Using FDA reports to inform a classification for health information technology safety problems

Abstract

Objective To expand an emerging classification for problems with health information technology (HIT) using reports submitted to the US Food and Drug Administration Manufacturer and User Facility Device Experience (MAUDE) database. Design HIT events submitted to MAUDE were retrieved using a standardized search strategy. Using an emerging classification with 32 categories of HIT problems, a subset of relevant events were iteratively analyzed to identify new categories. Two coders then independently classified the remaining events into one or more categories. Free-text descriptions were analyzed to identify the consequences of events. Measurements Descriptive statistics by number of reported problems per category and by consequence;inter-rater reliability analysis using the k statistic for the major categories and consequences. Results A search of 899 768 reports from January 2008 to July 2010 yielded 1100 reports about HIT. After removing duplicate and unrelated reports, 678 reports describing 436 events remained. The authors identified four new categories to describe problems with software functionality, system configuration, interface with devices, and network configuration; the authors' classification with 32 categories of HIT problems was expanded by the addition of these four categories. Examination of the 436 events revealed 712 problems, 96% were machinerelated, and 4% were problems at the humanecomputer interface. Almost half (46%) of the events related to hazardous circumstances. Of the 46 events (11%) associated with patient harm, four deaths were linked to HIT problems (0.9% of 436 events). Conclusions Only 0.1% of the MAUDE reports searched were related to HIT. Nevertheless, Food and Drug Administration reports did prove to be a useful new source of information about the nature of software problems and their safety implications with potential to inform strategies for safe design and implementation.

Safe Practices for Copy and Paste in the EHR

“…These events were organized first by the system involved as well as standardized tagging taxonomies (AHRQ, HM, Magrabi) [37][38][39]. Overall, these events were consistent with copy and paste use and associated problems described in the literature.…”

Using statistical text classification to identify health information technology incidents

“…Nevertheless, some manufacturers have voluntarily listed their systems, and in our previous work we analyzed HIT incidents reported to the FDA. 11 The new Patient Safety Action and Surveillance Plan from the Office of the National Coordinator proposes to monitor HIT adverse event reports in MAUDE to identify HIT patient safety risks. 12 …”

“…Another approach is to perform keyword searches and eliminate non-HIT incidents through manual reviews of smaller subsets of reports. 11 On the basis of this approach, we previously searched almost 900 000 MAUDE reports to identify over 400 relating to HIT. A similar approach was used to identify 99 HIT reports from 42 616 patient safety incidents in an Australian incident-monitoring database.…”

A Primer to the Structure, Content and Linkage of the FDA’s Manufacturer and User Facility Device Experience (MAUDE) Files

“…However, naïve linking of the six MAUDE file types that comprise an adverse event record can result in erroneous findings, while understanding the nuances of the various file types and how they work together can be exceedingly time-intensive. [14][15][16][17][18][19][20][21] The MAUDE database contains medical device problem and outcome information that can inform general reviews, specific product inquiries, and examination of adverse event reporting trends over time. The goal of this paper is to provide novice users with information gained through practical experience about the basic structure and content of the MAUDE database.…”