Process Improvement Strategies Research Articles

Process improvement strategy (PIS) and employee productivity amid COVID-19 pandemic among bank employees

PurposeThis study aims to examine process improvement strategy (PIS) (proxied by remote work, workforce training, and technological innovation), and employee productivity amid the COVID-19 pandemic among bank employees.Design/methodology/approachThe study employed cross-sectional and descriptive design by applying multistage sampling techniques using convenience sampling to select the study organization and stratified and simple random sampling to select 900 respondents for the study. Data were collected by using validated measures of the study variables designed into a questionnaire. Pearson’s correlation and simple regression analysis were employed to establish relationships and causal effects among variables respectively.FindingsResults showed significant relationships between the PIS (work-from-home, workplace training, and technological innovation) and the outcome variable (employee productivity); and predictive capabilities between the PIS and the outcome variables (employee productivity). The study revealed that remote work accounted for the highest variability (R2 = 0.775) in employee productivity, followed by workplace training (R2 = 0.499), and finally investment in technological innovation (R2 = 0.486)] and as such PIS fosters employee productivity and may, therefore, be applied when faced with a similar pandemic in the future.Originality/valueThe study was recognized for its significance in examining how PIS supports enhancing employee productivity in banks and, by extension, other organizations during a pandemic. The research has proven to be crucial in providing insights into bank management in emerging economies and other organizations worldwide that have previously gone unnoticed during a pandemic. It has aided in the extension of existing literature on PIS and employee productivity by carefully developing a framework, thus covering practical knowledge gaps.

Incremental Societal Costs of Perioperative Complications Following Adult Elective Inpatient Major Therapeutic Surgery in the State of Florida: A Seven-Year Retrospective Epidemiological Analysis.

Introduction There is an expanding role for anesthesiologists in the preoperative optimization and postoperative management of patients, often in the context of a so-called perioperative surgical home. Such efforts typically include enhanced recovery after surgery (ERAS) protocols and often an anesthesiologist-led team for perioperative management. Studies of the cost-effectiveness of such approaches have generally been conducted at single institutions, with most patients cared for by small numbers of surgeons. This limitation creates generalizability issues as to whether improvement was related mostly to organizational culture or the studied surgeons' practices (non-generalizable) versusthe procedures (generalizable). We studied whether other organizations can rely on achieving similar benefits following the adoption of a studied process improvement strategy at a single institution. Methods All patients undergoing elective major therapeutic inpatient surgery discharged between October 2015 and June 2022 at non-federal hospitals in the state of Florida were included. For each discharge, the United States Medicare Severity Diagnosis-Related Group (MS-DRG) weighting factor (i.e., the multiplier for the hospital's base rate for admissions that determines reimbursement) and the Clinical Classification Software Refined (CCSR) code for the principal procedure were determined at admission and discharge from the state's inpatient healthcare database based on the diagnoses present at those time points. An increase in the weighting factor from admission to discharge represents societal costs from perioperative complications. Statewide, by hospital, and by surgeon, we calculated the total increase for each CCSR's weighting factor. Our primary hypothesis was that surgeon variability would be statistically greater than CCSR variability but that the incremental effect would be <5%. If CCSR and surgeon variability were comparable, this would be supportive of generalizability. In contrast, if there were a predominant effectrelated to the surgeon, results from one institution might not be applicable to others. Results Among the 1,482,344 discharges studied, the pooled (N=7 years) contributions to MS-DRG weighting factor increases from the upper 20% of surgeons were 2.8% more than from the upper 20% of CCSRs (95% CI 1.9%-3.9%, p=0.0006). Those CCSRs accounted for 85.5% (95% CI 79.4%-91.7%, p<0.0001) of the total increase in the MS-DRG weighting factor. The average contribution of the top two surgeons at each hospital to that hospital's increase in the weighting factor ranged among CCSRs from 68% to 97%.The median and 75th percentile of surgeons performing at least 10% of the total number of cases at each hospital was similar to those values for the contributions to the increases in the MS-DRG weighting factor, median 2.0 to 3.0, and 75th percentile 1.75 to 4.0. Conclusions Because variability among surgeons in their contributions to increases in the MS-DRG weighting factor only slightly exceeded the variability among CCSR surgical categories, perioperative surgical home and ERAS study research results involving single institutions and a small number of surgeons would likely be generalizable to other hospitals and healthcare systems. Funding agencies should not be hesitant to fund single-center perioperative surgical home studiesand ERAS interventions based on concerns related to lack of generalizability.

Intelligent optimization of steam gasification catalysts for palm oil waste using support vector machine and adaptive transition marine predator algorithm

The present study investigates the optimization of the steam gasification process for the conversion of palm oil waste into environmentally friendly energy, utilizing the catalytic properties of calcium oxide and coal bottom ash. The objective of our research is to investigate the enhancement of the conversion process by employing a machine-learning approach. Specifically, we utilize a support vector machine (SVM) to model and evaluate the impact of different operational parameters on the resulting gas mixture. One notable feature of this study involves the incorporation of an adaptive marine predator algorithm (AMPA) into the SVM framework, aiming to enhance the predicted precision and efficiency of the model. The primary focus of this study revolves around the development of an intelligent optimization framework that surpasses conventional machine learning techniques, hence providing a more dynamic and efficient strategy for process improvement. The SVM model’s performance, as assessed against experimental benchmarks, exhibits a notable degree of predictive accuracy and substantial concurrence with observed data. This increase in performance indicates that our methodology has the potential to make a significant contribution to the enhancement of renewable catalysts in gasification processes. The findings of this study could potentially have significant ramifications for the advancement of renewable energy production and the creation of intelligent systems in complicated industrial applications.

Process Intensification for Enhanced Fluoride Removal and Recovery as Calcium Fluoride Using a Fluidized Bed Reactor.

This study explored the feasibility of fluoride removal from simulated semiconductor industry wastewater and its recovery as calcium fluoride using fluidized bed crystallization. The continuous reactor showed the best performance (>90% fluoride removal and >95% crystallization efficiency) at a calcium-to-fluoride ratio of 0.6 within the first 40 days of continuous operation. The resulting particle size increased by more than double during this time, along with a 36% increase in the seed bed height, indicating the deposition of CaF2 onto the silica seed. The SEM-EDX analysis showed the size and shape of the crystals formed, along with the presence of a high amount of Ca-F ions. The purity of the CaF2 crystals was determined to be 91.1% though ICP-OES analysis. Following the continuous experiment, different process improvement strategies were explored. The addition of an excess amount of calcium resulted in the removal of an additional 6% of the fluoride; however, compared to this single-stage process, a two-stage approach was found to be a better strategy to achieve a low effluent concentration of fluoride. The fluoride removal reached 94% with this two-stage approach under the optimum conditions of 4 + 1 h HRT combinations and a [Ca2+]/[F-] ratio of 0.55 and 0.7 for the two reactors, respectively. CFD simulation showed the impact of the inlet diameter, bottom-angle shape, and width-to-height ratio of the reactor on the mixing inside the reactor and the possibility of further improvement in the reactor performance by optimizing the FBR configuration.

Abstract TP119: Predicting Posterior Circulation Stroke During Emergency Triage: Dizzy-7 Project

Introduction: “Stroke code” activation is a uniform process to summon healthcare stakeholders to orchestrate the rapid sequential steps for urgent management in patients with possible stroke. Acute dizziness, a common emergency department (ED) presentation, frequently leads to stroke code activation; however, cancellation rates remain high and process improvement strategies are warranted. Methods: We analyzed stroke identification accuracy, cancellation rates, and clinical characteristics in patients presenting with an acute vestibular syndrome to inform process improvement strategies for stroke code activation. We developed an ED triage diagnostic algorithm termed, “Dizzy-7”, based on evidence incorporating key history and physical examination elements derived in patients with acute posterior circulation ischemia. Subsequent analyses were performed on algorithmic utilization and its ability to predict stroke. Results: 1599 patients presented with acute dizziness over a 4-month period (2022-2023). Stroke code activation occurred in nearly one in four (366/1599) these presentations. 20% (319/1599) were ultimately diagnosed with stroke and of these, 49% (319/366) were identified following stroke code activation. The Dizzy-7 algorithm was used infrequently (4%) among all acute dizziness presentations. Of the 65 cases that incorporated the algorithm, 16 resultant stroke code activations occurred with 1 confirmed diagnosis (6%). We analyzed stroke alert cancellation and found an increased frequency in cancellation for those without use of the protocol at 22% (77/350) compared to those who did use it at 6% (1/16). Discussion: Accurate and reliable identification of acute ischemic stroke among patients presenting with acute dizziness remains complex. Implementation of a triage diagnostic algorithm based on contemporary evidence was infrequently implemented. Process improvement efforts targeted at greater algorithmic use, interprofessional collaboration, and education may improve stroke code utilization efficiency. Although based on limited sample size, a trend towards reduced stroke code cancellation rates were seen throughout the pilot Dizzy-7 algorithm use.

Assessing Exergy Efficiency in Computer-Aided Modeled Large-Scale Production of Chitosan Microbeads Modified with Thiourea and Magnetite Nanoparticles

Chitosan, the deacetylated derivative of chitin, is a biopolymer with many applications in different sectors, such as pharmaceutical, food, and wastewater treatment, amongst others. It can be used as a source for synthesizing bioadsorbents modified with chelators and nanoparticles for the removal of pollutants. In this report, we conducted an exergy analysis to evaluate the large-scale production of chitosan-based bioadsorbents modified with iron nanoparticles and chelators. The objective was to identify energy inefficiencies and propose technological enhancements to improve energy utilization. The process was simulated using Aspen Plus V.10® software, enabling the quantification of chemical and physical exergies for the species and streams involved. We calculated process irreversibilities, exergy losses, waste exergy, and utility exergy flows for each stage and the overall process. These findings provide valuable insights into optimizing energy utilization in the production of chitosan-based bioadsorbents. The overall exergy efficiency was 4.98%, with the washing and drying stages of nanoparticles and adsorbent synthesis accounting for the largest contribution to process irreversibilities and exergy destruction. To increase the global exergy efficiency of the process, it is proposed to implement process improvement strategies, such as mass or energy integration, to obtain better energy performance.

Improving Operating Room Efficiency Through Reducing First Start Delays in an Academic Center.

Delays in operating room (OR) first-case start times can cause additional costs for hospitals, healthcare team frustration and delay in patient care. Here, a novel process improvement strategy to improving first-case start times is presented. First case in room start times were recorded for ORs at an academic medical center. Three interventions-automatic preoperative orders, dot phrases to permit re-creation of unavailable consent forms, and improved H&P linking to the surgical encounter-were implemented to target documentation-related delays. Monthly percentages of first-case on-time starts (FCOTS) and time saved were compared with the "preintervention" time period, and total cost savings were estimated. During the first 3-months after implementation of the interventions, the percentage of FCOTS improved from an average of 36.7%-52.7%. Total time savings across all ORs over the same time period was found to be 55.63 hours, which is estimated to have saved a total of $121,834.52 over the 3-month interventional period. By implementing multiple quality improvement interventions, delays to first start in room OR cases can be meaningfully reduced. Quality improvement protocols targeted toward root causes of OR delays can be a significant driver to reduce healthcare costs.

The better work, better care framework: 7 strategies for sustainable healthcare system process improvement

ABSTRACT Healthcare systems are under pressure to control costs and improve performance. Efforts to apply improvement trends such as “Lean” and other industrial engineering approaches have led to degradation of the working environment for healthcare professionals. Research is increasingly demonstrating how poor working environments contribute to declines in care quality and has led to calls for a “quadruple aim” with a focus on the working environment alongside quality, cost, and patient experience factors. This paper contributes to the debate by using a “systems” perspective to propose seven strategies by which healthcare systems might be improved without compromising the working environment. This article presents a rationale for these strategies based on current organisational psychology and human factors research and how these strategies might be deployed in practice. The authors argue that better working conditions leads to better care for patients and presents a viable approach for both practitioners and researchers to pursue the “Better Work, Better Care” agenda.

Using FOCUS-PDSA Quality Improvement Methodology Model in Healthcare: Process and Outcomes.

Using FOCUS-PDSA Quality Improvement Methodology Model in Healthcare: Process and Outcomes.

Perancangan Autolamp pada Mesin Cutting untuk Meminimasi Produk Cacat Menggunakan Metode QFD di CV. XYZ

Current technological developments benefit the Indonesian garment industry. Garment business must continue to innovate and improve the quality of their products in order to compete in an increasingly competitive market. CV. XYZ is a garment company in Bandung with superior products PDL shirts. The company is facing conflicts over fabric cutting process defects that have not been controlled. It is not yet known exactly the root cause of the cutting process resulting in high product defects. The purpose of this study is to determine the causes of high defects in the cutting process and design improvement strategies in the cutting process that suit user needs. The method used is FMEA which aims to determine the highest causes of defects in the cutting process so that strategies are obtained to minimize product defects, and the QFD method is used to design improvement strategies in the cutting process.. The results of the FMEA analysis found that the main cause of defects in the cutting process was eye fatigue in the operator caused by insufficient lighting in the cutting area. Using the QFD method produces an autolamp design that is integrated into the cutting machine with the function of providing lighting to the cutting area to make it easier for operators to see the fabric cutting pattern area. By using the QFD method in designing autolamp on cutting machines, it can produce product designs that meet the needs of cutting operators and have optimal features.

D153. Improving Operating Room Efficiency Through Reducing First Start Delays in an Academic Center

PURPOSE: Delays in operating room (OR) first case start times can cause additional costs for hospitals, healthcare team frustration and delay patient care. Here, we present our findings on a novel process improvement strategy and its effects on improving first case start times at an academic medical center. METHODS: First case in room start times were recorded for operating rooms at an academic medical center. Three interventions - automatic pre-operative orders, dot phrases to permit re-creation of unavailable consent forms, and improved H&P linking to the surgical encounter - were implemented to target documentation-related delays. Monthly percentages of first case on-time starts (FCOTS) and time saved were compared to the “pre-intervention” time period. Total cost savings from reduced operating room time was also estimated. RESULTS: During the first 3-months after implementation of the interventions, the percentage of FCOTS improved from an average of 36.7% to 52.7%. Total time savings across all operating rooms over the same time period was found to be 55.63 hours, which is estimated to have saved a total of $121,834.52 over the three-month interventional period. CONCLUSION: By implementing multiple quality improvement interventions, delays to first start in room OR cases can be meaningfully reduced. In high volume surgical centers and hospitals, these incremental changes can lead to substantial cost savings in both direct and indirect costs. Understanding the root causes of OR delays and designing quality improvement protocols to target those root causes can ultimately be a significant driver to reduce healthcare costs.

Process and catalyst improvements for the dry reforming of methane

Catalyst and process improvement strategies for dry reforming of methane (DRM) are shown by enhancing the performance of an existing Ni/Al2O3 catalyst and adding oxygen to the feed. Alumina-supported Ni-Co catalyst, Ni/Co molar ratio = 3, was synthesized and calcined at 500 and 850 °C to take advantage of the possible strong metal-support interactions. The freshly reduced catalysts contained Ni-Co alloys. Higher CH4 and CO2 conversions, H2 and CO yields and H2/CO ratio during DRM and oxidative dry reforming of methane (ODRM) were achieved at 600 and 750 °C and two space-velocities for Ni3Co-500 due to a higher effective dispersion of 4.9 %. Significant carbon formation and activity loss occurred during DRM. Increasing the reaction temperature and/or with O2 co-feed increased the CH4 conversion. The outlet concentrations were stable, and carbon formed was significantly less. Changes in the crystallite size and near-surface alloy composition in the spent catalyst were detected.

Growth Process and Optical Properties of Cs2ZrCl6 Doped with Ce3+ and Li+ Crystals

Cs2ZrCl6 (CZC) has very promising scintillation properties in the application of gamma-ray spectroscopy. So far, undoped crystals of this composition have been studied, but the growth of the large-scale doped single crystals has not been reported so far. In this paper, a process improvement strategy is reported. Large-scale Cs2ZrCl6:Ce,Li (CZC:Ce,Li) single crystals with excellent energy resolution are obtained by appropriately adjusting the temperature gradient and growth rate. CZC:Ce,Li single crystals doped with 0.5, 1.5, and 3.0 mol % Ce3+ were grown by the Bridgman method. After the phase purity of the sample was determined by X-ray diffraction analysis, the crystal defects were determined by the energy-dispersive X-ray spectroscopy, and the crystal growth process was improved on this basis. The transmission spectrum confirmed the improvement of crystal quality. The energy resolution of CZC:Ce,Li crystals grown by the improved process is 4.3%, which confirmed that the improved process is conducive to the growth of bulk doped CZC single crystals, and hence, our results provide a basis for the growth of large-scale doped CZC single crystals.

Excellent dielectric energy storage properties of barium titanate based Pb-free ceramics through composition modification and processing improvement

To acquire electric capacitors with enhanced energy storing performance, a composition embellishment and process improvement strategy were adopted. A serial of lead-free (Ba0.875Bi0.125) (Li0.0625Nb0.0625Ti0.875)O3(BBLNT) ceramics were prepared via both conventional solid-state method and viscous polymer processing technology (VPP). The BBLNT-VPP ceramics achieved an ultrahigh energy storing density of 5.34 J/cm3 and a reasonable efficiency of 88% at 470 kV/cm. In addition, the ceramics have particularly extraordinary temperature stability of Wrec2.8 J/cm3, △η2.5% over 30–150 °C, as well as excellent frequency stability with Wrec3.46 J/cm3, η88%, △Wrec±2.7% and △η±4% in the range of 5–300 Hz. Meanwhile, the power density of the ceramic remained above 84.04 MW/cm3 when the temperature was increased from room temperature to about 150 °C, indicating the ceramics possess great promise. Therefore, the BBLNT-VPP ceramics with excellent properties obtained in this work can be potentially applied in dielectric capacitors.

Comparative functional microbiome profiling of various animal manures during their anaerobic digestion in biogas production processes

Anaerobic digestion (AD) for bio-methane production continues to be plagued by major problems such as acidification, ammonia inhibition, long reaction periods, and expensive biogas upgrading. In this study, the authors suggest that intrinsic microbial roles during AD have previously been understudied yet they are the basis for discovery of effective and substrate-specific strategies for biogas process improvement. A comparison of the functional microbiome profiling of fresh cow, horse, pig, and chicken manures sourced from seven farms around Gauteng in South Africa was done. Correlation of profiles of the daily and cumulative biogas and bio-methane production determined in an automatic methane potential system (AMPTS), six intermediate AD compounds (propionate, butyrate, formic acid, lactic acid, ethanol, and acetate) observed using a modular Thermo Scientific Vanquish Core high performance liquid chromatography (HPLC) system, and active microbiome observed through Illumina 16S rDNA high-throughput sequencing suggests that cow manure AD went through 2 quick and efficient phases while horse manure showed 3 phases with hydrolysis being the rate limiting step, pig manure showed 4 phases and was dominated with hydrogenotrophic methanogenesis, and chicken manure had 2 phases affected by ammonia inhibition. It was inferred from the findings, that co-digestion of the horse manure within the first 9 days with cow manure, manipulation of Methanococcus hydrogenotrophs from pig manure AD in 2 stage reactor co-digestion systems, introduction of Methanococcus-rich inoculum from a pig manure AD system (between Day 15 & Day 24) as well as trace nutrient supplementation to boost SAOB, are strategies that can improve hydrolysis & methanogenesis in horse manure AD, upgrade biogas quality from various substrates, counter ammonia inhibition in chicken manure AD as well as in other similar substrates respectively.

Nursing Workforce Optimization Study: A Multi-method Evaluation and Process Improvement Intervention for HIV Service Delivery in Tanzania and Zambia.

Nurses are often suboptimally used in HIV care, due to misalignment of training and practice, workflow inefficiencies, and management challenges. We sought to understand nursing workforce capacity and support implementation of process improvement strategies to improve efficiency of HIV service delivery in Tanzania and Zambia. We conducted time and motion observations and task analyses at 16 facilities followed by process improvement workshops. On average, each nurse cared for 45 clients per day in Tanzania and 29 in Zambia. Administrative tasks and documentation occupied large proportions of nurse time. Self-reported competency was low at baseline and higher at follow-up for identifying and managing treatment failure and prescribing antiretroviral therapy. After workshops, facilities changed care processes, provided additional training and mentorship, and changed staffing and supervision. Efficiency outcomes were stable despite staffing increases. Collaborative approaches to use workforce data to engage providers in improvement strategies can support roll-out of nurse-managed HIV treatment.

Maximization of Resources in Health Care Facilities: Simple Review Article

Internationally, public health systems are under pressure to fulfill rising healthcare demand while facing increasing financial constraints. The amount of health outcomes that can be obtained with public healthcare spending must consequently be maximized. The debate of resource allocation in medical systems is crucial because, in systems with various financing sources, resources used to treat one sickness or person cannot be used to treat another condition or person. Initiatives to improve quality and safety are essential throughout the health care system. It is crucial to use a variety of process improvement strategies to spot inefficiencies and provide patients with unnecessary, yet preventable, carousing various techniques and tools for quality improvement, including as Plan-Do-Study-Act (PDSA), Six Sigma, and others. Several of the Global Sustainable Development Goals have included the idea of fairness in the delivery of health services, particularly the goal of universal health coverage. The efficiency of healthcare delivery at both the operational and system levels continue to be a topic of study as a result of rising healthcare expenditures and limited resources. Therefore, given little resources and complex population health needs, health planners and managers have had to struggle with striking a balance between the two.

Observational process data analytics using causal inference

AbstractVoluminous process data are available with the paradigm shift toward smart manufacturing. However, most historical data are observational, containing noncausal correlations due to confounders and mediators. Estimating causal effects from observational data remains a bottleneck in leveraging them for active applications such as optimization and control. This work aims to introduce a causal modeling framework for analyzing observational process data and extracting quantitative causal information. We demonstrate a real‐world application in steel manufacturing where causal inference is used to analyze observational production data and improve the steelmaking process. Additionally, we propose a novel formulation for identifying critical process parameters from observational data, where causal inference is combined with variance‐based methods to estimate corresponding risks of interventions to the manufacturing system. The proposed methods are compared with statistical ones to illustrate that causally interpreting statistical correlation leads to problematic results, while the provided workflow generates satisfactory strategies for process improvement.

Integrating 1G with 2G Bioethanol Production by Using Distillers’ Dried Grains with Solubles (DDGS) as the Feedstock for Lignocellulolytic Enzyme Production

First-generation (1G) bioethanol is one of the most used liquid biofuels in the transport industry. It is generated by using sugar- or starch-based feedstocks, while second-generation (2G) bioethanol is generated by using lignocellulosic feedstocks. Distillers’ dried grains with solubles (DDGS) is a byproduct of first-generation bioethanol production with a current annual production of 22.6 million tons in the USA. DDGS is rich in fiber and valuable nutrients contents, which can be used to produce lignocellulolytic enzymes such as cellulases and hemicellulases for 2G bioethanol production. However, DDGS needs a pretreatment method such as dilute acid, ammonia soaking, or steam hydrolysis to release monosaccharides and short-length oligosaccharides as fermentable sugars for use in microbial media. These fermentable sugars can then induce microbial growth and enzyme production compared to only glucose or xylose in the media. In addition, selection of one or more suitable microbial strains, which work best with the DDGS for enzyme production, is also needed. Media optimization and fermentation process optimization strategies can then be applied to find the optimum conditions for the production of cellulases and hemicellulases needed for 2G bioethanol production. Therefore, in this review, a summary of all such techniques is compiled with a special focus on recent findings obtained in previous pieces of research conducted by the authors and by others in the literature. Furthermore, a comparison of such techniques applied to other feedstocks and process improvement strategies is also provided. Overall, dilute acid pretreatment is proven to be better than other pretreatment methods, and fermentation optimization strategies can enhance enzyme production by considerable folds with a suitable feedstock such as DDGS. Future studies can be further enhanced by the technoeconomic viability of DDGS as the on-site enzyme feedstock for the manufacture of second-generation bioethanol (2G) in first-generation (1G) ethanol plants, thus bridging the two processes for the efficient production of bioethanol using corn or other starch-based lignocellulosic plants.

A Systematic Review of Nursing Practice Workarounds.

Nursing practice workarounds (NPWs) are a significant problem for health care organizations. Identified NPWs serve as a catalyst for innovation to improve efficiency, patient safety, and system design. To date, a systematic review of NPW literature has not been performed. The aim of this systematic review was to synthesize evidence of NPW definitions, context, and prevention strategies, utilizing previous research to develop a framework that examines the current state of this phenomenon and implications for clinical practice, while highlighting the need for future research. A systematic review of the literature was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Academic Search, Ovid MEDLINE, PubMed, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and Google Scholar databases were reviewed for eligible studies from 2013 to 2020. Results were further screened and sorted by relevance and scored for quality. Thirteen studies were included. Studies lacked the use of theory, and NPW definitions were varied. Nursing workarounds occurred most frequently when implementing new technology (46%) and when administering medications (31%). Contributing factors were workplace stressors and obstructions in workflow environment. Workaround prevention strategies include open communication and a proactive approach addressing conditions, situations, and processes. Overall study quality was low. This systematic review provides valuable information for critical care nurses and administrators regarding NPW. Implications for practice include the need for proactive and open communication between nurses and administrators when new technology and/or patient care processes require NPW. Administrative considerations include process and environmental improvement strategies to remove perceived workflow barriers. Future research to examine causes and consequences of NPW is needed to identify interventions for NPW prevention. Specific nursing considerations include workload, staffing and time constraints, and impacts of work-related stress levels. Critical care nursing processes should be examined for common NPW challenges. Interventions developed to address these challenges should then be tested to further advance evidence-based critical care nursing care.