Enhancing cassava grater design: A customer-driven approach using AHP, QFD, and TRIZ integration.

Due to consistent cassava cultivation, small-scale processing centers rely heavily on the cassava grater. However, these machines face stagnation in innovation and design evolution, leading to inefficiencies, limited capacity, and inconsistent output. Adding to these challenges is the competitive global market, demanding a focus on design enhancements. This study employs a multi-faceted approach involving the Analytic Hierarchy Process (AHP), Quality Function Deployment (QFD) and Theory of Inventive Problem Solving (TRIZ) to prioritize customer requirements, propose technically aligned solutions, and offer innovative design options for cassava graters. A total of 10 customer requirements (CR), 21 technical solutions (TS), and 63 innovative design options (IDO) were established and prioritized, aiming for easy adoption by fabricators, engineers, manufacturers, and artisans. Implementing these insights boosts cassava grater efficiency and productivity and significantly advances knowledge. This work presents a thorough scientific framework for product design, empowering local manufacturers to remain viable and relevant in the rapidly changing field of product enhancement.

Decoding stakeholder priorities of safety culture preferences in the oil and gas industry.

Safety culture is a critical determinant of organisational performance, particularly in high-risk industries especially in oil and gas. Understanding stakeholder preferences is essential for developing effective strategies that enhance safety culture. This study utilised the Analytic Hierarchy Process (AHP) to prioritise stakeholder preferences, identifying key elements of safety culture in Malaysia's oil and gas sector. This study employed a structured methodology to evaluate safety culture within the oil and gas industry, focusing on 18 sub-elements across three key domains: psychological, behavioural, and situational factors. A diverse sample of industry experts was recruited using purposeful and snowball sampling to ensure a comprehensive representation of stakeholder views. The AHP framework was applied to analyse the data, utilizing structured questionnaires and multicriteria decision-making techniques to prioritize the identified safety culture elements. The AHP analysis identified distinct priorities among different professional groups within the oil and gas sector. Safety and Health Practitioners emphasized practical elements such as safety rules and management commitment, while academicians prioritized knowledge and training. Management personnel highlighted the importance of safety ownership and communication, whereas policymakers focused on broader, policy-oriented aspects. The findings suggest that safety culture improvement initiatives should be tailored to address the specific needs and priorities of each professional group. A nuanced understanding of stakeholder preferences is crucial for developing comprehensive strategies that integrate observable behaviours, situational conditions, and psychological factors, ultimately fostering a robust safety culture in the oil and gas industry.

Selection of data analytic techniques by using fuzzy AHP TOPSIS from a healthcare perspective.

The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with different Data Analytic (DA) and machine learning algorithm approaches. Researchers, scientists, and industrialists must manage or select the best approach associated with DA in healthcare. This scientific study is based on decision analysis between the DA factors and alternatives. The information affects the whole system in a rational manner. This information is very important in healthcare sector for appropriate prediction and analysis. The evaluation discusses its benefits and presents an analytic framework. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) approach is used to address the weight of the factors. The Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) address the rank of the data analytic alternatives used in healthcare sector. The models used in the article briefly discuss the challenges of DA and approaches to address those challenges. The assorted factors of DA are capture, cleaning, storage, security, stewardship, reporting, visualization, updating, sharing, and querying. The DA alternatives include descriptive, diagnostic, predictive, prescriptive, discovery, regression, cohort and inferential analyses. The most influential factors of the DA and the most suitable approach for the DA are evaluated. The 'cleaning' factor has the highest weight, and 'updating' is achieved at least by the Fuzzy-AHP approach. The regression approach of data analysis had the highest rank, and the diagnostic analysis had the lowest rank. Decision analyses are necessary for data scientists and medical providers to predict diseases appropriately in the healthcare domain. This analysis also revealed the cost benefits to hospitals.

Analyzing risk factors of tuberculosis using type-2 interval-valued trapezoidal fuzzy numbers with Einstein aggregation operators extended to MCDM.

The principal motive of this work is to evolve and initiate an extension from interval-valued fuzzy sets to type-2 interval-valued fuzzy sets (T2IVFS) related to weighted aggregation functions containing the Einstein operator. The chief reason for this extension is that the constancy of the terms can also be taken into data during the aggregation operation. The main goal of this article is to compose the aggregation operators and their characteristics such as the Type-2 interval-valued fuzzy Einstein weighted arithmetic aggregating operator (T2IVFEWA), Type-2 interval-valued fuzzy Einstein weighted geometric aggregating operator (T2IVFEWG), and the characteristics are expressed. At last, to intimate the effectiveness of the suggested approach and explicate the purpose of these operators, a hybrid multi-criteria decision-making problem (MCDM) to select the best risk factor for Tuberculosis (TB) is considered and the result is compared with the outcome of the existing operators and methods. Additionally, a sensitivity analysis was conducted to verify the robustness of the proposed decision-making process.

Is smart city low-carbon? Evidence from China.

Smart cities were originally conceived to address a myriad of urban challenges arising from rapid urbanization, including energy scarcity, congestion, and environmental degradation. The Chinese government has made substantial efforts to advance smart city initiatives. However, the extent to which the integration of smart technologies contributes to urban sustainability, especially within a high-carbon urbanization paradigm, poses a critical question in light of escalating extreme weather events and worsening global challenges. Urgency is underscored in prioritizing low-carbon strategies within smart city frameworks. This paper presents a Multicriteria Decision Making Network (MCDN) approach to assess and rank the low-carbon levels (LCL) of 36 pilot smart cities in China. Findings reveal that overall LCL among these cities remains relatively modest, with significant disparities attributed to varying economic, social, institutional, cultural, and environmental contexts. The study also delves into the nexus between urban intelligence and LCL, highlighting a discernible positive correlation between a city's smartness and its low-carbon profile. Moreover, empirical evidence suggests that advancements in smart technologies are conducive, albeit to varying degrees, to enhancing urban LCL. In light of these findings, recommendations are made to fortify economic and social advancement, bolster management practices, and foster multi-stakeholder collaboration to propel the coordinated development of smart and low-carbon initiatives in China.

Maintaining the Psychological Well-Being of Physicians in the Uncertain Work Environment: A Practitioners Perspective.

COVID-19 significantly altered the healthcare ecosystem and forced us to stretch the capacity to ensure healthcare delivery services. Physicians were on the frontline and acted as an important cog in the wheel of healthcare delivery. This unprecedented situation forced them to adopt to a new norm amidst uncertainty, potentially impacting their mental well-being and overall health. The study aims to investigate the coping strategies for physicians to maintain their psychological well-being during uncertain events such as COVID-19. By employing Analytic Hierarchy Process (AHP), the research prioritizes coping strategies that can improve physicians' psychological well-being. This study affirms that the physicians working in healthcare during pandemic preferred adaptive strategies over maladaptive strategies. Maintained exercise, yoga/meditation (or similar), and behavioral disengagement are the three most preferred coping strategies. The study will benefit physicians and the policy makers, to achieve their agenda of enhancing physicians' psychological resilience during uncertain events, ultimately contributing to the continuity and quality of healthcare delivery.

Validation of effect of composite additive on optimized combustion characteristics of CI engine using AHP and GRA method.

The primary focus of this study is the validation of composite additives with the help of additional optimization methods and the analysis of its effect on the combustion characteristics of compression ignition (CI) engines. Previous work on the identification of the correct multi additive combination by Taguchi and the TOPSIS optimization method has shown substantial improvements in the performance and emission characteristics of CI engines. The same work was extended using the GRA Optimization method with the Multi-Criteria Decision-Making (MCDM) optimization technique known as the Analytic Hierarchy Process (AHP) to validate the optimization results from the previous optimization work. Remarkably, all optimization methods yielded consistent results, pointing to the superiority of the composite additive sample 'D8EH6E4 hence supporting the outcome of previous work. Subsequent testing and comparison of this novel composite additive with baseline diesel fuel for combustion characteristics analysis demonstrated notable improvements in combustion parameters, including a 25 % reduction in the rate of pressure rise, an 18 % decrease in net heat release rate, and a 6 % decrease in mean gas temperature.

Modelling and optimization of an existing onshore gas gathering network using PIPESIM.

Pakistan has limited natural gas reserves, and most are found onshore. This article reports on the problems of an onshore gas gathering network (GGN) analysed through steady-state simulation modelling using PIPESIM software. The research methodology incorporates a comprehensive steady-state hydraulic analysis considering fluid flowing velocity limitations, liquid holdup and slugging along with other issues faced by gas gathering networks. The steady-state hydraulic analysis has led us to pinpoint specific GGN pipelines facing critically low gas velocities and consequent liquid holdup. Addressing these issues involved application of PIPESIM software for modelling, considering various operating schemes of gas-producing wells and their associated pipelines. To select an optimal operating scheme, the study utilized the Analytic Hierarchy Process (AHP) for operational optimization, to identify the most effective solution for reduced liquid holdup, improving production, and ensuring the safe operation among available alternatives. Findings from our hydraulic analysis highlight the importance of reducing GGN outlet pressure to mitigate challenges associated with liquid holdup which causes slugging and back pressure effect at source leading to low production and poor performance of the GGN. Study of three alternative cases reveals that decreasing outlet pressure lowers the liquid holdup, improve gas flowing velocities, and enhanced overall production. These findings validate our hypothesis that reducing GGN outlet pressure is a viable strategy to lower the liquid holdup in pipelines. This research offers significant value by providing a comprehensive solution to GGN liquid holdup, low flowing velocities, back pressure and low production challenges. The integration of steady-state hydraulic analysis, simulation modelling with PIPESIM, and the application of AHP for optimization contributes novel insights into the optimization of operation of gas gathering networks. Emphasizing the reduction of liquid holdup and enhancing production through outlet pressure adjustments offers a practical framework for optimizing the functionality of gas gathering networks.

Exploring the Usage of Social Media Networking Platforms Among Medical Practitioners: Reasons, and Proposed Features for Improved Experience.

PURPOSE: This study aims to identify and prioritize the reasons for social media use among medical practitioners to facilitate the selection of the most appropriate social media platforms for healthcare providers. The findings of this study will help address the challenges posed by the wide variety of available social media platforms and assist healthcare providers in choosing platforms that best meet their professional needs. DESIGN/METHODOLOGY/APPROACH: This cross-sectional study was conducted in the period of two months, i.e., August and September 2021. This study is based on the AHP (Analytic Hierarchy Process) method of the MCDM (Multi-Criteria Decision-Making) approach. In the first phase, a four-hour brainstorming session was held to identify the medical Practitioner's reasons for social media usage; in the second phase, the identified reasons were linked with the top five social media platforms to determine the prioritized order of preference. FINDINGS: The top three reasons driving medical practitioners' usage of social media platforms include "Getting an update on current affairs," "Network with industry professionals," and "Healthy Lifestyle and Wellness Promotion." In contrast, the bottom three causes include "Advocacy for causes," "Get Updates about friends and family members," and "Opinions and ideas sharing." The prioritized order of social media platforms is LinkedIn, followed by Instagram, WhatsApp, Facebook, and Twitter. PRACTICAL IMPLICATIONS: This study helps solve the medical Practitioner's dilemma of selecting suitable social media platforms that serve their intended functions. In the future, it is expected that the usage of SM platforms will increase for causes such as Institution Branding and Healthcare Issues related Advocacy as well. ORIGINALITY/VALUE: Previous research has not adequately identified the reasons driving social media usage by physicians. This study is one of the few studies that has attempted to prioritize reasons for social media usage by physicians and has provided a prioritized list of social media platforms.

Evaluation of different drying methods on the quality of Cinnamomum cassia barks by analytic hierarchy process method.

Cinnamomum cassia Presl is a major food spice as well as traditional herbal medicine with anti-inflammatory, analgesic, and stomachic properties, which must be dried to preserve its quality, but mostly by using traditional, ineffective drying method. In order to find a scientific drying method by evaluating different drying methods that could influence the quality of C. cassia, ten indices were employed to evaluate different drying methods in C. cassia using the Analytic Hierarchy Process (AHP) method though calculating the total scores and ranking the priority. Four quality markers (Q-Markers) (coumarin, cinnamyl alcohol, cinnamaldehyde and o-methoxycinnamaldehyde) were isolated from the samples and analyzed by high performance liquid chromatography (HPLC) method under different drying methods. The results showed that various drying methods had multiple effects on the physicochemical qualities, essential oil content, and Q-Marker contents. Compared with other drying methods, oven-drying of 45 °C (45OD) maintained optimal levels of color and aroma, it also significantly shortened the drying time by 225 h than traditionally shade-drying (SHD) method with the drying rate (48.35 %), and obtained the highest essential oil content (3.05 %) and Q-Marker contents (30.23 mg g-1). Furthermore, the ash content (4.22 %) were satisfied with the stipulation of Chinese pharmacopoeia in 45OD samples. Applying AHP allowed us to identify 45OD as the optimal drying method with the highest total score (9.00), followed by the traditional shade-drying (SHD) method (7.88). The present study is the first report to apply the AHP method for quality evaluation of drying processing in C. cassia. It can provide the theoretical basis for evaluating an excellent method for C. cassia drying processing, as well as the rational use of different drying methods to furtherly develop the high quality C. cassia industry.

Decision making in human resource management: a systematic review of the applications of analytic hierarchy process.

The Analytic Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (FAHP), and Analytic Network Process (ANP) methods are widely used for decision-making across various fields, and have shown success in numerous applications within human resource management (HRM). The purpose of this study is to present a systematic literature review on the applications of AHP, FAHP, and ANP in human resource management. The search process encompassed two main online databases, Scopus and Web of Science. This research covers a total of 180 application papers. To help readers extract quick and meaningful information, references are summarized in tabular format. The results showed that these methods have been applied in various domains of HRM such as performance management and appraisal, selecting human resources, talent attraction and retention, intellectual capital, workplace safety, reward management, e-HRM, green HRM, etc. To the best of our knowledge, no comprehensive research review has yet been conducted on the applications of AHP in HRM.

Mapping Vulnerability to Potential Crisis Events in Surabaya City: A GIS-Based Approach.

Background: This study aims to develop a vulnerability map for Surabaya using GIS-based Multi-Criteria Decision Analysis (MCDA) to assess the city's vulnerability to COVID-19. Methods: Six key factors influencing vulnerability were identified and their relative importance determined through the Analytic Hierarchy Process (AHP) pairwise comparison matrix. GIS was utilized to classify Surabaya's vulnerability into five levels: very low, low, medium, high, and very high. Results: The resulting vulnerability map provides essential insights for decision-makers, healthcare professionals, and disaster management teams. It enables strategic resource allocation, targeted interventions, and formulation of comprehensive response strategies tailored to specific needs of vulnerable districts. Conclusions: Through these measures, Surabaya can enhance its resilience and preparedness, ensuring the well-being of its residents in the face of potential emergency outbreaks.

Exploring climate-smart forestry in Mediterranean forests through an innovative composite climate-smart index.

In recent years, Climate-Smart Forestry (CSF) has emerged as an innovative approach to sustainable forest management, aiming to enhance forest resilience and to balance the provision of ecosystem services facing climate-related threats. This study introduces for the first time a new composite climate-smart index (ICSF) to assess CSF. The methodological approach comprises the following steps: (i) the selection and evaluation of CSF indicators; (ii) the weighting of these indicators; and (iii) the assessment of CSF for Mediterranean forests in two distinct periods, specifically 2005 and 2015. Eight indicators were selected from a systematic literature review. The Analytic Hierarchy Process was applied to translate the preferences obtained through an online questionnaire from a network of CSF-expert stakeholders into weights, at both indicators and criteria levels (i.e., adaptation, mitigation, and the social dimension). Results reveals that indicators "tree species composition", "forest damage", and "regeneration" are of crucial importance for CSF assessment. The comparison of the CSF value between the years 2005 and 2015, shows a slight increase in CSF ratings. The ICSF serves as a comprehensive index of CSF covering all aspects of that concept, i.e. adaptation, mitigation, and the social dimension (including production). The national-scale analysis provides an overview of the dynamics that involve forest management of Mediterranean forests against climate change. The study offers a practicable method for CSF evaluation with its allover set of indicators, representing a suitable tool for supporting forest managers to mitigate the negative impacts of climate change.

Analyzing the impact of artificial intelligence on operational efficiency in wastewater treatment: a comprehensive neutrosophic AHP-based SWOT analysis.

The escalating global challenges of population growth, climate crisis, and resource depletion have intensified water scarcity, emphasizing the critical role of wastewater treatment (WWT) in environmental preservation. While discharging untreated wastewater poses extinction risks to various species, effective WWT operations are indispensable for ecosystem continuity and sustainable water sources. Recognizing the complexity of WWT management, this study delves into the potential of artificial intelligence (AI) in strategic planning and decision-making within the WWT domain. Through a comprehensive SWOT analysis, this study evaluates the strengths, weaknesses, opportunities, and threats associated with AI integration in WWT processes. Utilizing the SWOT analysis framework, key criteria are identified, and their importance weights are assessed via the interval-valued neutrosophic analytical hierarchy process (IVN-AHP). According to analysis, the strengths in WWT are crucial, but potential opportunities and threats should not be ignored. The results of the study highlight several key findings regarding the integration of AI in WWT processes. While concerns about the reduction in human resources and potential unemployment, as well as the activation time and high energy consumption of AI systems, are identified as significant challenges, the study underscores the success of AI in data analytics as a strong aspect. Specifically, advanced data analysis techniques and the ability to proactively prevent problems emerge as important strengths of AI in WWT. WWT operators and practitioners are encouraged to prioritize the adoption of advanced data analysis techniques and proactive problem-solving strategies to maximize the effectiveness of AI integration in WWT processes.

Study on stability evaluation of goaf based on AHP and EWM-taking the northern new district of Liaoyuan city as an example.

Throughout the history of coal mining in all countries of the world, large areas of goaf have been left behind, and sudden collapses and surface subsidence of large areas of goaf may occur, especially for mining areas with long mining cycles. The northern new district of the Liaoyuan mining area has been subjected to nearly half a century of mining activities, accompanied by a gradual accumulation of disasters, which have occurred frequently in recent years. In order to assess the stability of the goaf in the study area, this paper proposes a hybrid decision-making multi-factor integrated evaluation method. The distribution of underground goafs was determined using geophysical exploration techniques (seismic survey and transient electromagnetic method) and geological drilling exploration. First, an evaluation index system was established based on the specifications of the goaf, the ecological and geological environment, and the mining conditions; the system included 14 indicators. Two weight calculation methods, AHP-EWM, were employed to determine the comprehensive weight of each indicator by combining subjective and objective weights on the basis of improved game theory. Subsequently, the fuzzy comprehensive evaluation method was utilised to complete the stability rating of each block in the study area, and MapGIS and ArcGIS were employed to complete the drawing of the stability zoning map of the northern new district goaf. The study area was divided into three zones of stability, basic stability and instability, according to the critical value. These zones accounted for 23.03%, 36.45% and 40.52% of the total area of the study area, respectively. The comprehensive on-site investigation revealed a decrease in the size and number of collapse pits and the rate of damage to the houses from the unstable zone to the stable zone. This indicates that the results of the division are consistent with the actual situation. The classification results are consistent with the actual ground disaster situation, thus verifying the rationality and validity of the evaluation method. The results indicate that the stability of the study area is generally at the lower middle level.

Application of optical images and analytical hierarchy process model for solid waste dumping site analysis in Kombolcha town, Northeastern, Ethiopia.

Improper open dumping of solid wastes caused different serious problems in fast-growing towns in Ethiopia like Kombolcha town. This unsuitable solid waste dumping management brings health challenges by spreading diseases, contaminating water, polluting air, and spreading of different disease-causing insects such as mosquitoes. Therefore, selecting suitable solid waste dumping site analysis (SWDSA) is very essential to minimize these negative effects related to improper solid waste dumping in such towns. The primary goal of this study is to use optical images and the AHP model to find appropriate solid waste dumping sites in Kombolcha Town. The nine governing factors such as soil texture, geology, faults, groundwater well points (GWWPs, rivers, roads, built-up, Land use land cover (LULC) and slopes, were considered to achieve the aim of this study. These factors were extracted and delineated from the various optical data such as Landsat 8 images, digital elevation model, Google Earth images, geological map, soil map, and also field survey. The factor classes and factors were ranked and weighted utilizing a comparison matrix according to importance and finally by applying the AHP spatial analysis extension tool in Arc GIS software the SWDSA map of the study area was generated. Therefore, as a result of this study about 19.4 km2 (22.8 %), 22.8 km2 (26.8 %), 20.5 km2 (24.1 %), 16.1 km2 (18.9 %), and 6.2 km2 (7.3 %) of the study area falls in not suitable, less suitable, moderately suitable, suitable and highly suitable ranges respectively. Based on the result of this further analysis, D is the 1st suitable site with a score is 83.6 %, site B is the 2nd suitable site is a score is 83.2 %, site C is the 3rd suitable site with a score of 65.1 % and site A is the last suitable site and scored 60.4 %. Therefore, this study strongly recommends that the waste management municipal office of Kombolcha town and other concerned government and non-government bodies apply and consider these identified the best suitable solid waste dumping sites.

Application of geospatial technology on land suitability analysis for wheat and maize farming: In a case of Guder sub-watershed North West Oromia, Ethiopia.

Cereal crops like wheat and maize are crucial to providing food security in rural areas of Ethiopia. However, due to population growth, agricultural practices for these cereal crops have been expanded to vulnerable areas, and increasing land degradation. Geospatial technologies are essential for decision-making to reduce land degradation and ensure sustainable agriculture activities. In the Guder sub-watershed, Oromia regional state of Ethiopia, where land degradation has been a persistent issue, agricultural suitability study is crucial. This study is focused on the Guder sub-watershed, which aimed to analyze the land suitability based on ten controlling parameters, including elevation, slope, soil texture, soil depth, soil PH, soil drainage, proximity to the road, temperature, rainfall and land use/land cover, for the two most significant cereal crops (wheat and maize). All of these factors were weighted in accordance with the relative importance of each component for the appropriateness of wheat and maize land suitability using MCDA and AHP method, based on the recommendations of numerous writers and expert opinions. The findings of the study showed that 6 %, 50.58 %, 23.26 %, and 20.26 % of the total study area were highly, moderately, marginally and not suitable for wheat cultivation, respectively, whereas 5.1 %, 57.3 %, 17.3 %, and 20.3 % of the study area were highly, moderately, marginally and not suitable for cultivating maize crop respectively. This result support decision makers to develop land use planning thereby improve productivity and minimize land degradation.

Constructing an evaluation index system for clinical nursing practice teaching quality using a Delphi method and analytic hierarchy process-based approach.

BACKGROUND: The key step in evaluating the quality of clinical nursing practice education lies in establishing a scientific, objective, and feasible index system. Current assessments of clinical teaching typically measure hospital learning environments, classroom teaching, teaching competency, or the internship quality of nursing students. As a result, clinical evaluations are often insufficient to provide focused feedback, guide faculty development, or identify specific areas for clinical teachers to implement change and improvement. Therefore, the purpose of our study was to to construct a scientific, systematic, and clinically applicable evaluation index system of clinical nursing practice teaching quality and determine each indicator's weight to provide references for the scientific and objective evaluation of clinical nursing practice teaching quality. METHODS: Based on the "Structure-Process-Outcome" theoretical model, a literature review and Delphi surveys were conducted to establish the evaluation index system of clinical nursing practice teaching quality. Analytic Hierarchy Process (AHP) was employed to determine the weight of each indicator. RESULTS: The effective response rate for the two rounds of expert surveys was 100%. The expert authority coefficients were 0.961 and 0.975, respectively. The coefficient of variation for the indicators at each level ranged from 0 to 0.25 and 0 to 0.21, and the Kendall harmony coefficients were 0.209 and 0.135, respectively, with statistically significant differences (P < 0.001). The final established index system included 3 first-level, 10 second-level, and 29 third-level indicators. According to the weights computed by the AHP, first-level indicators were ranked as "Process quality" (39.81%), "Structure quality" (36.67%), and "Outcome quality" (23.52%). Among the secondary indicators, experts paid the most attention to "Teaching staff" (23.68%), "Implementation of teaching rules and regulations (14.14%), and "Teaching plans" (13.20%). The top three third-level indicators were "Level of teaching staff" (12.62%), "Structure of teaching staff" (11.06%), and "Implementation of the management system for teaching objects" (7.54%). CONCLUSION: The constructed evaluation index system of clinical nursing practice teaching quality is scientific and reliable, with reasonable weight. The managers' focus has shifted from outcome-oriented to process-oriented approaches, and more focus on teaching team construction, teaching regulations implementation, and teaching design is needed to improve clinical teaching quality.

High disease burden and healthcare resource usage in patients with acute porphyria-A population-based analysis.

BACKGROUND AND AIMS: Acute porphyria is a chronic recurrent disease with late diagnosis, heterogeneous clinical presentations and potentially devastating complications. The study aimed at providing real-world evidence on the natural course of acute porphyria, patient characteristics, disease burden, and healthcare utilization before diagnosis. METHODS: This observational study used anonymized claims data covering 8 365 867 persons from German statutory health insurance, spanning 6 years (2015-2020). Patients with at least one diagnosis of acute porphyria during the index period (2019-2020) were classified into three groups by attack frequency. These findings were compared with two age- and sex-adjusted reference groups: the general population and fibromyalgia patients. Prevalence over the index period was calculated for all porphyria patients and those with active acute porphyria. RESULTS: We revealed a prevalence of 79.8 per 1 000 000 for acute porphyria, with 12.9 per 1 000 000 being active cases. Acute porphyria patients, particularly with frequent attacks, demonstrated a higher comorbidity burden compared to the general population. Within the year before the recorded diagnosis, patients with acute porphyria required a median of 23.0 physician visits, significantly higher than the general population's 16.0. Additionally, 33.8% were hospitalized at least once during this period, a notably higher proportion than the general population (19.3%). CONCLUSIONS: This study's findings, collected before the introduction of givosiran, as the first approved preventive therapy for acute porphyria in Europe, highlight the need for healthcare strategies and policies tailored to the complex needs of acute porphyria patients. The significant healthcare demands, heightened comorbidity burden, and increased healthcare system utilization emphasize the urgency of developing a comprehensive support infrastructure for these patients. Also, these acute porphyria real-world findings provide additional insights on disease characteristics in Germany.

Sustainability in the Public Healthcare Sector: Insights From an Analytical Hierarchy Process Analysis.

Background This study aimed to identify sustainability priorities within Oman's healthcare sector using the analytical hierarchy process (AHP) methodology. Mainly, it focused on assessing the relative importance of economic, environmental, and social factors and their sub-elements in sustaining Oman's healthcare system. Methodology A semi-quantitative, cross-sectional design was employed to collect data from 23 Omani healthcare experts with at least 10 years of experience in five different public hospitals in Oman. The AHP methodology was used to analyze pairwise comparisons of sustainability factors and derive their priorities. The consistency ratio was calculated to ensure the reliability of the analysis, and the transitivity rule was applied to address inconsistencies in pairwise comparisons. Results The findings revealed a strong emphasis on environmental and social sustainability, with economic considerations ranking comparatively lower. Circular practices emerged as a key priority within the environmental domain, while patient satisfaction stood out within the social domain. The analysis showed the integration between healthcare, environmental health, and societal well-being, emphasizing the need for holistic approaches to sustainability. Conclusions This study contributes to the understanding of healthcare sustainability by providing empirical evidence of stakeholder preferences within Oman's healthcare system. By quantitatively assessing the relative importance of economic, environmental, and social factors, it informs decision-making and resource allocation toward sustainable healthcare development. The findings also support the argument for integrated approaches to healthcare sustainability that balance economic efficiency with environmental protection and social inclusion.