Total Test Cost Research Articles

Costs of unnecessary repeated diagnostic tests in cholecystectomy.

The purpose of this study was to calculate the number, rate and cost of unnecessarily repeated tests on the patients who underwent open cholecystectomy and laparoscopic cholecystectomy and figure out the share of the unnecessarily repeated test costs in total test expenditures and total treatment expenditures. Alkaline phosphatase, alanine aminotransferase, aspartate transaminase, gamma glutamyl transferase, Total bilirubin, whole abdominal ultrasonography, upper abdominal ultrasonography, hepatobiliary ultrasonography tests, which were among the tests used in the patients who underwent cholecystectomy. The research group included 1296 patients. All records of the patients within totally 180days of period including 90days of pre-cholecystectomy and 90days of post-cholecystectomy period were analysed. Necessity/Unnecessary criteria of the tests were identified in accordance with literature data, expert opinions and American Society of Anaesthesiologists Physical Status Classification scores. It was determined that unnecessary test costs consisted of 8.48% of the total test costs and 0.93% of the total treatment expenditures. This study showed that age, gender, surgical technique, and American Society of Anesthesiologists scores significantly differentiated unnecessary repeated test costs. Reducing the use of excessive health service and the related health expenditures, working to reveal its financial and medical benefits are crucial for the reimbursement agency, health service hosts and patients.

Donor Screening Revisions of Fecal Microbiota Transplantation in Patients with Ulcerative Colitis.

Fecal microbiota transplantation (FMT) has been recognized as a promising treatment for dysbiosis-related diseases. Since 2014, FMT has been utilized to treat ulcerative colitis (UC) in our clinical studies and has shown efficacy and safety. As donor screening (DS) is the primary step to ensure the safety of FMT, we report our experience with DS and present the screening results to improve the prospective DS criteria and provide references for future studies. The donor candidates were screened according to the DS criteria. The first DS criteria were proposed in June 2014 and revised substantially in May 2018. We further sorted the screening results and costs of laboratory tests. From June 2014 to April 2018, the DS eligibility rate was 50%. The total laboratory testing cost for each candidate was JPY 17,580/USD 160.21. From May 2018 to September 2021, the DS eligibility rate was 25.6%. The total laboratory testing cost for each candidate was JPY 40,740/USD 371.36. The reduction in donor eligibility rates due to more stringent criteria should be considered for cost and safety. Studies must consider the latest updates and make timely modifications in the DS criteria to ensure patient safety.

Pathology ordering practices in junior doctors

Background: The total cost of pathology testing has increased year on year at Gosford and Wyong Hospitals. Pathology ordering makes up a large proportion junior doctors’ workload but there is little formal education during internship and residence on how to rationalise pathology ordering.

Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.

Pooled testing efficiency increases with test frequency

Pooled testing increases efficiency by grouping individual samples and testing the combined sample, such that many individuals can be cleared with one negative test. This short paper demonstrates that pooled testing is particularly advantageous in the setting of pandemics, given repeated testing, rapid spread, and uncertain risk. Repeated testing mechanically lowers the infection probability at the time of the next test by removing positives from the population. This effect alone means that increasing frequency by x times only increases expected tests by around [Formula: see text] However, this calculation omits a further benefit of frequent testing: Removing infections from the population lowers intragroup transmission, which lowers infection probability and generates further efficiency. For this reason, increasing testing frequency can paradoxically reduce total testing cost. Our calculations are based on the assumption that infection rates are known, but predicting these rates is challenging in a fast-moving pandemic. However, given that frequent testing naturally suppresses the mean and variance of infection rates, we show that our results are very robust to uncertainty and misprediction. Finally, we note that efficiency further increases given natural sampling pools (e.g., workplaces, classrooms) that induce correlated risk via local transmission. We conclude that frequent pooled testing using natural groupings is a cost-effective way to provide consistent testing of a population to suppress infection risk in a pandemic.

Construction of minimum cost reliability acceptance sampling plans for multistage process

ABSTRACT In this paper an attempt is made to derive lot acceptance sampling plans based on failure censored data. The items in the lot having multiple quality charecteristics are processed through multistage production process. We assume that quality charecteristics of the units follow exponential distribution with different parameters. The acceptance criterion for the given lot is obtained based on the average-life of units in the sample at every stage. Two nonlinear optimiztion problems which minimize the expected total testing costs at the acceptable quality level are solved. Further, a sensitivity analysis study is conducted to assess the behaviour of testing costs with respect to changes in producer's risk, consumer's risk, and sample sizes. The plan parameters are obtained by solving nonlinear mixed integer programming problem by using genetic algorithm solver in MATLAB. Some numerical exapmles and two case studies are discussed to illustrate our sampling plans.

Costs and Cost-Effectiveness of User-Testing of Health Professionals' Guidelines to Reduce the Frequency of Intravenous Medicines Administration Errors by Nurses in the United Kingdom: A Probabilistic Model Based on Voriconazole Administration.

AimIn the UK, injectable medicines are often prepared and administered by nurses following the Injectable Medicines Guide (IMG). Our earlier study confirmed a higher frequency of correct administration with user-tested versus standard IMG guidelines. This current study aimed to model the cost-effectiveness of user-testing.MethodsThe costs and cost-effectiveness of user-testing were explored by modifying an existing probabilistic decision-analytic model. The adapted model considered administration of intravenous voriconazole to hospital inpatients by nurses. It included 11 error types, their probability of detection and level of harm. Model inputs (including costs) were derived from our previous study and other published data. Monte Carlo simulation using 20,000 samples (sufficient for convergence) was performed with a 5-year time horizon from the perspective of the 121 NHS trusts and health boards that use the IMG. Sensitivity analyses were undertaken for the risk of a medication error and other sources of uncertainty.ResultsThe net monetary benefit at £20,000/quality-adjusted life year was £3,190,064 (95% credible interval (CrI): −346,709 to 8,480,665), favouring user-testing with a 96% chance of cost-effectiveness. Incremental cost-savings were £240,943 (95% CrI 43,527–491,576), also favouring user-tested guidelines with a 99% chance of cost-saving. The total user testing cost was £6317 (95% CrI 6012–6627). These findings were robust to assumptions about a range of input parameters, but greater uncertainty was seen with a lower medication error risk.ConclusionsUser-testing of injectable medicines guidelines is a low-cost intervention that is highly likely to be cost-effective, especially for high-risk medicines.

Randomised controlled trial of a prognostic assessment and management pathway to reduce the length of hospital stay in normotensive patients with acute pulmonary embolism.

The length of hospital stay (LOS) for acute pulmonary embolism (PE) varies considerably. Whether the upfront use of a PE prognostic assessment and management pathway is effective in reducing the LOS remains unknown. We conducted a randomised controlled trial of adults hospitalised for acute PE: patients were assigned either to a prognostic assessment and management pathway involving risk stratification followed by predefined criteria for mobilisation and discharge (intervention group) or to usual care (control group). The primary end-point was LOS. The secondary end-points were the cost of prognostic tests and of hospitalisation, and 30-day clinical outcomes. Of 500 patients who underwent randomisation, 498 were included in the modified intention-to-treat analysis. The median LOS was 4.0 days (interquartile range (IQR) 3.7-4.2 days) in the intervention group and 6.1 days (IQR 5.7-6.5 days) in the control group (p<0.001). The mean total cost of prognostic tests was EUR 174.76 in the intervention group, compared with EUR 233.12 in the control group (mean difference EUR -58.37, 95% CI EUR -84.34- to -32.40). The mean total hospitalisation cost per patient was EUR 2085.66 in the intervention group, compared with EUR 3232.97 in the control group (mean difference EUR -1147.31, 95% CI EUR -1414.97- to -879.65). No significant differences were observed in 30-day readmission (4.0% versus 4.8%), all-cause mortality (2.4% versus 2.0%) or PE-related mortality (0.8% versus 1.2%) rates. The use of a prognostic assessment and management pathway was effective in reducing the LOS for acute PE.

Minimizing cost associated with management of heparin‐induced thrombocytopenia: A cost analysis of various laboratory testing models

Management of patients with suspected heparin-induced thrombocytopenia (HIT) can lead to significant costs. Reported cost-saving initiatives have focused on minimizing inappropriate testing in low-risk patients and optimizing alternative anticoagulant selection. We sought to further investigate how utilizing various HIT laboratory testing models would impact total cost of testing and alternative anticoagulant use. Utilizing a retrospective cohort of adult patients tested for HIT over three years within our institution, we evaluated how utilization of four distinct laboratory models impacted total number of HIT test combinations completed, time to HIT testing finalization, percentage of patients discharged from the hospital prior to HIT testing finalization, total alternative anticoagulant days, and total anticipated major bleed events. Additionally, we calculated cost of laboratory testing and alternative anticoagulant associated with each model. A total of 482 patients were included in our cohort. A laboratory testing model that utilized an in-house platelet factor 4 (PF4)-heparin enzyme-linked immunosorbent assay (ELISA) completed three days weekly, and reflex serotonin release assay (SRA) with a five-day turnaround resulted in the shortest mean time to HIT testing finalization, lowest percentage of patients discharged prior to HIT testing finalization, and lowest total alternative anticoagulant days. Institutions should evaluate current HIT laboratory testing practices and assess for opportunities for optimization. Testing models utilizing a PF4-heparin antibody ELISA with a reflex SRA for positive results may improve testing metrics and lead to lower utilization of alternative anticoagulants.

Classification with Few Tests through Self-Selection

We study test-based binary classification, where a principal either accepts or rejects agents based on the outcomes they get in a set of tests. The principal commits to a policy, which consists of all sets of outcomes that lead to acceptance. Each agent is modeled by a distribution over the space of possible outcomes. When an agent takes a test, he pays a cost and receives an independent sample from his distribution as the outcome. Agents can always choose between taking another test and stopping. They maximize their expected utility, which is the value of acceptance if the principal's policy accepts the set of outcomes they have and 0 otherwise, minus the total cost of tests taken. We focus on the case where agents can be either "good" or "bad" (corresponding to their distribution over test outcomes), and the principal's goal is to accept good agents and reject bad ones. We show, roughly speaking, that as long as the good and bad agents have different distributions (which can be arbitrarily close to each other), the principal can always achieve perfect accuracy, meaning good agents are accepted with probability 1, and bad ones are rejected with probability 1. Moreover, there is a policy achieving perfect accuracy under which the maximum number of tests any agent needs to take is constant — in sharp contrast to the case where the principal directly observes samples from agents' distributions. The key technique is to choose the policy so that agents self-select into taking tests.

Pre-vaccination testing could expand coverage of two-dose COVID vaccines

Recent evidence indicates that a single dose of mRNA-based vaccines produce similar immune responses in people with evidence of past infection compared with two doses in immunologically naive individuals. For COVID-19 vaccines with two dose regimens, point-of-care antibody testing for prior infection when administering the first dose could enable expanded vaccine access in a cost-effective manner. Generally, antibody tests with sensitivity and specificity well below that typically accepted for product licensure would still enable expanded vaccine coverage, though to be cost-beneficial total test cost (i.e. procurement and administration) needs to be less than roughly a third of total vaccine dose cost. For highly sensitive (90%) and specific (99%) tests, coverage could be expanded by more than 33%. Tests with the appropriate performance characteristics are plausible, though likely need setting specific tailoring.

P089 The cost of repeat ANA testing in north west London pathology services

Abstract Background/Aims The anti-nuclear antibody (ANA) test is commonly used to screen for autoimmune connective tissue (CTD) disease. It is a test that should be used judiciously and should only be requested if a patient presents with symptoms suggestive of a CTD and should not be used as a screening test for vague musculoskeletal symptoms. Recent studies have demonstrated that it is often repetitively requested in those patients both with a known positive and known negative ANA with little value in altering a diagnosis. With this information in mind, we sought to examine the frequency and associated cost of repeat ANA testing in hospital trusts served by North West London Pathology Services (NWL). Methods The trusts included in the study were Imperial College Healthcare NHS Trust, Chelsea and Westminster Hospital Foundation Trust and Hillingdon Hospitals NHS Foundation Trust. Data was obtained regarding how many patients had repeat ANA testing in total between these trusts between 2017-2019. The data was obtained via a freedom of information request. Results In total, there were 6,799 instances of repeated ANA testing in the same patient across three trusts over three years. This included one patient who had 16 ANA tests in a single year in 2017. The cost of an ANA test is £12.27. The total cost of repeat ANA testing in the three years across three trusts was £83,423.73 (£27,807.66 per year on average). Data is provided in tabular form and gives a breakdown of the number of repeat ANA tests per year and how many times the test was repeated in the same patient. Conclusion The requesting of unnecessary tests can add to a hospital pathology workload and is associated with significant cost. It has been previously demonstrated in the literature that repeat ANA testing is of little value and rarely alters the diagnosis of a rheumatic disease. There is a large burden of repeated ANA testing in North West London Pathology Services and this is associated with significant expense. More judicious use of ANA testing can result in significant cost saving. This is the first study to specifically examine the cost of repeat ANA testing in the NHS. Disclosure M. Colquhoun: Other; MC has received support to attend conferences from Pfizer. M. Mouyis: None.

Impact of Treatment Sequencing on Outcomes and Costs in Relapsed Follicular or Other Low Grade B-Cell Non-Hodgkin Lymphoma - Results of an Evidence-Based Budget Impact Model

Introduction: The choice of initial therapy in follicular lymphoma can be a key determinant in future therapy, as irreversible toxicities with first line regimens can impact the patient's ability to tolerate future treatment. Minimizing drug exposure will result in less frequent occurrence of significant adverse events and associated treatment costs. In the era of COVID-19 pandemic, there is additional benefit to minimizing the number of patient visits and hospital admissions. Limited information exists related to the outcomes and associated costs of existing treatment sequences. Additionally, treatment administration at different types of clinical sites results in varied reimbursement models, making informed evaluation of clinical and financial evidence challenging. Methods: The current study applies a budget impact model methodology in order to describe the associated impact of treatment selection and sequencing on outcomes and costs in the treatment of relapsed or refractory low-grade follicular lymphoma in first line therapy followed by Consolidation and also in first line therapy to second line therapy. Key model inputs included: Number of treatment cycles, number of days a treatment was received, duration of response (DOR), rate of side effects and associated costs, and total treatment costs, including drugs, medical treatment, laboratory testing and adverse event costs. Treatment outcomes were based on the published literature that summarized the overall response rate, median DOR, and toxicity. Treatment regimen costs were evaluated based on payer pricing, Wholesale Acquisition Cost (WAC), Average Selling Price (ASP) and Average Wholesale Price (AWP) and modified to adjust for weight-based dosing and negotiate payer reimbursement rates. Associated medical costs for medical treatment and supportive care were estimated using current Medicare fee schedule rates. Included were seven options for first line therapy of follicular lymphoma from 2020 NCCN Guidelines - (Bendamustine + rituximab (BR); Bendamustine + Obinutuzumab (OB); CHOP rituximab (RCHOP); CHOP + Obinutuzumab (OCHOP); CVP+ rituximab (RCVP); CVP + Obinutuzumab (OCVP); Lenalidomide + rituximab (R2)), followed by three for Consolidation (Rituximab maintenance (RM); Obinutuzumab maintenance (O); Radioimmunotherapy (RIT with 90 Y-ibritumomab tiuxetan (Y90-IT, Zevalin)) and three Second Line therapy options (RIT; Lenalidomide only; Lenalidomide + Obinutuzumab (LO)). Results: The treatment sequence of first line BR followed by Consolidation with RIT Y90 (Zevalin) had the longest predicted DOR (2586 days). The associated treatment sequence costs were $212,485 for BR followed by Y90-IT, compared with $233, 388 for BR followed by rituximab maintenance, which had a predicted DOR of 2478 days. The predicted DOR for treatment sequences starting with OCHOP, OCVP and RCHOP and followed by RIT with Y90-IT was approximately 1000 days less than BR followed by Y90-IT for a cost difference of $4,421, $12,914 and $25,826, respectively. The treatment sequence of first line BR followed by Second Line RIT Y90-IT had the second longest predicted DOR of 2586 days at costs of $212,485, compared to 2778 days for BR followed by LO, at a total sequence costs of $796,695. Conclusion: The use of Y90-IT in Consolidation or Second Line treatment demonstrated desired patient outcomes at one of the lowest cost profiles. Additionally, Y90-IT administration can be completed in only two clinic visits, reducing patient travel and contact, improving safety in an era of COVID-19 precautionary measures and reducing cost. Figure 1. Duration of Response and Total Sequence Costs for Twelve First Line to Consolidation and First Line to Second Line Treatment Regimens. Disclosures McBride: Merck: Speakers Bureau; Coherus BioSciences: Consultancy, Speakers Bureau; Pfizer: Consultancy; Bristol-Myers Squibb: Consultancy; MorphoSys: Consultancy; Sandoz: Consultancy.

Cost-sensitive feature selection on multi-label data via neighborhood granularity and label enhancement

Multi-label feature selection, which is an efficient and effective pre-processing step in machine learning and data mining, can select a feature subset that contains more contributions for multi-label classification while improving the performance of the classifiers. In real-world applications, an instance may be associated with multiple related labels with different relative importances, and the process of obtaining different features usually requires different costs, containing money, and time, etc. However, most existing works with regard to multi-label feature selection do not take into consideration the above two critical issues simultaneously. Therefore, in this paper, we exploit the idea of neighborhood granularity to enhance the traditional logical labels into label distribution forms to excavate the deeper supervised information hidden in multi-label data, and further consider the effect of the test cost under three different distributions, simultaneously. Motivated by these issues, a novel test cost multi-label feature selection algorithm with label enhancement and neighborhood granularity is designed. Moreover, the proposed algorithm is tested upon ten publicly available benchmark multi-label datasets with six widely-used metrics from two different aspects. Finally, two groups of experimental results demonstrate that the proposed algorithm achieves the satisfactory and superior performance over other four state-of-the-art comparing algorithms, and it is effective for improving the learning performance and decreasing the total test costs of the selected feature subset.

A Shared Diagnostic Stewardship Approach to Autoimmune Encephalopathy Send-Out Testing

Abstract As part of our laboratory testing utilization at University of Louisville Hospital (ULH), any send-out test ≥$500 must be assessed by the clinical chemistry fellow or pathology resident for clinical necessity and as a way to provide consultation to the ordering physician on appropriate test utilization. In 2018, we noticed a prominent increase in the volume of panels for autoimmune encephalopathy (AE) and related disorders being ordered. This was met with considerable cost to the hospital, a lack of consensus on which panels should be ordered, and poor understanding of the clinical utility of these panels. These challenges presented an ideal project for our newly-formed diagnostic stewardship committee (DSC) at ULH. Through collaboration with the DSC, we were able to form a sub-committee with the Department of Neurology to develop an algorithm-based approach for ordering of these AE panels. Our goals were to improve diagnostic utility for the betterment of patient care, improve test utilization, and decrease cost associated with panel ordering. Prior to involvement of the DSC, we analyzed the number and cost of all AE panels ordered in 2018. We also calculated the number of positive panels and reviewed patient data to determine if a positive panel corresponded with a clinical outcome. After presenting our data to the DSC, an evidence-based approach was taken in collaboration with the Department of Neurology to develop an algorithm for AE test ordering. Results were analyzed for true positive rate, defined as a patient testing positive for an antibody with known etiology or association with AE based on result interpretation provided by Mayo Clinical Laboratories. The total cost of tests was also analyzed before implementation of the algorithm (January 1, 2019-July 31, 2019) and post-implementation (August 1, 2019-December 31, 2019). In 2018, 77 AE panels were ordered with an estimated charge to the laboratory of $137,510. The true positive rate was 10%. Based on these test ordering patterns, we projected that 120 tests would be ordered in 2019, totaling &amp;gt;$200,000. Prior to the implementation of the algorithm in 2019, 55 tests were ordered, totaling $105,210. Total true positive rate was 3.6%. After implementation of the algorithm, 23 tests were ordered, totaling $50,220. The true positive rate was 13%. Using a shared diagnostic stewardship approach, we were able to develop an evidence-based algorithm for guiding physicians for AE panel ordering. Comparing test ordering patterns pre and post-implementation in 2019, our true positive rate more than tripled (3.6% to 13%), indicating that our algorithm was able to successfully identify the at-risk population for development of AE disorders. This was met with a &amp;gt;50% decrease in the number of tests ordered, and a total cost savings of $54,990 compared to the first half of 2019.

Cost and cost-effectiveness of a simplified treatment model with direct-acting antivirals for chronic hepatitis C in Cambodia.

In 2016, Médecins Sans Frontières established the first general population Hepatitis C virus (HCV) screening and treatment site in Cambodia, offering free direct-acting antiviral (DAA) treatment. This study analysed the cost-effectiveness of this intervention. Costs, quality adjusted life years (QALYs) and cost-effectiveness of the intervention were projected with a Markov model over a lifetime horizon, discounted at 3%/year. Patient-level resource-use and outcome data, treatment costs, costs of HCV-related healthcare and EQ-5D-5L health states were collected from an observational cohort study evaluating the effectiveness of DAA treatment under full and simplified models of care compared to no treatment; other model parameters were derived from literature. Incremental cost-effectiveness ratios (cost/QALY gained) were compared to an opportunity cost-based willingness-to-pay threshold for Cambodia ($248/QALY). The total cost of testing and treatment per patient for the full model of care was $925(IQR $668-1631), reducing to $376(IQR $344-422) for the simplified model of care. EQ-5D-5L values varied by fibrosis stage: decompensated cirrhosis had the lowest value, values increased during and following treatment. The simplified model of care was cost saving compared to no treatment, while the full model of care, although cost-effective compared to no treatment ($187/QALY), cost an additional $14 485/QALY compared to the simplified model, above the willingness-to-pay threshold for Cambodia. This result is robust to variation in parameters. The simplified model of care was cost saving compared to no treatment, emphasizing the importance of simplifying pathways of care for improving access to HCV treatment in low-resource settings.

Costs of cannabis testing compliance: Assessing mandatory testing in the California cannabis market.

Most U.S. states that have regulated and taxed cannabis have imposed some form of mandatory safety testing requirements. In California, the country's largest and oldest legal cannabis market, mandatory testing was first enforced by state regulators in July 2018, and additional mandatory tests were introduced at the end of 2018. All cannabis must be tested and labeled as certified by a state-licensed cannabis testing laboratory before it can be legally marketed in California. Every batch that is sold by licensed retailers must be tested for more than 100 contaminants, including 66 pesticides with tolerance levels lower than the levels allowable for any other agricultural product in California. This paper estimates the costs of compliance with mandatory cannabis testing laws and regulations, using California's testing regime as a case study. We use state government data, data collected from testing laboratories, and data collected from lab equipment suppliers to run a set of Monte Carlo simulations and estimate the cost per pound of compliance with California's new cannabis testing regulations. We find that cost per pound is highly sensitive to average batch size and testing failure rates. We present results under a variety of different assumptions about batch size and failure rates. We also find that under realistic assumptions, the loss of cannabis that must be destroyed if a batch fails testing accounts for a larger share of total testing costs than does the cost of the lab tests. Using our best estimates of average batch size (8 pounds) and failure rate (4%) in the 2019 California market, we estimate testing cost at $136 per pound of dried cannabis flower, or about 10 percent of the reported average wholesale price of legal cannabis in the state. Our findings explain effects of the testing standards on the cost of supplying legal licensed cannabis, in California, other U.S. states, and foreign jurisdictions with similar testing regimes.

Systematic Preoperative Complementary Tests in Elective Minor and Medium Pediatric Surgery: Is it Time to Revalue?

Introduction: Prescription of routine complementary tests preoperatively has become a tradition for all practitioners. These tests are ordered frequently but their contribution doesn’t seem that significant. The aim of our study is to find out whether these systematic preoperative tests, prescribed for children undergoing elective minor and medium surgeries, were truly indicated or unjustified. Patients and Methods: We conducted a prospective, observational study including 230 children admitted for scheduled surgery with minor to medium bleeding risk. Several parameters were collected: the surgery and anesthesia characteristics, complementary preoperative tests, the tests prescriber, their usefulness and the cost of the prescription. Results: The mean age was 3 years old. The majority (95%) belonged to ASA I class. Twenty-eight percent of these children couldn’t walk yet. Eighty-two percent of the undergone surgeries had a minor bleeding risk. In 74% of cases, the chosen technique was a general anesthesia combined to local anesthesia. For the 230 patients studied, 857 complementary tests were requested. A systematic blood assessment was performed for all the patients. Only 35,86% of the realized tests were actually indicated. Excluding blood group, analysis of other tests showed that only 28,71% of them were abnormal. The total cost of the complementary tests was 8919.1 dinars of which 64,14% were spent on non-indicated tests. Conclusion: The systematic routine prescribing of blood tests must be forsaken to switch to a selective and rational prescription. Recommendations and guidelines may afford a precious help to organize the blood tests prescription procedure.

Dynamic testing resource allocation modeling for multi-release software using optimal control theory and genetic algorithm

PurposeThe use of software is overpowering our modern society. Advancement in technology is directly proportional to an increase in user demand which further leads to an increase in the burden on software firms to develop high-quality and reliable software. To meet the demands, software firms need to upgrade existing versions. The upgrade process of software may lead to additional faults in successive versions of the software. The faults that remain undetected in the previous version are passed on to the new release. As this process is complicated and time-consuming, it is important for firms to allocate resources optimally during the testing phase of software development life cycle (SDLC). Resource allocation task becomes more challenging when the testing is carried out in a dynamic nature.Design/methodology/approachThe model presented in this paper explains the methodology to estimate the testing efforts in a dynamic environment with the assumption that debugging cost corresponding to each release follows learning curve phenomenon. We have used optimal control theoretic approach to find the optimal policies and genetic algorithm to estimate the testing effort. Further, numerical illustration has been given to validate the applicability of the proposed model using a real-life software failure data set.FindingsThe paper yields several substantive insights for software managers. The study shows that estimated testing efforts as well as the faults detected for both the releases are closer to the real data set.Originality /valueWe have proposed a dynamic resource allocation model for multirelease of software with the objective to minimize the total testing cost using the flexible software reliability growth model (SRGM).

Optimal design of accelerated degradation test plan under modified ramp-stress loading

This paper deals with the design of optimal modified ramp-stress Accelerated Degradation Test (ADT) using the assumption that the product's degradation path follows Wiener process. In an ADT, failure occurs when the performance characteristic crosses the critical value the first time. The model parameters are estimated using method of maximum likelihood. The optimum plan consists of finding the optimum number of specimens, optimum stress change point(s), and optimum stress rates by minimising asymptotic variance of estimate of q-th quantile life at use condition, subject to the constraint that total testing or experimental cost does not exceed a pre-specified budget. A numerical example is given to demonstrate the proposed model. Sensitivity analysis is carried out to examine the robustness of the proposed plan. A comparative study is performed to highlight the merit of the proposed plan.