Applying healthcare failure mode and effect analysis to patient pain management in the anesthesia recovery period

Objective: To standardize pain management in the anesthesia recovery period and improve the effects of analgesia on acute postoperative pain.Methods: Using healthcare failure mode and effect analysis(HFMEA), we analyzed the primary cause of patients' pain and subsequently determined the process and risk priority number(RPN).Results: Actions were taken to improve patients' pain. After using HFMEA, the experimental group's visual analog scale(VAS) scores were lower than those of the control group at 1 h and at discharge from the post-anesthetic intensive care unit(PAICU). The differences were statistically significant(P < 0.05).Conclusions: The application of failure mode and effect analysis can relieve pain and improve the quality of nursing.

Application of Fuzzy Decision-Making Theory and Conflict-Resolution Method to Failure Mode and Effect Analysis of Industrial Valve

It is not objective to rate the decision-making factors in the traditional failure mode and effect analysis,so fuzzy semantic theory is used in this paper.Six fuzzy semantic scales and their corresponding semantics are summarized,and a defuzzification method is studied to obtain the fuzzy value table of the six fuzzy semantic scales.For the conflicts between experts in the traditional failure mode and effects analysis,a conflict-resolution algorithm is studied to obtain the failure risk order.Finally,a certain type of industrial valve is used as an example to prove the validity of the theory proposed in this paper.

Effect of Healthcare Failure Mode and Effect Analysis on Reducing Error Risk of Neonatal Parenteral Nutrition Solution Dispensing

[Objectives]To investigate the effect of healthcare failure mode and effect analysis(HFMEA)on reducing error risk of neonatal parenteral nutrition solution dispensing.[Methods]A research team was established to identify the failure mode(FM)in each link of the formulation process of neonatal parenteral nutrition solution by HFMEA,quantify the severity(S),occurrence(O)and detection(D)of FM,and evaluate FM by risk priority number(RPN).For FM with the values of RPN>16,failure cause analysis was conducted,and corresponding improvement measures were formulated.The weight coefficient and random consistency ratio(CR)of deployment process were calculated in Matlab R2018a by compiling the Analytic Hierarchy Process(AHP)program.Six months after the implementation of improvement measures,the implementation effect was evaluated by comparing the changes of the values of RPN which was evaluated comprehensively and the rate of dispensing errors before and after the implementation of HFMEA.[Results]In the preparation process of neonatal parenteral nutrition solution,a total of 13 FMs with medium and above risk were found,the weight coefficient of medical order review,dosing and mixing was 0.2703,the weight coefficient of drug dispensing check and review was 0.1432,the weight coefficient of print label was 0.1015,the weight coefficient of distribution was 0.0716,and CR=0.0491<0.1.After six months of intervention,the total RPN value decreased by 64.81%from 127.8 to 45.0.The deployment error rates were significantly lower after the implementation,and the difference was statistically significant(P<0.05).[Conclusions]HFMEA can effectively reduce the error risk in preparation of neonatal parenteral nutrition solution,improve the quality of dispensing and promote the safety of neonatal medication.

Air target intention recognition and causal effect analysis combining uncertainty information reasoning and potential outcome framework

Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition techniques.Facing with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)model.The target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain datasets.Then,the HIR model is utilized to recognize intent for a tested sample from uncertain datasets.Finally,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested sample.Data retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample attributes.The simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.

Impact of failure mode and effects analysis-based emergency management on the effectiveness of craniocerebral injury treatment

BACKGROUND Craniocerebral injuries encompass brain injuries,skull fractures,cranial soft tissue injuries,and similar injuries.Recently,the incidence of craniocerebral injuries has increased dramatically due to the increased numbers of traffic accidents and aerial work injuries,threatening the physical and mental health of patients.AIM To investigate the impact of failure modes and effects analysis(FMEA)-based emergency management on craniocerebral injury treatment effectiveness.METHODS Eighty-four patients with craniocerebral injuries,treated at our hospital from November 2019 to March 2021,were selected and assigned,using the random number table method,to study(n=42)and control(n=42)groups.Patients in the control group received conventional management while those in the study group received FMEA theory-based emergency management,based on the control group.Pre-and post-interventions,details regarding the emergency situation;levels of inflammatory stress indicators[Interleukin-6(IL-6),C-reactive protein(CRP),and procalcitonin(PCT)];incidence of complications;prognoses;and satisfaction regarding patient care were evaluated for both groups.RESULTS For the study group,the assessed parameters[pre-hospital emergency response time(9.13±2.37 min),time to receive a consultation(2.39±0.44 min),time needed to report imaging findings(1.15±4.44 min),and test reporting time(32.19±6.23 min)]were shorter than those for the control group(12.78±4.06 min,3.58±0.71 min,33.49±5.51 min,50.41±11.45 min,respectively;P<0.05).Pre-intervention serum levels of IL-6(78.71±27.59 pg/mL),CRP(19.80±6.77 mg/L),and PCT(3.66±1.82 ng/mL)in the study group patients were not significantly different from those in the control group patients(81.31±32.11 pg/mL,21.29±8.02 mg/L,and 3.95±2.11 ng/mL respectively;P>0.05);post-intervention serum indicator levels were lower in both groups than pre-intervention levels.Further,serum levels of IL-6(17.35±5.33 pg/mL),CRP(2.27±0.56 mg/L),and PCT(0.22±0.07 ng/mL)were lower in the study group than in the control group(30.15±12.38 pg/mL,3.13±0.77 mg/L,0.38±0.12 ng/mL,respectively;P<0.05).The complication rate observed in the study group(9.52%)was lower than that in the control group(26.19%,P<0.05).The prognoses for the study group patients were better than those for the control patients(P<0.05).Patient care satisfaction was higher in the study group(95.24%)than in the control group(78.57%,P<0.05).CONCLUSION FMEA-based craniocerebral injury management effectively shortens the time spent on emergency care,reduces inflammatory stress and complication risk levels,and helps improve patient prognoses,while achieving high patient care satisfaction levels.

Analysis of genetic effects and correlations for nutrient quality traits of indica rice in different environments

Understanding the variation for the expressionof genes in different environments is one of themajor goals in qualitative genetics. In this pa-per, the genetic models for quantitative traitsof endosperm in cereal crops were used to eval-uate the seed, cytoplasm and maternal geneticeffects as well as the genotype × environment(GE) interaction effects, and to predict thebreeding value of parents and genotypic corre-lation for nutrient quality traits of indica rice (Oryza sativa L.).

Risk Evaluation in Blood Donation Using Failure Mode and Effective Analysis

The recognition and management of risk in donation process and blood product is critical to ensure donor and patient safety. To achieve this goal, the failure mode and effects analysis (FMEA) is a convenient method;moreover it was used to prevent the occurrence of adverse events and look at what could go strong at each step. This study aimed to utilize FMEA in central blood bank in Khartoum to evaluate the potential risk and adverse event that may occur during the donation process. According to the severity, occurrence and the detection of each failure mode, the risk priority number (RPN) was calculated to determine which of the failures should take priority to find a solution and applying corrective action to reduce the failure risk. The statistical package for social sciences (SPSS) version 11 was used as descriptive and analytical statistics tool. The FMEA technique provides a systematic method for finding vulnerabilities in a process before they result in an error, and in this study a satisfactory outcome was reached.

Failure Mode Effects and Criticality Analysis Method of Armored Equipment Based on Testability Growth

In view of the low level testability of armored equipment,the important significance of armored equipment testability growth is discussed in this paper.The failure mode effects and criticality analysis( FMECA) method to realize testability growth is introduced.Centering on the testability growth demands of new armored equipment,the deficiencies of traditional FMECA are analyzed.And an enhanced FMECA( EFMECA) method is proposed.The method increases the analysis contents,combines the information before the failure occurrence and impending failure modes together organically.Then the failure symptoms is analyzed,the failure modes and effects is determined,and the state development trend is predicted.Finally,the application of EFMECA method is illustrated by the example of the failure mode of typical armored equipment engine.

An Empirical Study of Downstream Analysis Effects of Model Pre-Processing Choices

This study uses an empirical analysis to quantify the downstream analysis effects of data pre-processing choices. Bootstrap data simulation is used to measure the bias-variance decomposition of an empirical risk function, mean square error (MSE). Results of the risk function decomposition are used to measure the effects of model development choices on model bias, variance, and irreducible error. Measurements of bias and variance are then applied as diagnostic procedures for model pre-processing and development. Best performing model-normalization-data structure combinations were found to illustrate the downstream analysis effects of these model development choices. In additions, results found from simulations were verified and expanded to include additional data characteristics (imbalanced, sparse) by testing on benchmark datasets available from the UCI Machine Learning Library. Normalization results on benchmark data were consistent with those found using simulations, while also illustrating that more complex and/or non-linear models provide better performance on datasets with additional complexities. Finally, applying the findings from simulation experiments to previously tested applications led to equivalent or improved results with less model development overhead and processing time.

Histologic analysis and long-term effect of acellular dermal matrix combined with autologous thin split-thickness skin graft

Objective To evaluate the long-term therapeutic effect and histologic result of ADM combined with autologous thin split-thickness skin graft.Methods 23 patients were treated with acellalar dermal matrix(ADM) combined with autoiogous

The Effect of Clinical Pathway in Patients with Acute Complicated Appendicitis

Clinical pathway (CP) is a medical management tool made by a group of medical specialists and specialized for certain diseases. It has been proved that CP was an efficient way to optimize the hospitalization management and control medical cost. In this paper, we focused on the effect of CP in the patients with acute complicated appendicitis via total duration of hospitalization, hospitalization time before operation, total cost of hospitalization and drug expenditure. From March 2014 to March 2015, the patients with conditions of appendicitis in Three Gorges Central Hospital of Wanzhou, Chongqing, were divided into CP group and non path control group to analyze the effect of the application of CP. Our data showed that there were no significant differences between two groups of patients in total duration of hospitalization, hospitalization time before operation, total cost of hospitalization and drug expenditure. The implementation of CP neither decreased the time of patients in hospital nor the total hospitalization cost. Besides, application of CP for acute appendicitis patients should distinguish between simple appendicitis and complicated appendicitis, simple appendectomy patients implement CP is beneficial, and patients with complicated appendicitis did not come from the benefit.

Research on the Effects of the Most Used Market Power Mitigation Mechanisms Considering Different Market Environments

The market power mitigation method of the supply-side has become one of the key points affecting the stability of the electricity spot market.Different mitigation mechanisms are used in the current mature electricity markets of the world.However,the same market power mitigation mechanism shows different effects in different market environments.Every market operator in the world needs the most efficient way to mitigate market power.Considering that there is no relevant literature discussing the market power effects of different mitigation methods in detail,the mitigation effects need to be discussed and further researched.So,we analyze the effects of the most utilized market power mitigation mechanisms while considering different market environments.Firstly,we establish a Nash-Stackelberg interactive game model to simulate the competitive strategies of power suppliers.Secondly,the different market power mitigation approaches are modeled.Then,a multi-agent system(MAS)genetic interior-point algorithm is proposed to solve the problem of suppliers.Finally,through the simulation analysis,the market power mitigation effects of different mechanisms while considering three operation states of the system in two market structures are all analyzed.

Multi-stage attack weapon target allocation method based on defense area analysis

For better reflecting the interactive defense between targets in practical combat scenarios,the basic weapon-target allocation(WTA)framework needs to be improved.A multi-stage attack WTA method is proposed.First,a defense area analysis is presented according to the targets’positions and the radii of the defense areas to analyze the interactive coverage and protection between targets’defense areas.Second,with the coverage status and coverage layer number,a multi-stage attack planning method is proposed and the multi-stage attack objective function model is established.Simulation is conducted with interactive defense combat scenarios,the traditional WTA method and the multi-stage WTA method are compared,and the objective function model is validated with the Monte-Carlo method.The results suggest that if the combat scenario involves interactive coverage of targets’defense areas,it is imperative to analyze the defense areas and apply the multi-stage attack method to weakening the target defense progressively for better combat effectiveness.