{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/90795"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/90795","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Pooling and segmentation to improve primary care prescription management","abstract":"Analyses of schedule history and medical records for large primary care medical practice are combined with time studies to develop a quantitative network flow model of the prescription management process, including metrics for the yield of prescription requests, excess requests for chronic & stable medications, and prescriptions that overflow from scheduled appointments. The model is used to estimate the impact of segmenting and pooling the prescription workflows into a central prescription management group, resulting in recommendations for a new prescription management system. Interventions on pharmacy/practice coordination for faxes, modification of the voicemail system, and improved workflow are piloted to validate model estimates. The recommended changes are expected to improve prescription response time and accuracy, reduce resource utilization, improve patient medicine compliance and, ultimately, patient health outcomes.","abstract_html":"Analyses of schedule history and medical records for large primary care medical practice are combined with time studies to develop a quantitative network flow model of the prescription management process, including metrics for the yield of prescription requests, excess requests for chronic &amp; stable medications, and prescriptions that overflow from scheduled appointments. The model is used to estimate the impact of segmenting and pooling the prescription workflows into a central prescription management group, resulting in recommendations for a new prescription management system. Interventions on pharmacy/practice coordination for faxes, modification of the voicemail system, and improved workflow are piloted to validate model estimates. The recommended changes are expected to improve prescription response time and accuracy, reduce resource utilization, improve patient medicine compliance and, ultimately, patient health outcomes.","abstract_has_math":false,"creators":["Sanderson, Thomas Daniel"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Leaders for Global Operations Program at MIT","school":null,"contributors":[],"advisors":["Retsef Levi and David Simchi-Levi."],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014","date_published":"2014","updated_at":"2026-07-22T22:22:13Z","subjects":["Sloan School of Management.","Engineering Systems Division.","Leaders for Global Operations Program."],"languages":["eng"],"rights":["M.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. 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