Hospital Management Based on Data Mining

The benefits of information system users are an important topic in research on information system implementation in general as well as in hospital information systems in particular. The study is applying structural equation modelling in determining the factors affecting personal benefits of information system users, with the antecedents being the combination of perspectives, and the outcomes including individual user results of the system in hospitals. The study was conducted in two phases: a preliminary study and a formal study. The preliminary study aimed to adjust and supplement the observed variables to be suitable for the actual conditions in Vietnam by conducting a preliminary survey with a questionnaire involving 55 samples to assess the internal consistency reliability, convergent validity, and discriminant validity of the measurement scales. The formal quantitative study, which employed linear structural analysis with PLS-SEM, was conducted on 215 samples of individuals who had previously used information systems in several hospitals in Vietnam. The proposed model explained 80.6% of the variance in user engagement with the system and 50.6% of the variance in user satisfaction when using the information system. In more detail, for user benefits, it is worth noting that the strongest impact intensity belongs to information quality and the weakest belongs to support structure. In addition, confidence in one’s own abilities also has a high impact on user benefits when using the information system.

Since hospital data include temporal trends of clinical symptoms and medical services, we can discover not only knowledge about temporal evolution of disease, but also one about medical practice from hospital information system. This paper proposes temporal data mining process and applied the method to capture temporal knowledge about nursing practice. The results show that the reuse of stored data will give a powerful tool for management of nursing schedule and lead to improvement of hospital services.

This chapter introduces exploratory data analysis (EDA) and visualization techniques for spatial data in S-Plus and S+SpatialStats. EDA involves methods of describing data and its structure in order to formulate hypotheses and check the validity of assumptions. In general, we will be concerned with the distribution of data and violations of local and global stationarity (as defined in chapter 1)—including trends and outliers. Although a researcher uses EDA techniques throughout spatial analysis and modeling, this chapter focuses on initial explorations—before analysis has been attempted. Analysis techniques for specific types of spatial data — geostatistical data, lattice data, and spatial point patterns, will be discussed in chapters 4, 5, and 6.

The integration of information systems in a hospital is accomplished by the introduction of a number of specialised and interconnected information systems. At the General Hospital of Athens G. Gennimatas, a clinical information system (CIS) is installed and running. Shortly after the operation of the clinical information system, the need to couple the CIS with a laboratory information system (LIS) became apparent. The LIS had to be interconnected with the existing clinical information system and the information system for the hospital administration. The difficulties encountered along the progress of this project and the decisions taken in order to obtain the determined goals are presented in this paper. The project management team designed a master plan for the entire duration of the works. Along the course of the project's development, many decisions had to be reconsidered, altered or postponed and many arguments had to be discussed leading to a number of compromises.

Hospital Information System (HIS) is a comprehensive, integrated information system designed to manage the administrative, clinical and support aspects of a hospital. It provides numerous advantages in patient care and hospital management. With the advancement in technology and cost effective solutions, HIS adoption among the hospitals has increased substantially in recent years. Various project management tools are available which helpful in effective planning and project monitoring. In spite of effective planning and implementation in phase manner, the concern remains regarding the challenges faced during implementation and usage of HIS. These challenges includes Technical Challenges like Security of Data, Unauthorized access, confidential information, integration of Medical Softwares to avoid duplicate entry and Administrative Challenges like involvement of stakeholders, user acceptance, lack of ownership etc. This can be subdued either by utilization of data entry operators or through offline and duplicate entries, but such implementation does not achieve the purpose of HIS. Apart from good project management, there are various other factors such as involvement of users, effective trainings, awareness program, secure and role based application, compliance to industry standards for easily integration with other applications etc., which increase success factor of implementation. This paper presents the challenges faced in implementation of HIS in super specialty hospital, Postgraduate Institute of Medical Education and Research, Chandigarh (PGIMER) and strategies adapted to overcome them.

As the rapid advancement and wide application of computer hardware, software and network, hospital information systems (HISs) have entered almost all hospitals in China and are becoming more important and covering more parts in daily hospital operations. Most functions in a HIS provide the users an easier and faster way in doing their medical tasks with graphic user interface. But the HIS is a management information system focusing on daily operations within hospital to improve efficiency of work by using online clinical data acquisition and processing. So, to some extent, a HIS improve quality of health care services, but it cannot measure and evaluate the quality of health care services. At present, hospitals in China are in a competitive environment. In order to attract more patients, high customers' satisfaction is most important for a hospital in the competition. Hospital services management system (HSMS), which is an information system of health care services management in hospital can improve quality of service and lead to cost reduction, high customers' satisfaction and great attractability to other hospitals' customers. In this paper, we study the HSMS. The main work as follows: review services management and HIS, analyze the contents of health care services management and the functions of a HSMS, design the framework of a HSMS, study the implementation technology of a HSMS, discuss the how to integrate a HSMS into a HIS.

Intrusion detection systems are used to detect attacks in a network. Machine learning (ML) approaches have been widely used to build such Intrusion Detection Systems (IDSs) because they are more accurate when built from a very large and representative dataset. In recent times, one of the benchmark datasets that are used to build ML-based Intrusion Detection models is CICIDS2017 dataset. The dataset is contained in eight groups and was collected from the Canadian Institute on Cyber Security dataset repository. The dataset is available in both PCAP and netflow formats. This study used the netflow records in the CIDIDS2017 dataset as they are found to contain newer attacks,very large and are found useful for traffic analysis. Exploratory Data Analysis (EDA) techniques were used to reveal various characteristics of the dataset. The general objective is to provide more insights on the nature, structure and issues with the dataset so as to identify the best ways for using it to achieve improved ML-based IDS models. Furthermore, some of the open problems that can arise from the use of the dataset in any machine learning-based Intrusion Detection systems are highlighted and possible solutions are briefly discussed. The EDA techniques used revealed important relationships among input variables and the target class. The study concluded that the EDA can better influence the decision of future IDS researches that use the dataset. Thus, improved machine learning-based intrusion detection systems can be built from the dataset once it is well understood and pre-processed.

As part of its most recent Efficiency Research Programme, which sought to advance understanding of workforce retention in health and social care, the Health Foundation have provided funding to a team within the Centre for Social Care, Health and Related Research at Birmingham City University. This project proposes to utilise exploratory data analysis techniques to investigate the underpinning contributory factors to nurse retention and ultimately patient safety across 10 acute and 10 mental healthcare providers. Exploratory data analysis techniques do not conform to the accepted hypothesis setting and testing associated with the traditional experimental research design within medicine and consequently, can be subject to criticism. However, these techniques afford bountiful opportunity to generate insight from real-world data; insight that could not be gleamed from experimental designs, therefore they warrant further investigation before being written off as ‘data dredging’.
 Exploratory data analysis techniques applied to large datasets that are routinely collected as part of standard care have the potential to revolutionise healthcare. Machine learning and artificial intelligence are becoming common place in everyday life but have been relatively slow to be adopted as a mechanism for improving healthcare. An aspect of the medical community’s reluctance to accept these techniques is a perceived lack of robustness in determining relationships, as hypotheses aren’t typically generated in advance and therefore the process exposes itself to unscrupulous actions where analyses are undertaken until a relationship is found. An element of this programme of work is to develop a set of standards for the application of these techniques to healthcare-generated data including, but not limited to and housing data in open access formats to improve transparency and reporting on findings.
 This session seeks to explore these issues with colleagues across disciplines, generating debate regarding novel approaches to complex issues.

Organizational decision to adopt hospital information system: An empirical investigation in the case of Malaysian public hospitals

Although in recent times the Saudi government has paid much attention to the adaptation of hospital information systems (HIS) and electronic medical records (EMR), the importance of utilising HIS to enhance medical research has been neglected. We aimed to (i) investigate the current state of medical research in Saudi Arabia, (ii) identify possible issues that hinder improvement of medical research and (iii) identify possible solutions to enhance the role of HIS in medical research in Saudi Arabia. We used a questionnaire and structured interview approach. Questionnaires were distributed to Saudi healthcare professionals. One hundred responses to our questionnaire were captured by the online Google Form designed specifically for our survey. Structured interviews with two IT professionals were conducted regarding technical aspects of their hospital data management systems. Six themes contributing to the inefficacy of HIS in medical research in Saudi Arabia emerged from the data: incorrect datasets, difficult data collection and storage, poor data analytics, a lack of system interoperability across different HIS for universal access and negative perception of the usefulness of HIS for medical research. Our findings suggest (i) cloud-based HIS would support efficient, reliable and integrated data collection and storage across all hospitals in Saudi Arabia; (ii) EMR data sources should be seamlessly linked to avoid incomplete, fragmented or erroneous EMR in Saudi Arabia; and (iii) collaboration between all hospitals in Saudi Arabia to adopt a uniform standard to support interoperability and improve data exchange and integration is necessary.

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.

This papers gives an approach to hospital management data by using statistical data mining. For analysis, distribution analysis, correlation and uniregression analysis and generalized linear model were applied. The results showed several interesting results, which suggests that the reuse of stored data will give a powerful tool to support a long-period management of a university hospital.

The rapid digitization of healthcare has made Hospital Information Systems (HIS) essential for improving patient care, optimizing clinical workflows, and strengthening overall hospital management. This study examined HIS acceptance among 32 paramedical professionals including laboratory technicians, radiology staff, and pharmacists in a tertiary care hospital in Kerala, applying the model of Technology Acceptance Model (TAM) as the guiding framework. Primary data were collected through a structured questionnaire and informal interview and analyzed using descriptive statistics, percentage analysis, and multiple regression. Results showed strong perceived usefulness, with over 84% of respondents agreeing that HIS improves task efficiency and documentation accuracy, and 90% rating the interface as simple and user-friendly. Despite this, about one-quarter expressed neutral or low confidence in daily operations due to limited IT exposure, and 18.8 % reported difficulty obtaining timely technical support. Regression analysis revealed that attitude toward HIS was the strongest predictor of usage intention, explaining 46.4 % of the variance. These findings highlight the need for department specific training, regular refresher programs, and responsive technical assistance to build user confidence and ensure sustainable HIS adoption, offering practical guidance for hospital administrators and policymakers aiming to advance digital health initiatives.

This quantitative study investigates the impact of organizational factors on Hospital Management Information Systems (HMIS), employing the PRISM framework. The absence of a search menu linked to the primary key of national identity number in the HMIS was scrutinized for its effects. Results reveal significant influences of organizational factors on technical and behavioral aspects of HMIS. Notably, periodic evaluations by the IT team significantly enhance technological advancements within hospitals, while frequent training sessions for HMIS users markedly improve their comprehension of system functionalities. These findings underscore the pivotal role of organizational strategies in shaping the effectiveness and efficiency of HMIS, offering valuable insights for optimizing healthcare information management practices. Highlights : Organizational factors significantly influence technical enhancements in Hospital Management Information Systems. Frequent evaluations by the IT team contribute to technological advancements within hospital systems. Regular user training sessions enhance comprehension and utilization of HMIS functionalities Keywords: Hospital Management Information Systems, Organizational Factors, PRISM Analysis, Technology Improvement, User Training

Understanding Technology and People Issues in Hospital Information System (HIS) Adoption: Case study of a tertiary hospital in Malaysia.