Smart Infusion Pumps Research Articles

Collaboration to Remove Barriers to Pump Integration With the Electronic Health Record.

The Institute for Safe Medication Practices and The Joint Commission recommend the implementation of bidirectional smart infusion pump interoperability with the electronic health record (EHR) to improve medication safety. However, there are barriers associated with implementation of this process. The purpose of this process improvement project was to identify, evaluate, and implement improvements in pump integration with the EHR to decrease manual programming and increase the use of the smart pump functions (the dose error reduction system or infusion guardrails). A medication safety task force was formed, and end users were surveyed for barriers. The task force found and implemented solutions to improve the process. Infusion pump integration rates for seven hospitals improved from 79.4% to 91.8% (p < .001), and the use of smart pump programming increased from 84.7% to 93.6%. Including all stakeholders in the project allowed barriers to be identified and solutions to be implemented. As more healthcare systems implement technology-related processes to improve patient safety, this work can guide medication safety teams on how to optimize technology use by removing barriers to the use of pump integration with the EHR.

Evolution of Intravenous Medication Errors and Preventive Systemic Defenses in Hospital Settings-A Narrative Review of Recent Evidence.

Intravenous drug administration has been associated with severe medication errors in hospitals. The present narrative review is based on a systematic literature search, and aimed to describe the recent evolution in research on systemic causes and defenses in intravenous medication errors in hospitals. This narrative review was based on Reason's theory of systems-based risk management. A systematic literature search covering the period from June 2016 to October 2021 was conducted on Medline (Ovid). We used the search strategy and selection criteria developed for our previous systematic reviews. The included articles were analyzed and compared to our previous reviews. The updated search found 435 articles. Of the 63 included articles, 16 focused on systemic causes of intravenous medication errors, and 47 on systemic defenses. A high proportion (n = 24, 38%) of the studies were conducted in the United States or Canada. Most of the studies focused on drug administration (n = 21/63, 33%) and preparation (n = 19/63, 30%). Compared to our previous review of error causes, more studies (n = 5/16, 31%) utilized research designs with a prospective risk management approach. Within articles related to systemic defenses, smart infusion pumps remained most widely studied (n = 10/47, 21%), while those related to preparation technologies (n = 7/47, 15%) had increased. This narrative review demonstrates a growing interest in systems-based risk management for intravenous drug therapy and in introducing new technology, particularly smart infusion pumps and preparation systems, as systemic defenses. When introducing new technologies, prospective assessment and continuous monitoring of emerging safety risks should be conducted.

Infusion pump innovation: Embracing change for patients and bottom lines.

Within the infusion delivery landscape, significant room exists for an improved experience with more intuitive and interoperable solutions. The majority of smart infusion pumps still rely on technology developed more than a decade ago. Many Canadian healthcare institutions regularly undergo a comprehensive re-evaluation of infusion fleets, to modernize infusion delivery for patients across the country. Amid the availability of new technologies with evidence demonstrating their ability to elevate the current standards of care, this article argues for the need for healthcare systems to prepare for, and embrace, change when it comes to new technologies. Clinical informatics consultant, Helen Edwards, delves into why new technologies are needed now more than ever. She shares her experience with the Ivenix Infusion System, capturing how it can help redefine clinical workflows, reduce costs across the entire healthcare continuum, and better support patient care. She also offers insights on how to effectively introduce new technologies and cultivate an environment that is likely to be open and adaptive to the change. As the Canadian healthcare landscape continues to evolve, the proactive adoption of new technologies will be a step towards advancing the outcomes for patients and the sustainability of Canadian healthcare infrastructures.

Incorrect use of smart infusion pumps causes medication errors in NICU

Incorrect use of smart infusion pumps causes medication errors in NICU

SEFH National Survey-2019: general characteristics, staffing, material resources and information systems in Spain's hospital pharmacy departments

ObjectiveTo publicize the results regarding the general characteristics, human resources, materials and information systems of Spanish hospital pharmacy departments arising from SEFH's 2019 Survey on the Situation of Spanish Hospital Pharmacy Departments. MethodAn online questionnaire was sent to the heads of the 368 hospital pharmacy departments affiliated to SEFH. The questionnaire included 77 questions grouped into 8 dimensions. The information was collected between March and September 2019. ResultsThe overall response rate was 54.3%. Sixty-nine percent of hospitals were public and the most commonly reported hospital size was 101-250 beds. Nine percent of responding hospitals remained open round the clock and 57.5% did not offer a continued care service. A total of 41.9% of hospitals dispensed medications to outpatients in the afternoon and 52.7% of hospital pharmacy departments were accredited to some quality standard. The mean number of specialist pharmacists per pharmacy Department was 5.34 (SD: 6.22); 47% of pharmacists spent at least half their working day in a clinical unit. Hospital pharmacy departments had a mean of 0.3 (SD: 0.7) or 0:9 (SD: 1.4) automated storage and dispensing carousels, depending on whether they were horizontal or vertical, respectively. A total of 16.1% of beds were assisted by automated dispensing systems, a figure that reached 33.5% in hospitals with more than 1,000 beds. Three percent of hospital pharmacy departments had a robotized system for compounding chemotherapy medications and 24.8% had a traceability and safety system. Smart infusion pumps were used by 21.4% of hospitals. Electronic prescriptions were implemented in 98.8% of hospitals for inpatients and in 62% for outpatients. ConclusionsSpanish hospital pharmacy departments face a shortage of specialist pharmacists, although incorporation of such professionals to clinical units has doubled in the last few years. There has been an increase in the level of automation of the logistic processes involved in medication dispensing, but there is still significant room for improvement in the area of robotized dispensing and compounding traceability systems. This data could play an invaluable role in the design of future action plans.

The Impact of Using Smart Infusion Pumps among Nursing Practice

The most prevalent cause of medical injuries is medication errors especially when patients take multiple medications at the same period of time with different doses. One of the technologies that have been developed to improve patient outcomes is the smart infusion pump, which has the ability to identify several programming problems when applied correctly. However, based on existing use, there are contradictory reports on smart pumps' potential to avoid patients' harm in the absence of other features, as well as deliver professional care to patients. This study aimed to understand the experience of nurses when performing smart infusion pumps in their practice, the influence of this technology on their confidence, and how much this technology is trusted to rely on to prevent medical errors. Previous studies focused entirely on longitudinal and quantitative studies, which take a long time and cost a lot. A qualitative study collected from an online survey that contained three types of questions: open-ended questions, closed-ended questions, and rating questions to evaluate participants' answers about smart infusion pumps among their practices in Saudi Arabia hospitals, a survey targeting nursing staff and we got 30 replies. The outcomes have revealed a significant impact of smart infusion pumps on nursing practice.

City‐wide medication use process standardization and implementation of intravenous patient‐controlled analgesia consensus recommendations at an academic medical center

AbstractIntroductionIndianapolis Coalition for Patient Safety, Inc. (ICPS) identified practice variation across participating health‐systems related to intravenous Patient‐Controlled Analgesia (PCA) in 2018. No evidence‐based published recommendations were available to provide optimization for the medication use process during this evaluation, leading to development of an ad hoc interdisciplinary group to address gaps.ObjectivesPrimary objectives were to operationalize safe use of PCA and evaluate implementation of ICPS PCA consensus recommendations at an academic medical center by assessing PCA prescribing patterns following policy and electronic health record (EHR) changes. Secondary objectives focused on markers of adoption changes and employee engagement.MethodsICPS formed an interdisciplinary, diverse group of content experts representing six health‐systems to review current PCA processes. Significant variations were identified, and a gap‐analysis was completed to develop consensus recommendations. To evaluate implementation of these recommendations, a retrospective pre‐/post‐analysis was completed of patients at a safety‐net, academic medical center from March 2021 to July 2022 who received an order for PCA. Prescribing patterns and electronic documentation were analyzed.ResultsThe ICPS PCA Safety Summit developed 45 consensus recommendations addressing the following PCA medication use processes: ordering, patient assessment, administration, EHR design, documentation tools, smart pump drug library settings, policies, adverse event monitoring, and education. Evaluation included a total of 155 patients. The ordered total number of morphine milligram equivalent (MME) potentially available per day to a patient from PCA, electronic documentation of opioid tolerance, and PCA smart infusion pump review all significantly improved post‐implementation.ConclusionCity‐wide standardization and development of PCA consensus guidelines filled a gap in practice to provide direction and optimization for the medication use process surrounding these high‐alert medications. Organizational results following implementation provide evidence that using new EHR order sets and incorporating opioid tolerance resulted in more intentional PCA prescribing and more thorough electronic nursing documentation.

Smart Use of Smart Infusion Pumps.

Smart infusion pumps have reduced but not eliminated medication errors. These errors are frequently related to misuse or underuse of the safety features of the pump.The Institute for Safe Medication Practices offers safety considerations for using smart pumps and suggestions for maintaining an institution's smart pump drug library.

Development of smart infusion pumps: state of the art and future perspectives

Abstract This review discusses the working principle, design advantages, and limitations of intelligent infusion pumps, and points out the research prospects of intelligent infusion pumps in personalized closed-loop management and prospective medication decision-making.

Does circle priming improve smart infusion pump and electronic health record interoperability for chemotherapy in a pediatric hematology/oncology setting?

The objective of this project was to assess the percentage of interoperability compliance within our pediatric hematology/oncology patient care areas for intravenous chemotherapy medications before and after the implementation of circle priming. We conducted a retrospective quality improvement project at an inpatient pediatric hematology/oncology floor and outpatient pediatric infusion center before and after implementation of circle priming. There was a statistically significant increase in percent interoperability compliance for the inpatient pediatric hematology/oncology floor from 4.1% prior to implementation of circle priming to 35.6% after (odds ratio 13.1 (95% CI, 3.96-43.1), p < 0.001), as well as for the outpatient pediatric infusion center from 18.5% to 47.3%, respectively (odds ratio 3.9 (95% CI, 2.7-5.9), p < 0.001). Implementation of circle priming has significantly increased the percentage of interoperability compliance for intravenous chemotherapy medications in our pediatric hematology/oncology patient care areas.

The Impact of Smart Pump Technology in the Healthcare System: A Scope Review.

Smart infusion pump technology prevents errors caused by parenteral therapy. This paper aims to review the recent literature about smart pump uses, cases and adverse events, and strategies to minimize these disadvantages. Literature was explored from January 2000 to November 2021 using Google Scholar, PubMed, and ScienceDirect. There were assessments of the advantages and adverse effects of using smart pumps and strategies to overcome the adverse effects of smart pumps. The advantage of using smart pumps is that they decrease errors like incorrect rate and dose. Other benefits include a decrease in medication event rates and the ability to connect smart pumps to home health providers. However, compliance rates were negatively influenced by improper smart pumps and the overriding of soft alerts, which can cause alert fatigue and drug library update delays. Recent studies have tried to address the negative issues by improving drug library compliance and decreasing alerts to avoid alert desensitization. The investigations revealed that the smart pumps reduced errors but would only prevent some programming errors. Compliance with utilizing smart pump technology is critical in stopping medication errors. Opportunities for future improvement are broad, including integrating a smart pump infusion with the hospital system, implementing auto programming, and designing smart pump devices to be lighter, smaller, and more portable instead of the heavy, large smart pump used by most hospitals today.

From Discovery to Implementation and Interoperability of a New Smart Infusion Pump Designed for Usability and Patient Safety

Clinicians increasingly rely on technology designed for efficiency, ease of use, and patient safety; this is especially true for large volume infusion pumps. Drug Error Reduction Systems administered via smart infusion pumps offer beneficial safety options for intravenous medication administration, though they may increase complexity. Fort HealthCare successfully implemented smart pump technology designed by a new vendor (Ivenix, Inc.), including eventual integration with the electronic health record, in an expedited timeline through continual collaboration with key stakeholders and ongoing quality improvement.

WORKING PRINCIPLE AND INTELLIGENCE OF SMART INFUSION PUMP

There is a tremendous demand on the critical care resources due to the extensivespread of the ongoing coronavirus pandemic and the large number of patients requiring critical care.The efficacy of a device directly influences how long a patient lives since patients are often receivingcritical care. Smart infusion pump is a medical device that can drip fluids into the patient's body. Thisdevice is considered as one of the most safety-critical medical devices due to the way it functions andthe risks it presents. The main objective of this work is to develop an affordable infusion pump usingembedded technology. The main tactic is to develop equipment that can identify air bubbles in infusionpump tubing since even a little one might obstruct blood flow and result in mortality. This method mayprovide consumers an accurate result, making it the greatest method for identifying bubbles and savinglives.

Pharmacy practice in hospital settings in GCC countries: Dispensing and administration

PurposeTo outline dispensing and administration practices in hospital pharmacy across the Gulf Cooperation Councils (GCC) countries’ hospitals. Paucity of data in appraising hospital pharmacy practice in GCC regions motivated us to conduct this study. MethodsA modified survey questionnaire was prepared from the American Society of Health-System Pharmacist (ASHP) survey questions. Three major domains of questions for general characteristics of the medication use process for dispensing and administration were identified. These were, (1) medication distribution system, and medication distribution technology, (2) technology used to compound sterile preparations, compounding I.V. medication and method of compounding nutrition support preparations, (3) medication administration practices, medication orders, medication administration records (MARs), and technician activities. A list of hospitals was obtained from the Ministry of Health of the targeted GCC countries. A secure invitation link containing a survey questionnaire was sent to the participants directly. ResultsSixty-four hospitals responded to this survey. The overall response rate was 52%. Most surveyed hospitals have centralized inpatient medications distribution system (75.0%). About 37.5% of hospitals used automated dispensing cabinets (ADCs) in their patient care areas. Compounding sterile preparations in the pharmacy, barcode verification technology, workflow management technology, and robotic technology were used by 17.2%, 15.6%, and 4.7% of hospitals, respectively. In using safety technology for medication administration, almost all hospitals have partially or completely implemented an electronic health record (EHR). About 40.6% of hospitals used electronic medication administration records (e-MARs), 20.3% used bar-code-assisted medication administration (BCMA), and 35.9% used smart infusion pumps. ConclusionThe results of this survey revealed an opportunity to improve the medication use management process on dispensing and administration practices in hospitals in GCC countries.

Machine learning approach to predict delay in smart infusion pump

Wireless smart infusion pumps are currently under development. It is critical to ensure that the patient receives the correct drug concentration. Practically, the performance of the pump has relied on the minimum startup delay. The minimization of the startup delay is prominent in open-type infusion pumps and rarely in closed types. The emphasis on reducing startup delay puts practitioners and caregivers at ease while ensuring patient safety. The startup delay of the infusion pump is based on the flow rate and the lag time. The prediction of the flow rate and lag time for an infusion pump is necessitated to ensure a safe drug dosage for the patient. Currently, machine learning methods and computational methods to predict the desired parameter are widely used in healthcare applications and medical device performance. The reduction of start-up delay can be achieved by predicting its associated parameters lag time and flow rate. The flow rate is dependent on the speed of the infusion pump, which has to be calculated based on the number of gears and revolutions. The speed of the pump has to be predicted for accurate flow delivery. Our present research attempts to predict the lag time of an infusion pump using different kernel functions of support vector regression (SVR). The performance of the SVR for each kernel function is compared with R2, RMSE, MAE, and prediction accuracy. The prediction accuracy of 99,7 % has been obtained in optimized SVM.

Development of a proactive process to harmonize policy, infusion pump library, and electronic health record entries for continuous infusions at an academic medical center.

Standardized processes to order and prepare medications can decrease the potential for error and provider uncertainty. Our health system utilizes a standard concentration policy, smart infusion pumps, and the electronic health record (EHR) to catalog, order, and deliver intravenous medications. A need for a more proactive and formalized process to ensure medication listings are harmonized between these 3 resources was identified. Standardizing these resources can reduce confusion, reduce time spent in pharmacy operations and nursing workflow, and may improve patient safety. The purpose of this quality improvement project was to compare and resolve inconsistencies between these 3 sources and to create a new process to assure uniformity in a complex work environment. An audit-style comparison and evaluation of entries for continuous infusions within the standard concentration policy, the pump library, and the EHR was conducted. All continuous infusion entries within any one of these 3 sources were included. Key exclusion criteria included pediatric and neonatal infusions, intermittent infusions, and infusions in procedural areas. We compared the policy, the pump library, and the EHR to identify, document, and resolve discrepancies in medication name, concentration, rate, and volume; fluid restriction concentration; and upper and lower pump limits. A new method to ensure proactive continuity and consistent updates to the 3 sources was implemented into existing operational workflows. We recommended a total of 82 updates to policy (n = 48), the pump library (n = 30), and the EHR (n = 4) out of 187 continuous infusion entries. Standardizing infusion resources will reduce confusion, and improve pharmacy operations, nursing workflow, and patient safety.

EVALUATION OF MEDICAL GRADE INFUSION PUMP PARAMETER USING GAUSSIAN PROCESS REGRESSION

Prediction techniques are extensively used in medical applications and health care devices. The prediction of the infusion flow rate for the required drug dosage and drug concentration in a smart wireless infusion pump is necessary for precise drug flow for the patients. In this paper, the prediction model has been developed to predict the lag time using Gaussian Process Regression (GPR) technique with a squared exponential kernel. Currently, a smart wireless infusion pump is incorporated with its smart drug library. The required parameters such as drug dosage, drug flow rate are utilized as inputs to predict the lag time and to minimize start-up delays using the proposed regression technique. The evaluation of the prediction model is done by the coefficient of determination (R2), mean absolute error (MAE), and root-mean-squared error (RMSE). These prediction results are verified for predicting lag time for two different carrier flowrates 10 ml/hr and 50 ml/hr. The outcome of the study indicates that the regression model GPR has better prediction accuracy with a mean R2 of 0.9. Hence, the GPR technique is capable to achieve quick infusion and optimal flow rate with minimized lag time for smart infusion pumps.

Dose error reduction software in medication safety risk management \u2013 optimising the smart infusion pump dosing limits in neonatal intensive care unit prior to implementation

BackgroundSmart 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.MethodsThis 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).ResultsOf 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.ConclusionsSimulation-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.

A Systemised Approach to Smart Pump Integration with an Electronic Medical Record System – An Australian Experience

ABSTRACT Background: Smart pump integration with Electronic Medical Record (EMR) systems offers an opportunity to introduce a closed-loop medication management system in hospital settings. Closed-loop medication management systems minimise human errors, improve nursing workflow and efficiency, and optimise patient safety. In this descriptive observational study, we will outline some of the key steps required to successfully integrate a smart pump dataset with EMR computerised provider/physician order entry (CPOE) systems. Methodology: The triple C model of consultation, collaboration and consolidation was used for the development and implementation of a smart infusion pump and EMR integration at a 160-bed specialist Australian hospital. This systemised approach allowed a methodical implementation process and ensured sustainability of the intervention. Key stakeholders were identified and engaged to establish a working group to align medication orders in the EMR and the smart pump library to ensure readiness of pump-EMR integration phase. Validation testing was conducted for each EMR infusion order to check successful auto-programming to a corresponding medication on the smart pump. The steps discussed are applicable to all hospital settings with EMR systems and smart pumps. Results: The smart pump dataset contained a total of 217 unique medications and fluids that were tested for interoperability. A total of 87% (188/217) passed full record testing. The remaining 13 % (29/217) were excluded from interoperability. The 13% of medication and fluids that were excluded was due to the medication being prescribed on paper (i.e. medicines with desensitisation regimen), the medication unable to be prescribed as a medicine in the EMR (i.e. blood products), the smart pump limitations to build safety limits around only one medicine (i.e. multi-additive infusions) or excluded due to specialist hospital formulary. Conclusion: This study using a systemised approach, that described and identified key stages and phases required for integration of smart pump infusions with an EMR system, to create a closed-loop medication management system in an Australian hospital setting. Highlights

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.