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Medication Errors with Infusion Pumps

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Medication Errors with Infusion Pumps Risk of Medication Errors With Infusion Pumps A Study of 1,004 Events From 132 Hospitals Across Pennsylvania Matthew Taylor, PhD & Rebecca Jones, MBA, RN DOI: 10.33940/biomed/2019.12.7 The risk of medication errors with infusion pumps is well established, yet a better under- standing is needed of the scenarios and factors associated with the errors. Our study ex- plored the frequency of medication errors with infusion pumps, based on events reported to the Pennsylvania Patient Safety Reporting System (PA-PSRS) during calendar year 2018. Our study identified a total of 1,004 events involving a medication error and use of an infusion pump, which occurred at 132 different hospitals in Pennsylvania. Fortunately, a majority of medication errors did not cause patient harm or death; however, we did find that 22% of events involved a high-alert medication. Our study shows that the frequency of events varies widely across the stages of medication process and types of medication error. In a subset of our data, we manually reviewed a free-text narrative field in each event report to better un- derstand the nature of errors. For example, we found that a majority of wrong rate errors led to medication being infused at a faster rate than intended, and user programming was the most common contributing factor. Overall, results from our study can help providers identify areas to target for risk mitigation related to medication errors and the use of infusion pumps. Keywords: infusion pump, IV pump, smart pump, medication error, risk factors, adverse events, patient safety, Pennsylvania, high-alert medication, medical device Corresponding author Patient Safety Authority Disclosure: The authors declare that they have no relevant or material financial interests. Patient Safety I December 2019 I 61 nfusion pumps are essential for of PA-PSRS, we also narrowed our search Table 1. Frequency of Events During 2018 With a Medication Error and Use of an Infusion Pump administering fluid, nutrients, and to events that occurred at hospitals and St ages of Medication Process medications intravenously (IV) to were submitted to PA-PSRS between Jan- Types o f To t al patients; however, the use of in- uary 1 and December 31, 2018. M ed Erro r Events1 Prescribing Transcript ion Preparat io n Administ ration Monitoring Ot her Ifusion pumps is also associated with Dose omission 126 0 0 2 114 6 7 Based on our query of PA-PSRS, we a high frequency of adverse events.1 Extra dose 16 2 0 0 12 1 3 identified a total of 1,004 events, from W rong* 595 34 23 39 468 50 58 Previous research has noted the need 1,004 which we selected a random sample Prescription/refill 13 6 0 3 4 0 1 for studies that capture the prevalence of 30% (n = 300 of 1,004) for manual delayed and context of errors associated with Medication list Events review. One author manually reviewed 2 1 1 1 0 0 1 inc orrec t infusion pumps, as such knowledge is the sample of 300 events and confirmed necessary to better understand scenar- M onitoring error 32 1 1 2 19 9 3 that the free-text narrative field in all Unauthorized ios and factors associated with greater 7 1 0 1 4 1 1 event reports (100%; n = 300 of 300) drug risk.2-7 Unfortunately, few studies have described a medication error with use of Inadequate pain 2 0 0 0 2 0 0 assessed medication errors with infu- an infusion pump. This finding indicates management sion pumps across more than 10 hospi- a high degree of confidence in the results Other 211 18 9 20 129 27 37 tals, during an extended period of time, of our database query, 95% CI [98.8%– Total Events 1,004 63 34 68 752 94 111 and across multiple factors (e.g., stage 100%; Clopper-Pearson exact method], 132 1 of medication process, type of medica- so we proceeded to include the full data Events may have involved more than one stage of medication process. tion error, and contributing factor). *”Wrong” is a term used in the PA-PSRS taxonomy to describe a type of medication error. Wrong is defined by 11 subtypes, which are listed in Figure 1. Hospitals Reporting set of 1,004 events in our analysis. an Event Study Methods and Results Our study revealed that the 1,004 intended (e.g., faster or slower). To assess inter-rater Figure 1. Subtypes of “Wrong” Medication Errors events were concentrated at 132 of In this study, we explored the Pennsyl- reliability of our classification, we used the kappa the hospitals in Pennsylvania. Among 11 vania Patient Safety Reporting System statistic, which indicates that we had a substantial Patient 8 the 132 hospitals with an event, we 12 (PA-PSRS)* database for events reported level of agreement (K = 0.812). During our initial found that the median was 3 events review we agreed on Rate classification in 88% (n = Route 12 as a medication error that included the per hospital and a mean of 7.61 (SD: 165 of 187) of events. Thereafter, we reviewed all Drug use of an infusion pump. Our database 14.79) per hospital. 29 query included a total of 39 unique key- 22 disagreements and came to consensus on the Dosage Form 31 words that were paired with the term Based on information provided by appropriate Rate classification per event, which event reporters, 99% (n = 996 of ultimately yielded 100% agreement and increased the 19% “pump.” The 39 unique keywords con- Concentration 32 sisted of “infusion,” “IV,” “smart,” and 1,004) of the events were identified as accuracy of our results. of Events Had 36 company names. We selected only Incidents‡ and 1% (n = 8 of 1,004) as Results from our classification revealed that 85% (n = Duration 33 Serious Events.# Also, 85% (n = 856 of a Rate Error names of companies who submitted a 158 of 187) of event reports provided sufficient in- Time 38 510(k) premarket notification† to the 1,004) of all medication errors reached formation to determine how the medication rate dif- ** U.S. Food and Drug Administration (FDA) the patient and high-alert medications fered from what was intended. Based on events with Underdosage 54 during years 2000–2018. In addition to were involved in 22% (n = 217 of sufficient information, we found that 64% (n = 101 Overdosage 72 using a keyword filter during our query 1,004) of the events. Table 1 shows a of 158) of events involved medication infusion at a cross tabulation of the 1,004 events. faster rate than intended, 32% (n = 50 of 158) infused Technique 99 * PA-PSRS is a secure, web-based system through The data show that the frequency of at a slower rate, and 4% (n = 7 of 158) had both a which Pennsylvania hospitals, ambulatory surgical events varies widely across the stages Rate (IV) 187 facilities, abortion facilities, and birthing centers sub- faster and slower rate (e.g., single event included two mit reports of patient safety–related incidents and of the medication process and types medications and were swapped on pump channels). 0 50 100 150 200 serious events in accordance with mandatory report- of medication error. In particular, the 85% While reviewing the 187 events with a Rate error, we Frequency of Events (2018) ing laws outlined in the Medical Care Availability and data reveal that 59% (n = 595 of 1,004) Reduction of Error (MCARE) Act (Act 13 of 2002). All of events were categorized as PA- attempted to identify the key contributing factor for of Events reports submitted through PA-PSRS are confidential, each event, based on information provided in the Figure 2. Factors Contributing to Rate Error and no information about individual facilities or pro- PSRS medication error taxonomy type viders is made public. free-text narrative field. We independently applied a Reached the “Wrong.” This type of medication error Device † According to the FDA, “medical device manufactur- categorization system that consisted of seven con- 4 Patient is further categorized into 11 different Maintenance ers are required to submit a premarket notification or tributing factors, which are defined in Table 2. We 510(k) if they intend to introduce a device into commer- subtypes (see Figure 1). Malfunction cial distribution for the first time or reintroduce a device evaluated our inter-rater reliability of event classifi- 4 that will be significantly changed or modified to the ex- In Figure 1, we focused on the subtypes cation with the Kappa statistic,11 which revealed that 8 tent that its safety or effectiveness could be affected.” of wrong medication error and found we had a substantial level of agreement (K = 0.730).12 Patient Behavior 4 ‡ “Incident” is defined as an event, occurrence, or situation involving the clinical care of a patient in a that 19% (n = 187 of 1,004) of the We agreed on Rate classification in 84% (n = 157 of Insufficient medical facility which could have injured the patient events were categorized as having 187) of events during our initial review. To increase Information 16 but did not either cause an unanticipated injury or a Rate error. Based on this finding, the accuracy of our results, we reviewed all 30 dis- Pre-Administration require the delivery of additional healthcare services 18 to the patient.9 we manually reviewed the free-text agreements and came to consensus on the appropri- Process Problem 22% # “Serious Event” is defined as an event, occurrence, narrative field for all 187 event reports ate contributing factor classification for each event, Tubing/ 19 or situation involving the clinical care of a patient in a with a Rate error to better understand which then resulted in 100% classification agreement.
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