Inappropriate Allocation Research Articles

Assessing Nurses Problems in Pursuing Higher Education, Implementing Evidence Based Practice and Patient Care Delivery

Aim: To assess problems of nurses related to higher education, evidence-based practice and patient care delivery. Study design: Cross-Sectional survey. Place and duration of study: Department of Nursing. UHS Lahore from 1st June 2019 to 31st December 2019. Methodology: Two hundred and thirteen nurses working in selected hospitals were enrolled. A self-structured questionnaire comprising of 21 questions was used for collection of data. Results: HE1, HE2, HE3 and HE4 statement had higher mean score, and the EBP1 and EBP6 statements had higher mean score. PCD6 statement had lower mean score as compared to remaining statements. Conclusion: Nurses were facing problems in pursuing higher education by not giving chance for higher education and due to unavailability of financial support. For implementing of evidence-based practices nursing professionals were not supportive and patient care delivery was affecting due to workload and inappropriate allocation of working units. Keywords: Nurses, Problems, Higher education, Evidence based practice, Patient care delivery

A new method of determining decision-making unit congestion under inter-temporal dependence

Congestion is an essential concept in data envelopment analysis (DEA). It occurs when the decrease in at least one decision-making unit (DMU) input increases at least one output without affecting the other inputs or outputs. Although various methods have discussed congestion determination in static DEA, congestion calculation in dynamic DEA under inter-temporal dependence has not been considered in the literature. This paper deals with the congested input levels in multi-period production systems under inter-temporal dependence and the inter-temporal dependence of production periods due to the stock capital. Due to the importance of evaluating DMUs in the presence of time factors, this paper expands the determination of congestion of DMUs under the time factor and dependence of input and output levels in periods. The proposed models determine the congested unit in the assessment window and characterize the extra-input and lack-output amounts in all of the congested unit components in each period of the assessment window. This paper aims to specify production system performance in different evaluation periods by determining the dynamic congestion of DMUs. This paper proposes a method to identify the congested paths. The main advantage of this method is to prevent inappropriate allocation of the resources during evaluation periods of the assessment window. The validity of the proposed method is investigated through an example in the banking sector. Moreover, this method can be utilized in other sectors to homogeneous units with the same structure.

Dynamic performance-Energy tradeoff consolidation with contention-aware resource provisioning in containerized clouds.

Containers have emerged as a more portable and efficient solution than virtual machines for cloud infrastructure providing both a flexible way to build and deploy applications. The quality of service, security, performance, energy consumption, among others, are essential aspects of their deployment, management, and orchestration. Inappropriate resource allocation can lead to resource contention, entailing reduced performance, poor energy efficiency, and other potentially damaging effects. In this paper, we present a set of online job allocation strategies to optimize quality of service, energy savings, and completion time, considering contention for shared on-chip resources. We consider the job allocation as the multilevel dynamic bin-packing problem that provides a lightweight runtime solution that minimizes contention and energy consumption while maximizing utilization. The proposed strategies are based on two and three levels of scheduling policies with container selection, capacity distribution, and contention-aware allocation. The energy model considers joint execution of applications of different types on shared resources generalized by the job concentration paradigm. We provide an experimental analysis of eighty-six scheduling heuristics with scientific workloads of memory and CPU-intensive jobs. The proposed techniques outperform classical solutions in terms of quality of service, energy savings, and completion time by 21.73–43.44%, 44.06–92.11%, and 16.38–24.17%, respectively, leading to a cost-efficient resource allocation for cloud infrastructures.

Renewable energy source allocation in electrical distribution system using water cycle algorithm

Achieving maximum potential benefits through appropriate allocation of distributed generation (DG) in electrical distribution systems is yet a challenging issue. Since the inappropriate allocation of DG adversely affects the distribution system. The present paper introduces a novel metaheuristic optimization method for solving the allocation of renewable energy sources (RES) in a practical distribution system. The algorithm has been effectively implemented on a practical Indian 28 – bus distribution system to allocate wind turbines (WT) and solar photovoltaic (SPV) arrays to achieve technical benefits of power loss minimization and bus voltage profile improvement. The simulation results obtained by the present method are compared with existing literature and it is found to be better.

Economic efficiency of coastal hotel companies

The article focuses on the analysis of the economic efficiency of Slovenian coastal hotel companies in the period between 2015 and 2018. We applied non-parametric Data Envelopment Analysis to estimate economic efficiency and the panel regression analysis to explain the association between economic efficiency, economic growth, and the hotel location. The results showed that most coastal hotel companies were economically inefficient associated with decreasing returns to scale. As a key source of inefficiency we identified inappropriate allocation of inputs. Given the high concentration of hotels in the municipality of Piran, the hypothesis on higher efficiencies in this location area has been rejected. Most coastal municipalities were negatively related to the economic efficiency of the hotel companies. We also rejected the hypothesis that economic growth affected the economic efficiency of the Slovenian coastal hotel companies.

Evaluating the use of the landslide database in spatial planning in mountain communes (the Polish Carpathians)

Landslide hazards and risk assessment should be a basic tool in risk management, as well as an integral part of spatial planning, especially in mountain areas The study addresses the problem of inappropriate allocation of land for residential and economic functions in terms of landslide hazard. The research covered the area of the Polish Carpathians within voivodships of Małopolskie and Podkarpackie, in which there are 201 communes. The occurrence of landslides in relation to existing and potential residential areas was examined in detail for 14 selected communes. This area due to their geological structure and relief is prone to landslides in inhabited areas. The current vector databases of landslides (the Landslide Counteracting System-LCS, SOPO Polish acronym), data on planning coverage in communes (Ministry of Development and Central Statistical Office of Poland), location of existing buildings (Database of Topographic Objects, BDOT, Polish acronym), and range and purpose of local spatial development plan (LSDP; Geo-System) were used. A high natural hazard of landslides in the 14 analysed communes in the Polish Carpathians (1–23% of the communes area) was demonstrated, as well as faulty spatial planning related to the designation of land for development in local plans (up to 11% on landslides). Dissemination of knowledge about landslide locations and threats and proper spatial planning is the most effective form of reducing the risk of landslide losses. Landslide data and maps should be made widely available to local communities, along with information on planned land use. It is necessary to raise landslide awareness among local communities with information campaigns and to consider scientific arguments in the elaboration process of the LSDP, and while accelerating the process of updating them.

A deterministic river temperature model to prioritize management of riparian woodlands to reduce summer maximum river temperatures

AbstractIncreasing river temperatures are a threat to cold water species including ecologically and economically important freshwater fish, such as Atlantic salmon. In 2018, ca. 70% of Scottish rivers experienced temperatures which cause thermal stress in juvenile salmon, a situation expected to become increasingly common under climate change. Management of riparian woodlands is proven to protect cold water habitats. However, creation of new riparian woodlands can be costly and logistically challenging. It is therefore important that planting can be prioritized to areas where it is most needed and can be most effective in reducing river temperatures. The effects of riparian woodland on channel shading depend on complex interactions between channel width, orientation, aspect, gradient, tree height and solar geometry. Subsequent effects on river temperature are influenced by water volume and residence time. This study developed a deterministic river temperature model, driven by energy gains from solar radiation that are modified by water volume and residence time. The resulting output is a planting prioritization metric that compares potential warming between scenarios with and without riparian woodland. The prioritization metric has a reach scale spatial resolution, but can be mapped at large spatial scales using information obtained from a digital river network. The results indicate that water volume and residence time, as represented by river order, are a dominant control on the effectiveness of riparian woodland in reducing river temperature. Ignoring these effects could result in a sub‐optimal prioritization process and inappropriate resource allocation. Within river order, effectiveness of riparian shading depends on interactions between channel and landscape characteristics. Given the complexity and interacting nature of controls, the use of simple universal planting criteria is not appropriate. Instead, managers should be provided with maps that translate complex models into readily useable tools to prioritize riparian tree planting to mitigate the impacts of high river temperatures.

Attention switching deficit in patients of Parkinson’s disease who experience freezing of gait

Attention switching is involved in postural adjustments for gait. A deficit in attention switching was expected among patients having Parkinson's disease and experiencing freezing. There was a deficit in attention switching abilities among the patients of Parkinson's disease, having episodes of freezing of gait. The task accuracy and reaction time of the freezing group was significantly reduced compared to the non-freezing group having Parkinson's disease and healthy control group on total AST task performance, congruent and incongruent trials. The non-freezing group with Parkinson's disease was also slower than the healthy control group, but its accuracy was not affected. The results suggest that patients with freezing of gait experienced a stronger deficit in attention-switching than the non-freezing group of Parkinson's disease. This attention switching deficit among freezers may imply inappropriate allocation of attention for postural responses required for stepping and resulting in freezing. Also, the non-freezing group may have prioritized accuracy over time as a compensatory strategy that may be slowing their gait but prevents freezing.

From digital divide to digital inclusion: Challenges for wide-ranging digitalization in Pakistan

The developments, in information and communication technology (ICT), have significantly impacted on some key sectors of societies (such as transport, health, business, education and communication) in many developed and developing countries of the world. However, the Internet has proliferated unevenly across the world, resulting in a global digital divide. In the past decade, concerns related to technology ‘haves’ and ‘haves not’ have grown in prominence in the countries of South Asia (including India, Pakistan, Bangladesh and Nepal) that are witnessing an increased digital divide. This study specifically looks at the case of Pakistan. The country's digital inequalities are increasing in terms of the public's access and their use of the Internet and ICT devices (such as mobile phones and computers). Therefore, drawing on the framework of digital divide, this study aims is to explore the diverse challenges that underpin digital divide in Pakistan, and the policy-related issues that affect wide-ranging digitalization in the country. To achieve this aim, this study uses qualitative methods of document review and in-depth interviews and offers thematic analysis of data. This study reveals that contextual factors, including urban-rural divide, gender disparity, income and educational inequalities, religious and cultural barriers, all together underpin Pakistan's existing digital divide. This study further unpacks policy-related challenges, including: a lack of policy evaluation and refinement; a lack of focused research; and inappropriate allocations of funds at federal, national and sectoral levels that affect wide-ranging digitalization in the country.

MO1038JOB BURNOUT IN RARE DISEASE RESEARCH PHYSICIANS DURING COVID-19 PANDEMIC

Background and AimsDoctors are exposed to high levels of stress in their profession and are particularly susceptible to experiencing burnout. Rare disease researches are enlightening, with more workload to clinicians, especially during the Covid-19 pandemic. We aim to explore the mental influence of participating in rare disease researches on clinicians.MethodDoctors received electronic questionnaires regarding job-burnout in October 2020. The modified Maslach Burnout Inventory-General Survey (MBI-GS) was used to evaluate job burnout state. The MBI-GS consisting of three dimensions, emotional exhaustion (five questions), cynicism (five questions), and reduced personal accomplishment (six questions). The 7-grade Likert scale is adopted in each question, from 0 point (never) to 6 points (very frequently). Job burnout was considered if the average score of any dimension is no less than three. ResultsQuestionnaires from all 203 doctors were analysed in this study, with females (70.0%, n=140). Age ranging from 25 to 39, 40 to 54, and above 55 were 41.4%, 50.7%, 7.9%, respectively. Nearly half of the subjects (50.2%, n=102) fulfil the definition of job-burnout, which was fewer than that in the residency program (50.2% vs. 62.9%, p=0.02). An inappropriate evaluation system (36.0%) and lack of private time (35.5%) were the leading cause of job-burnout. The pressure of scientific researches (79.3%) and career promotion (58.1%) was the major source of mental pressure.Doctors who participated in rare disease researches (46.8%, n=95) did not show significant differences in burnout rate than individuals who did not (44.2% vs 55.6%, p=0.123), nor as in three dimensions (27.3% vs 36.1%, p=0.183 for emotional exhaustion, 21.1% vs 20.4%, p=0.905 for cynicism, 21.1% vs 27.8%, p=0.267 for reduced personal accomplishment). Logistic analysis revealed that high requirement from superior (22.5% vs 6.9%, p= 0.001), pressure from family (33.3% vs 17.8%, p=0.010), inappropriate job allocation (47.1% vs 29.7%, p= 0.019) as well as delayed off-work time (p=0.013) were independent risk factors of job-burnout. Physicians who participate in rare disease research had better job allocation (75.8% vs. 49.1%, p<0.001), but not in the other three risk factors. ConclusionMore workload did not increase the job-burnout of physicians participating in the rare disease research, which might be contributed by the appropriate job allocation.

Interpretive structural modelling of inter-agency collaboration risk in public safety networks

Inter-agency collaboration is a well-established, yet very difficult process in public governance. Despite the fact that it is often unsuccessful, collaboration risk research is still undeveloped and the impact of this risk on the effectiveness of joint activities is still underestimated. This issue is of particular significance in public safety networks, where inter-agency collaboration processes are conducted under the conditions of the complexity and uncertainty. For this reason, the article is intended to: (1) identify factors of collaboration risk in public safety networks, (2) determine the impact of individual risk factors on inter-agency collaboration outcomes, (3) identify the relationship between risk factors of inter-agency collaboration in public safety networks, and (4) analyse the growth of this risk in public safety networks. These purposes were achieved using the Systematic Literature Review based on PRISMA Group methodology and Interpretive Structural Modelling together with MICMAC analysis. The applied research approach also has some limitations resulting from the number of experts. However, the results obtained allow us to better understand issues of inter-agency collaboration risk in public safety networks. They identify key collaboration risk factors, such as inappropriate collaboration rules and inadequate allocation of tasks and resources. In consequence, they indicate risk symptoms that are worth keeping track of in order to prevent collaboration ineffectiveness.

Loss-Voltage Sensitivity Analysis Based Battery Energy Storage Systems Allocation and Distributed Generation Capacity Upgrade

Distributed Generation (DG) has become a key component in modern power industry due its significant advantages over the traditional power generation methods. Nevertheless, best expected outcomes can only be achieved with optimal allocation of DG resources where inappropriate allocation may impose problems in power system stability, protection and quality. This paper presents analytical approaches for optimizing the DG size, BESS (Battery Energy Storage Systems) capacities and power dispatch in Medium Voltage (MV) networks. Since most of the existing analytical approaches related to optimizing DG sizes for minimizing network losses and voltage deviations have considered individual objective function separately, both parameters may not be minimized simultaneously. Thus, in this paper, an analytical methodology was formulated based on an objective function built on new parameter Loss-Voltage Sensitivity Index (LVSI) that evaluates both minimum impact of network loss and voltage variations for optimizing the DG size. The results obtained from this approach were compared with a conventional Genetic Algorithm (GA) formulated by the authors. The BESS capacities are determined considering the effects of Load Proportionality Factor (LPF), State of Charge limits (SOC) of battery storages, number of load areas and the portion of daily off-peak solar generation period energy consumption expected to be served by each BESS unit. The significance of this BESS capacity determination methodology is highlighted as the BESS capacities can be numerically calculated whereas in existing work, they are heavily relying on conventional optimization techniques which do not give an idea about the internal behavior of parameters which determine the capacities of BESS units. Moreover, an optimal BESS dispatch algorithm is also presented in this paper for minimizing the energy losses and voltage deviations. The applicability of the proposed methodologies are verified using the standard IEEE-33 and IEEE-69 test bus systems. Simulations carried out in MATLAB is used to illustrate the accuracy and the appropriateness of the proposed approaches.

Self-Adapting Channel Allocation for Multiple Tenants Sharing SSD Devices

Solid-state drives (SSDs) have been widely deployed in high-performance data center environments, where multiple tenants usually share the same hardware. However, traditional SSDs distribute the users&#x2019; incoming data uniformly across all SSD channels, which leads to numerous access conflicts. Meanwhile, SSDs that blindly allocate one or several channels to one tenant sacrifice device parallelism and capacity. When SSDs are shared by tenants with different access patterns, inappropriate channel allocation results in SSD performance degradation. In this article, we propose a self-adapting channel allocation mechanism, named SSDKeeper, for multiple tenants that share one SSD. SSDKeeper employs a machine learning-assisted algorithm to take full advantage of SSD parallelism while providing performance isolation. By collecting multitenant access patterns, SSDKeeper predicts an optimal channel allocation strategy for multiple tenants using the well-trained model. To further consume the blocks in different channels evenly, SSDKeeper equips with a novel channel swap scheme to prolong the SSD lifespan. Comparing with traditional SSDs, SSDKeeper reduces the overall latency of read and write by 12.6&#x0025; and the lifespan is prolonged up to <inline-formula> <tex-math notation="LaTeX">$3.7\times $ </tex-math></inline-formula>.

Intraoperative waste segregation initiative among anesthesia personnel to contain disposal costs

Approximately 90% of medical waste generated in the operating room (OR) is considered to be non-infectious and non-regulated (Wyssusek, Keys & van Zundert, 2019). Frequently, this waste is inappropriately disposed of into infectious regulated medical waste containers. Due to differences in waste treatment, improper segregation can lead to the misuse or inappropriate allocation of resources, environmental pollution, and increased cost for institutions. A waste segregation initiative was instituted in a tertiary care medical center in the anesthesia work-space of 35 ORs. This initiative included education of medical waste management to increase anesthesia staff knowledge and compliance with waste segregation and optimization of existing waste disposal containers to decrease waste disposal costs. After implementation, there was an increase in overall provider knowledge (p < 0.001) particularly in the categories of medication vial disposal, medication disposal and identification of items for disposal in the sharps containers (p ≤ 0.05). Data suggests a 34.7% increase in providers reporting to always practice waste segregation (p ≤ 0.05). Additionally, there was a statistically significant decrease in overall weight of regulated medical waste items from 0.33 kg/case to 0.09 kg/case (p < 0.001). This decrease in regulated waste supports an improvement in waste segregation and inappropriate items being disposed of in the general trash container. The omission of inappropriate waste was further confirmed by a segregation audit that showed an overall increase in correctly segregated regulated waste of 65%. Collectively, this lead to a cost savings of $15.60 per OR per week, or $28,392 annually.

Impact of nonclinical factors on intensive care unit admission decisions: a vignette-based randomized trial (V-TRIAGE).

ObjectiveTo assess the impact of intensive care unit bed availability, distractors and choice framing on intensive care unit admission decisions.MethodsThis study was a randomized factorial trial using patient-based vignettes. The vignettes were deemed archetypical for intensive care unit admission or refusal, as judged by a group of experts. Intensive care unit physicians were randomized to 1) an increased distraction (intervention) or a control group, 2) an intensive care unit bed scarcity or nonscarcity (availability) setting, and 3) a multiple-choice or omission (status quo) vignette scenario. The primary outcome was the proportion of appropriate intensive care unit allocations, defined as concordance with the allocation decision made by the group of experts.ResultsWe analyzed 125 physicians. Overall, distractors had no impact on the outcome; however, there was a differential drop-out rate, with fewer physicians in the intervention arm completing the questionnaire. Intensive care unit bed availability was associated with an inappropriate allocation of vignettes deemed inappropriate for intensive care unit admission (OR = 2.47; 95%CI 1.19 - 5.11) but not of vignettes appropriate for intensive care unit admission. There was a significant interaction with the presence of distractors (p = 0.007), with intensive care unit bed availability being associated with increased intensive care unit admission of vignettes inappropriate for intensive care unit admission in the distractor (intervention) arm (OR = 9.82; 95%CI 2.68 - 25.93) but not in the control group (OR = 1.02; 95%CI 0.38 - 2.72). Multiple choices were associated with increased inappropriate allocation in comparison to the omission group (OR = 5.18; 95%CI 1.37 - 19.61).ConclusionIntensive care unit bed availability and cognitive biases were associated with inappropriate intensive care unit allocation decisions. These findings may have implications for intensive care unit admission policies.

Application of data computing for resource scheduling in manufacturing industries

Cloud based solutions and services can be used in production sectors to maximize profit and to develop complex products through reconfiguration of manufacturing supply chain through dynamic process. Scheduling and allocation of resources to tasks is a critical issue, since inappropriate allocation and scheduling may affect the utilization rate, cost and time. Cloud manufacturing encompass flexible services from manufacturing enterprise with IT based services to improve the performance of an application. This work considers Differential Evolutionary (DE) and Gravitational Search algorithm for implementation, since these approaches can narrow the solution search space and improves convergence rate. The tasks and resources used for the experimentation process were classified and incorporated from casting industries. The computational results on the identified workflow proves that, DEGSA algorithm maximizes resource utilization, maintains load balance and minimizes the computational time of jobs.

Optimal time management on linear accelerator: A logical model to reduce patient waiting time.

Optimal time management is of utmost importance in the radiotherapy department. Inappropriate allocation of time slots leads to prolonged waiting times and decreased patient satisfaction during external beam radiotherapy. The present study tests a logical model to improve the waiting time for the patients. The treatment time, waiting time, and causes of delay were studied from November 4, 2014, to July 24, 2015. New rules were framed for treatment slot allocation from December 26, 2014. The treatment slots were classified based on the treatment technology (three-dimensional conformal radiotherapy and intensity-modulated radiotherapy) with inclusion of "buffer slots" and patient education. The results were compared before and after rules. A total of 1032 time slots were analyzed, of which 225 "before rules" and 807 "after rules," respectively. There was a significant reduction in the average waiting time for treatment in on-time patients (median [interquartile range (IQR)] of 25.2 min [31.75] vs. 3 min [3.5]; P< 0.00001) as well as in late-coming patients (median [IQR] of 38.2 min [13.795] vs. 21.11 min [12.75]; P= 0.00006). 59.7% (71 patients) of the treatment was delayed "before rules" as opposed to 32.2% (137 patients) "after rules" in on-time patients. Due to better patient education, there was a significant improvement in the patient punctuality toward the allotted time. The treatment slots classified based on the teletherapy technique with buffer slots, and patient education helps in better time management on linear accelerator. This methodology significantly reduces waiting time and thereby the number of patients having delay in the treatment.

Health-care reform implementation challenges at suburban areas in Isfahan province: A qualitative study.

BACKGROUND:Health system reform plan in public health sector in Iran in the first phase focused on improving primary health care in suburban areas in and around big cities. The present study was conducted to assess the implementation process challenges of the reform plan in comprehensive health service centers at suburban areas of Isfahan in 2019.MATERIALS AND METHODS:This qualitative study with conventional content analysis approach was conducted in 2019. Participants were purposefully selected and interviewed at provincial levels from Isfahan University of Medical Sciences health department and health-care providers of comprehensive health services centers. The saturation point was reached after 21 face-to-face semi-structured interviews. Thematic analysis was employed to analyze transcribed documents assisted by MAXQDA version 10.RESULTS:The results revealed four main themes; the human resource management, the executive management, the electronic infrastructure, and the resource management. The major challenges in the implementation planning process included: the referral system, monitoring and supervision, electronic services infrastructure in the design and development of the EHR called the SIB system, lack of instructions guide, salaries and benefits, inconsistent financial and human resources and inappropriate allocation of theses resources.CONCLUSION:Despite the achievements in the development of the Iran health system reform plan, there were many challenges in the implementation planning process. It is recommended that theses challenges be reviewed and amended by health system managers and policymakers.

Explaining return on equity through economic value added and its components by modulating the quality of profit

From the point of view of investment, low profit quality is not desirable because it will lead to an inappropriate allocation of capital. Users will pay attention to the outcomes of the accounting system, including reported earnings, to measure economic growth. When value issues are raised, the criteria for assessing performance and quality must be evaluated. The present study seeks to study the difference between the economic value added information content and its components, based on the Biddle et al. (1997) and Weset and Worthington (2000) models. On the other hand, with the help of the modified Jones model, the quality of accruals was measured. Combined data (172) company-years (2009 to 2018) were used. The hypotheses were analyzed by regression and t, F test. According to the findings, the information content of the economic value added component of the economic value added is more aggregate. The results of the parent test indicate a significant difference between the content of the economic value added components. Adding the quality of profit to the model leads to a change in the information content of the models. The quality of profit is related to the relationship between economic value added and stock returns, and this interactive effect has also been observed in the level of economic value added components.

Staging Total Hip and Knee Arthroplasty Procedures Within 90 Days Increases Costs in Bundled Payment Programs

BackgroundUnder current Medicare bundled payment programs, when a patient undergoes a subsequent elective procedure within the 90-day episode-of-care, the first procedure is excluded from the bundle and a new episode-of-care initiated. The purpose of this study was to determine if staging bilateral total hip (THA) and total knee arthroplasty (TKA) procedures within 90 days have an effect on bundled episode-of-care costs. MethodsWe reviewed a consecutive series of Medicare patients undergoing staged primary THA and TKA from 2015-2019. Patients who underwent a prior procedure within 90 days were compared to those who had undergone a procedure 90-120 days prior. We then performed a multivariate analysis to identify the independent effect of staging timeframe on costs and outcomes. ResultsOf the 136 patients undergoing a staged bilateral THA or TKA, 48 patients underwent staged procedures within 90 days (35%) and 88 patients between 91-120 days (65%). There were no significant differences observed for demographics, comorbidities, complications, readmissions, or discharge disposition (all P > .05). Patients undergoing a staged procedure within 90 days had increased episode-of-care costs by $2021 (95% CI $11-$4032, P = .049), increased postacute care costs by $2019 (95% CI $66-$3971, P < .001), and reduced per-patient margin by $2868 (95% CI-$866-$4869, P = .005). DiscussionPatients undergoing staged bilateral THA or TKA within 90 days have increased episode-of-care costs compared to those undergoing a staged procedure from 91-120 days. Since patients may still not be fully recovered from the first procedure, CMS should address the inappropriate allocation of costs to ensure institutions are not penalized.