Smart pumps improve medication safety but increase alert burden in neonatal care

Frontline nursing staff's perceptions of intravenous medication administration: the first step toward safer infusion processes-a qualitative study

OBJECTIVES

Intravenous medication errors continue to significantly impact patient safety and outcomes. This study sought to clarify the complexity and risks of the intravenous administration process.

DESIGN

A qualitative focus group interview study.

SETTING

Focused interviews were conducted using process mapping with frontline nurses responsible for medication administration in September 2020.

PARTICIPANTS

Front line experiened nurses from a Japanese tertiary teaching hospital.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome measure was to identify the mental models frontline nurses used during intravenous medication administration, which influence their interactions with patients, and secondarily, to examine the medication process gaps between the mental models nurses perceive and the actual defined medication administration process.

RESULTS

We found gaps between the perceived clinical administration process and the real process challenges with an emphasis on the importance of verifying to see if the drug was ordered for the patient immediately before its administration.

CONCLUSIONS

This novel and applied improvement approach can help nurses and managers better understand the process vulnerability of the infusion process and develop a deeper understanding of the administration steps useful for reliably improving the safety of intravenous medications.

Optimizing the Use of Dose Error Reduction Software on Intravenous Infusion Pumps

BACKGROUND AND OBJECTIVES

Intravenous infusions have the potential to cause significant harm in patients and are associated with a high rate of adverse drug events and medication errors. Infusion pumps with dose error reduction software (DERS) can be used to reduce errors by establishing safe infusion parameters. In 2019, a quality improvement project was initiated with the aim to increase DERS compliance from 46% to 75% at our specialty institution by October 1, 2022.

METHODS

An interdisciplinary group was tasked with improving compliance with DERS by identifying key drivers, including informed staff, engaged staff, and an accurate smart pump library. We used the Model for Improvement framework to guide this improvement project, and Plan-Do-Study-Act (PDSA) cycles were used to plan for interventions. PDSA cycles included drug library updates, education, and unit-level compliance reporting. Weekly average DERS compliance was monitored as the outcome measure, and weekly pump alerts per 100 infusions were monitored as a balancing measure; statistical process control charts were used to monitor measures from 2018 to 2022.

RESULTS

Over the course of 25 months, 8 PDSA cycles resulted in 5 centerline improvements from a baseline mean of 46% to a final mean of 78%. Pump alerts per 100 infusions decreased from 15.9 to 6.4 with the first PDSA cycle and then continued to decrease to 3.9 with subsequent interventions.

CONCLUSIONS

Although features like DERS can help ensure safe medication administration, continuous improvement efforts to increase DERS compliance without increasing alert burden are needed to ensure that benefits of this technology are optimized.

National evaluation of harm associated with patient safety incident reports related to the provision of parenteral nutrition to patients, using a national incident reporting system

BACKGROUND

Parenteral nutrition (PN)-related patient safety incidents have been associated with harm. Large-scale studies are scarce, and little is known about contributory factors. This study evaluated PN-related incident reports that described harm using a national database.

MATERIALS AND METHODS

A retrospective evaluation of incident reports involving PN in England and Wales reported to the National Reporting and Learning System between 2015 and 2020. We described frequency by degree of reported harm and incident characteristics. Content analysis was undertaken to understand contributory factors for reports related to moderate/severe harm or death.

RESULTS

12,907 incident reports were identified. After screening, 2242 were evaluated; 1879 (83.8%) reported no harm, 309 (13.8%) low harm, 47 (0.02%) moderate harm, 4 (0.002%) severe harm, 3 (0.001%) deaths. The most reported age group, medication process, and error category were neonates (<28 days) (n = 570/1923, 29.6%), administration (n = 1126/2242, 50%), and omitted medication/ingredient (n = 291/2242, 13%), respectively. Content analysis of reports related to moderate/severe harm and death revealed patient age of <1 year, dependence on home PN (HPN), comorbidities, and staff errors as contributory factors.

CONCLUSIONS

This is the first evaluation of PN-related incident reports in England and Wales to our knowledge. We demonstrated a low frequency of reports related to moderate or severe harm or death. More incidents were reported for neonates and during the administration processes. To reduce harm, systems/procedures that reduce errors in high-risk patients (eg, neonates, patients receiving HPN) need to be established within organizations. Database limitations of voluntary reporting systems were recognized.

Protocolization of Analgesia and Sedation Through Smart Technology in Intensive Care: Improving Patient Safety

BACKGROUND

The risk of medication errors in intensive care units is high, primarily in the drug administration phase.

LOCAL PROBLEM

Management of high-alert medications within intensive care units in the study institution varied widely. The aim of this quality improvement project was to protocolize and centralize the management of high-alert medications in acute care settings and to implement smart intravenous infusion pump technology in intensive care units.

METHODS

The project was conducted in 4 phases: (1) protocolization and standardization of intravenous mixtures, (2) centralization of intravenous mixture preparation in the Pharmacy Department, (3) programming of the smart pumps, and (4) dissemination and staged implementation of intravenous mixture protocols. Smart pumps (Alaris, CareFusion) were used to deliver the medicines, and the manufacturer's software (Alaris Guardrails, CareFusion) was used to analyze data regarding adherence to the drug library and the number of programming errors detected.

RESULTS

Morphine, remifentanil, fentanyl, midazolam, dexmedetomidine, and propofol were included. After implementation of the smart pumps, 3283 infusions were started; of these, 2198 were programmed through the drug library, indicating 67% compliance with the safety software. The pumps intercepted 398 infusion-related programming errors that led to cancellation or reprogramming of drug infusions.

CONCLUSIONS

Protocolization and centralization of the preparation of high-alert sedative and analgesic medications for critically ill patients and the administration of these drugs using smart pump technology decrease variability of clinical practice and intercept potentially serious medication errors.

Optimizing Pediatric Patient Safety in the Emergency Care Setting

Patient safety is the foundation of high-quality health care and remains a critical priority for all clinicians caring for children. There are numerous aspects of pediatric care that increase the risk of patient harm, including but not limited to risk from medication errors attributable to weight-dependent dosing and need for appropriate equipment and training. Of note, the majority of children who are ill and injured are brought to community hospital emergency departments. It is, therefore, imperative that all emergency departments practice patient safety principles, support a culture of safety, and adopt best practices to improve safety for all children seeking emergency care. This technical report outlined the challenges and resources necessary to minimize pediatric medical errors and to provide safe medical care for children of all ages in emergency care settings.

Optimizing Pediatric Patient Safety in the Emergency Care Setting

This is a revision of the previous American Academy of Pediatrics policy statement titled "Patient Safety in the Emergency Care Setting," and is the first joint policy statement by the American Academy of Pediatrics, the American College of Emergency Physicians, and the Emergency Nurses Association to address pediatric patient safety in the emergency care setting. Caring for children in the emergency setting can be prone to medical errors because of a number of environmental and human factors. The emergency department (ED) has frequent workflow interruptions, multiple care transitions, and barriers to effective communication. In addition, the high volume of patients, high-decision density under time pressure, diagnostic uncertainty, and limited knowledge of patients' history and preexisting conditions make the safe care of critically ill and injured patients even more challenging. It is critical that all EDs, including general EDs who care for the majority of ill and injured children, understand the unique safety issues related to children. Furthermore, it is imperative that all EDs practice patient safety principles, support a culture of safety, and adopt best practices to improve safety for all children seeking emergency care. This policy statement outlines the recommendations necessary for EDs to minimize pediatric medical errors and to provide safe care for children of all ages.

Dose error reduction software in medication safety risk management - optimising the smart infusion pump dosing limits in neonatal intensive care unit prior to implementation

Background

Smart infusion pumps with dose error reduction software can be used to prevent harmful medication errors. The aim of this study was to develop a method for defining and assessing optimal dosing limits in a neonatal intensive care unit’s smart infusion pump drug library by using simulation-type test cases developed based on medication error reports.

Methods

This mixed-methods study applied both qualitative and quantitative methods. First, wrong infusion rate-related medication errors reported in the neonatal intensive care unit during 2018–2019 were explored by quantitative descriptive analysis and qualitative content analysis to identify the error mechanisms. The researchers developed simulation-type test cases with potential errors, and a literature-based calculation formula was used to set upper soft limits to the drug library. The limits were evaluated by conducting programming of pumps without errors and with potential errors for two imaginary test patients (1 kg and 3.5 kg).

Results

Of all medication errors reported in the neonatal intensive care unit, 3.5% (n = 21/601) involved an error or near-miss related to wrong infusion rate. Based on the identified error mechanisms, 2-, 5-, and 10-fold infusion rates, as well as mix-ups between infusion rates of different drugs, were established as test cases. When conducting the pump programming for the test cases (n = 226), no alerts were triggered with infusion rates responding to the usual dosages (n = 32). 73% (n = 70/96) of the erroneous 2-, 5-, and 10-fold infusion rates caused an alert. Mix-ups between infusion rates triggered an alert only in 24% (n = 24/98) of the test cases.

Conclusions

Simulation-type test cases can be applied to assess the appropriateness of dosing limits within the neonatal intensive care unit’s drug library. In developing the test cases, combining hospital’s medication error data to other prospective data collection methods is recommended to gain a comprehensive understanding on mechanisms of wrong infusion rate errors. After drug library implementation, the alert log data and drug library compliance should be studied to verify suitability of dosing limits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-022-03183-8.

Safety Considerations for the Inpatient Medication-Use Process in Pediatric and Neonatal Patients

The delivery of safe and effective healthcare to pediatric and neonatal patients presents unique challenges to the medication-use system. The diversity of patients within this population and the consequences of ontogeny on pharmacokinetics and pharmacodynamics directly impact the safe use of medications in children and increase the risk of adverse drug events.1 This review will explore the medication-use system for hospitalized children and neonates, discuss vulnerabilities within this system, and provide examples of advancements made to improve the pediatric medication-use system.

Human-Based Errors Involving Smart Infusion Pumps: A Catalog of Error Types and Prevention Strategies

Over 4000 preventable injuries due to medication errors occur each year in any given hospital. Smart pumps have been widely introduced as one means to prevent these errors. Although smart pumps have been implemented to prevent errors, they fail to prevent specific types of errors in the medication administration process and may introduce new errors themselves. As a result, unique prevention strategies have been implemented by providers. No catalog of smart pump error types and prevention strategies currently exists. The aim of this study is to review and catalog the types of human-based errors related to smart pump use identified in the literature and to summarize the associated error-prevention strategies. We searched MEDLINE, PubMed, PubMed Central, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) for literature pertaining to human-based errors associated with smart pumps. Studies related to smart pump implementation, other types of pumps, and mechanical failures were excluded. Final selections were mapped for error types and associated prevention strategies. A total of 1177 articles were initially identified, and 105 articles were included in the final review. Extraction of error types and prevention strategies resulted in the identification of 18 error types and ten prevention strategies. Through a comprehensive literature review, we compiled a catalog of smart pump-related errors and associated prevention strategies. Strategies were mapped to error types to provide an initial framework for others to use as a resource in their error reviews and improvement work. Future research should assess the application of the resources provided by this review.

Controlling Anesthesia Hardware With Simple Hand Gestures: Thumbs Up or Thumbs Down?

BACKGROUND

Modern consumer electronic devices and automobiles are often controlled by interfaces that sense physical gestures and spoken commands. In contrast, patient monitors and anesthesia devices are typically equipped with panel-mounted buttons, dials, and keyboards. The increased use of noncontact gesture-based interfaces in anesthesia may improve patient safety through more intuitive and prompter control of equipment and also through reduced rates of surface contamination. A novel gesture-based controller was designed and retrofitted to a standard GE Solar 8000M patient monitor. This type of technical innovation is rare, due to closely held proprietary input control systems on commercially produced clinical equipment. Nevertheless, we hypothesized that anesthesiologists would find a contactless gesture interface straightforward to use.

METHODS

A gesture-based interface system was developed to control a Solar 8000M patient monitor using a millimeter-wave radar sensor. The system was programmed to detect noncontact "rotate" and "press" gestures to control the patient monitor by implementing a virtual trim knob for interface control. Fifty anesthesiologists tested a prototype interface and evaluated usability by completing a short questionnaire incorporating modified Likert scales. These evaluations were performed in a nonpatient care environment so that respondents were not adversely task loaded during assessment, also allaying any ethical or safety concerns regarding use of this novel interface for patient management.

RESULTS

Anesthesia hardware was controlled reliably with 2 distinct gestures above the gesture sensor. The gesture-based interface generally was well received by anesthesiologists (8.09; confidence interval, 8.06-8.12 on a 10-point scale), who preferred the simpler "press" gesture to the "rotate" gesture (8.45; 8.39-8.51 vs 7.73; 7.67-7.79 on a 10-point scale; P = .005). The correlation between the preference scores for the 2 gestures from each anesthesiologist was strong (Pearson r = 0.49; 0.25-0.68; P < .001). Advancing level of training (resident, fellow, attending 1-10 years, attending >10 years) was not correlated with preference scores for either gesture (Spearman ρ = -0.02; -0.30 to 0.26; P = .87 for "press" and Spearman ρ = 0.08; -0.20 to 0.35; P = .58 for "rotate").

CONCLUSIONS

The use of gesture sensing for controlling anesthesia equipment was well received by a cohort of anesthesiologists. Even though the simpler "press" gesture was preferred over the "rotate" gesture, the intrarespondent correlation indicates that the preference for gestures as a whole is the stronger effect. No adverse relationship was found between acceptability and anesthesia experience level. Gesture sensing is a promising new area to simplify and improve the interaction between the anesthesiologist and the anesthesia workstation.

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.

Convolutional neural network-based ambient light-independent panel digit surveillance technique for infusion pumps

For effective patient therapy and improved patient safety, it is critical to administer medication accurately in accordance with doctor's prescription. However, accidents owing to the erroneous programing of infusion pumps caused by users have been consistently reported in several documents. In this study, the authors propose a novel surveillance technique for infusion pumps to continuously monitor the variations in panel digits using a convolutional neural network model, and evaluate the performance of the implemented technique. During the experimental evaluation, 1st-step ROIs and 2nd-step ROIs were successfully extracted from the frame images regardless of the ambient lighting conditions. The final accuracies of the implemented CNN model are 99.9% for both the training (172,800 images) and validation (1080 images) dataset while the final losses for the training and validation datasets are 0.48 and 0.45 after 13th epoch, respectively. In the 24-h continuous monitoring test, the accuracy of the model for volume recognition considering all the 1440 measurements (960 for day-lighting and 480 for night-lighting) is 95.5%, whereas in day-lighting and night-lighting modes the accuracies of the model are 98.2% and 90.0%, respectively. Based on these experimental results, the proposed surveillance technique incorporating infusion pumps is expected to improve the safety of patients who need long-term treatments via infusion pumps, reducing the burden on the nurses and hospitals.

Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study

Background

At present, electronic health records (EHRs) are the central focus of clinical informatics given their role as the primary source of clinical data. Despite their granularity, the EHR data heavily rely on manual input and are prone to human errors. Many other sources of data exist in the clinical setting, including digital medical devices such as smart infusion pumps. When incorporated with prescribing data from EHRs, smart pump records (SPRs) are capable of shedding light on actions that take place during the medication use process. However, harmoniz-ing the 2 sources is hindered by multiple technical challenges, and the data quality and utility of SPRs have not been fully realized.

Objective

This study aims to evaluate the quality and utility of SPRs incorporated with EHR data in detecting medication administration errors. Our overarching hypothesis is that SPRs would contribute unique information in the med-ication use process, enabling more comprehensive detection of discrepancies and potential errors in medication administration.

Methods

We evaluated the medication use process of 9 high-risk medications for patients admitted to the neonatal inten-sive care unit during a 1-year period. An automated algorithm was developed to align SPRs with their medica-tion orders in the EHRs using patient ID, medication name, and timestamp. The aligned data were manually re-viewed by a clinical research coordinator and 2 pediatric physicians to identify discrepancies in medication ad-ministration. The data quality of SPRs was assessed with the proportion of information that was linked to valid EHR orders. To evaluate their utility, we compared the frequency and severity of discrepancies captured by the SPR and EHR data, respectively. A novel concordance assessment was also developed to understand the detec-tion power and capabilities of SPR and EHR data.

Results

Approximately 70% of the SPRs contained valid patient IDs and medication names, making them feasible for data integration. After combining the 2 sources, the investigative team reviewed 2307 medication orders with 10,575 medication administration records (MARs) and 23,397 SPRs. A total of 321 MAR and 682 SPR dis-crepancies were identified, with vasopressors showing the highest discrepancy rates, followed by narcotics and total parenteral nutrition. Compared with EHR MARs, substantial dosing discrepancies were more commonly detectable using the SPRs. The concordance analysis showed little overlap between MAR and SPR discrepan-cies, with most discrepancies captured by the SPR data.

Conclusions

We integrated smart infusion pump information with EHR data to analyze the most error-prone phases of the medication lifecycle. The findings suggested that SPRs could be a more reliable data source for medication error detection. Ultimately, it is imperative to integrate SPR information with EHR data to fully detect and mitigate medication administration errors in the clinical setting.