Transfer Delay Research Articles

Abstract TP59: Prehospital Identification Of Acute Ischaemic Stroke With Large Vessel Occlusion

Background: The prehospital stroke scale B-FAST (Gaze deviation, Face paresis, Arm weakness, Visual loss and Speech disruptions ) was implemented in the Emergency Medical Services (EMS) in the Western Norway Regional Health Trust (1,1 million catchment population; eight primary stroke centres (PSC) ; two comprehensive stroke centres (CSC)) in 2019 to detect acute ischaemic stroke (AIS) patients with large vessel occlusion (LVO). Prehospital presence of gaze deviation (B-symptom)and at least one FAST symptom, may lead to PSC bypass and proceed directly to a CSC. The aim of the study was to investigate the sensitivity of the B-FAST scale detecting LVO in the prehospital setting. Methods: Retrospective study including patients with at least one B-FAST symptom at EMS arrival. We obtained patient data from all code red stroke dispatches from Emergency Medical Communication Centres (EMCC) and local endovascular treatment (EVT) registries in the period August-December 2020. Variables collected were clinical features, CT examination and reperfusion treatment. Definition of prehospital positive B-FAST was presence of Gaze deviation (B-symptom)and at least one FAST symptom at EMS arrival. Results: We collected data on 643 patients, 59 were diagnosed with a LVO stroke at hospital arrival. In the LVO group, 7 of 59 patients presented with prehospital positive B-FAST, resulting in a sensitivity of 12 %. EVT was performed in 38/59 (64%) cases. Two patients were false negative and positive predictive value was 78%. Specificity was 99% and negative predictive value 83%. Median transfer delay for patients initially admitted to a PSC before transfer to a CSC, was 130 min (IQR 60-167 min). Conclusion: The use of B-FAST by EMS personnel for identification of AIS patients with LVO has a low sensitivity, but presence of gaze deviation predicts LVO stroke with high certainty.

Adaptive Bandwidth Management Model for Wireless Mobile Ad-hoc Network

The quality of service (QoS) component in a mobile ad-hoc network has an active role in the current network scenario. In a dynamic mobile ad hoc network, ensuring optimum QoS with a scarce network resource is a significant challenge. To achieve QoS, it is essential to adopt some effective and efficient mechanisms. We have proposed an adaptive bandwidth manager model (ABMM) which uses a bandwidthsharing concept along with the flexible bandwidth reservation algorithm (FBRA) for an effective, quick and authentic data transfer. During real-time data transfer, to make communication effective, we make use of bandwidth-sharing network design problems and the concept of reserving bandwidth in high-performance networks. In our proposed model we are concentrating on the maximum utilization of resources, and using the scheduling concept to provide the minimum required bandwidth guarantee to QoS flows. Our goal is to reduce the delay in data transfer and enhance the throughput while properly utilizing the system resources. Our simulation result also shows that our model improves the network performance.

Acuity-Based Allocation of ICU-Downstream Beds with Flexible Staffing

Intensive care units (ICUs) are crucial resources within hospitals, caring for the most critically ill patients. We propose a novel modeling framework that improves the outflow of ICU patients by anticipating unit interactions and resource sharing within the system. Across an arbitrary bipartite network of units, we consider two types of downstream staffing (baseline and flexible) and a two-stage decision process. In the first stage, we determine the level of flexible bed staffing using existing physical beds at downstream units in anticipation of incoming transfers from the ICUs. In the second stage, we determine the allocation of ICU patients to downstream beds. The goal of the model is to reduce inefficiencies and transfer delays causing ICU bed block due to lack of space in downstream units. We formulate a dynamic multiperiod model and analyze the dual of its (relaxed) stationary counterpart. Decomposing the relaxed stationary model into an ICU and downstream subproblems, we calculate the relative values of downstream beds and derive a practical acuity-based policy for the daily operational decisions. Using a large-scale simulation calibrated with historic hospital data, we demonstrate that our acuity-based policy reduces the number of long-run diverted ICU arrivals, particularly in high-demand scenarios, thus improving ICU throughput, when compared with a deterministic, a generalized randomized-most-idle, and static policies. History: Accepted by J. Paul Brooks, Area Editor for Applications in Biology, Medicine, & Healthcare. Funding: This work was partially supported by National Science Foundation [Grants CMMI-1635301/1635410/1635642]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.1267 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2021.0133 ) at ( http://dx.doi.org/10.5281/zenodo.7194693 ).

Handedness in low-birthweight children: Insights in lateralization.

Low-birthweight (LBW) children (n = 96) weighing less than 2.5 kg at birth and normal birthweight (NBW) children (n = 96) from Delhi, India, between the ages of 5 and 12 years were assessed for intelligence with Ravens Colored Progressive Matrices (RCPM), their handedness and hand proficiency for unimanual and bimanual performance. The objective was to know if there is a relation between birthweight and the development of handedness. Compared with NBW children, the LBW group had lower percentile scores for the RCPM. The LBW children were less lateralized than the NBW children in the hand preference test. The LBW children were faster than the NBW for sorting objects with each hand separately, but they were slower in the bimanual envelope task. This indicates a delay in interhemispheric transfer and the development of the corpus callosum that connects the cerebral hemispheres to enable bimanual coordination. In the absence of more direct evidence, hand skill was used as an index of the extent of lateralized control for performance. Findings indicate a relation between birthweight and lateralization in children tested for hand preference.

Modeling of Water Transfer Delay for Optimal Operation of Integrated Electrical-Water System

This paper investigates the transfer delays of a water distribution system (WDS). The delay implies that water balance between the supply and demand does not meet instantly, which may affect the regulation capability of WDS on the electricity consumption profile. Current research did not consider the role the transfer delay plays in the cooperative operation of power system and WDS. Not considering the delay hinders the water flow dynamics from being used to provide energy flexibility for the power system operation. An electrical-water analogy method is proposed to model the water transfer delay of WDS. The cooperative operation model of the WDS and power system is created to facilitate the incorporation of wind power to the power system and lower the operation cost. Moreover, a graph-based searching scheme is developed to enable efficient and accurate calculation of the pressures and water flows in the WDS network. Case studies are presented to demonstrate the merits of the proposed electrical-water analogy method in power system operation.

Placement of Edge Servers in Mobile Cloud Computing using Artificial Bee Colony Algorithm

Utilizing smart mobile devices for entertainment, education, and social networking has grown recently. Even though mobile applications are getting more sophisticated and resource-intensive, the computing power of mobile devices is still constrained. Mobile phone applications can perform better by shifting parts of their functions to cloud servers. However, because the cloud is frequently positioned far from mobile phone users, there may be a significant and unpredictable delay in the data transfer between users and the cloud. It is crucial for mobile applications since customers value rapid responses greatly. Users of mobile phones can get close-up access to information technology and cloud computing services thanks to mobile edge computing. In this article, the main goal is to use an artificial bee colony meta-innovative algorithm to solve the problem of placing edge servers in mobile edge computing. Moreover, load balancing between servers is one of the challenges discussed in this article. To deal with this issue, determination the locations of the servers using considering the distribution of workload between servers as a cost function in the artificial bee colony algorithm is a focused issue in this study. The results of the proposed method are compared with the load balancing criteria. The results of K-means compared to the clustering method show the superiority of the proposed method with regard to the loading criteria compared to this clustering method.

Decentralized Dispatch of Distributed Multi-Energy Systems With Comprehensive Regulation of Heat Transport in District Heating Networks

Distributed Energy Systems(DES) interconnected with Electric Power Network(EPN) and District Heating Network(DHN) have drawn great attention recently as they promote user-side coordination of multi-energy flows. However, the difference in physical nature between electric power transmission and heat transport has brought difficulties to the modelling and decentralized optimization. In this article, a new DHN model considering delay and storage features of pipeline heat migration and heat transfer between fluids is proposed through trigonometric expansion of the decision series and the heat current method. The model comprehensively characterizes the heat transport in the system and a dispatch problem considering hybrid regulation of fluid flow rates and temperatures in DHN is then established. A primal-decomposition-based decentralized gradient descent method in accompany with Alternating Direction Method of Multipliers(ADMM) is proposed to optimize the DESs in a fully decentralized manner. Case study on two test systems validates the effectiveness of the proposed model and method to further harness the potential of DHN, which reduce renewable energy curtailment by 17.3% and 27.0% respectively.

In-network Placement of Reusable Computing Tasks in an SDN-based Network Edge

Edge computing is aimed to support compute-intensive data-hungry interactive applications which can hardly run on resource-constrained consumer devices and may suffer from running in the cloud due to the long data transfer delay. The edge network nodes' heterogeneous and limited (compared to the cloud) capabilities make the computing task placement a challenge. In this paper, we propose a novel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-network</i> task placement strategy aimed at minimizing the edge network resources usage. The proposal specifically accounts for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">time-limited reusable</i> computing tasks, i.e., tasks whose output can be cached to serve requests from different consumers for a certain time. Caching such results, during their time validity, achieves the twofold benefit of reducing the service provisioning time and improving the edge resource utilization, by avoiding redundant computations and data exchange. The devised strategy is implemented as a network application of a Software-defined Networking Controller in charge of overseeing the edge domain. We formulate the optimal task placement through an integer linear programming problem, and we define an efficient heuristic algorithm that well approximates the solution achieved through a standard optimal solver. Achieved results show that the proposal successfully meets the targeted objectives in a wide variety of simulated scenarios, by outperforming benchmark solutions.

Grid-based geospatial analysis of areas vulnerable to prehospital transportation of emergency patients in Jeju

During emergencies, the time from symptom onset to definitive treatment determines the final outcome. Therefore, the emergency medical service (EMS) system in Korea, aims to transfer patients requiring emergency care to appropriate medical facilities within 30 minutes. This is in an attempt to improve the chances of survival and reduce sequelae. We attempted to locate areas vulnerable to prehospital transportation and identify hot spots with high demand for emergency medical helicopters in Jeju, by using a grid-based geospatial analysis. This retrospective cross-sectional observational study employed EMS data of 119 ambulance run sheets spanning from January 1, 2010 to September 30, 2018 in Jeju. The location data of emergency patients was superimposed on the spatial analysis frame using the geographic information system (GIS). Subsequently, the locations of long-distance transfer and delayed transfers to the hospital were analyzed, to identify hot spots where the demand for helicopter emergency services would be high. Of the total analysis targets, 42.2% (20,288 people) took more than 30 minutes from reporting to 119 dispatchers to hospital transfer. As the transfer time interval increased, the patient occurrence time increased in the city of Jeju, increased in Seogwipo, and the ratio of patients/ guardians to select a transfer hospital rose with significant differences. This study identified the characteristics related to time delays in prehospital transfer of emergency patients in Jeju, and the areas vulnerable to prehospital emergency care were derived and visualized through spatial analysis using the GIS.

구조용 목재의 축열성능 향상을 위한 상변화물질/바이오차 적용 복합 교차집성재 개발

In this study, phase change materials (PCM) was applied to the core-layer of cross-laminated timber (CLT) to improve the low thermal storage performance of CLT. To solve the phase leakage of PCM, PCM/biochar composites were prepared in a vacuum state by impregnating PCM (n-heptadecane) in biochars that were pyrolyzed at 400 and 500 °C, respectively. Gypsum boards with improved thermal storage performance was prepared by mixing 10 wt% of the prepared PCM/biochar composites, and these were applied to the core-layer of the CLT to develop a hybrid CLT. The physical and chemical properties of PCM/biochar composite were evaluated through FT-IR, SEM, TGA, and DSC analysis, and the thermal performance of P/B board and hybrid CLT was evaluated through heat transfer experiments. The surface temperature reduction and heat transfer delay effect of hybrid CLT to which biochar produced at a pyrolysis temperature of 400 °C was applied was excellent.

A mobile application for STEMI care optimization: pilot implementation project report

Abstract Background In an effort to improve outcomes of STEMI patients, we developed a secure mobile application (app) to streamline real-time communication and coordination between multiple teams taking care of STEMI patients in a large health care system. The app includes multi-level alarm and notification systems, instant EKG transmission for quick interpretation, activation of the cardiac catheterization laboratory (CCL) after expert case review, secure video chat among team members facilitating clinical discussion, continuous updates on patients' clinical status and ambulance location tracking. Purpose One of the major shortcomings in STEMI system of care has been long delays in transfer of patients from non-PCI capable hospitals to a receiving center for primary PCI. To address the challenges of interhospital transfer, we designed a pilot project employing the app for STEMI transfer from a first contact hospital to our CCL. This report assesses the effect of the app on door-to-device time by comparing the key metric for STEMI transfer before (historic) and after app launch. Methods The pilot project involved key leadership stakeholders from Emergency Medicine and Nursing Departments at the referring hospital, CCL and our transfer center. During pilot period (July 2021 to January 2022) the referring center activated STEMI alarms using app activation in parallel with the previously established STEMI activation process via traditional phone calls to the transfer center. The built-in workflow redundancy was introduced to ensure the rapid and efficient, and at the same time, safe and reliable response to STEMI alert. In preparation for the pilot, more than 250 people were provisioned accounts, trained on their user-specific roles and scheduled in the app according to their schedules. Results A total of 40 suspected STEMIs were activated through the app during the pilot study; among them 30 cases were accepted for transfer and 10 rejected. After excluding patients who expired during transfer, were intubated, or had normal coronaries, final study population included 13 STEMI cases activated through the app. These cases were compared with 43 STEMIs activated through the traditional pathway from January 2019 to July 2021 before app launch. After implementing the app, the mean door-to-device time for STEMI transfer decreased from 120.3±48.3 to 91.8±15.4 min (P=0.002) (Figure 1). The significant improvement, 29 min (24%), of the key metric for interhospital transfer resulted in all STEMI cases meeting AHA goal of door-to-device time ≤120 minutes after the app launch. The respective percent of STEMI cases meeting the goal before app was 71% (Figure 2). Conclusions Implementation of a mobile app into STEMI workflow of a large urban healthcare system had a significant impact on the quality of care for transfer of STEMI patients, which has also helped bring our clinical practice closer to the AHA guidelines pertaining to the first door-to-device time. Funding Acknowledgement Type of funding sources: None.

723: BEDSIDE NURSE STAFFING ON PATIENT OUTCOMES AND THROUGHPUT IN A PEDIATRIC CARDIAC INTENSIVE CARE UNIT

Introduction: Healthcare throughput is the progression of patients from admission to discharge, limited by bed occupancy and hospital capacity. This study examines Heart Center throughput, cascading effects of limited beds, transfer delays, and nursing assignments on outcomes utilizing elective surgery cancellation during the initial COVID-19 pandemic wave. Methods: Nursing assignments, patient data, and transfers were collected. Elective surgery cancellation was March-May 2020. Heart Center occupancy (Stepdown Unit and Cardiac Intensive Care Unit), transfer delays, and patient outcomes were analyzed controlling for patient factors, surgical risk, staffing, and time effects. Setting: Retrospective single-center study Patients: Heart Center admissions January 1, 2018 – December 31, 2020. Results: There were 2,589 patients, median age 5 months (6 days-4 years), 1,543 (60%) surgical, 1,046 (40%) medical. Mortality was 3.9% (n=101), median stay 5 days (3-11 days), median 1:1 nursing assignments 40% (33%-48%), median occupancy 54% (43%-65%) for Stepdown Unit and 81% (74%-85%) for Cardiac Intensive Care Unit. Every 10% increase in Stepdown Unit occupancy had a 0.5-day increase in Cardiac Intensive Care Unit stay (p=0.044), 2.1% increase 2-day readmission (p=0.023), and 2.6% mortality increase (p< 0.001). Every 10% increase in Cardiac Intensive Care Unit occupancy had 3.4% increase in surgical delay (p=0.016) and 6.5% increase in transfer delay (p=0.020). Elective surgery cancellation reduced high occupancy days (23% to 10%, p< 0.001), increased 1:1 nursing (34% to 55%, p< 0.001), decreased transfer delays (19% to 4%, p=0.008), and decreased mortality (3.7% to 1.5%, p=0.044). Conclusions: Cancelation of elective surgery was associated with increased 1:1 nursing assignments and decreased mortality. Increased Cardiac Stepdown Unit occupancy resulted in longer Cardiac Intensive Care Unit stay, and increased Cardiac Intensive Care Unit occupancy increased transfer and surgical delays. Additional studies are need to understand the interaction of staffing and outcomes.

Collaborative slot secondary allocation based on flight wave operation

PurposeFlights are often delayed owing to emergencies. This paper proposes a cooperative slot secondary assignment (CSSA) model based on a collaborative decision-making (CDM) mechanism, and the operation mode of flight waves designs an improved intelligent algorithm to solve the optimal flight plan and minimize the total delay of passenger time.Design/methodology/approachTaking passenger delays, transfer delays and flight cancellation delays into account comprehensively, the total delay time is minimized as the objective function. The model is verified by a linear solver and compared with the first come first service (FCFS) method to prove the effectiveness of the method. An improved adaptive partheno-genetic algorithm (IAPGA) using hierarchical serial number coding was designed, combining elite and roulette strategies to find pareto solutions.FindingsComparing and analyzing the experimental results of various scale examples, the optimization model in this paper is greatly optimized compared to the FCFS method in terms of total delay time, and the IAPGA algorithm is better than the algorithm before in terms of solution performance and solution set quality.Originality/valueBased on the actual situation, this paper considers the operation mode of flight waves. In addition, the flight plan solved by the model can be guaranteed in terms of feasibility and effectiveness, which can provide airlines with reasonable decision-making opinions when reassigning slot resources.

How does kinesiophobia affect short- and long-term gait parameters in individuals with total knee arthroplasty surgery?

Delays in weight transfer due to various fears after Total knee arthroplasty (TKA) surgery negatively affect recovery. Therefore, the presence of kinesiophobia is essential for the success of the treatment. This study was planned to investigate the effects of kinesiophobia on Spatio-temporal parameters in patients who underwent unilateral TKA surgery. This study was a prospective and cross-sectional study. Seventy patients with TKA were assessed preoperatively in the 1st week (Pre1W) and post- operatively in the 3rd month (Post3M) and 12th month (Post12M). Spatiotemporal parameters were assessed using the Win-Track platform (Medicapteurs Technology, France). The Tampa kinesiophobia scale and Lequesne index were evaluated in all individuals. A significant relationship was found between the Pre1W, Post3M, and Post12M periods and Lequesne Index scores (p<0.01), and this relationship was in favor of improvement. In the Post3M period, kinesiophobia increased compared to the Pre1W period, and kinesiophobia decreased effectively in the Post12M period (p<0.01). The effect of kine-siophobia was evident in the first postoperative period. In the correlation analyses between spatiotemporal para- meters and kinesiophobia, significant negative correlations were observed (p<0.01) in the early postoperative period (Post3M). Evaluating the effectiveness of kinesiophobia on Spatio-temporal parameters at different time intervals before and after TKA surgery may be necessary for the treatment process.

WITHDRAWN: The impact of delays in inter-hospital transfers on ST-elevation myocardial infarction

WITHDRAWN: The impact of delays in inter-hospital transfers on ST-elevation myocardial infarction

An improved thermal single particle model and parameter estimation for high-capacity battery cell

Single particle model (SPM) is an electrochemical model which can be used with energy balance to calculate the state of charge, terminal voltage, and temperature of the battery. The conventional SPM neglects the lithium-ion dynamics in the electrolyte, and the energy balance usually does not consider the heat transfer delay from the battery center to the surface. These lead to model errors when SPM is used for high-capacity battery cells. In this study, we propose several strategies to improve the model accuracy for high-capacity battery cells. First, the actual discharge capacity is considered by modifying the desired Li-ion flux at the electrode surface. Second, a part of the equivalent circuit model is integrated with SPM to consider the resistance in the electrolyte computationally efficiently. Third, the delay in the heat transfer from the center to the surface is represented using a second-order system dynamic. In electric vehicles, battery cells are stacked as a pack; we account for the additional heat generated by stacking pressure-induced swelling repression. Finally, parameter estimation is conducted to determine the best parameter values of the model using the experimental data. The reference values are set using a dimensionless scale-up approach. When the parameters are estimated and the model is tested with the validation data, the error percentages in the calculated terminal voltage and temperature are smaller than 2.0410% and 3.5032%, respectively, even with the cell variances.

Mapping access to care and identification of barriers for traumatic brain injury in a South African township.

South Africahas a high traumatic injury burden resulting in a significant number of persons suffering from traumatic brain injury (TBI). TBI is a time-sensitive condition requiring a responsive and organized health system to minimize morbidity and mortality. This study outlined the barriers to accessing TBI care in a South African township. This was a multimethod study. A facility survey was carried out on health facilities offering trauma care in Khayelitsha township, Cape Town, South Africa. Perceived barriers to accessing TBI care were explored using qualitative interviews and focus group discussions. The four-delay framework that describes delays in four phases was used: seeking, reaching, receiving, and remaining in care. We purposively recruited individuals with a history of TBI (n = 6) and 15 healthcare professionals working with persons with TBI (seven individuals representing each of the five facilities, the heads of neurosurgery and emergency medical services and eight additional healthcare providers who participated in the focus group discussions). Quantitative data were analysed descriptively while qualitative data were analysed thematically, following inductive and deductive approaches. Five healthcare facilities (three community health centres, one district hospital and one tertiary hospital) were surveyed. We conducted 13 individual interviews (six with persons with TBI history, seven with healthcare providers from each of the five facilities, neurosurgery department and emergency medical serviceheadsand two focus group discussions involving eight additional healthcare providers. Participants mentioned that alcohol abuse and high neighbourhood crime could lead to delays in seeking and reaching care. The most significant barriers reported were related to receiving definitive care, mostly due to a lack of diagnostic imaging at community health centres and the district hospital, delays in interfacility transfers due to ambulance delaysand human and infrastructural limitations. A barrier to remaining in care was the lack of clear communication between persons with TBI and health facilities regarding follow-up care. Our study revealed that various individual-level, communityand health system factors impacted TBI care. Efforts to improve TBI care and reduce injury-related morbidity and mortality must put in place more community-level security measures, institute alcohol regulatory policies, improve access to diagnostics and invest in hospital infrastructures.

Examining the Performance of Software Defined Virtual Local Area Network

For more than three decades, the Virtual Local Area Network (VLAN) has been one of the most popular systems virtualization groups of users on both local and corporate networks. Because of the advantages that VLAN provides, network managers and operators have continued to use it in the creation of their networks and have even extended its use to include cloud computing networking. Previous research studies have established a lot of issues associated with VLAN architecture. Typically, it was revealed that it is difficult to set up a complex VLAN, and even it is successful, it leads to computational time-consuming, and prone to error to process majority of complex VLAN. Considering this, the current research examines the performance of “Software Defined- VLAN”. This is because Software-Defined Network (SDN) is a viable alternative network architecture that allows the separation of information and control functions on devices. It appears to be a promising optimized option VLAN administration. The SDN-enabled VLAN testbed was set out and implemented using OpenFlow. SDN-Enabled VLAN and a conventional VLAN. The finding revealed that SDN-enabled VLAN offers higher network performance, lower packet transfer delay, and a more efficient configuration.

New insight into the melting process of PA 6 fibers: Determining tension-induced changes of enthalpy by HTA-assisted DSC analysis

Differential scanning calorimetry (DSC) measurements of fibers are affected from insulation effects originating from the specific specimen geometry with poor contact between the material sample and the crucible bottom. This causes a delay in heat transfer, resulting in a time-blurred curve of the enthalpy signal. Therefore, a precise interpretation of the enthalpy and corresponding entropy contributions to the peaks arising from molecular arrangement is hardly possible. Within this contribution, the application of the heat transfer agent (HTA) method improves the heat transfer towards the fibers, thus, resulting in more differentiated thermograms and allowing new insight into the melting behavior and conclusions as regards the enthalpic contributions attributed to different effects in fiber specimens. Conducted measurements of different Polyamide 6 (PA 6) fibers conditioned by mechanical treatment indicate a correlation between mechanical loading and the related amount of heat of fusion determined by DSC. Thermal treatment provided an extended view on the development of the signals and transition states from fiber geometry to bulk melt matter. All processes which contribute to the DSC signal are visualized by means of heat-stage microscopy enabling an improved interpretation of the obtained DSC signals.

A Fog Computing Framework in IoT Healthcare Environment: Towards A New Method Based on Tasks Significance

The Internet-of-Things (IoT) is an important technology and is considered the future of the Internet. Healthcare is described as one of the important areas in IoT used for remote patient monitoring. Real-time remote monitoring health applications are important as delays in data transfer between the cloud, and the application may be unacceptable. Fog computing refers to a geographically distributed computing system with several devices connected to the same network to achieve flexible and collaborative computation, storage, and communication services. Fog computing is mainly used for efficient data processing between sensors and cloud computing as it reduces the volume of data exchanged between sensors and the cloud, thereby improving the whole system’s efficiency. Wireless sensor networks (WSN) are also used in health monitoring systems to simultaneously transfer huge data volumes (of different priority levels and length values) to the fog computing system. Hence, there is a need to appropriately implement a task scheduling mechanism that can accurately prioritize tasks irrespective of their length. This study aims to systematically review the existing fog computing technologies in the Internet of things HealthCare (IoTH) systems and improve the performance of the available static task scheduling algorithms using the Tasks Classification (TC) method where task importance is paramount. The performance of the suggested approach was evaluated based on the Max-Min scheduling algorithm (SA).