Development and Application of Integrated Indicators for Assessing Healthcare Waste Management Systems in Kenyan Hospitals

Healthcare waste management (HCWM) is an important aspect of healthcare delivery globally because of its hazardous and infectious components that have potential for adverse health and environmental impacts. The paper introduces a set of indicators for assessing HCWM systems in hospitals. These indicators are: HCWM policies and standard operating procedures, management and oversight, logistics and budget support, training and occupational health and safety, and treatment, disposal and waste treatment equipment housing. By plotting a mark on a continuum which is defined as good and poor on the extremes and is connected with all other marks in a spoke arrangement, it’s possible to describe a baseline for HCWM in any specific hospital. This baseline can be used to improve awareness of the actors and policy-makers, compare the same hospital at a different point in time, to compare observations by different evaluators and to track improvements. Results suggest that in Kenya, the application of such indicators is useful for evaluating which priorities should be addressed to improve outcomes in HCWM systems. Systematic sampling technique was used to identify and collect data by use of observational checklist, interviews, visual verification and review of documents and a HCWM assessment tool. The objective is to suggest an integrated management tool as a method to identify prevailing problems with a HCWM system. The method can be replicated in other contexts worldwide, with a focus on the developing world. The integrated indicators focus on management of HCW and not its potential impact on human health and environment, an area recognized to be critical for future research.

Understanding Patients’ Symptoms Management Using Objective and Subjective Indicators among Patients with Systemic Lupus Erythematosus

Background: Descriptive statistics have been used to document the high prevalence of sleep disorders, fatigue, and pain in patients with systemic lupus erythematosus (SLE). Objectives: To describe day-to-day variations in sleep indicators, physical activity level, pain, and fatigue measured using objective and subjective indicators in lupus patients with sleep disorders. Methods: We selected three patients with sleep disorders, measured by the Pittsburgh Sleep Quality Index score (≥9), out of 20 participants followed up for 4 weeks. We compared the self-rated quality of life (QoL) measured using the Pittsburgh Sleep Quality Index (PSQI) with that of objectively measured sleep indicators monitored using the Nemuri scan. The detailed data collection methods have been previously published. Results: The sleep status generated by the Nemuri scan revealed that Case A with a flare and Case B without a flare required frequent daytime rest. The PSQI sleep duration and sleep latency were generally in agreement with the monitored data, although the PSQI failed to capture the complexity of sleep disorders, particularly the fluctuations in the quality of sleep indicators. Patient C approximately 4 hours on weekdays and 10 hours on Saturday nights. All three cases had high fatigue levels, and their moderate-to-vigorous physical activity duration was less than one-half of duration that recommended by the World Health Association. Conclusion: Visual display for objective monitoring of sleep quality is an excellent tool for understanding patients who require frequent resting and irregular sleep indicators. Objective monitoring of sleep quality, along with self-rated pain and fatigue, promotes an understanding of how patients with SLE cope with severe symptoms.

Monitoring of Sleep Indicators, Physical Activity, Pain, and Fatigue in Patients with Systemic Lupus Erythematosus and Relations among These Variables: A Pilot Study

Background: Poor sleep, fatigue, and pain are major health problems in patients with systemic lupus erythematosus (SLE). However, only cross-sectional surveys on these health outcomes have been conducted, and the association between day-to-day fluctuations remains unknown. Objectives: We aimed to characterize daily fluctuations in sleep quality, physical activity, pain, and fatigue in patients with SLE. Method: Exploratory study with a cross-sectional design. Two rheumatology centers (a university hospital and a prefectural hospital) in Japan between September 2017 and May 2019. The sample size was set to 20. Demographic and clinical data were collected. Sleep and physical activity were measured with monitoring devices;pain and fatigue levels were recorded daily during the 4-week period. The Pittsburgh Sleep Quality Index, Short Form Health Survey-12, the Japanese version of the Lupus Patient Outcome, and SLE Disease Activity Index 2000 were collected at the start and end of the study. Descriptive statistics and coefficients of variation (CV) were tabulated to examine daily fluctuations. Pearson correlation coefficients were obtained for monitored variables. Results: The mean age was 43.7 ± 8.5 years, and the mean SLE duration was 16.0 ± 7.2 years. The mean moderate-to-vigorous physical activity (MVPA) duration was 7.8 ± 5.8 min/day, and the mean total sleep duration was 391.8 ± 65.3 min, with a mean sleep efficiency of 88.6% ± 6.1%. Daily fluctuations were high for leaving the bed frequency, MVPA duration, pain, and waking after sleep onset. Seventeen participants showed correlations between some of the variables, such as fatigue or longer MVPA duration and poorer sleep outcomes;longer sleep latency and increased frequency of leaving the bed;and higher physical activity and increased pain and fatigue. Conclusion: The quality of sleep and fatigue fluctuated daily, and correlations existed between these variables, as well as for pain and physical activity. The impact of MVPA duration on pain and fatigue is of concern as increased physical activity may worsen the quality of life patients with SLE. The monitoring of sleep and physical activity using the device seems feasible for SLE symptom management.

Investigating the causal associations between five anthropometric indicators and nonalcoholic fatty liver disease:Mendelian randomization study

BACKGROUND Although the etiology of nonalcoholic fatty liver disease(NAFLD)has not been thoroughly understood,the emerging roles of anthropometric indicators in assessing and predicting the risk of NAFLD have been highlighted by accumulating evidence.AIM To evaluate the causal relationships between five anthropometric indicators and NAFLD employing Mendelian randomization(MR)design.METHODS The Anthropometric Consortium provided genetic exposure data for five anthropometric indicators,including hip circumference(HC),waist circumference(WC),waist-to-hip ratio(WHR),body mass index(BMI),and body fat percentage(BF).Genetic outcome data for NAFLD were obtained from the United Kingdom Biobank and FinnGen Consortium.Genome-wide significant single nucleotide polymorphisms were chosen as instrumental variables.Univariable MR(UVMR)and multivariable MR(MVMR)designs with analytical approaches,including inverse variance weighted(IVW),MR-Egger,weighted median(WM),and weighted mode methods,were used to assess the causal relationships between anthropometric indicators and NAFLD.RESULTS Causal relationships were revealed by UVMR,indicating that a higher risk of NAFLD was associated with a perunit increase in WC[IVW:odds ratio(OR)=2.67,95%CI:1.42-5.02,P=2.25×10^(−3)],and BF was causally associated with an increased risk of NAFLD(WM:OR=2.23,95%CI:1.07-4.66,P=0.033).The presence of causal effects of WC on the decreased risk of NAFLD was supported by MVMR after adjusting for BMI and smoking.However,no causal association between BF and NAFLD was observed.In addition,other causal relationships of HC,WHR(BMI adjusted),and BMI with the risk of NAFLD were not retained after FDR correction.CONCLUSION This study establishes a causal relationship,indicating that an increase in WC is associated with a higher risk of NAFLD.This demonstrates that a suitable decrease in WC is advantageous for preventing NAFLD.

Development of Spectral Features for Monitoring Rice Bacterial Leaf Blight Disease Using Broad-Band Remote Sensing Systems

As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv.oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result ofthe disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remotesensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutionsoffer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapiddispersal under suitable conditions, making it difficult to track the disease at a regional scale with a single sensorin practice. Therefore, it is necessary to identify or construct features that are effective across different sensors formonitoring RBLB. To achieve this goal, the spectral response of RBLB was first analyzed based on the canopyhyperspectral data. Using the relative spectral response (RSR) functions of four representative satellite or UAVsensors (i.e., Sentinel-2, GF-6, Planet, and Rededge-M) and the hyperspectral data, the corresponding broad-bandspectral data was simulated. According to a thorough band combination and sensitivity analysis, two novel spectralindices for monitoring RBLB that can be effective across multiple sensors (i.e., RBBRI and RBBDI) weredeveloped. An optimal feature set that includes the two novel indices and a classical vegetation index was formed.The capability of such a feature set in monitoring RBLB was assessed via FLDA and SVM algorithms. The resultdemonstrated that both constructed novel indices exhibited high sensitivity to the disease across multiple sensors.Meanwhile, the feature set yielded an overall accuracy above 90% for all sensors, which indicates its cross-sensorgenerality in monitoring RBLB. The outcome of this research permits disease monitoring with different remotesensing data over a large scale.

The Impact of Health Information Technology on Hospital Performance: A Systematic Integrative Literature Review

Objective: To review, categorise, and synthesise findings from literature on health information technology (HIT) functionalities, HIT use, and the impact of HIT on hospital performance. Materials and Methods: We conducted a systematic integrative literature review based on a compre-hensive database search. To organise, categorise and synthesise the ex-isting literature, we adopted the affordance actualization theory. To align the literature with our research framework, we used four categories: 1) the functionalities of HIT and how these functionalities are measured;2) use and immediate outcomes of HIT functionalities;3) different perfor-mance indicators and how HIT functionalities affect them;and 4) what hospital characteristics influence the outcome of hospital performance. Results: Fifty-two studies were included. We identified four types of HIT. Only ten studies (19.2%) define the use of HIT by explicitly meas-uring the use rate of HIT. We identified five dimensions of hospital per-formance indicators. Every dimension showed mixed results;however, in general, HIT has a positive impact on mortality and patient readmis-sions. We found several hospital characteristics that may affect the rela-tionship between HIT and hospital-level outcomes. Discussion: Further efforts should focus on embedded research on HIT functionalities, use and effects of HIT implementations with more performance indicators and adjusted for hospital characteristics. Conclusion: The proposed framework could help hospitals and researchers make decisions regard-ing the functionalities, use and effects of HIT implementation in hospi-tals. Given our research outcomes, we suggest future research opportuni-ties to improve understanding of how HIT affects hospital performance. .

Progress in the Study of Laboratory Indicators Related to Acute Pancreatitis

Acute pancreatitis (AP) is one of the more common gastrointestinal diseases in clinics and is characterized by rapid progression, many complications, and high mortality. When it develops into severe pancreatitis, its prognosis is poor. Therefore, early assessment of the degree of inflammatory response plays a crucial role in the treatment plan and prognosis of patients. More and more studies have shown that the levels of D-dimer (D-D), angiotensin-2 (Ang-2), phosphate, heparin-binding protein (HBP), retinol-binding protein-4 (RBP4), and osteoblastic protein (OPN) are closely related to the severity of acute pan-creatitis and can be used as effective indicators for early assessment of AP. In this paper, the research progress of the above indicators in assessing the severity of AP is summarized.

Evidence-Based Nursing Practice of Reducing Immune-Related Skin Toxicity of Tumor Patients Guided by Sensitive Indicators

Purpose research on nursing sensitive indicators in tumor Patients application effect in immune-related skin toxicity management. Method select our hospital April to June, 202360 cases patients with immune therapy settings as the control group. August-October, 2023 60 cases the patients treated with immune therapy were the experimental group. The control group adopted regular nursing methods, while the experimental group sensitive Indicators, evidence-based give preventive care. The social situation, psychological state, physical function, quality of life score, incidence of skin toxicity caused by immune checkpoint inhibitors, moderate and above of the two groups of patients were compared. Incidence of skin toxicity. Result: experience group SAS score, SDS score higher than the control group, the difference was statistically significant (P < 0.05);The incidence of skin toxic reactions caused by immune checkpoint inhibitors and the incidence of moderate and above skin toxic reactions in the experimental group are lower than those in the control group, and the difference is statistically significant (P < 0.05). Conclusion: sensitive indicator guidance evidence-based preventive care can reduce the degree of immune-related skin toxicity, improve the psychological state and quality of life of tumor patients treated with immune therapy and reduce the incidence of adverse reactions, improve nursing quality and patient satisfaction.

Study on Temperature Disaster Indicators of Passion Fruit in Southwest Fujian, China

In China, meteorological forecasting relies on meteorological data obtained from regional and national stations. However, there were discrepancies between the data collected from the meteorological station at the passion fruit growing base and the data from regional and national stations. Consequently, the high and low temperature disaster indicators determined by the meteorological station at the passion fruit growing base cannot be applied to meteorological forecasting. To address this issue and facilitate the monitoring and early warning of high and low temperature disasters in passion fruit cultivation in Fujian, China, we used multi-source hourly temperature data (including the data from meteorological observation stations in passion fruit growing bases, the nearest regional stations, and national surface conventional meteorological observation stations) in three cities in southwestern Fujian (Longyan, Sanming, and Zhangzhou) spanning the years 2020 to 2022. By employing comprehensive statistical analysis methods (0.5 interval division and Cumulative frequency), we identified that passion fruit in southwestern Fujian was susceptible to high temperature disasters during the blooming-fruiting period, as well as low temperature disasters during the sprouting period. Consequently, we developed high and low temperature disaster indicators based on data from regional and national stations for different phenological periods of passion fruit in this region.

Optimization Management of Industrial Organizations Based on Performance Indicators

This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based on intelligent agents, ontologies and data mining. It is implemented by PASSI (Process for Agent Societies Specification and Implementation) methods for agent design and implementation, the Methodology for Knowledge Modeling and Hot-Winters for data prediction. Intelligent agents not only track indicators but also store the knowledge of managers within the company. Ontologies are used to manage the representation and presentation aspects of knowledge. Data mining makes it possible to: make the most of all available data;model the industrial process of data selection, exploration and modeling;and transform behaviors into predictive indicators. An instance of the IMS named SYGISS, currently in operation within a large brewery organization, allows us to observe very interesting results: the extraction of indicators is done in less than 5 minutes whereas manual extraction used to take 14 days;the generation of dashboards is instantaneous whereas it used to take 12 hours;the interpretation of indicators is instantaneous whereas it used to take a day;forecasts are possible and are done in less than 5 minutes whereas they did not exist with the old management. These important contributions help to optimize the management of this organization.

Visualization analysis of the capability of weapon system of systems for multi-dimensional indicators

In the field of weapon system of systems(WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly and intuitively by visualization of multi-dimensional indicators. A method of machine learning and visualization is proposed, which can display and analyze the capabilities of different WSOS in a two-dimensional plane. The analysis and comparison of the comprehensive capability of different components of WSOS is realized by the method, which consists of six parts: multiple simulations, key indicators mining, three spatial distance calculation, fusion project calculation, calculation of individual capability density, and calculation of multiple capability ranges overlay. Binding a simulation experiment, the collaborative analysis of six indicators and 100 possible kinds of red WSOS are achieved. The experimental results show that this method can effectively improve the quality and speed of capabilities analysis,reveal a large number of potential information, and provide a visual support for the qualitative and quantitative analysis model.

NATIONAL KNOWLEDGE INNOVATION SYSTEMS: EVOLUTION, DEFINITION AND INDICATORS

The paper examines the three stages of the evolution of national innovation systems: national technology innovation systems, national innovation systems and national knowledge innovation systems. A national knowledge innovation system is a network of institutions and organizations which jointly or individually contributes to the knowledge innovation (including scientific and technical knowledge innovation). The author stresses that knowledge innovation will occur in all processes of the produc-tion, transmission and use of knowledge. There are four subsystems in this system: scientific knowledge innovation, technical knowledge innovation, knowledge trans-mission and knowledge use subsystem. The author also lists some indicators for the System.

Clinical assessment indicators of postpartum hemorrhage: A systematic review

Objective: The assessment indicators of postpartum hemorrhage(PPH) were systematically reviewed to explore their relationship with blood loss as an early warning sign to identify potential PPH for prompt intervention.Methods: A systematic literature search of 9 databases was conducted according to inclusion and exclusion criteria using a comprehensive strategy. Strengthening the Reporting of Observational Studies in Epidemiology(STROBE) strategy was chosen as the tool for quality assessment of included studies, and data concerning the basic study characteristics and assessment indicators were extracted.Results: Eleven studies were included in this review. The assessment indicators in different reports covered heart rate, blood pressure, placental and birth canal check, hemoglobin(Hb), hematocrit(HCT),coagulation function tests, hemodynamic parameters and arterial blood gas, but no data on the assessment of postpartum uterine contraction were found. The relationship between indicators and blood loss varies.The overall quality of 9 manuscripts was comparatively high or moderate, and 2 were rated as low.Conclusions: The association between blood loss and clinical symptoms is not conclusive based on the present studies, and specific cut-off points could not be formulated to determine the approximate amount of blood loss. However, some cut-off points can be considered warning signs for the need of advanced interventions, such as heart rate, prothrombin time, and placental implantation. Further research on comprehensive assessment and cut-off points should be performed such that birth attendants can distinguish PPH as early as possible.

Providing Performance Evaluation Indicators for Intelligent Transportation Systems (The Case Study of Tehran-Karaj Freeway Located in Iran)

Intelligent Transportation Systems (ITS) play a fundamental role in reducing traffic congestion and increasing safety during daily transportation. These systems can also be useful in improving social welfare leading to general satisfaction. Proper performance evaluation can be efficient in improving the performance of these systems, and providing a scientific assessment index system can assist decision-makers in smart communities to plan for the development of ITS. However, the evaluation of these systems requires identifying appropriate indicators of performance evaluation that are consistent with the views of the beneficiaries of these systems. In this paper, performance evaluation indicators of ITS have been identified, and three indicators entitled “environmental and safety”, “assistance in reducing traffic congestion” and “attractive public transport” are presented to evaluate the performance of these systems. Moreover, the intelligent transport systems of the Tehran-Karaj Freeway in Iran are studied, and inferential statistical methods are employed to test the research hypotheses. It is worth noticing that in this study, a one-sample T-test method is used for hypotheses assessment and the SPSS software was used to analyze the findings. Also, the results demonstrated that the performance of ITS in the Tehran-Karaj Freeway regarding the indicators, such as “Declaration of route blocking information due to maintenance or reconstruction” and “Declaration of path geometry conditions” has not been acceptable.

Investigation of a Simple and Cheap Source of a Natural Indicator for Acid-Base Titration: Effects of System Conditions on Natural Indicators

This study investigated a natural indicator for acid-base titration which is extracted from guinea corn leaves popularly called “waakye leaves” in Ghana. Four types of acid-base titration were studied: strong acid versus (v/s) strong base, strong acid versus weak base, weak acid versus strong base, and weak acid versus weak base. The indicator color change, pH range and the average titre values were determined for each type of acid-base titration. These values were comparable to those obtained from three standard indicators: methyl orange, methyl red and phenolphthalein. Total flavonoids (TF) and condensed tannin (CT) from the crude leaves extract were determined which might be the major reasons for the activity of the extract as an indicator for simple acid-base titration. The authors suggest that the natural indicator is cheap, available, simple to extract, user and environmentally friendly and could be an excellent replacement for standard indicators.

Analysis of the Performance Indicators of the PV Power System

The energy assessment of the PV power systems is carried out by using different types of performance indicators that benchmark the output of these systems against the PV panel maximum output at hypothetical operation conditions. In this paper, a comparative analysis of six types of performance indicators is conducted and a new performance indicator which considers PV panel slope and orientation is proposed. The proposed indicator is benchmarking the PV system actual output against the maximum output of the same system if it would operate in two axis tracking mode. The proposed performance indicator is used to develop a friendly user calculator of PV system output that can be used by, energy providers and PV system installers to evaluate the output of the PV grid connect network. The advantage of the developed calculator is high-lighted by a case study that estimates energy capacity of different residential rooftop PV systems installed in a residential suburb in Sydney.

A Set of Coherent Indicators for the Assessment of the Energy Profitability of Energy Systems

The concern on climate change and on the limitations of fossil fuels is leading to the promotion of renewable-based energy options. However, the assessment of the energy profitability of a technology is still a controversial topic, especially when renewable-based systems are compared with non-renewable ones and when the depletion of the stocks of available resources is not accounted properly. As a matter of fact, some popular energy indicators do not seem to cover all the aspects of the problem, with the risk of drawing ambiguous conclusions. A set of life cycle-based indicators is proposed in order to establish a more reliable approach to the assessment of energy products which decouples the different contributions given by renewable and non-renewable resources. The proposed set of indicators has been quantified for different groups of energy products and compared with an energy indicator frequently used (i.e. EROI). A coherent assessment of the depletion of energy resources and of the energy profitability of the products is presented. The indicators could even contribute to understand the feasibility of energy projects and plans by evaluating their impact on the stock of energy resources.

Effect of foot reflexology on pain and physiological indicators in postoperative patients:A systematic review and meta-analysis

Aim:To determine the effect of foot reflexology intervention on pain and physiological indicators in postoperative patients.Data resources:The Cochrane library,PubMed,EMBASE,MEDLINE,SCOPUS,CINAHL,China National Knowledge Infrastructure(CNKI),VIP,and Wan Fang Data were searched from inception until January2020.Review methods:Studies were screened according to the PICOS principle.The methodological quality was assessed with Cochrane Risk of Bias Tool.Meta-analysis was performed using RevMan 5.3 software.Results:5 randomized clinical trials involving 318 participants were included in the meta-analysis.There were significant differences in pain and heart rate in postoperative patients between the two groups.Conclusion:The foot reflexology intervention decrease the postoperative pain and heart rate for the postoperative patients.It can be considered to be an effective non-pharmaceutical therapy to reduce the postoperative pain and heart rate.The evidence is not enough to prove the effectiveness of reducing postoperative blood pressure,respiratory rate,pulse rate and oxygen saturation using the foot reflexology.

Territorial Planning for Coastal Zones in Chile:The Need for Geographical-Environmental and Natural Risk Indicators for Spatial Decision Support Systems

Coastal zones are very dynamic and fragile environments, constituting a landscape ever more heterogeneous, fragmented and with increasing levels of complexity due to the changing relationship between man and nature. Integrated coastal zone management therefore requires detailed knowledge of the system and its components, based—to a large extent—on technical and scientific information. However, the information generated must be in line with the political requirements necessary for decision-making and planning. Thus the use of indicators to give a simplified view of the many components of the territory, and at the same time to provide important information about patterns or trends, becomes a tool of the utmost importance. These indicators can be understood as measurable characteristics of the environment, which facilitate comprehension of the processes occurring at different scales and serve as a reference to inform the population and support decision-making. The aim of the present note is to demonstrate briefly the need to develop geographical-environmental and natural risk indicators to facilitate comprehension of the dynamic of spatial and temporal landscape patterns, particularly in coastal environments. This approach offers an historical summary of the natural, socio-economic and political processes which currently make up the territory, and which without doubt will continue to influence it in the future. At the same time, it is proposed that information should be integrated on the basis of this framework with a view to generating spatial decision support systems in a context of planning and integrated management of the coastal zones of Chile.

Assessing fire severity in Turkey's forest ecosystems using spectral indices from satellite images

Fire severity classifications determine fire damage and regeneration potential in post-fire areas for effective implementation of restoration applications.Since fire damage varies according to vegetation and fire characteristics,regional assessment of fire severity is crucial.The objectives of this study were:(1)to test the performance of different satellite imagery and spectral indices,and two field—measured severity indices,CBI(Composite Burn Index)and GeoCBI(Geometrically structured Composite Burn Index)to assess fire severity;(2)to calculate classification thresholds for spectral indices that performed best in the study areas;and(3)to generate fire severity maps that could be used to determine the ecological impact of forest fires.Five large fires in Pinus brutia(Turkish pine)and Pinus nigra subsp.pallasiana var.pallasiana(Anatolian black pine)—dominated forests during 2020 and 2021 were selected as study sites.The results show that GeoCBI provided more reliable estimates of field—measured fire severity than CBI.While Sentinel-2 and Landsat-8/OLI images performed similarly well,MODIS performed poorly.Fire severity classification thresholds were determined for Sentinel-2 based RdNBR,dNBR,dSAVI,dNDVI,and dNDMI and Landsat-8/OLI based dNBR,dNDVI,and dSAVI.Among several spectral indices,the highest accuracy for fire severity classification was found for Sentinel-2 based RdNBR(72.1%)and Landsat-8/OLI based dNBR(69.2%).The results can be used to assess and map fire severity in forest ecosystems similar to those in this study.