skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Analysis of Medication Error Reports

Conference ·
OSTI ID:893256

In medicine, as in many areas of research, technological innovation and the shift from paper based information to electronic records has created a climate of ever increasing availability of raw data. There has been, however, a corresponding lag in our abilities to analyze this overwhelming mass of data, and classic forms of statistical analysis may not allow researchers to interact with data in the most productive way. This is true in the emerging area of patient safety improvement. Traditionally, a majority of the analysis of error and incident reports has been carried out based on an approach of data comparison, and starts with a specific question which needs to be answered. Newer data analysis tools have been developed which allow the researcher to not only ask specific questions but also to “mine” data: approach an area of interest without preconceived questions, and explore the information dynamically, allowing questions to be formulated based on patterns brought up by the data itself. Since 1991, United States Pharmacopeia (USP) has been collecting data on medication errors through voluntary reporting programs. USP’s MEDMARXsm reporting program is the largest national medication error database and currently contains well over 600,000 records. Traditionally, USP has conducted an annual quantitative analysis of data derived from “pick-lists” (i.e., items selected from a list of items) without an in-depth analysis of free-text fields. In this paper, the application of text analysis and data analysis tools used by Battelle to analyze the medication error reports already analyzed in the traditional way by USP is described. New insights and findings were revealed including the value of language normalization and the distribution of error incidents by day of the week. The motivation for this effort is to gain additional insight into the nature of medication errors to support improvements in medication safety.

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
893256
Report Number(s):
PNNL-SA-42728; TRN: US200625%%53
Resource Relation:
Conference: Proceedings of IMECE 2004 ASME International Mechanical Engineering Congress and Exposition held in Anaheim, California, 121-126
Country of Publication:
United States
Language:
English

Similar Records

A UMLS-based spell checker for natural language processing in vaccine safety
Journal Article · Mon Feb 12 00:00:00 EST 2007 · BMC Medical Informatics and Decision Making (Online) · OSTI ID:893256

Development of Analysis Methods that Integrate Numeric and Textual Equipment Reliability Data
Program Document · Fri Sep 15 00:00:00 EDT 2023 · OSTI ID:893256

Microbial Forensics: A Scientific Assessment
Conference · Mon Feb 17 00:00:00 EST 2003 · OSTI ID:893256