Comparison of Automated versus Manual Programming of Infusion Pumps

Uncovering Discrepancies in IV Vancomycin Infusion Records between Pump Logs and EHR Documentation

BACKGROUND

Infusion start time, completion time, and interruptions are the key data points needed in both area under the concentration-time curve (AUC)- and trough-based vancomycin therapeutic drug monitoring (TDM). However, little is known about the accuracy of documented times of drug infusions compared with automated recorded events in the infusion pump system. A traditional approach of direct observations of infusion practice is resource intensive and impractical to scale. We need a new methodology to leverage the infusion pump event logs to understand the prevalence of timestamp discrepancies as documented in the electronic health records (EHRs).

OBJECTIVES

We aimed to analyze timestamp discrepancies between EHR documentation (the information used for clinical decision making) and pump event logs (actual administration process) for vancomycin treatment as it may lead to suboptimal data used for therapeutic decisions.

METHODS

We used process mining to study the conformance between pump event logs and EHR data for a single hospital in the United States from July to December 2016. An algorithm was developed to link records belonging to the same infusions. We analyzed discrepancies in infusion start time, completion time, and interruptions.

RESULTS

Of the 1,858 infusions, 19.1% had infusion start time discrepancy more than ± 10 minutes. Of the 487 infusion interruptions, 2.5% lasted for more than 20 minutes before the infusion resumed. 24.2% (312 of 1,287) of 1-hour infusions and 32% (114 of 359) of 2-hour infusions had over 10-minute completion time discrepancy. We believe those discrepancies are inherent part of the current EHR documentation process commonly found in hospitals, not unique to the care facility under study.

CONCLUSION

We demonstrated pump event logs and EHR data can be utilized to study time discrepancies in infusion administration at scale. Such discrepancy should be further investigated at different hospitals to address the prevalence of the problem and improvement effort.

Usability of smart infusion pumps: A heuristic evaluation

Although smart infusion pumps were built to eliminate medication errors, new types of usability errors have arisen. The purposes of this study were to determine potential risks when using smart pumps during secondary medication administration and to identify opportunities for design improvements. We observed and analyzed nurses when they interacted with smart pumps and heuristically evaluated the smart pump to identify usability problems. Forty-three usability problems were identified with the smart pump. The usability problems have the potential to create high cognitive burden on nurses and to increase the likelihood of mistakes. We discuss design and process improvement recommendations for each major finding from this study.

Quantifying the Impact of Infusion Alerts and Alarms on Nursing Workflows: A Retrospective Analysis

BACKGROUND

Smart infusion pumps affect workflows as they add alerts and alarms in an information-rich clinical environment where alarm fatigue is already a major concern. An analytic approach is needed to quantify the impact of these alerts and alarms on nursing workflows and patient safety.

OBJECTIVES

To analyze a detailed infusion dataset from a smart infusion pump system and identify contributing factors for infusion programming alerts, operational alarms, and alarm resolution times.

METHODS

We analyzed detailed infusion pump data across four hospitals in a health system for up to 1 year. The prevalence of alerts and alarms was grouped by infusion type and a selected list of 32 high-alert medications (HAMs). Logistic regression was used to explore the relationship between a set of risk factors and the occurrence of alerts and alarms. We used nonparametric tests to explore the relationship between alarm resolution times and a subset of predictor variables.

RESULTS

The study dataset included 745,641 unique infusions with a total of 3,231,300 infusion events. Overall, 28.7% of all unique infusions had at least one operational alarm, and 2.1% of all unique infusions had at least one programming alert. Alarms averaged two per infusion, whereas at least one alert happened in every 48 unique infusions. Eight percent of alarms took over 4 minutes to resolve. Intravenous fluid infusions had the highest rate of error-state occurrence. HAMs had 1.64 more odds for alerts than the rest of the infusions. On average, HAMs had a higher alert rate than maintenance fluids.

CONCLUSION

Infusion pump alerts and alarms impact clinical care, as alerts and alarms by design interrupt clinical workflow. Our study showcases how hospital system leadership teams can leverage infusion pump informatics to prioritize quality improvement and patient safety initiatives pertaining to infusion practices.

Usability of volumetric infusion pumps in pediatric intensive care

OBJECTIVE

To analyze the usability of two infusion pump models in a Pediatric Intensive Care Unit.

METHOD

This is a cross-sectional study of exploratory descriptive quantitative approach. A task was carried out in a controlled environment using infusion pump with 72 nursing staff members from August to September 2018. The Methodological Guideline for Medical Care Equipment Assessment Studies and the quality model proposed by NBR ISO/IEC 9126-1 were followed. Descriptive statistical analysis was used applying Fisher's exact test, binomial test and Mann-Whitney test.

RESULTS

91.7% of tasks were completed. The infusion pump-2 model was associated (p < 0.001) with operationalization, tasks accomplished with non-conformities, use of a manual calculator (measure effectiveness) and task accomplishment time (measure efficiency).

CONCLUSION

Efficacy and efficiency measures can evidence a better context of usability of IPs and identify interaction failures with the nursing staff to be improved in care practice.