An Integrated Business Intelligence Framework for Healthcare Analytics (original) (raw)
Related papers
Business Intelligence and its Applications in the Public Healthcare System
Business intelligence (BI) has been known as a popular tool in business management and decision support systems. BI helps to transform raw data into smart information. There are many BI tools such as extract transform and load (ETL), data warehouse, online analytical processing (OLAP), and dashboard. BI tools are usually used in public health fields for financial and administrative purposes. Now BI is also helping public health organisations with diagnosing and treating patients with long term conditions and evaluating alternative treatments based on outcomes analyses. BI is composed of four steps: integration, storage, analysis, and presentation. BI usually uses a dashboard in the presentation step to deliver the information to end users. The development an effective dashboard is still a challenge.
Business Intelligence Solutions in Healthcare A Case Study: Transforming OLTP system to BI Solution
Healthcare environment is growing to include not only the traditional information systems, but also a business intelligence platform. For executive leaders, consultants, and analysts, there is no longer a need to spend hours in design and develop of typical reports or charts, the entire solution can be completed through using Business Intelligence "BI" software. This paper discusses current state-of-the-art B.I components (tools) and outlines hospitals advances in their businesses by using B.I solutions through focusing on inter-relationship of business needs and the IT technologies. We also present a case study that illustrates of transforming a traditional online transactional processing (OLTP) system towards building an online analytical processing (OLAP) solution.
Healthcare Business Intelligence: The Case of University’s Health Center
E-CASE & E-TECH, 2012
Organizations, private or public, feel increasing pressures, forcing them to respond quickly to changing conditions and be innovative in the way they operate. Such activities require organizations to be agile and make frequent and strategic, tactical, and operational decisions. Making such decision may require considerable amounts of timely and relevant data, information, and knowledge. Every semester university admits new students; they do subject them to medical screening which sometimes includes the staffs and returning students. However, the results of the medical test from the laboratory technologists and the doctors, such as patient diagnosis, treatment and medical prescription are currently kept in the health center data repository for record purposes without being further explored for their managerial activities. Therefore, this paper applies Business Intelligence (BI) method for exploring the university health center database repository. The data warehouse was built for the activities in university health center and a prototype was developed at the end, while the system is evaluated by the prospective users of the system. The result of this research helps the university health center management by simplifying the technique needed for managerial decision making and forecasting future activities that would help the center. Also, the health care BI is also useful to know the medical statistics of the patients in university community and the drugs that need to be frequently ordered for.
Business Intelligence for Healthcare
E-Health and Telemedicine: Concepts, Methodologies, Tools, and Applications, 2000
Using an interpretive case study approach, this chapter describes the data quality problems in two companies: (1) a Multi-Facility Healthcare Medical Group (MHMG), and (2) a Regional Health Insurance Company (RHIS). These two interpretive cases examine two different processes of the healthcare supply chain and their integration with a business intelligence system. Specifically, the issues examined are MHMG's revenue cycle management and RHIS's provider enrollment and credentialing process. A Data and Information Quality (DIQ) assessment of the revenue cycle management process demonstrates how a framework, referred to as PGOT, can identify improvement opportunities within any information-intensive environment. Based on the assessment of the revenue cycle management process, data quality problems associated with the key processes and their implications for the healthcare organization are described. This chapter provides recommendations for DIQ best practices and illustrates these best practices within this real world context of healthcare.
Business intelligence in healthcare organizations
Proceedings of the 35th Annual Hawaii International Conference on System Sciences
The management of healthcare organizations starts to recognize the relevance of the definition of care products in relation to management information. In the turmoil between costs, care-results and patient satisfaction the right balance is needed and can be found in upcoming information and communication technology. The ICT developments are a challenge in two directions, inside toward massive Data warehouses , outside toward internet dissemination. These new technologies deliver new solutions for old problems. This paper argues that although the new technology has a high potential, a great deal of the solution will be of an organizational nature. In four cases we show the spectrum from organizational solutions (changing structure and definitions, forms and procedures), to ICT solutions (changing systems and infrastructures).Main results of this study were the notion that model bases, although in theory existent for more than two decades are still scarce in healthcare organizations. Secondl, a big gap, both on content and on price, was noticed between decision oriented and model oriented systems. Finally the definition of terminology and the standardization were time consuming tasks on the road to management information in the four cases studied. Business Intelligence can be the integration between the organizational and ICT component by using a management model and a concept of integrated systems. The use of intranet and internet as communication channels for management information is seen as the challenge for the near future.
Understanding business intelligence in the context of healthcare
Health Informatics Journal, 2009
In today's fast changing healthcare sector, decision makers are facing a growing demand for both clinical and administrative information in order to comply with legal and customer-specific requirements. The use of Business Intelligence (BI) is seen as possible solution to this actual challenge. As the constituent research about BI is primarily focussed on the industrial sector, it is the aim of this contribution to translate and amend the current findings for the healthcare context. For this purpose, different definitions of BI are examined and condensed in a framework. Furthermore, the sector-specific preconditions to effectively use and the future role of BI are discussed.
Journal of the American Medical Informatics Association, 2010
Healthcare is increasingly dependent upon information technology (IT), but the accumulation of data has outpaced our capacity to use it to improve operating efficiency, clinical quality, and financial effectiveness. Moreover, hospitals have lagged in adopting thoughtful analytic approaches that would allow operational leaders and providers to capitalize upon existing data stores. In this manuscript, we propose a fundamental re-evaluation of strategic IT investments in healthcare, with the goal of increasing efficiency, reducing costs, and improving outcomes through the targeted application of health analytics. We also present three case studies that illustrate the use of health analytics to leverage preexisting data resources to support improvements in patient safety and quality of care, to increase the accuracy of billing and collection, and support emerging health issues. We believe that such active investment in health analytics will prove essential to realizing the full promise of investments in electronic clinical systems.
Business Intelligence (BI) Significant Role in Electronic Health Records - Cancer Surgeries Prediction: Case Study, 2022
Medical datasets reflect a great environment as they integrate analyses of structured and unstructured data that holds several benefits for medical sector. With a continues demand for implementing Electronic Health Records (EHRs), there is a relative requirement for utilizing data mining (DM) techniques to find out useful data, unknown patterns and inference rules from data stored in EHRs which help in a real-time decisions making process and prove-based practice for medical providers and experts. Business Intelligence (BI) is a technology able to process the huge data inside EHRs repository for enhancing the quality of medical delivery. DM is data processing techniques that considered a critical part of the BI platform. In this paper, we highlight significance of the BI integration with the EHRs to aid medical providers and professionals in real-time detection and prediction for several diseases. For more explanation, we apply BI technology with support of clustering technique as one of DM methods, for cancer surgeries prediction to prove the power of cooperating BI and EHRs in medical area.
Information-Analytical Support to Medical Industry
2019
The list of tasks that are solved by the medical information-analytical system is determined and it is shown that it is expedient to develop such a system based on an integrated approach, covering information technologies, methods, and tools for data analytics, modeling, forecasting and decision-making. It is suggested to build a medical information-analytical system on the principles of systematicity, variable equipment composition, modularity, openness, compatibility and use of a set of basic design solutions. The component-hierarchical design method has been improved, the architecture of the medical informationanalytical system has been developed, and the list of components and tasks to be solved has been defined.