Test Error Rate Research Articles

Analysis of factors associated with use of real-world data in single technology appraisals of cancer drugs by the National Institute for Health and Care Excellence

ObjectivesThis study investigates factors associated with use of real-world data (RWD) in economic modelling for single technology appraisals (STAs) of cancer drugs by the National Institute for Health and Care Excellence (NICE) to improve systematic understanding of the use of RWD. MethodsThe data were extracted from STAs of cancer drugs, for which NICE issued guidance between January 2011 and December 2022 (n=267). Binary regression was used to test hypotheses concerning the greater or lesser use of RWD. Bonferroni-Holm correction was used to control error rates in multiple hypotheses tests. Several explanatory variables were considered in this analysis, including time (Time), incidence rate of disease (IR), availability of direct treatment comparison (AD), generalisability of trial data (GE), maturity of survival data in trial (MS) and previous technology recommendations by NICE (PR). The primary outcome variable was any use of RWD. Secondary outcome variables were specific uses of RWD in economic models. ResultsAD had a statistical negative association with any use of RWD whereas no associations with non-parametric and parametric use of RWD were found. Time had several statistical associations with use of RWD (validating survival distributions for the intervention, estimating progression-free survival for the intervention, estimating overall survival for comparators and transition probabilities). ConclusionsRWD were more likely to be used in economic modelling of cancer drugs when randomised controlled trials failed to provide relevant clinical information of the drug for appraisals, particularly in the absence of direct treatment comparisons. These results, based on analysis of data systematically collected from previous appraisals, suggest that uses of RWD were associated with data gaps in the economic modelling. While this result may support some of the claimed advantages of using RWD when evidence is absent, the question, the extent to which use of RWD in indirect treatment comparisons reduces uncertainty is still to be determined.

3D Lightweight Cryptosystem Design For IoT Applications Based On Composite S-Box

The security of the Internet of Things (IoT) depends on strong cryptographic functions that require extensive computation and resources. The security of Internet of Things (IoT) relies on the use of strong cryptographic functions that demand extensive computation and resources. Therefore, the selection of a cryptographic system is influenced by the computational and communicational capabilities of IoT devices, including their energy requirements, memory constraints, and execution time. This paper aims to develop a lightweight and secure encryption algorithm for IoT applications, focusing on advancing cryptanalysis techniques. We propose a new lightweight algorithm named enhanced 3D RECTANGLE, designed to deliver robust security for IoT applications and optimized for cell phones with minimal memory usage, low power consumption, and efficient performance. The RECTANGLE block cipher was chosen for this research due to its high efficiency and speed relative to other lightweight algorithms, despite some security issues. The proposed enhanced 3D RECTANGLE algorithm improves confusion and diffusion properties through a new 3D array block rotation method for 4x4 plaintext, based on a 128-bit key and 16 rounds. Additionally, we designed a 4x4 composite S-Box with a Galois field pipelining structure, offering a more advanced solution compared to the Look-Up Table method. The cryptanalysis, avalanche effect, and bit error rate tests were conducted to verify the security strength of the proposed algorithm. The proposed algorithm was evaluated against two existing algorithms, RECTANGLE and Extended 3D RECTANGLE. The enhanced 3D RECTANGLE algorithm provides better cryptanalysis, demonstrating a 40% avalanche effect and achieving a bit error rate (BER) of 31%, indicating its greater effectiveness compared to the other two lightweight algorithms.

Ecg signal watermarking using QR decomposition.

This study introduces a novel watermarking technique for electrocardiogram (ECG) signals. Watermarking embeds critical information within the ECG signal, enabling data origin authentication, ownership verification, and ensuring the integrity of research data in domains like telemedicine, medical databases, insurance, and legal proceedings. Drawing inspiration from image watermarking, the proposed method transforms the ECG signal into a two-dimensional format for QR decomposition. The watermark is then embedded within the first row of the resulting R matrix. Three implementation scenarios are proposed: one in the spatial domain and two in the transform domain utilizing discrete wavelet transform (DWT) for improved watermark imperceptibility. Evaluation on real ECG signals from MIT-BIH Arrhythmia database and comparison to existing methods demonstrate that the proposed method achieves: (1) higher Peak Signal-to-Noise Ratio (PSNR) indicating minimal alterations to the watermarked signal, (2) lower bit error rates (BER) in robustness tests against external modifications such as AWGN noise (additive white Gaussian noise), line noise and down-sampling, and (3) lower computational complexity. These findings emphasize the effectiveness of the proposed QR decomposition-based watermarking method, achieving a balance between robustness and imperceptibility. The proposed approach has the potential to improve the security and authenticity of ECG data in healthcare and legal contexts, while its lower computational complexity enhances its practical applicability.

Forensic discrimination of fiber microspectrophotometry data by resampling and repeating two-sample hypothesis testing

Textile fibers are important forensic trace evidence in criminal investigations. Colored textile fibers are often analyzed using non-destructive microspectrophotometry. However, when the spectra of questioned and known samples are very similar, it is difficult to compare the spectra visually. Chemometric methods, such as principal component analysis and agglomerative hierarchical clustering, have been applied to microspectrophotometry data. In this study, we used two-sample hypothesis testing as a chemometric approach for discrimination of fiber samples without reducing or eliminating the dimensionality of the data. Cotton fibers dyed with vat dyes were analyzed by microspectrophotometry. We examined suitable data types and statistical methods for test fiber samples by resampling and repeating hypothesis testing. A combination of spectral data type and statistical method was identified that provided a good balance of type I (false exclusion) and type II (false inclusion) error rates in two-sample hypothesis testing of the fibers.The main advantage of our chemometric approach is that an appropriate method for samples can be selected by using the type I and II error rates. Furthermore, our method can use all the measured data for the calculation without reducing or eliminating the dimensionality of the data, so it is not necessary to reduce variables or smooth the spectrum. This statistical method also requires no training set. Therefore, two-sample hypothesis testing could be applied to fibers of different types, colors, or materials from those used in this study. Resampling and repeating two-sample hypothesis testing technique is promising as a new chemometric approach for comparing microspectrophotometry spectra.

Current trend of biapenem susceptibility and disc diffusion breakpoints in Enterobacterales and Pseudomonas aeruginosa

IntroductionBiapenem has been recently approved by the Drug Controller General of India for the treatment of complicated urinary tract infections (cUTI). However, there are no assessment studies that evaluate the in-vitro activity of biapenem against contemporary ESBL-producing Indian Enterobacterales isolates. To determine the activity of biapenem against contemporary ESBLs and/or OXA-1/ampC producing Enterobacterales and Pseudomonas aeruginosa isolates. MethodologyIsolates were tested for susceptibility to biapenem and its comparators using the broth microdilution method. Presence of ESBLs (SHV, TEM, CTX-M) genes, OXA-1, and ampC genes (ACC, ACT, DHA, CIT/CMY, FOX) using multiplex PCR. ResultsAgainst ESBL with OXA-1 and/or ampC-producing E. coli, ESBL-K. pneumoniae, and cephalosporin-resistant P. aeruginosa, biapenem showed in-vitro activity similar to that of meropenem. Overall, a biapenem disc concentration of 10 μg provided no error rates for testing E. coli, K. pneumoniae, and P. aeruginosa isolates. ConclusionIt is more accurate to test biapenem at a 10 μg disc concentration and apply more stringent disc diffusion breakpoints for interpretation.

Transmission characterization of atmospheric laser communication based on an all-optical wavelength converter

We demonstrate a free-space optical (FSO) communication scheme based on an all-optical wavelength converter (AOWC). An all-optical wavelength converter is constructed based on the four-wave mixing (FWM) effect, and information replication is achieved by adjusting the pump power and wavelength spacing to convert the light. The feasibility and stability of each channel in a strong turbulent channel are verified through an eye diagram and bit error rate testing, with a total transmission rate of 30 Gb/s. It has been proven that improving conversion efficiency helps to reduce the bit error rate of transmitted signals. This article presents an experimental analysis of free-space information transmission based on AOWC for the first time, providing a reference for establishing high-speed multiplexing communication.

Evaluation of Cognitive Functions in Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention: A Prospective Pilot Study.

It is not clear whether cognitive functions are impaired in young patients with acute coronary syndrome (ACS). This study aims to detect whether or not there is cognitive impairment and cerebral changes in young patients with ACS undergoing percutaneous coronary intervention (PCI). All 50 patients with ACS who were treated with primary PCI were eligible for this prospective study. All participants had normal cognitive function before ACS. Brain magnetic resonance imaging (MRI) was performed to quantify changes in brain white and gray matter. Cognitive functions (CFs) were evaluated by seven cognitive tests. Patients were categorized by MRI findings and test scores were compared from the first day to after the first month. We determined 25 patients with impaired CFs on the first day. After the first month, we identified 18 patients with transient impaired CFs. No structural difference was observed between impaired CF and normal CF. While 25 patients had a score of 1 according to Fazekas, 10 patients had a score of 1 according to MTLA. While the mean Stroop test completion time and Stroop test error rate scores were significantly higher on the first day than after the first month in the Fazekas+ group (p = 0.003, p < 0.001, respectively), other cognitive test scores-except clock drawing test, digital span forwards, and backwards-were significantly lower on the first day compared to after the first month in the Fazekas+ group (p < 0.05). Patients with ACS have transient impairment in cognitive functions. Acute coronary syndrome is not associated with structural changes in the brain.

Handwritten stenography recognition and the LION dataset

AbstractIn this paper, we establish the first baseline for handwritten stenography recognition, using the novel LION dataset, and investigate the impact of including selected aspects of stenographic theory into the recognition process. We make the LION dataset publicly available with the aim of encouraging future research in handwritten stenography recognition. A state-of-the-art text recognition model is trained to establish a baseline. Stenographic domain knowledge is integrated by transforming the target sequences into representations which approximate diplomatic transcriptions, wherein each symbol in the script is represented by its own character in the transliteration, as opposed to corresponding combinations of characters from the Swedish alphabet. Four such encoding schemes are evaluated and results are further improved by integrating a pre-training scheme, based on synthetic data. The baseline model achieves an average test character error rate (CER) of 29.81% and a word error rate (WER) of 55.14%. Test error rates are reduced significantly (p&lt; 0.01) by combining stenography-specific target sequence encodings with pre-training and fine-tuning, yielding CERs in the range of 24.5–26% and WERs of 44.8–48.2%. An analysis of selected recognition errors illustrates the challenges that the stenographic writing system poses to text recognition. This work establishes the first baseline for handwritten stenography recognition. Our proposed combination of integrating stenography-specific knowledge, in conjunction with pre-training and fine-tuning on synthetic data, yields considerable improvements. Together with our precursor study on the subject, this is the first work to apply modern handwritten text recognition to stenography. The dataset and our code are publicly available via Zenodo.

Control of false discoveries in grouped hypothesis testing for eQTL data

BackgroundExpression quantitative trait locus (eQTL) analysis aims to detect the genetic variants that influence the expression of one or more genes. Gene-level eQTL testing forms a natural grouped-hypothesis testing strategy with clear biological importance. Methods to control family-wise error rate or false discovery rate for group testing have been proposed earlier, but may not be powerful or easily apply to eQTL data, for which certain structured alternatives may be defensible and may enable the researcher to avoid overly conservative approaches.ResultsIn an empirical Bayesian setting, we propose a new method to control the false discovery rate (FDR) for grouped hypotheses. Here, each gene forms a group, with SNPs annotated to the gene corresponding to individual hypotheses. The heterogeneity of effect sizes in different groups is considered by the introduction of a random effects component. Our method, entitled Random Effects model and testing procedure for Group-level FDR control (REG-FDR), assumes a model for alternative hypotheses for the eQTL data and controls the FDR by adaptive thresholding. As a convenient alternate approach, we also propose Z-REG-FDR, an approximate version of REG-FDR, that uses only Z-statistics of association between genotype and expression for each gene-SNP pair. The performance of Z-REG-FDR is evaluated using both simulated and real data. Simulations demonstrate that Z-REG-FDR performs similarly to REG-FDR, but with much improved computational speed.ConclusionOur results demonstrate that the Z-REG-FDR method performs favorably compared to other methods in terms of statistical power and control of FDR. It can be of great practical use for grouped hypothesis testing for eQTL analysis or similar problems in statistical genomics due to its fast computation and ability to be fit using only summary data.

A Self-Defense Copyright Protection Scheme for NFT Image Art Based on Information Embedding

Non-convertible tokens (NFTs) have become a fundamental part of the metaverse ecosystem due to its uniqueness and immutability. However, existing copyright protection schemes of NFT image art relied on the NFTs itself minted by third-party platforms. A minted NFT image art only tracks and verifies the entire transaction process, but the legitimacy of the source and ownership of its mapped digital image art cannot be determined. The original author or authorized publisher lack an active defense mechanism to prove ownership of the digital image art mapped by the unauthorized NFT. Therefore, we propose a self-defense copyright protection scheme for NFT image art based on information embedding in this paper, called SDCP-IE. The original author or authorized publisher can embed the copyright information into the published digital image art without damaging its visual effect in advance. Different from the existing information embedding works, the proposed SDCP-IE can generally enhance the invisibility of copyright information with different embedding capacity. Furthermore, considering the scenario of copyright information being discovered or even destroyed by unauthorized parties, the designed SDCP-IE can efficiently generate enhanced digital image art to improve the security performance of embedded image, thus resisting the detection of multiple known and unknown detection models simultaneously. The experimental results have also shown that the PSNR values of enhanced embedded image are all over 57db on three datasets BOSSBase, BOWS2 and ALASKA#2. Moreover, compared with existing information embedding works, the enhanced embedded images generated by SDCP-IE reaches the best transferability performance on the advanced CNN-based detection models. When the target detector is the pre-trained SRNet at 0.4bpp, the test error rate of SDCP-IE at 0.4bpp on the evaluated detection model YeNet reaches 53.38%, which is 4.92%, 28.62% and 7.05% higher than that of the UTGAN, SPS-ENH and Xie-Model, respectively.

Efficacy of Learning Disorder Treatment for Reading or Mathematics Disorders: An Open Study.

This study aimed to identify the effectiveness of treatment programs for children with reading (RD) or mathematics disorders (MD). Structured treatment programs were developed to improve phonological awareness and number sense among children and adolescents with RD or MD, respectively, and the effectiveness of the learning disorder treatment programs were evaluated. We used standardized, objective diagnostic, and evaluation tools not only to recruit participants with RD, MD, or comorbid attention deficit and hyperactivity disorder, but also to assess the effectiveness of the treatments regarding both improved core neurocognitive deficits of RD or MD and academic achievement. Forty children with RD or MD received one-on-one treatments from therapists. In the RD group, treatment effects were observed in all subtests. In the word and paragraph reading tests, the accuracy rates and fluency improved. The results of the phonological working memory test, word-sound correspondence test, and rapid automatic naming tests also improved. In the MD group, the accuracy rate and fluency on the arithmetic test improved. An increase in the accuracy rate in the size and distance comparison tests and a decrease in the error rate in the estimation test were also observed. However, there were no improvements in reaction time in these subtests. Learning disorder treatment programs that focus on improving phonological awareness or number sense in children with RD or MD improved achievement, phonological awareness, and number sense.

Comparing type 1 and type 2 error rates of different tests for heterogeneous treatment effects

Psychologists are increasingly interested in whether treatment effects vary in randomized controlled trials. A number of tests have been proposed in the causal inference literature to test for such heterogeneity, which differ in the sample statistic they use (either using the variance terms of the experimental and control group, their empirical distribution functions, or specific quantiles), and in whether they make distributional assumptions or are based on a Fisher randomization procedure. In this manuscript, we present the results of a simulation study in which we examine the performance of the different tests while varying the amount of treatment effect heterogeneity, the type of underlying distribution, the sample size, and whether an additional covariate is considered. Altogether, our results suggest that researchers should use a randomization test to optimally control for type 1 errors. Furthermore, all tests studied are associated with low power in case of small and moderate samples even when the heterogeneity of the treatment effect is substantial. This suggests that current tests for treatment effect heterogeneity require much larger samples than those collected in current research.

Optimization of the installation techniques of distributed optic fiber sensors and measurement accuracy analysis for asphalt pavement based on finite element methods

The accurate measurement strain is critical to evaluating the structural integrity of asphalt pavements. The measurement strain error is caused by the encapsulation and installation of distributed optical fiber sensor (DOFS) for pavement monitoring. This study introduces an innovative approach to correct installation error. Firstly, a DOFS is embedded into asphalt pavement to simulate the mechanical response caused by traffic load. The optimal installation technology for each asphalt layer is proposed. In addition, the strain correction formula considering the pavement temperature is proposed for different asphalt layer. A rutting test is used to evaluate monitoring performance. Finally, a test road was built. A continuous temporal and spatial distribution strain of DOFS caused by traffic load is obtained. The results indicate that the average error rate of strain testing effectively decreases for each asphalt layer. In summary, this paper contributes to obtaining more accurate measurement strain of DOFS in pavement monitoring.

Evaluation of the Properties of High Strength Lightweight Concrete with High Temperature History

In this study, we evaluated the compressive strength and ultrasonic velocity based on the temperature and age of ordinary aggregate and lightweight aggregate concrete (30 and 60 MPa) and examined their correlation. The unit weight and compressive strength of ordinary aggregate and lightweight aggregate concrete were measured to evaluate the mechanical properties and examine the correlation between ultrasonic velocity and compressive strength. The W/B ratio was set at 0.41 and 0.28, and measurements were made at 1, 3, 7, 28, 56, and 91 days. The physical properties were evaluated at 23, 100, 200, 300, 500, and 700 ℃. In all test specimens, compressive strength and ultrasonic speed increased with age; and the higher the temperature, the lower the compressive strength and ultrasonic speed. By analyzing the correlation between ultrasonic velocity and compressive strength, a strength prediction equation in the form of an exponential function was found. Moreover, from the error rate test, we confirmed that the strength prediction equation generally had an error rate of 15% or less.

Performance evaluation of the data transmission link with Bessel-Gaussian beams through a tunable smoke channel

We simulate and experimentally demonstrate a 1 Gbps free-space optical (FSO) communication system in a smoke chamber with the Bessel–Gaussian (BG) beam. Firstly, we simulate and analyze the attenuation and bit error rate (BER) of BG and Gaussian beams in the smoke channel based on the Monte Carlo method. The results show that BG beams have more advantages than Gaussian beams in smoke transmission. Then we generate a BG beam based on the spatial light modulator (SLM) method, the BG beam’s central spot shows a stable diameter of about 0.9 mm propagating 3.2 m in space. The 1 Gbps 1550 nm on/off keying (OOK) signal is loaded on the BG beam via a bit error rate test (BERT). Next, a tunable smoke channel is established based on an acrylic chamber, and the attenuation and visibility of the smoke channel are characterized in real-time. Finally, the intensity distributions, power stability, power attenuation and BER performance of the BG and Gaussian beams’ transmission links in the tunable smoke channel are investigated. The experimental results show the improvements in transmission performance under the smoke channel conditions using BG beams. Compared with Gaussian beams, BG beams exhibit lower power attenuation (reduced by up to 3.13 dB) and a more stable receiver (decreased by 23 % in standard deviation). Additionally, the BER of 1 Gbps of the transmission link with the BG beam improved by 7.18 dB–10.17 dB in the tunable smoke channel (0.5–2 m). As the length of the smoke channel increases, the improvement of the BG beam in the smoke channel increases as well. The BG beam has shown remarkable advantages in transmission links through the smoke channel. The research offers a robust and generalized proposal for FSO communications based on structured beams.

Improving Security in the Internet of Vehicles: A Blockchain-Based Data Sharing Scheme

To ensure the aggregation of a high-quality global model during the data-sharing process in the Internet of Vehicles (IoV), current approaches primarily utilize gradient detection to mitigate malicious or low-quality parameter updates. However, deploying gradient detection in plain text neglects adequate privacy protection for vehicular data. This paper proposes the IoV-BDSS, a novel data-sharing scheme that integrates blockchain and hybrid privacy technologies to protect private data in gradient detection. This paper utilizes Euclidean distance to filter the similarity between vehicles and gradients, followed by encrypting the filtered gradients using secret sharing. Moreover, this paper evaluates the contribution and credibility of participating nodes, further ensuring the secure storage of high-quality models on the blockchain. Experimental results demonstrate that our approach achieves data sharing while preserving privacy and accuracy. It also exhibits resilience against 30% poisoning attacks, with a test error rate remaining below 0.16. Furthermore, our scheme incurs a lower computational overhead and faster inference speed, markedly reducing experimental costs by approximately 26% compared to similar methods, rendering it suitable for highly dynamic IoV systems with unstable communication.

Comparison of Type I Error Rates of Siegel-Tukey and Savage Tests among Non-Parametric Tests

Comparison of Type I Error Rates of Siegel-Tukey and Savage Tests among Non-Parametric Tests

A34: Factors to Indicate Overweight for Youth from 5-11-Year-Old

Purpose: According to the World Health Organization, obesity has nearly tripled since 1975 in the U.S. (Obesity, n.d.). Considerable research was done to find reasons to deal with obesity. In last 10 year’s obesity related research, the major focuses were metabolic syndrome, physical activity, and eating disorder. In this study, two subsets of the National Health and Nutrition Examination Survey (2013-2014 NHANES) were used to test what variables were critical to indicate overweight of youth from 5- to 11-year-old. Dietary subset reflected nutrients obtained from foods, beverages, and water. Physical activity subset based on the Global Physical Activity Questionnaire, meanwhile, including questions related to daily activities, leisure time activities, and sedentary activities. No obesity classification but Body Mass Index (BMI) was in the dataset. According to CDC, a high BMI can indicate high body fatness (CDC, 2022), which is related to overweight and obesity. BMI was selected as our dependent variable. Methods: Considering the relationship of some features and BMI was highly non-linear, tree regression was applied to analyze the data. R studio was used as the platform to grow trees. 1383 observations of 12 variables of physical activity subset, 1020 observations of 15 variables of dietary subset, and 934 observations of 24 variables of mix subset obtained after data was cleaned were put into analysis. After growing the trees, pruning was done to obtain a subtree with the lowest test error rate. Results: For dietary subset, age was critical to construct the tree. 2 terminal nodes indicated BMI equaled to 17.05 and 19.82 for age less or larger than 8.5, respectively. For physical activity subset, variables of age and days of daily physically active over 60 minutes in a week contributed to tree construction. It’s outstanding that for youth age above 10.5, physically active days in a week popped out, BMI equaled to 23.02 and 20.25 for it less than 6.5 and larger than 6.5, respectively. The pattern of mixed subset was like dietary subset, age outstand. BMI equaled 17.36 and 19.72 for age less and larger than 8.5, respectively. Conclusion: For youth age from 5-11, daily nutrients intake played less important role than age in overweight indication. However, physical activity threw significant influence after youth age over 10. To be physically active for at least 60 minutes daily is important and reasonable to take into consideration when to intervene with youth who are overweight and obese with physical activity after 10.

Comparison of type I error rates of Wald-Wolfowitz, Kolmogorov-Smirnov, and Mann-Whitney tests in small, equal, and large sample volumes

Sosyal bilimlerde, varyansın normalliği ve homojenliği gibi önemli varsayımların ihlal edildiği durumlarda, parametrik olmayan istatistiksel testlerin kullanılması önerilmektedir. Bu tür durumlarda, bağımsız iki örneklemin verilerini test etmek için Wald-Wolfowitz Sıra Sayıları Testi, Kolmogorov-Smirnov İki Örneklem Testi ve Mann-Whitney Testi gibi non-parametrik testlere başvurulmaktadır. Bu çalışma, bu üç farklı test yönteminin belirli koşullar altında I. tip hata oranlarını karşılaştırmak amacıyla gerçekleştirilmiştir. Bu çerçevede, her bir testin I. tip hata oranları, büyük ve küçük örneklem grupları için ayrı ayrı analiz edilmiştir. Araştırmada Uniform-like, Logistic-like ve Double exponential-like dağılımları ile 24 farklı örnek büyüklüğü kombinasyonu kullanılmıştır. Örneklerin yarısı büyük, yarısı küçüktür. Küçük örneklerin içinde hem eşit hem de farklı hacimlere sahip örnekler bulunmaktadır. Benzer şekilde, büyük örneklerin içinde de hem eşit hem de farklı hacimlere sahip örnekler bulunmaktadır. Elde edilen verilere dayalı olarak Mann-Whitney, Kolmogorov-Smirnov ve Wald-Wolfowitz testlerinin I. tip hata oranları, her kombinasyon için büyük bir Monte Carlo Simülasyonu ile hesaplanmıştır. Sonuçlar, örnek büyüklükleri ve örnek hacmi farklılıklarından bağımsız olarak incelendiğinde, Kolmogorov-Smirnov İki Örneklem Testi'nin Mann-Whitney ve Wald-Wolfowitz testlerine göre daha düşük bir I. tip hata oranına sahip olduğunu göstermektedir. Bu çalışma, araştırmacılara bağımsız iki örneklem verilerini test etmek için en uygun istatistiksel yöntemi seçerken dikkate almaları gereken önemli bir bilgi sunmaktadır.

Comprehensive improvements in the emergency laboratory test process based on information technology

ObjectiveTo explore the application effects of information technology (IT) on emergency laboratory testing procedures.MethodsIn this study, IT-based optimisation of the emergency laboratory testing process was implemented between October and December 2021. Thus, the emergency laboratory test reports from January to September 2021 were placed into the pre-optimised group, while those from January to September 2022 were categorised into the post-optimised group. Besides, the emergency laboratory test report time, emergency laboratory test report time limit coincidence rate, error rate, and employee and patient satisfaction levels in individual months and across the whole period were described. Moreover, changes in the above indicators before and after the implementation of IT-based optimisation were explored and the application effects of IT-based optimisation were also evaluated.ResultsThe emergency laboratory test report times after the implementation of IT-based optimisation were shorter than those before IT-based optimisation (P < 0.05). The total number of laboratory test items before and after information optimization amounted to 222,139 and 259,651, respectively. Also, IT-based optimisation led to an increase in the emergency laboratory test report time limit coincidence rate from 98.77% to 99.03% (P < 0.05), while the emergency laboratory test report error rate fell from 0.77‱ to 0.15‱ (P < 0.05). Additionally, IT-based optimisation resulted in increases in both employee satisfaction, from 80.65% to 93.55% (N = 31, P > 0.05), and patient satisfaction, from 93.06% to 98.44% (P < 0.05).ConclusionThe automation and IT-based optimisation of the emergency laboratory testing process significantly reduces the emergency laboratory test report time and error rate. Additionally, IT-driven optimization enhances the alignment of emergency laboratory test report deadlines and enhances the overall quality and safety of emergency laboratory testing.