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Algorithm to Systematically Reduce Human Errors in Healthcare

The purpose of the research was to develop an algorithm to permanently reduce human errors in the healthcare industry. The algorithm will be able to be applied to all healthcare organizations and provide a preventative approach to errors. The research involved looking at past methods of error reduction/prevention. Certain methods proved to be useful in generating the algorithm like the Healthcare Failure Modes and Effects Analysis while others like Root Cause Analysis proved to only have limited success. The algorithm takes a three phase approach to reducing errors. Phase One identifies the potential error producing situations. Phase Two uses error proofing principles and known solution directions to generate solutions while Phase Three uses a new method developed called Solution Priority Number to rank and evaluate the solutions. Throughout the algorithm many worksheets have been developed to aid in a team?s progression through the process. Two case studies were performed. The first case study followed a traditional team through the error prevention process while the second case used the algorithm. When comparing the two cases the team using the algorithm finished the process in shorter time, produced more effective failure modes, and generated a richer set of solutions to error proof the process.

Identiferoai:union.ndltd.org:NCSU/oai:NCSU:etd-12012005-073356
Date02 December 2005
CreatorsSeastrunk, Chad Stephen
ContributorsDr. Jeff Thompson, Dr. Jeff Joines, Dr. Timothy Clapp
PublisherNCSU
Source SetsNorth Carolina State University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://www.lib.ncsu.edu/theses/available/etd-12012005-073356/
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