{"id":1851,"date":"2020-12-30T13:54:11","date_gmt":"2020-12-30T18:54:11","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-hbappitch\/submission\/locaid\/"},"modified":"2021-02-07T19:30:01","modified_gmt":"2021-02-08T00:30:01","slug":"locaid-ai-optimized-platform-for-mobile-healthcare-workforce-dispatch","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-hbappitch\/submission\/locaid-ai-optimized-platform-for-mobile-healthcare-workforce-dispatch\/","title":{"rendered":"locAID: AI-Optimized Platform for Mobile Healthcare Workforce Dispatch"},"content":{"rendered":"

\"locAID-Title\"<\/p>\n

locAID is a workforce optimization tool designed for nurses and other medical professionals who travel to the patient\u2019s location to provide clinical care. locAID offers a combination of scheduling, navigation, and electronic health record (EHR) functionality by leveraging advances in ML\/AI as well as platforms and network effects. There is no other product in the market today that combines the individual capabilities of these three components into a single unified keystone solution. The mobile health industry is projected to grow exponentially in the coming years. Amid the COVID-19 crisis, in particular, the importance of optimizing the mobilization of limited healthcare resources has only become more imperative. In addition, technology and underlying infrastructure such as mobile adoption, IoT, and ubiquity of sensors are advancing at breakneck speed. We believe that locAID, which at its core is a platform-as-a-service (PaaS) company, is best positioned to reap the benefits of these advances in such a fast-growing market in a way that was never possible before.<\/p>\n

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\"locAID-Who<\/p>\n

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\"locAID-Introduction\"<\/p>\n

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\"locAID-The<\/p>\n

Stakeholder Pain-Points<\/b><\/u>
\nPayers and home health agencies<\/b> – Workforce utilization inefficiencies, lack of real-time accountability.
\nTraveling Nurses<\/strong> – Stress, burnout, too much time devoted to easily automatable tasks.
\nPatients<\/strong> \u2013 Quality of care and patient safety issues, lack of transparency.<\/p>\n

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Value is created for enterprise clients and other users by providing a unified platform together with algorithms that streamline the patient-nurse interactions along the different stages. Value capture could be through subscription-based, consumption-based, or freemium models.<\/p>\n

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\"locAID-Market<\/p>\n

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\"locAID-Savings<\/p>\n

Large insurance companies such as UnitedHealth Group daily dispatch hundreds of nurses and other medical professionals to various points of care including acute hospitals, nursing homes, and the patient\u2019s residence. Two additional visits per nurse per day<\/b>, achieved by using the locAID optimization engine, will result in annual savings<\/b> in excess of $100M<\/b>.<\/p>\n

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\n","protected":false},"excerpt":{"rendered":"

locAID is an AI-driven workforce optimization tool designed for nurses and other medical professionals who travel to the patient\u2019s location to provide clinical care.<\/p>\n","protected":false},"author":14649,"featured_media":1937,"comment_status":"open","ping_status":"closed","template":"","categories":[532,527,487,557,581,548,526,506,463,558,533,574,575,473],"class_list":["post-1851","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-ai","category-analytics","category-app","category-business-analytics","category-business-intelligence","category-covid","category-data","category-digital-platform","category-healthcare","category-machine-learning","category-mobility","category-patients","category-point-of-care","category-scheduling","hck-taxonomy-organization-locaid","hck-taxonomy-industry-information-technology","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-hbappitch\/round\/contestant-submissions-january-2021\/","_links":{"self":[{"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/hck-submission\/1851","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/hck-submission"}],"about":[{"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/types\/hck-submission"}],"author":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/users\/14649"}],"replies":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/comments?post=1851"}],"version-history":[{"count":15,"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/hck-submission\/1851\/revisions"}],"predecessor-version":[{"id":2220,"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/hck-submission\/1851\/revisions\/2220"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/media\/1937"}],"wp:attachment":[{"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/media?parent=1851"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-hbappitch\/wp-json\/wp\/v2\/categories?post=1851"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}