Data Collection System Research Articles

One faith for different realities: accounting and management practices of Benedictine monasteries

Purpose This paper aims to explore how the accounting and management practices of monastic institutions were shaped by their surrounding social, political, geographical and economic environments, as well as religious ideologies, during critical historical periods. Design/methodology/approach By applying institutional theory and the comparative international accounting history perspective, this study conducts a comparative analysis of archival records from two monasteries, examining how their accounting and managerial practices were influenced by differing institutional logics. The research relies on systematic archival data collection, complemented by secondary sources, to analyze how religious beliefs shaped the accounting and management practices of these institutions and the degree of convergence between the two. Findings This study found that both monasteries adapted their accounting and management practices to their external environments. San Placido demonstrated resilience amidst disruptions such as wars and earthquakes, while Silos showed financial sophistication through diverse income streams. The resilience of these institutions was driven by their ability to align internal operations with external political, economic and social factors. This adaptability, coupled with strategic management, enhanced their capacity to maintain financial stability, illustrating the direct link between external changes, organizational resilience and improved financial health. Research limitations/implications This study highlights the historical interplay between religious principles and accounting management practices in Benedictine monasteries by comparing two monasteries. It reveals how external environments shape internal operations, showcasing the resilience and adaptability of these institutions in maintaining financial sustainability through the alignment of external pressures with internal resilience mechanisms, which in turn bolster their financial health. Originality/value This research contributes valuable insights to historical managerial and accounting literature, shedding light on the financial resilience and strategies used by Benedictine monasteries. It underscores the enduring respectful legacy of their accounting practices and the unique interplay between spiritual devotion and organizational structure within these institutions.

Vaccine-preventable diseases in migrants to Europe: a systematic review

Abstract Migrant populations in Europe are at increased risk of under-immunisation and therefore likely to be at high risk of vaccine-preventable diseases (VPD), yet the relationship between migration and VPD incidence is not fully understood. This study aimed to explore the prevalence of VPDs in migrant populations in Europe and to define at-risk groups. Following PRISMA guidelines, Embase, MEDLINE and Global Health were searched for peer-reviewed papers published from 1st January 2010. Inclusion criteria comprised primary research on VPD cases (measles, mumps, rubella, diphtheria, pertussis, tetanus) among migrants to/within EU/EEA and Switzerland. We defined migrants as foreign-born nationals. Forty-seven eligible studies from 15 EU/EEA countries and Switzerland were included, with a total of 1357 migrant VPD cases reported. Analysis revealed 1357 migrant cases across measles (28 publications; 926 cases), pertussis (9; 267 cases), mumps (9; 107 cases), diphtheria (11; 67 cases), rubella (2; 6 cases imported from Romania and Pakistan), tetanus (2; 2 cases). Over-representation of measles cases was observed among migrant children and adolescents, predominantly from the WHO Europe region (particularly Bulgaria, Bosnia and Herzegovina and Serbia). Migrants of East African origin were over-represented among diphtheria cases. This study underscores the association between migration and VPD cases in EU/EEA and Switzerland, establishing a clear association between European migrant children and adolescents in measles outbreaks, and adult migrants from East Africa in diphtheria cases. This study suggests strengthening systems for targeted catch-up vaccination for migrants is imperative upon arrival in European countries to align them with national schedules, alongside the need to improve data collection and surveillance systems to inform effective public health interventions. Key messages • Migrant populations in Europe face heightened risk of vaccine-preventable diseases and need to be better incorporated into catch-up vaccination initiatives on arrival. • Improved data collection and surveillance systems are crucial for informing effective public health interventions targeting migrant populations.

A comparative analysis of national dementia plans: preventive strategies in five European countries

Abstract Background About 8.5% of people aged +65 live with dementia in Europe. Preventive measures can avert up to 40% of cases. The aim of the study is to analyse National Dementia Plans (NDP) in Europe, to elicit how much dementia prevention is considered a priority and whether policies are evidence-based. Methods A qualitative comparative analysis was performed between NDPs of countries with the best healthy life expectancy in the elderly in Europe. The NDPs of France, Ireland, Italy, Spain, and Sweden were included. The consensus on actions and elements of prevention policies was evaluated, according to the WHO recommendations and to Cheung’s framework designed for evaluating chronic diseases policies. Results All the NDPs prioritised early diagnosis, public awareness, and community engagement for dementia risk reduction. They fostered the development of information system for data collection and established committees for progress monitoring. However, not all NDPs defined timelines for policy implementation and most of them expired years ago. NDPs included prevention research agenda, but their preventive actions did not address alcohol consumption, traumatic brain injury, and air pollution, representing 3 well-known risk factors attributable for the 15% of preventable cases. Neither integration of dementia with other chronic disease preventive strategies was present and a clear allocation of funds for NDPs always missed. Conclusions NDPs partially address risk factors of preventable cases. All countries need to update their NDPs, integrating new scientific evidence and allocating clear financial funds. This can potentially prevent millions of new cases, decreasing the burden of disease and improving the sustainability of health systems. Key messages • NDPs do not target adequately dementia in Europe. • New evidence-based preventive policies, including most recent identified risk factors, would have a clear impact on burden of disease and health systems’ sustainability.

Patient-Reported Indicator Surveys (PaRIS): making the case for co-development and adaptation to national contexts

Abstract In this presentation we discuss the early implementation of the OECD’s Patient-Reported Indicator Surveys (PaRIS) in primary care, highlighting the importance of co-development and national adaptation. The PaRIS initiative focuses on collecting patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) from individuals with chronic conditions and their primary care providers. This data collection is critical as populations age and the prevalence of chronic conditions increases, necessitating health systems that prioritize patient-centered care. The co-development process of the PaRIS survey involved extensive international collaboration, incorporating feedback from policymakers, healthcare providers, patients, and academics, thereby enhancing the relevance and ownership of the project. An example of successful stakeholder engagement is the creation of the PaRIS Patient Advisory Panel, which included representatives from various patient organizations who participated in all stages of the survey’s development. Challenges encountered during pilot implementations varied by country, influenced by factors like existing data infrastructures and regulatory environments. For instance, countries lacking robust data collection systems faced more significant hurdles in adapting the survey to their contexts. The article emphasizes that while rigorous standardization is essential for making international comparisons, adaptation to local contexts is crucial for addressing specific implementation challenges. The joint efforts of all stakeholders are vital for the success of international initiatives like the PaRIS survey. Such collaborative efforts not only facilitate the collection of meaningful data but also contribute to the enhancement of primary care quality through informed policymaking and improved patient care practices.

What to do with your maintenance records for protection layers?

AbstractCollecting and analyzing operation and maintenance data is essential to process safety. The analysis aims to demonstrate that what is installed in the field achieves the required performance so that adjustments can be made if the required performance is not met. Very large organizations routinely have data collection systems and resources for data analysis. Midsized and smaller organizations collect the same data in various ways but often need help to analyze it. This paper presents examples of American Petroleum Institute (API) 754 Tier 3 and 4 metrics related to protection layers and how to use available plant data to support their analysis.

The Influence of Graph Theory Approach in Preventing Cheating at Higher Learning Institution: A case of Institute of Accountancy Arusha

Academic dishonesty has been more common in recent years, both through self-reported and detected cases, which has brought significant attention to the issue of cheating in educational settings. Students often cheat for a variety of reasons, including lack of study time, unclear learning objectives, fear of failing, peer pressure, and parental pressure for academic success. Students who rely on plagiarizing answers miss the opportunity to build their skills and may face challenges in job requirements. The problem of cheating / copying the neighbor's works during the examination is particularly well known. With graph theory especially graph coloring, it is proposed to develop the students' sitting arrangement that can be the solution of cheating. An experimental case study focuses on three master's programs, three bachelor's degree programs, three diploma programs, and three certificate programs at the Institute of Accountancy Arusha. This is done when one room or a venue is assigned to two or more programs with different backgrounds depending on the size of the room. The result shows that using graph coloring has reduced the tendency of students to copy or ask questions from their neighbors in the examination room. Based on the assessment of graph theory's effectiveness in preventing cheating at the Institute of Accountancy Arusha, several recommendations can be made. First, the institution should invest in developing a comprehensive data collection system that captures relevant information such as seating arrangements, student interactions, and exam performance patterns. Collaboration with other institutions in implementing similar technologies could also create a shared knowledge base and lead to best practices in academic integrity. Finally, continuous monitoring and evaluation of this system should be conducted to refine its processes and adapt to new cheating technique.

Measurement-Based Care in a Remote Intensive Outpatient Program: Pilot Implementation Initiative.

The ongoing mental health crisis, especially among youth, has led to a greater demand for intensive treatment at the intermediate level, such as intensive outpatient programs (IOPs). Defining best practices in remote IOPs more broadly is critical to understanding the impact of these offerings for individuals with high-acuity mental health service needs in the outpatient setting. Measurement-based care (MBC), or the routine and systematic collection of patient-reported data throughout the course of care to make meaningful changes to treatment, is one such practice that has been shown to improve patient outcomes in mental health treatment. Despite the literature linking MBC to beneficial clinical outcomes, the adoption of MBC in clinical practice has been slow and inconsistent, and more research is needed around MBC in youth-serving settings. The aim of this paper is to help bridge these gaps, illustrating the implementation of MBC within an organization that provides remote-first, youth-oriented IOP for individuals with high-acuity psychiatric needs. A series of 2 quality improvement pilot studies were conducted with select clinicians and their clients at Charlie Health, a remote IOP program that treats high-acuity teenagers and young adults who present with a range of mental health disorders. Both studies were carefully designed, including thorough preparation and planning, clinician training, feedback collection, and data analysis. Using process evaluation data, MBC deployment was repeatedly refined to enhance the clinical workflow and clinician experience. The survey completion rate was 80.08% (3216/4016) and 86.01% (4218/4904) for study 1 and study 2, respectively. Quantitative clinician feedback showed marked improvement from study 1 to study 2. Rates of successful treatment completion were 22% and 29% higher for MBC pilot clients in study 1 and study 2, respectively. Depression, anxiety, and psychological well-being symptom reduction were statistically significantly greater for MBC pilot clients (P<.05). Our findings support the feasibility and clinician acceptability of a rigorous MBC process in a real-world, youth-serving, remote-first, intermediate care setting. High survey completion data across both studies and improved clinician feedback over time suggest strong clinician buy-in. Client outcomes data suggest MBC is positively correlated with increased treatment completion and symptom reduction. This paper provides practical guidance for MBC implementation in IOPs and can extend to other mental health care settings.

Pobreza Energética en Chorrera Mirador: Implementación y Monitoreo de un Sistema Híbrido Solar-Eólico

This work studies energy poverty in the community of Chorrera Mirador, located in Chimborazo, Ecuador. Energy poverty, defined as the inability to cover basic energy needs such as heating, cooking, and refrigeration, affects rural areas of Latin America. In Ecuador, this problem is exacerbated in rural areas, where more than half of the population suffers from it. The article proposes a methodology to measure energy poverty using the multidimensional energy poverty index (MEPI), which evaluates multiple conditions associated with this problem in households. The results reveal moderate energy poverty in the community, which justifies the implementation of a hybrid solar and wind renewable energy system (SHER) to mitigate it. The SHER was sized based on the daily energy demand and the solar and wind resources available in the area. A data collection system is included to monitor the voltage stability and power production of the system. The results demonstrate the functionality of the system and its ability to satisfy the energy demand of the community. The study concludes that the implementation of the SHER, together with the use of low-consumption lighting elements, contributes to mitigating energy poverty in the Chorrera Mirador community, improving the quality of life of its inhabitants. In addition, the data collection system allows for long-term analysis, which makes it easier to identify possible improvements and strategies to optimize its operation

Statistical Analysis of Frechet Distribution in Step-Up and Step-Down Testse

This study explores the application of the Frechet distribution in step-up and step-down tests, investigating its effectiveness and applicability in extreme value analysis. Through systematic collection and statistical analysis of experimental data, this paper first clarifies the basic concept of the Frechet distribution and the physical significance of its parameters. It then analyzes the design principles of step-up and step-down tests and their data processing methods, focusing on evaluating the performance of the Frechet distribution in describing maximum and minimum value characteristics. The results show that the Frechet distribution can effectively fit experimental data, providing a significant theoretical basis for the evaluation of material and structural performance in engineering. However, the paper also points out the limitations of applying the Frechet distribution and suggests future research directions.

The future of tourism: interview with Bernadett Papp on brining equity into debates on tourism development and destination governance

PurposeAs the Journal of Tourism Futures celebrates its 10th Anniversary, Dr Stefan Hartman (head of department at the European Tourism Futures Institute, NHL Stenden University of Applied Sciences) interviews Bernadett Papp (senior researcher at the European Tourism Futures Institute (ETFI) at NHL Stenden University of Applied Sciences) about her recent work in tourism practice and academic and future perspectives on topics relevant to the future of tourism.Design/methodology/approachA personal interview was held on September 16, 2024.FindingsBernadett Papp draws attention to the importance of bringing equity into debates on tourism development and destination governance. She sees a crucial role for governments, the redesign of institutional frameworks, monitoring and data collection and rethinking systems of governance.Originality/valueThe interview provides unique insights into the viewpoints of Papp, highlighting the importance of the still understudied topic of equitable tourism. A topic that still requires a lot of work before hitting mainstream approaches to destination development, even though it should have been on the policy agendas for many years already.

Analysis and prediction of energy consumption in office buildings with variable refrigerant flow systems: A case study

Accurately predicting building air-conditioning energy consumption is particularly important for energy management. However, for small datasets, there is a lack of simple and effective prediction methods applicable to multiple buildings. In order to fully explore the energy consumption mode of Variable Refrigerant Flow (VRF) air conditioning system and improve the accuracy of the model. This study uses the weather data of an outdoor meteorological data collection system and the air conditioning system and energy consumption data of an office building in Jinan. Initial analysis revealed that occupant behavior and daily variations in outdoor air temperatures significantly impact the energy consumption of air conditioning systems. Then, by applying the random forest algorithm and Pearson correlation analysis, the study identified daily average outdoor air temperature and VRF indoor unit running time as critical features for prediction. Subsequently, three machine learning models—Multiple Linear Regression (MLR), Back Propagation Neural Network (BPNN), and Long Short-Term Memory (LSTM) neural network—were developed and assessed using a 4:1 training-to-testing set ratio. Comparative analysis revealed that all models performed robustly, with the MLR model exhibited superior predictive accuracy (R2 (Coefficient of Determination) = 0.98, MAE (Mean Absolute Error) = 0.005 kWh/(m2·day), and RMSE (Root Mean Square Error) = 0.007 kWh/(m2·day) for the testing set) and simplicity. Furthermore, the effectiveness of the MLR model in handling small sample sizes was confirmed through cross-validation of data from two additional office buildings, highlighting its suitability for predicting energy consumption of VRF air conditioning systems in office buildings.

Identifying and quantifying exposures involving counterfeit opioid analgesic products

Introduction The increasing presence of counterfeit opioid drugs in the United States can contaminate data collection systems and confound estimates derived from surveillance of the opioid epidemic. Data sources and analyses that can quantify the contribution of counterfeit opioid products are needed to provide accurate and timely data to inform public health responses. We describe a novel approach to identify and quantify intentional abuse and misuse exposures involving suspected counterfeit opioid products in United States poison center data. Methods An ecological study was performed using data, including narrative case notes, reported to participating United States Poison Centers of the Researched Abuse, Diversion and Addiction Related Surveillance System between 2009-Quarter 1 and 2021-Quarter 4. A machine learning natural language processing approach was used to develop a predictive model. Results Sensitivity for detecting suspected non-counterfeit-involved exposures by the predictive model was 92%, specificity was 73%, and the area under the receiver operating characteristic curve was 92%. Overall, only 2.1% of intentional abuse and misuse exposure calls were predicted to be suspected counterfeit-involved during 2009–2021; however, we observed an exponential increase in suspected counterfeit exposures over this time period. There was a 7-fold increase in the estimated number of suspected counterfeit exposures from 2009 to 2021, and 23.7% of all opioid analgesic intentional abuse and misuse exposures were suspected counterfeit-involved in 2021. Discussion We demonstrate the feasibility and reliability of using machine learning natural language processing to identify exposures involving suspected counterfeit opioid products in United States poison center data. Results suggest that suspected counterfeits have had a meaningful influence on rates of intentional abuse exposures to opioid analgesics in more recent years. Conclusions The increasing presence of counterfeit opioid drugs can contaminate data collection systems and compromise the reliability of the data.

HeritageRoots: Developing Interconnected Immersive Experiences for Cultural Preservation and Education

In this paper, we present technical implementation details, describe the virtual world procedural generation pipeline, and discuss potential uses in cultural preservation, museum exhibits, and education of HeritageRoots, an innovative software infrastructure designed for preserving indigenous narratives and oral histories. HeritageRoots consists of two interconnected systems - (1) a web-based knowledge graph (KG) data collection and management system which stores, connects, and presents indigenous traditional knowledge (ITK) in the form of narratives, myths, and testimonies from multiple cultures and languages; (2) a virtual environment rendering pipeline which utilizes large language models (LLM), Unity3D, and Meta Quest software development kit (SDK) to procedurally generate virtual worlds from the KG data. Preliminary system evaluation with Ecuadorian Kichwa narratives showed promising results in (1) academic community interest and support, (2) the possibility of developing an infrastructure capable of connecting indigenous narratives with modern scientific knowledge via KGs and (3) procedurally generating virtual worlds from KG.

Toward a public outreach and community engagement strategy on cancer in Newfoundland and Labrador: an initial road map and recommendations

Abstract Background: The province of Newfoundland and Labrador has one of the highest incidence and mortality rates for cancer among the Canadian provinces. Sharing accessible knowledge on cancer is an important part of cancer control and population health efforts. However, bringing useful health information and knowledge exchange events to residents requires an efficient and accessible system. Objectives: We aimed to create a road map and recommendations for effective public outreach and community engagement on cancer in Newfoundland and Labrador. Methods: We used the following information, experience, or public engagement tools to gather information to inform our work: discussions with the members of the Public Interest Group on Cancer Research, researchers' experiences with recruitment and knowledge translation activities, feedback provided to 2 public conferences delivered (Public Conference on Genetics delivered in 2020 and Public Conference on Cancer delivered in 2022—where the target audience was general public), and 2 public town halls (one in-person, one virtual) and 2 individual consultation sessions with key stakeholders. Information gathered was then summarized. Results: We identified a rich set of cancer-related topics for which to organize public events on cancer. In addition, a large number of public outreach and engagement options were identified, emphasizing the fragmented, inefficient, and resource-intensive nature of public outreach and community engagement efforts in the province. Based on the information collected, we developed an initial road map and recommendations to inform future public engagement activities and strategies. In addition, our group has started to implement the road map for our current and future public engagement activities. Conclusions: We present key cancer-related topics that are of public interest and issues and opportunities for recruitment and delivery of knowledge and events to residents of Newfoundland and Labrador. This information can be useful for researchers, organizations, and the health care system in the province. However, more inclusive consultations, larger collaborations, funding, and systematic data collection are needed to build a province-wide public outreach network on cancer and to identify more comprehensive public engagement options. The work presented here can potentially guide these efforts. Our work is also expected to inspire other provinces, states, and communities to assess their public outreach status and help develop road maps co-led by patients to progress their public engagement efforts in cancer.

International Validation of the Vascular Registry of Switzerland, Swissvasc: A VASCUNET Report

Data validity and completeness is essential for registry data, and a meaningful interpretation of differences between countries can only be made if the data are robust within each of the countries. Therefore, the VASCUNET collaboration has performed validation of several vascular registries and has so far published the validation results of national vascular registries of Sweden, Denmark, and Malta. The findings of the validation of the Swissvasc Registry, the vascular registry of Switzerland, are presented here. Five of 34 hospitals participating in Swissvasc were visited by two international validators. Independent evaluation of the procedures of carotid endarterectomy, infrarenal abdominal aortic aneurysm (AAA) repair, and bypass surgery for lower extremity arterial disease (LEAD) was performed. Local administrative data and Swissvasc Registry data were compared for external validation, as well as registry data of 15 randomly picked cases within each group with data from individual patient records for internal validation. Hospital administrative data identified 265 carotid, 399 AAA, and 399 LEAD procedures, whereas Swissvasc identified 265 carotid, 398 AAA, and 395 LEAD procedures. Four LEAD procedures were found in hospital administrative data but not in Swissvasc. External validity was 100% for carotids, 99.8% for AAA, and 99% for LEAD. In internal validation, 5.2% of the variable data were missing in Swissvasc, and 2.4% were different from data in patient records, resulting in external validity of 92.8% for carotids, 94.4% for AAA, and 90.1% for LEAD. The VASCUNET template was used for international validation of registry data, and demonstrated that Swissvasc is a reliable system of quality data collection for the participating vascular centres, with excellent external validity and good internal validity. Quality in the Swissvasc registry data was clearly superior to local administrative data.

Empowering decentralized production: A distributed manufacturing system for additive manufacturing processes

This work presents a pilot distributed manufacturing system for decentralized additive manufacturing, focusing on the Interdisciplinary Center for Advanced Manufacturing Systems (ICAMS) capabilities at Auburn University. The paper outlines the first phase of a multi-phase implementation plan and demonstrates the developed capabilities. The vision is to coordinate geographically separated manufacturing facilities as a cohesive unit. In our work, we prioritize instantaneous communication for file and information sharing. The Manufacturing Hub and Remote Cell, two facilities within driving distance, are coordinated in terms of part design, printing, and inspection procedures for a distributed Additive Manufacturing process. To enable coordination between the two facilities, ICAMS addresses three technological needs. These needs consider information sharing, process standardization, and data collection and monitoring. A network attached storage facilitates information sharing, a database-connected graphical user interface streamlines and standardizes the manufacturing process, and a data collection system facilitates process monitoring. The graphical user interface allows for order placement, progress monitoring, and communication updates. The developed phased plan, collaborative workflow, technological solutions, and production protocols demonstrate the potential for decentralized additive manufacturing. Successful integration of communication, design, printing, and quality assurance processes sets the foundation for future advancements in decentralized manufacturing systems.

Federated deep reinforcement learning based trajectory design for UAV-assisted networks with mobile ground devices

Exploiting highly maneuverable unmanned aerial vehicles (UAVs) has been considered as an efficient way to assist wireless systems, e.g., for applications of data collection. However, several challenges remain to be addressed in the design of such UAV-assisted networks, including multi-UAV joint trajectory determination, data privacy protection, and adaption to the complex channel environment particularly with mobile ground devices (GDs). In this paper, we study a multi-UAV assisted data collection system where UAVs collect data locally from mobile GDs. The aim is to minimize the whole operation time cost via jointly optimizing the UAVs’ three-dimensional (3D) trajectory together with the GDs’ communication scheduling, while satisfying the constraints of no-fly zones (NFZs) and collision avoidance. With a nonconvex feasible set (due to the NFZs), the established problem is nonconvex. Moreover, the randomness of GDs movements significantly reduces the performance of a typical redesign, i.e., determining the UAVs’ trajectory and users’ scheduling before starting the data collection task. To tackle these issues, we first transform the established problem into a Markov decision one, and then propose a multi-agent federated reinforcement learning (MAFRL)-based approach to optimize the dynamic long-term objective via jointly determining UAVs’ 3D trajectory and GD’s communication scheduling. A multi-step propagation technique and a dueling network architecture are adopted to enhance the neural network utilized to train agents, i.e., to accelerate the convergence rate of the proposed method and improve its overall stability. Finally, experimental results reveal the effectiveness of our proposed method in the considered practical scenario.

The Quality Improvement Review Board: An Innovative Approach to Oversight of Projects That Do Not Meet Criteria of Human Subject Research.

This article describes the development of an institutional quality improvement review board (QIRB) as an effective and efficient method for reviewing and overseeing institutional quality improvement (QI) initiatives. QI projects involve the systematic collection and analysis of data and the implementation of interventions designed to improve the quality of clinical care and/or educational programs for a distinct population in a specific setting. QI projects are fundamentally distinct from human subjects research (HuSR); however, the differences between them are subtle and highly nuanced. Determining whether a project meets the definition of QI or qualifies as HuSR, thus requiring institutional review board (IRB) review, can be confusing and frustrating. Nevertheless, this distinction is highly consequential due to the heavy regulatory requirements involved in HuSR and IRB oversight. Making the correct determination of a project's regulatory status is essential before the project begins. Project leaders may not realize that their work meets the definition of HuSR and, therefore, might conduct the project without appropriate IRB review. Therefore, best practices dictate that project leaders should not decide which type of institutional review is appropriate for their projects. In addition, when QI project teams attempt to disseminate the results of their work, documentation of formal review and approval is generally required by peer-reviewed journals and professional organizations. However, institutional review mechanisms are rarely available. Projects that do not meet the definition of HuSR fall outside the purview of IRBs and most institutions do not have an alternative review body. This creates frustration for both project leaders and IRB administrators. Apart from IRB review, a separate process for reviewing QI projects offers several benefits. These include (1) relieving the burden on busy IRB staff; (2) promoting scholarly activity; (3) protecting the institution, project leaders, and participants from HuSR conducted outside of appropriate IRB review; and (4) promoting rigorous QI methods.

REVIEW: INSTRUMEN KUESIONER PADA PASIEN DIABETES MELITUS

Diabetes mellitus (DM) is a chronic disease with increasing prevalence worldwide, posing major challenges in patient management and monitoring. Questionnaire instruments are an important tool in DM patient evaluation because they allow systematic and measurable data collection regarding various aspects of the disease, including quality of life, self-management, and perceptions of care. This review article provides a comprehensive overview of various questionnaire instruments used for DM patient evaluation, interpretation of questionnaire results, and grouping based on categories. The review results indicate that the selection of an appropriate instrument must take into account the specific context of the patient population and the evaluation goals. Additionally, we group the evaluation instruments into several categories, including the patient's level of knowledge, compliance with treatment, severity of symptoms, fear of needles, mental condition, and improvement in the patient's quality of life. The conclusion of this article emphasizes the importance of questionnaires in DM management, as well as the need for further research to develop more comprehensive and responsive instruments. Questionnaire instruments, when selected and used appropriately, can improve clinical decision-making and the quality of care provided to DM patients.

Information System for Data Collection on Building Tools and Materials Using the Rational Unified Process (RUP) Method

UD. FLORA records the re-inventory of building equipment that has been sold by reading the transactions one by one in the ledger. A proper way is needed to overcome the problems that occur. This research aims to create an information system software. In making information system software, a method is needed that can carry out the stages from initial design to implementation of the software. This research uses the Rational Unified Process (RUP) method, namely a software development approach that is carried out repeatedly (iterative), focuses on architecture (architecture-centered), is more directed based on use cases (use case driven). This research produces a tool data collection application at UD. FLORA using the RUP method. The existence of an information system for data collection on building equipment using the Rational Unified Process method means that UD. FLORA can be helped in managing building equipment data collection. The system enables real-time transaction recording, providing better insight into inventory status, and supporting more accurate decision-making.