Provider issues related to patient controlled analgesia and nurse controlled analgesia errors in a pediatric hospital
Stropp, Travis J.
MetadataShow full item record
Background: Medical errors are a danger to patient safety and a significant cause of morbidity and mortality. Additionally, they increase expenditures in an already significantly indebted U.S. health care system. Much confusion exists about definitions of medical errors, which include medication errors and adverse drug events (ADEs). Several federal and international organizations have attempted to standardize definitions in order to streamline data collection, but until these standards are universally adopted, error reports and trends are still subject to questions of validity. Reporting errors, in general, has become a more socially acceptable practice in health care with the advent of several anonymous reporting databases. There have also been several initiatives aimed at reducing the incidence of errors, which range from national programs to intrafacility guidelines. Several pieces of health information technology (HIT) have made an impact on error incidence and data collection, although there is much room for improvement. Patient controlled analgesia (PCA) pumps for pain management have been in existence for decades, and "smart pump" software has improved their safety and ease of programming. PCA use in children presents challenges to clinicians, and the characteristics of providers who write PCA orders and those who program PCA pumps may play a role in the incidence of events related to PCA. This study seeks to elucidate trends in errors as they related to these different PCA providers in a pediatric hospital in the northeastern U.S. and provide recommendations for how PCA practice can be improved in this facility. Methods: Safety Event Reporting System (SERS) reports of PCA events (n = 117) during the period of 2004 - 2012 were analyzed retrospectively to determine several key variables for data analysis. The main focus of this analysis was those variable trends related to providers, including: proportion of events caused by human error, proportion of events related to subcategories of human error, proportion of types of prescribers involved in PCA events, proportion of errors in medical and surgical patients, proportion of errors occurring on day and night shifts for the nursing staff, and proportion of events that were dosing mistakes. Statistical analysis was performed for these results when possible to determine significance. Results: Human errors were implicated in 84.1% of events, whereas PCA pump mechanical errors and software errors were implicated in 7.1% and 7.9% of events, respectively. Statistically significant differences were found in all variables tested, including the proportion of nursing errors (60.9%) versus prescriber errors (28.7%) (p < 0.0002). For types of prescribers, the proportion of PCA events occurring when a M.D. wrote the PCA order (56.41%) was statistically different than when a N.P. wrote the PCA order (39.32%) (p = 0.0129). More surgical patients (61.5%) were affected by PCA events than medical patients (36.8%) (p < 0.0002). There were more events occurring on the nursing staff day shift (59.8%) than the night shift (36.8%) (p = 0.0004). Finally, dosing mistakes (66.7%) were implicated in significantly more PCA events than any other error type (33.3%) (p < 0.0002). Conclusion: Several recommendations for improving the safety of PCA in pediatric pain management are justified by the results of this data analysis. First, further education and simulation for entering PCA orders into the CPOE system is needed for all prescribers. Secondly, further education and simulation in PCA pump programming and system set-up is needed for all nursing staff members. In regard to prescriber credentials, it is recommended that Pain Treatment Service (PTS) staff members train M.D. residents in writing PCA orders and entering them into the CPOE system. Finally, it is recommended that the SERS management team publish standardized error report content and entry format in order to streamline data analysis for quality improvement (QI) purposes.