Best care practices in anesthesiology : development and evaluation of an electronic feedback system to improve physician compliance with evidence-based practices
Name
230934237-MIT.pdf
Description
Full printable version
Size
3.14 MB
Format
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Checksum (MD5)
a212f671df7e489790abd24986a02a83
Author(s)
Sarin, Pankaj, M.D. University of Rochester
Advisor(s)
Lucila Ohno-Machado.
Date Issued
2007
Publisher
Massachusetts Institute of Technology
Abstract
Recently, hospitals, regulatory agencies, and insurers have renewed their focus on improving patient care and safety. Outcomes based measures are being utilized and hospitals are being asked to report on whether patients are being treated according to a standard of care or a best practice guideline. As peri-operative physicians, anesthesiologists are able to evaluate and, to a great degree, affect the pre-operative, intra-operative, and post-operative course of a patient. However, several barriers exist. Although best practice guidelines exist, current models to risk stratify patients need improvement. Individual anesthesiologists currently have no uniform way to measure patient outcomes, either in an institutional or provider specific manner, and many treat patients based on anecdotal experience rather than on evidence based medicine. We addressed these issues through development of an electronic feedback system. The demonstration system targeted the problem of postoperative nausea and vomiting (PONV) in the ambulatory surgery patient population. Because performance of existing PONV risk prediction models was poor and could not be used for educational purposes, we created a new PONV risk prediction model and compared it against existing models. The new, improved risk prediction model was incorporated into an electronic system that gathered patient outcomes data related to best care practice and then fed back the information to care providers. After implementation of the electronic feedback system, we evaluated its efficacy in improving compliance with best care practices.
Description
Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2007.
Includes bibliographical references (leaves 55-57).
Subjects
Harvard University--MIT Division of Health Sciences and Technology.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
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