Hospital Management System Research Articles

Public Hospital Workers' Views on the Process of Switching from the Hospital Information Management System to the e-Health Information System in a Province

The purpose of this study is to investigate the views, reasons for satisfaction, and difficulties encountered by medical staff members regarding the Hospital Information Management System (HIMS) in state hospitals located in Amasya and its surrounding areas. It also assesses the knowledge and experiences of healthcare professionals with e-Health apps in public hospitals, emphasizing their opinions and recommendations for assistance, training, adaptation, and involvement throughout the integration of these applications into healthcare services. The goal of the study is to better understand how healthcare professionals feel about digital technologies and to provide suggestions for raising the caliber of healthcare services. The Amasya Provincial Health Directorate oversees four facilities where the research was carried out. Following permission by the ethics committee, data gathering was underway on April 22, 2024, with a pilot research carried out in April of the same year. There are 913 healthcare workers in the population, and a minimum sample size of 405 at a 95% confidence interval was found to be appropriate. Using the'stratified, simple random' approach, the sample was selected and split into three strata based on occupational groupings. With a median age of 37, 38.8% of the 405 participants were female. 34.2% of physicians, 33.7% of midwives, nurses, and health officers, and 40.4% of medical secretaries and data entry staff expressed satisfaction when HIMS satisfaction was analyzed. The system's capacity to decrease errors and enhance workflow was one of the primary factors contributing to user satisfaction. Furthermore, 42.7% of individuals worked nights. Compared to other professional groups, physicians utilized e-health applications like e-prescription and e-report more frequently. Physicians were more likely to employ telemedicine than other healthcare professionals, who were less knowledgeable in this field. The study recommends developing training methodologies specific to various professional groups and expanding the use of e-Health applications. The study highlights the need for regular in-service training, a more robust technical infrastructure, and user-friendly interfaces to boost healthcare personnel' satisfaction with e-Health. In summary, this study offers important information for strengthening e-Health and HIMS applications and presents important suggestions for raising the caliber of healthcare services through digital transformation.

Data-driven explainable machine learning for personalized risk classification of myasthenic crisis

ObjectiveMyasthenic crisis (MC) is a critical progression of Myasthenia gravis (MG), requiring intensive care treatment and invasive therapies. Classifying patients at high-risk for MC facilitates treatment decisions such as changes in medication or the need for mechanical ventilation and helps prevent disease progression by decreasing treatment-induced stress on the patient. Here, we investigated whether it is possible to reliably classify MG patients into groups at low or high risk of MC based entirely on routine medical data using explainable machine learning (ML). MethodsIn this single-center pseudo-prospective cohort study, we investigated the precision of ML models trained with real-world routine clinical data to identify MG patients at risk for MC, and identified explainable distinctive features for the groups. 51 MG patients, including 13 MC, were used for model training based on real-world clinical data available from the hospital management system. Patients were classified to high or low risk for MC using Lasso regression or random forest ML models. ResultsThe mean cross-validated AUC classifying MG patients as high or low risk for MC based on simple or compound features derived from real-world clinical data showed a predictive accuracy of 68.8% for a regularized Lasso regression and 76.5% for a random forest model. Studying feature importance across 5100 model runs identified explainable features to distinguish MG patients at high or low risk for MC. Feature importance scores suggested that multimorbidity may play a role in risk classification. ConclusionThis study establishes feasibility and proof-of-concept for risk classification of MC based on real-world routine clinical data using ML with explainable features and variance control at the point of care. Future research on ML-based prediction of MC should include multi-center, multinational data collection, more in-depth data per patient, more patients, and an attention-based ML model to include free-text.

Integration of a dose management system in the public hospitals of Cyprus: Key areas and initial outcomes.

Despite the growing use of dose management systems (DMSs), there is limited guidance on their optimal setup. This study aims to fill this gap by outlining the process followed to integrate "DOSE" (Qaelum NV, Belgium) DMS within the Cypriot public hospitals. DOSE was connected to the available central PACS, followed by a thorough data and functioning validation. A preliminary study was also conducted to assess the DOSE's ability to establish typical dose values in diagnostic radiography. Overall, over 70 x-ray units were configured. For some connections, it was necessary to first adjust the unit's DICOM attributes or to utilise the DICOM coercion technique. The DICOM image header was sometimes preferred over the DICOM RDSR, as the chosen data source. This study underscored the importance of understanding the equipment's technical capabilities for a successful DMS integration, while personnel with expertise in diagnostic radiology and the IT aspects of medical physics proved to have a vital role in the process. The pilot study showed that DOSE is an effective tool for establishing typical dose values and assessing compliance with relevant dose levels.

Performance -based management system in hospital emergency

Background: Given the emphasis on evidence -based management in recent years and one of the new management methods is performance -based management, the purpose of this study was to establish an initial performance -based management system in the emergency department of Nikan Hospital in Tehran. Methods: Establishment of a science -based management system in the Nikan Hospital Emergency System includes six steps: 1) Determining the mission and goals of the organization, 2) Integrated Performance Assessment System 3) Response to Function, 4) Collection of Performance Data, 5) Data analysis, analysis, and performance data, 6) use of performance information to improve the organization. Results: Delays in the provision of bars, photography, experiments and specialized consultations in the crowded hours of emergency (20 to 24). The satisfaction of the patients was less than the service during emergency background (14 to 20). 70% of the patients declared recovery and about 70% announced that they would go to the hospital next time. Conclusion: Implementation of performance -based management system in the country's hospitals that lack the necessary infrastructure should pay many attentions and time and energy in this regard.

The level of attitude of managers and employees towards the goals and concepts of comprehensive quality law management system in hospitals

Comprehensive quality management should be considered as a management system that ensures the correct and continuous execution of work at all levels of the hospitals. This system is a direct way to sustain progress and a coherent and comprehensive effort that is used to continuously improve all aspects of a hospitals activities to achieve competitive advantages. The emphasis of the comprehensive quality management system is on increasing the satisfaction of customers or consumers through the management of methods. This system thinks about the continuous improvement of the hospitals activities through individual managers and employees, and finally the effort to improve the performance of all hospitals levels. raises This research is based on the purpose of an applied research from the point of view of the descriptive correlation method. The studies that have been done so far have presented methods and tools of comprehensive quality management to evaluate and implement this system in both industrial and commercial hospitals. are These studies identified dimensions and factors of comprehensive quality management for its evaluation and study. These tools help both researchers and managers to implement comprehensive quality management in the hospitals.

Assessment of Smartness Status in Public Hospitals and Its Relationship with Characteristics and Performance Indicators

Background: The need for smartification is increasingly recognized in public hospitals, making it crucial to identify the current status, gaps, and factors influencing hospital smartness. Objectives: This study aimed to assess the smartness status of public hospitals and investigate its correlation with hospital characteristics and performance indicators. Methods: This descriptive-analytical cross-sectional study was conducted in seven public hospitals in Alborz Province, Iran, during 2023 - 2024. We assessed the characteristics and performance indicators of the hospitals using a researcher-developed questionnaire and evaluated their smartness status with the standardized "Smart Hospital Evaluation" checklist. Data analysis was performed using SPSS24 software, utilizing independent t-tests, Pearson's correlation, Spearman's correlation, and analysis of variance (ANOVA) tests. Results: The smartness status of the hospitals was found to be moderate, with 71% of hospitals falling into this category. A significant correlation was observed between the smartness of hospital units, the type of hospital (teaching or non-teaching), and the hospital's specialization (specialized or general) (P = 0.013). Significant and direct correlations were also found between information technology and hospital units (P = 0.043), management systems and clinical processes (P = 0.008), and overall smartness and clinical processes (P = 0.049). Conclusions: Public hospitals need improvements in smartness indicators. Factors such as whether the hospital is teaching or non-teaching and whether it is specialized or general should be taken into account. Moreover, hospital smartification efforts should adopt a comprehensive approach, considering all dimensions of smartness.

Characteristics and Trends of Workplace Violence towards Frontline Health Workers under Comprehensive Interventions in a Chinese Infectious Disease Hospital.

This study investigated workplace violence (WPV) toward frontline health workers under comprehensive interventions to improve the occupational safety and health management system in a Chinese infectious disease hospital. The risk assessment of WPV using an international questionnaire was conducted in 2018 and 2021 to compare the perceived levels of exposure to WPV and intervention measures before and after the intensification of anti-violence measures in the hospital context. Additionally, qualitative data were collected in 2021 through semi-structured and unstructured interviews, providing complementary information about WPV toward frontline health workers (HWs). After establishing the occupational safety and health management system (OSHMS), the total incidence rate of WPV decreased from 60.90% in 2018 to 34.44% in 2021. Psychological violence declined significantly from 60.90% in 2018 to 33.89% in 2021. The endorsement of precautionary measures increased significantly from 2018 to 2021, including patient screening recognition, patient protocol, shift or rota changes, etc. A thematic analysis of several subthemes shows that HWs had an in-depth understanding of WPV, recognizing its multifaceted consequences in the context of complex risk factors. This study demonstrates a significant decrease in WPV, psychological violence, verbal abuse, bullying/mobbing, and ethnic discrimination after implementing the comprehensive OSHMS.

A nomogram model for early recurrence of HBV-related hepatocellular carcinomas after radical hepatectomy.

To identify the risk factors and construct a predictive model for early recurrence of hepatitis B virus(HBV-)- related hepatocellular carcinomas(HCCs) after radical resection. A total of 465 HBV-related HCC patients underwent radical resections between January 1, 2012 and August 31, 2018.Their data were collected through the inpatient information management system of the First Affiliated Hospital of University of Science and Technology of China. Survival and subgroup analyses of early recurrence among male and female patients were performed using Kaplan-Meier curves. The independent risk factors associated with early postoperative tumor recurrence were analyzed using multivariate Cox proportional hazards regression model. Based on these independent risk factors, a risk function model for early recurrence was fitted, and a column chart for the prediction model was drawn for internal and external validation. A total of 181 patients developed early recurrences, including 156 males and 25 females. There was no difference in the early recurrence rates between males and females. Tumor diameters>5cm, microvascular invasion and albumin level<35 g/L were independent risk factors for early recurrence. A nomogram for the early recurrence prediction model was drawn; the areas under the curve for the model and for external verification were 0.638 and 0.655, respectively. Tumor diameter>5 cm, microvascular invasion, and albumin level<35 g/L were independent risk factors for early recurrence. The prediction model based on three clinical indicators could predict early recurrence, with good discrimination, calibration, and extrapolation.

ASSESSING HEALTHCARE PROVIDERS’ ACCEPTANCE OF THE HOSPITAL MANAGEMENT SYSTEM IN A PRIVATE HOSPITAL IN SELANGOR, MALAYSIA

Introduction: In the current technological era, the implementation and use of information and communication technology are crucial for productivity and organizational management in the health sector. This study aimed to investigate factors influencing staff acceptance of the Hospital Management System (HMS) using the Unified Theory of Acceptance and Use of Technology (UTAUT) in a private hospital in Selangor, Malaysia. Methods: Semi-structured interviews were conducted with 25 healthcare professionals, including doctors, nurses, and administrative staff, to explore their experiences and perceptions of the HMS. Data collection was performed through interviews and observations and analyzed using thematic analysis with ATLAS.ti. Results: The study identified five key themes influencing HMS acceptance: performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioral intention. Participants emphasized the importance of system reliability, speed, and user-friendly interfaces for efficient workflow. Peer support and a technology-promoting organizational culture positively influenced system use. Comprehensive training and continuous technical support were crucial for user confidence. Despite recognizing the system's benefits, participants highlighted challenges such as inadequate system integration and the need for simultaneous digital and traditional record-keeping. Conclusion: Addressing these issues and tailoring the HMS to meet specific departmental needs can enhance user satisfaction and system effectiveness. The study underscores the importance of understanding user needs and providing robust support systems to facilitate the successful implementation and adoption of HMS in healthcare settings.

Intelligent generation method of infection risk map and management system in hospital waiting room for respiratory infectious diseases

Respiratory infectious diseases, such as seasonal influenza, pose significant risks to public health safety through airborne transmission. This study aims to explore methods for controlling airborne infection risk in waiting rooms, a hotspot for cross-infection. A database of 990 samples was established by integrating the results of computational fluid dynamics and social force model simulations into the Wells-Riley equation. We introduced two indicators, Pr (Particle Removal Efficiency) and Hr (High-risk Area Ratio), to evaluate the cleanliness performance of waiting room spaces. Additionally, the Sci (Space Cleanliness Index) was proposed as a criterion for evaluating architectural designs and fine-tuning fresh air system operational parameters. We also unveiled the mapping relationship between spatial morphology parameters and ventilation design parameters in relation to the cleanliness performance of waiting rooms. An infection-risk prediction proxy model was established based on machine learning methods, suitable for rapid prediction of spatial infection risks in waiting rooms and optimization of fresh air system operational parameters. The findings can be applied to the selection of hospital design schemes and the optimization of ventilation operational control strategies, aiding in strengthening infectious disease control and reducing the public health safety risks of cross-infection from respiratory infections during peak seasons in hospitals.

Dynamical behaviour and meta heuristic optimization of a hospital management software system

The growing demand for easily available healthcare in recent years has fuelled the digitization of healthcare services. The Hospital Management System (HMS) software stands out as a comprehensive solution among the software systems and tools that hospitals and clinics are developing in tandem with this trend. In order to effectively manage many facets of hospital operations, in this paper, we propose an approach for investigating software of this kind. Thus, we characterise the HMS software as a unique sort of batch arrival retrial queueing system (QS) that can handle both ordinary and priority patient demands. Furthermore, it permits patient resistance (balk) and departure (renege) in specific circumstances. The proposed model is additionally deployed within the framework of Bernoulli working vacation. The supplementary variable technique (SVT) has been utilised to obtain the necessary results. ANFIS, a soft computing tool, is used to validate the analytical results as well. Finally, this study seeks to enhance the cost-effectiveness of software creation by employing four unique optimization methods, aiming to achieve optimal efficiency in resource utilization.

Literature Review: Development of Electronic Medical Records In Hospital Management Information Systems

Introduction: Health technology today is developing very quickly from the initially conventional using paper to being computerized. This literature review aims to map and critically summarize the scientific evidence on the cost-effectiveness and acceptability of Computerized Physician Order Entry (CPOE) and Electronic Health Reports. This Journal have Question that need to be answered how does the development of CPOE in medical records affect cost-effectiveness improvement so that it can be accepted by many parties? Method used in this journal is literature review is conducted on journal articles related to costs and receipts in CPOE. The systematic search was conducted from 5 databases namely PubMed, Science Direct, ProQuest, DOAJ and Ebscohost. Journal articles are selected and selected following PRISMA guidelines. Twenty-five journal articles qualified based on predetermined criteria. At the end as result, Cost-effectiveness with CPOE is more likely to be found that it is easier to reach compared to conventional methods. In addition, the acceptance of patients and health workers is also high. These factors can have a positive or negative influence on the hospital management system because developing countries still need adequate resources so that they can run these methods. Discussion and conclusion CPOE systems can improve patient safety by detecting drug interactions and actions. It is necessary to develop medical records in order to provide effective financing and acceptance.

Analysis of The Implementation of The Occupational Safety and Health Management System at Bhayangkara Kendari Hospital

Background: The occupational safety and health management system is part of the overall management system in the context of controlling work-related risks in order to create a safe, efficient and productive workplace. The aim of this research is to analyze the implementation of the occupational safety and health management system in hospitals. According to the management report of the Occupational Safety and Health committee at Bhayangkara Kendari Hospital in 2023, it was stated that the hospital had not carried out occupational risk management as part of the hospital’s occupational safety and health planning. Method: This research is a qualitative descriptive research method. There were 11 informants in the research. The sampling technique used was purposive sampling. Results: The results of the research show that Bhayangkara Kendari Hospital has implemented an Occupational Safety and Health Policy and Occupational Safety and Health risk management planning, but the results obtained in the Implementation of Occupational Safety and Health, Monitoring and Evaluation in the Hospital’s Occupational Safety and Health program do not meet standards. Optimal Occupational Safety and Health. Conclusion: Bhayangkara Kendari Hospital has implemented the Hospital Occupational Safety and Health policy in accordance with Minister of Health Regulation No. 66 of 2016 with a commitment to implementing Occupational Safety and Health, but is hampered by the unavailability of special health services. There are still health workers who provide health services without using personal protective equipment, and there are still those who violate the KTR and there are no monthly and annual evaluation reports on Hospital Occupational Safety and Health. This research can be used as reference material for hospitals to optimally implement Hospital Occupational Safety and Health to increase the knowledge of health workers in implementing occupational safety and health by familiarizing themselves with occupational safety and health cultural behavior.

Smart Hospital Management System: Streamlining Healthcare Operations with SQL Integration

This research delves into the development and deployment of a Smart Hospital Management System (HMS), a pivotal solution for enhancing administrative efficiency and elevating patient care standards within healthcare institutions. Motivated by the pressing need to optimize hospital operations, the system seamlessly integrates modules encompassing patient registration, appointment scheduling, medical records management, billing, and inventory control. Leveraging modern technologies, particularly database management systems and web-based platforms, the HMS aims to bolster the efficiency, accuracy, and accessibility of healthcare services while prioritizing data security and regulatory compliance. The study scrutinizes the benefits and challenges associated with HMS adoption, shedding light on its potential impact on healthcare delivery and organizational performance. Furthermore, it underscores the contributions of this work to the research community, delineates future avenues for exploration, and offers insights into the promising prospects of smart healthcare systems.

Blood Bank Inventory Control

Abstract: "Rakt Sewa" be advanced blood bank inventory portal having been designated for optimizing and streamlining the management of blood within hospitals and blood banks. This innovative system provide real-time tracking!! and reporting capabilities, enabling healthcare professionals to efficiently monitor availability and the usage of different blood groups. The portal facilitate instant access to vital inventory data, assist medical staff in making informed decisions quicklie, particularly in emergency situations where time is of an essence. The core function of "Rakt Sewa" include automated inventory updates, expiry tracking, and integration with hospital management systems to ensure data accuracy and reduce manual entry errors. It also feature customizable alerts for low stock levels and expiring units!!!!, aiding in maintaining optimal stock levels and minimizing waste. Moreover, "Rakt Sewa" support detailed reporting and analytics tools that offer insights into usage patterns, demand forecasting, and supply chain management, allowing for better planning and resource allocation.

IoT Based Hospital Management

Nowadays, Internet of Things (IoT) is invading almost all sectors of life since it is based on connecting living or non-living things together through computer technology. It is responsible for connecting physical objects together through the internet. Healthcare and hospitals are one of the most important sectors that require a lot of attention to transfer their old form of documentation into SMART management systems. It is essential to analyze health data in order to increase the quality of patient’s care. Egypt being a development country is starting to substitute its old governmental systems into electronic SMART technology. IoT devices produce different types of data and transfer them to the cloud computing for storage and analysis. The benefits of using IoT in collecting, transferring, and analyzing patients’ data for the hospitals are attracting a lot of researchers. Therefore, the arrangement of smarter and more money saving healthcare services are becoming highly required. Security and privacy, device communication, and data collection and management are some of the challenges that face the IoT technology especially when used with hospital’s data. Accordingly, a proposed reference model for making SMART hospital management system is under construction in order to achieve the best performance. The model is taking into consideration both the functional and non-functional requirements of the different participants involved in the hospital management system

Protecting the patient’s data in the 21st century healthcare industry: Is the African continent ready for the digital space?

To ensure proper healthcare services and automation, including minimising medical errors and providing faster and more efficient healthcare, the medical field is experiencing innovative technological trends. They include automated patient records, hospital management system software, telemedicine, and the use of artificial intelligence devices. These innovations exist in more than just the global north, as they are slowly finding residence in African countries. Focusing on automated patient record, the article examines existing data protection legal frameworks in Africa to ascertain whether they provide effective remedy mechanisms patients can access should a breach occur. Taking cognisance of the current African Continental Free Trade Area Agreement (AfCFTA) aimed at creating a single market for goods and services; it is evident that healthcare services might have a continental approach. Thus, the article adopts a continental, regional, and national perspective. Using doctrinal method, the article compares the African Union Data Protection Convention with the European Union General Data Protection Regulation to draw lessons from the European Union Experience. The article finds that strengthened national mechanisms might provide the requisite remedy mechanisms patients can access to ensure enforcement of their rights to data protection.

The Establishment of an Emergency Management and Epidemiological Surveillance System in Hospital to Combat Pertussis

The Establishment of an Emergency Management and Epidemiological Surveillance System in Hospital to Combat Pertussis

HOSPITAL MANAGEMENT SYSTEM BASED ON WEB

Hospital Management Systems (HMS) represent a key advancement in healthcare technology designed to revolutionize operational efficiency, raise standards of patient care and ensure compliance with regulatory protocols. This paper explores the multifaceted functions of HMS, highlighting its role in automating administrative tasks, supporting real-time access to patient data, and facilitating seamless communication between healthcare professionals. Drawing on current research and practical implementations, we delve into the transformative potential of HMS, particularly in the context of recent innovations in telemedicine, data analytics, and remote monitoring systems. In our research, we present SIMRS, a robust hospital management information system developed using the waterfall method, strategically focused on the systematic improvement of hospital operations. By automating key processes such as patient registration, appointment scheduling, payment and inventory management, SIMRS optimizes hospital workflows and ultimately improves patient care delivery. In addition, we examine the empirical evidence that shows the significant impact of management systems and leadership traits on the quality of care in hospital settings, and highlight the indispensable role of effective leadership and management frameworks. Next, we discuss the technical foundations of HMS and highlight the integration of various programming languages and database management systems such as HTML, CSS, JavaScript, PHP, MySQL, and MongoDB. This cross-disciplinary approach underscores the synergy between technological innovation and healthcare management, paving the way for a more efficient patient- centered healthcare ecosystem. In summary, this research illuminates the transformative potential of HMS to revolutionize healthcare operations, improve patient outcomes and optimize resource allocation, advocating for its widespread adoption to shape the future of healthcare delivery. Key Words: JavaScript, MySql, HMS, Electronic Health Records, Telehealth

ADVANCED HOSPITAL MANAGEMENT SYSTEM

The Advanced Hospital Management System (AHMS) is a comprehensive program solution that coordinating different functionalities significant for effective hospital management. It includes modules for patient enrollment, appointment planning, electronic health records (EHR), charging and invoicing, stock administration, and detailing. One of the key highlights of AHMS is its interoperability, permitting consistent communication and data exchange between diverse departments inside the hospital as well as with outside partners such as laboratories, pharmacies, and insurance companies. This interoperability guarantees real-time access to patient data, encouraging convenient decision-making and progressing overall care coordination. Key Words: Django, Html, CSS, SQLite3.