux. Sensor technology on the other hand has also progressed over the years to reach a point where low-cost mass-produced smart sensors are becoming omnipresent. A variety of such sensors are now available, and new ones are being developed for specific needs, like for continuous health monitoring systems. New wireless sensing technologies are redefining the care services, processes and customer expectations. This is especially true for chronic disease management and eldercare. We develop a view point to understand at a broad level how the US healthcare system is currently evolving and what role could new technologies, like wireless sensing, play in shaping its near future. These new technologies are slowly gaining foothold in the market and could possibly reach a point of inflection soon where the population starts to adopt them in masses. By creating a new mental model of how various parts in the system interact with each other, we try and develop an understanding of which factors might affect the speed of adoption of these new technologies into the system.&lt;/Abstract>
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