scholarly journals COVID-19 Pandemic Planning: Simulation models to predict biochemistry test capacity for patient surges

2020 ◽  
Author(s):  
Martha E Lyon ◽  
Andrew Bajkov ◽  
Diane Haugrud ◽  
Barry D Kyle ◽  
Fang Wu ◽  
...  
Keyword(s):  
Simulation Models ◽  
Turnaround Time ◽  
Maximum Throughput ◽  
Field Hospital ◽  
Specific Test ◽  
Hospital Capacity ◽  
Pandemic Planning ◽  
Biochemistry Test ◽  
Turn Around Time ◽  
Future Patient

Abstract Background Patient surges beyond hospital capacity during the initial phase of the COVID-19 pandemic emphasized a need for clinical laboratories to prepare test processes to support future patient care. The objective of this study was to determine if current instrumentation in local hospital laboratories can accommodate the anticipated workload from COVID-19 infected patients in hospitals and a proposed field hospital in addition to testing for non-infected patients. Methods Simulation models predicted instrument throughput and turn-around-time for chemistry, ion-selective-electrode and immunoassay tests using vendor-developed software with different workload scenarios. The expanded workload included tests from anticipated COVID patients in two local hospitals and a proposed field hospital with a COVID-specific test menu in addition to the pre-pandemic workload. Results Instrumentation throughput and turn-around time at each site was predicted. With additional COVID-patient beds in each hospital the maximum throughput was approached with no impact on turnaround time. Addition of the field hospital workload led to significantly increased test turnaround times at each site. Conclusions Simulation models depicted the analytic capacity and turn-around times for laboratory tests at each site and identified the laboratory best suited for field hospital laboratory support during the pandemic.

scholarly journals To reduce the Turn Around Time (TAT) of trucks and improve in-plant logistics

2021 ◽  
Vol 57 (9) ◽  
pp. 6179-6189
Author(s):  
Kautuk Timane, Puneet Gusain, Dr. Prashant Barge
Keyword(s):  
Turnaround Time ◽  
Original Process ◽  
Whole Process ◽  
Time Motion ◽  
Motion Study ◽  
Effective Manner ◽  
New Process ◽  
Plant Operations ◽  
Turn Around Time ◽  
Major Factors

This paper talks about the reduction of in plant operations time and reduction of turn-around time of the trucks in any FMCG Company. The plant has almost 300 vehicles for loading and unloading. The current systems and process for receiving and dispatching of goods is poised with several challenges. This process with the inspection of material at the entry of a truck to the billing procedures in an effective manner is a challenge due to various constraints. The load, which needs to be dispatched in a day, requires a very less turnaround time of trucks but the actual time, when analysed, was significantly higher than what was required. Higher turnaround time was causing ineffective operations in terms of placing the vehicles in the plant by the transporters. Subsequently, there was a considerable deviation between the planned orders to be dispatched and actual dispatch of goods. The complete process was studied for identifying the loopholes and time motion study was conducted to analyse the current issues, which was leading to more VIVO time of vehicles. The whole process was analysed and thus major factors, which were causing the delay of the vehicles were identified. A survey was conducted to pen down the issues causing the problems in managing the in-plant logistics of the company. Results were analysed and was found that deployment of more manpower and optimizing the entire process would help only marginally towards achieving the goal. Hence, automating the redundant and time-consuming activities would help in achieving a considerable amount of reduction in the turn-around time of trucks. This will indirectly increase the dispatch quantities of the company. In addition, there is a requirement to redefine work, which would primarily mean altering the original process. Thus, various issues in the existing processes were identified and reduction in turnaround time was observed with the implementation of the new process and tools used to reduce the redundant processes

scholarly journals Effect of Specimen Transport Network System in the Turnaround Time on Patients Tuberculosis Genexpert Test Results in the West Region of Cameroon

2019 ◽  
Vol 7 (05) ◽  
Author(s):  
Ngala Solange Mudih ◽  
Bih Adelaide ◽  
Gamo Djouomo Francis
Keyword(s):  
Secondary Data ◽  
Turnaround Time ◽  
Transport Network ◽  
Reference Laboratory ◽  
Network System ◽  
The West ◽  
Average Decrease ◽  
West Region ◽  
Specimen Transport ◽  
Turn Around Time

Introduction : Specimen transport network system is a major tool in getting quick turnaround time for patient results in general and for tuberculosis (TB) diagnosis in particular given that TB is an airborne disease and any mismanagement of its specimens, sputum in particular, can lead to generation of aerosols, hence spread and infection of the persons transporting the specimens and the health care personnel receiving the specimens and the delay in the diagnosis leading to more spread of the bacilli and up to the death of the patient. It is therefore of great essence to establish a reliable specimen transport network system which is essential for effective TB patient care, allowing for rapid diagnosis, initiation of treatment and patient follow up in the West Region of Cameroon and Cameroon as a whole. This article is therefore aimed at establishing a better specimen transport network system to better the turn- around time for TB specimens in the West Region of Cameroon. Method: A descriptive retrospective study by means of secondary data collection was carried from January 2016 to July 2017 on 1,130 specimens requested by clinicians before the GeneXpert instruments were introduced in the West Region of Cameroon and from October 2017 to July 2018 when two GeneXpert instruments were introduced in the West region. Request forms with date of test requested at the health facilities in the West region and results registers in which date results from the Reference Laboratory were communicated to health facility in the West Region, were used as the data sources to calculate the turn- around time (TAT).  TAT was analyzed in hours and converted to days using excel. Results : Results from this study shows an average decrease in turnaround time of patient’s results from 26 days when the specimens were tested only at the Reference laboratory in Bamenda to 7 days when two GeneXpert instruments were introduced in the West region with a total of 2 platforms where tests could possibly be done. Conclusion : Re designing a better specimen transport network system and increasing the number of Xpert platforms not only in the West region but in all other regions of Cameroon, will reduce TAT for TB results to only 01 to 02 days, thus increase quality of prevention and treatment programs, thereby reducing costs and live savings of the population.

scholarly journals 412. Assessment and Capability of SARS-CoV-2 Detection in the Veterans Health Administration

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S273-S274
Author(s):  
Aditya Sharma ◽  
Gina Oda ◽  
Mark Holodniy
Keyword(s):  
Average Rate ◽  
Scale Up ◽  
Veterans Health Administration ◽  
The United States ◽  
Turnaround Time ◽  
Veterans Health ◽  
Health Administration ◽  
Maximum Throughput ◽  
Public Health Response ◽  
Specimen Collection

Abstract Background Rapid scale up of testing to detect Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is essential to direct clinical management, optimize infection control actions, and guide public health response efforts to mitigate the spread of Coronavirus Disease 2019 (COVID-19). As the largest integrated health care system in the United States, the Veterans Health Administration (VHA) supported the laboratory-based detection of COVID-19 in a network of 170 medical centers across the country. Methods SARS-CoV-2 testing data from VHA databases were analyzed to assess SARS-CoV-2 detection characteristics. Testing capacity was calculated by multiplying the number of inventoried instruments available for SARS-CoV-2 detection by estimates of instrument-specific maximum throughput with the assumption that instruments would be operational for 16 hours a day and 7 days a week. Results From March 01, 2020 to May 31, 2020, 224,059 Emergency Use Authorization approved RT-PCR tests for SARS-CoV-2 on more than 7 different assay platforms were conducted among 168,761 individuals attending VHA facilities; 10,048 individuals (5.9%) tested positive. During this period, the average rate of tests completed for SARS-CoV-2 increased to more than 4,000 per day (Figure 1A), the percentage of hospitalized individuals who were tested for SARS-CoV-2 increased to approximately 80% (Figure 1B), the median turnaround time from specimen collected to result reported decreased to less than 1 day (Figure 1C), and the percentage of SARS-CoV-2 clinical specimens collected in VHA facilities that were tested at VHA laboratories increased to more than 80% (Figure 1D). Based on inventories of high-throughput and rapid diagnostic instruments (Figure 2), VHA could perform at least 20,000 tests for SARS-CoV-2 per week. Figure 1. Testing metrics for SARS-CoV-2 across VHA facilities. A) Number of daily tests for SARS-CoV-2 completed. B) Percentage of hospitalized Veterans tested for SARS-CoV-2. C). Median turnaround time of completed tests for SARS-CoV-2 from specimen collection to result reported. D) Percentage of SARS-CoV-2 specimens collected in VHA facilities that were tested in VHA laboratories. Figure 2. Distribution of instruments to detect SARS-CoV-2 across VHA facilities. Conclusion Key indicators of laboratory performance for SARS-CoV-2 detection, including test turnaround time, percentage of hospitalized individuals tested, and overall testing volume improved substantially in VHA during the first 3 months of testing during the pandemic. Ongoing efforts seek to enhance just-in-time diagnostic capacity, ensure continuity of specimen collection supplies and laboratory consumables, and identify and minimize gaps in access to testing facilities. Disclosures All Authors: No reported disclosures

Models for Assessing Strategies for Improving Hospital Capacity for Handling Patients during a Pandemic

2022 ◽  
pp. 1-26
Author(s):  
Bahar Shahverdi ◽  
Elise Miller-Hooks ◽  
Mersedeh Tariverdi ◽  
Hadi Ghayoomi ◽  
David Prentiss ◽  
...  
Keyword(s):  
Discrete Event ◽  
Simulation Models ◽  
Tertiary Hospital ◽  
Health Care Facilities ◽  
External Support ◽  
Standards Of Care ◽  
Hospital Capacity ◽  
Hospital Units ◽  
Icu Length Of Stay ◽  
Patient Arrival

Abstract Objective: The aim of this study was to investigate the performance of key hospital units associated with emergency care of both routine emergency and pandemic (COVID-19) patients under capacity enhancing strategies. Methods: This investigation was conducted using whole-hospital, resource-constrained, patient-based, stochastic, discrete-event simulation models of a generic 200-bed urban U.S. tertiary hospital serving routine emergency and COVID-19 patients. Systematically designed numerical experiments were conducted to provide generalizable insights into how hospital functionality may be affected by the care of COVID-19 pandemic patients along specially designated care paths under changing pandemic situations from getting ready to turning all of its resources to pandemic care. Results: Several insights are presented. For example, each day of reduction in average ICU length of stay increases intensive care unit patient throughput by up to 24% for high COVID-19 daily patient arrival levels. The potential of five specific interventions and two critical shifts in care strategies to significantly increase hospital capacity is described. Conclusions: These estimates enable hospitals to repurpose space, modify operations, implement crisis standards of care, prepare to collaborate with other health care facilities, or request external support, increasing the likelihood that arriving patients will find an open staffed bed when one is needed.

scholarly journals Hospital Capacity and Operations in the Coronavirus Disease 2019 (COVID-19) Pandemic—Planning for the Nth Patient

2020 ◽  
Vol 1 (3) ◽  
pp. e200345 ◽  
Author(s):  
Joseph J. Cavallo ◽  
Daniel A. Donoho ◽  
Howard P. Forman
Keyword(s):  
Hospital Capacity ◽  
Pandemic Planning

Preparation of Electron Transparent Metal-Matrix Composites

1968 ◽  
Vol 26 ◽  
pp. 334-335 ◽  
Author(s):  
M. R. Pinnel ◽  
A. Lawley
Keyword(s):  
Stainless Steel ◽  
Load Transfer ◽  
Volume Fraction ◽  
Steel Wire ◽  
Initial Step ◽  
Interfacial Region ◽  
Matrix Composites ◽  
Specific Test ◽  
The Matrix ◽  
The One

Numerous phenomenological descriptions of the mechanical behavior of composite materials have been developed. There is now an urgent need to study and interpret deformation behavior, load transfer, and strain distribution, in terms of micromechanisms at the atomic level. One approach is to characterize dislocation substructure resulting from specific test conditions by the various techniques of transmission electron microscopy. The present paper describes a technique for the preparation of electron transparent composites of aluminum-stainless steel, such that examination of the matrix-fiber (wire), or interfacial region is possible. Dislocation substructures are currently under examination following tensile, compressive, and creep loading. The technique complements and extends the one other study in this area by Hancock.The composite examined was hot-pressed (argon atmosphere) 99.99% aluminum reinforced with 15% volume fraction stainless steel wire (0.006″ dia.).Foils were prepared so that the stainless steel wires run longitudinally in the plane of the specimen i.e. the electron beam is perpendicular to the axes of the wires. The initial step involves cutting slices ∼0.040″ in thickness on a diamond slitting wheel.

Advanced TEM sample preparation techniques for submicron Si devices

1995 ◽  
Vol 53 ◽  
pp. 516-517 ◽  
Author(s):  
P. B. Basham ◽  
H. L. Tsai
Keyword(s):  
Sample Preparation ◽  
Process Development ◽  
Light Transmission ◽  
Specific Area ◽  
Turnaround Time ◽  
Small Hole ◽  
Area Of Interest ◽  
Transmission Electron ◽  
Polished Side ◽  
Preparation Techniques

The use of transmission electron microscopy (TEM) to support process development of advanced microelectronic devices is often challenged by a large amount of samples submitted from wafer fabrication areas and specific-spot analysis. Improving the TEM sample preparation techniques for a fast turnaround time is critical in order to provide a timely support for customers and improve the utilization of TEM. For the specific-area sample preparation, a technique which can be easily prepared with the least amount of effort is preferred. For these reasons, we have developed several techniques which have greatly facilitated the TEM sample preparation.For specific-area analysis, the use of a copper grid with a small hole is found to be very useful. With this small-hole grid technique, TEM sample preparation can be proceeded by well-established conventional methods. The sample is first polished to the area of interest, which is then carefully positioned inside the hole. This polished side is placed against the grid by epoxy Fig. 1 is an optical image of a TEM cross-section after dimpling to light transmission.

Correlation of Pore Structure and Permeability by SEM-Image Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 428-429
Author(s):  
C. A. Callender ◽  
Wm. C. Dawson ◽  
J. J. Funk
Keyword(s):  
Image Analysis ◽  
Pore Structure ◽  
Imaging System ◽  
Pore Space ◽  
Simulation Models ◽  
Image Analyzer ◽  
Imaging Data ◽  
Sem Images ◽  
Thin Sections ◽  
Rock Types

The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabilities from 92 to 2153 md. Engineering tests reveal the lack of a consistent (predictable) relationship between porosity and permeability (Fig. 1). Finely polished thin sections were studied petrographically to determine rock texture. The studied thin sections represent four petrographically distinct carbonate rock types ranging from compacted, poorly-sorted, dolomitized, intraclastic grainstones to well-sorted, foraminiferal,ooid, peloidal grainstones. The samples were analyzed for pore structure by a Tracor Northern 5500 IPP 5B/80 image analyzer and a 80386 microprocessor-based imaging system. Between 30 and 50 SEM-generated backscattered electron images (frames) were collected per thin section. Binaries were created from the gray level that represents the pore space. Calculated values were averaged and the data analyzed to determine which geological pore structure characteristics actually affect permeability.

On the Robustness of Solution Strategy Classifications

2010 ◽  
Vol 31 (2) ◽  
pp. 68-73 ◽  
Author(s):  
María José Contreras ◽  
Víctor J. Rubio ◽  
Daniel Peña ◽  
José Santacreu
Keyword(s):  
Individual Differences ◽  
Study Strategies ◽  
Solution Strategy ◽  
Specific Test ◽  
Spatial Tasks ◽  
The Stability ◽  
Strategy Changes ◽  
Over Time

Individual differences in performance when solving spatial tasks can be partly explained by differences in the strategies used. Two main difficulties arise when studying such strategies: the identification of the strategy itself and the stability of the strategy over time. In the present study strategies were separated into three categories: segmented (analytic), holistic-feedback dependent, and holistic-planned, according to the procedure described by Peña, Contreras, Shih, and Santacreu (2008) . A group of individuals were evaluated twice on a 1-year test-retest basis. During the 1-year interval between tests, the participants were not able to prepare for the specific test used in this study or similar ones. It was found that 60% of the individuals kept the same strategy throughout the tests. When strategy changes did occur, they were usually due to a better strategy. These results prove the robustness of using strategy-based procedures for studying individual differences in spatial tasks.

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