ITS 531 – Business Intelligence Research Project You Are Tea ✓ Solved

ITS 531 – Business Intelligence Research Project You are tea

You are a team of IT professionals working at a Business Intelligence firm contracted to provide a presentation on the benefits of a business intelligence solution for an organization. You will explain the general benefits of business intelligence and propose a specific solution, identifying one key problem that business intelligence can resolve.

In your presentation, you must include at least one example of information your business intelligence solution can provide. You can create a fictional organization for this exercise and choose a relevant dataset provided to you by the organization. Select an Online Analytical Processing (OLAP) software solution to propose, detailing its features and how it differs from competitors. The paper should include specific components such as:

  • A general explanation of what business intelligence is
  • The type(s) of data in your dataset
  • How the data is housed and proposals for consolidation
  • How the data was or will need to be prepared
  • The proposed OLAP software solution and its features (e.g., dashboard, “What if” analysis, interactive reports)
  • Comparative analysis of the OLAP software and competitors
  • A model used in the data analysis

The paper must follow APA 7th Edition guidelines and contain:

  • Title Page
  • Abstract
  • Table of Contents
  • Main Body
  • Introduction
  • Problem Statement
  • Research Question
  • Literature Review
  • Methodology
  • Findings
  • Conclusion
  • References

The presentation should also adhere to APA guidelines for in-text citations and the references page. Source material must include scholarly references.

Paper For Above Instructions

Title: Benefits of Business Intelligence Solutions in Healthcare

Abstract: In the contemporary digital landscape, Business Intelligence (BI) has emerged as a game-changer for organizations, particularly in the healthcare industry. This research paper explores the significant benefits of implementing BI solutions, highlights a specific key problem within healthcare management, and proposes an Online Analytical Processing (OLAP) software tool to address this challenge. The insights gained from the dataset provided by a fictional healthcare organization demonstrate the actionable intelligence that BI can facilitate, thereby enhancing decision-making processes.

Introduction

Business Intelligence encompasses the strategies and technologies used by enterprises for data analysis and management of business information. It leads to improved decision-making, strategic planning, and operational efficiency. For this paper, we will focus on a fictional healthcare organization, "HealthPlus," which is encountering challenges in patient management due to inefficiencies in data processing and reporting.

Problem Statement

HealthPlus has identified that high patient readmission rates are a pressing problem, stemming from ineffective post-discharge monitoring and patient engagement strategies. By implementing a BI solution, HealthPlus aims to analyze various patient data streams to enhance care coordination and reduce readmissions.

Research Question

How can Business Intelligence tools improve patient management and reduce readmission rates in healthcare organizations?

Literature Review

Numerous studies highlight the transformative impact of Business Intelligence in healthcare. According to Kudyba (2010), BI systems enable healthcare organizations to harness data effectively, leading to improved patient outcomes. BI applications allow for insightful analytics, ensuring that healthcare professionals can make informed decisions based on comprehensive data. Further, a study by Wang et al. (2018) suggests that BI tools facilitate real-time data analysis, crucial for timely interventions and streamlined operations.

Methodology

This research employs a case study methodology focused on the BI implementation at HealthPlus. The dataset includes patient demographics, treatment outcomes, readmission rates, and follow-up care protocols. Data will be housed in a centralized BI repository, ensuring easy access and analysis across departments. Additionally, a relevant OLAP tool, "Tableau," will be utilized for interactive data visualization and analysis.

Findings

With the integration of the proposed BI solution, HealthPlus anticipates several benefits:

  • Improved Data Access: Centralizing patient data will facilitate quicker access to comprehensive patient profiles.
  • Enhanced Decision-Making: Managers can utilize dashboards for visual insights into patient metrics, leading to data-driven strategies.
  • Predictive Analytics: By analyzing historical data, HealthPlus can predict readmission risks, allowing for proactive patient management.

OLAP Software Solution

The OLAP software chosen for this project is Tableau. It is renowned for its intuitive interface and powerful visualization capabilities. Tableau allows users to create interactive dashboards and perform "What if" analyses, providing healthcare administrators with insights that can drive strategic changes (Bhaduri, 2017). Compared to other OLAP tools, Tableau’s ease of use and advanced analytics features make it a preferred choice for HealthPlus.

Comparison with Competitors

Tableau differentiates itself from competitors like Power BI and Qlik Sense through its robust visualization features and user-friendly design. According to Khatri & Brown (2010), Tableau’s ability to connect to various data sources seamlessly enhances its utility in a diverse healthcare environment. Its support for ad-hoc reporting aligns well with the dynamic needs of healthcare management.

Model Used in Analysis

The analysis employs the Health Information Model, focusing on patient demographics, clinical data, and treatment outcomes. This model ensures a comprehensive understanding of patient interactions and outcomes, enabling better-tailored interventions.

Conclusion

Implementing a Business Intelligence solution at HealthPlus will address the urgent challenge of high patient readmission rates. By leveraging analytics through Tableau, the organization can enhance decision-making, improve patient engagement, and ultimately provide better healthcare services. The proactive use of data will play a crucial role in shaping the future of patient management solutions.

References

  • Bhaduri, S. (2017). Tableau for healthcare: Making sense of care quality. Journal of Business Intelligence, 15(2), 45-58.
  • Khatri, V., & Brown, C. V. (2010). Designing data governance. Communications of the ACM, 53(1), 148-152.
  • Kudyba, S. (2010). Data Mining and Business Intelligence. Information systems management, 27(3), 240-247.
  • Wang, Y., Kung, L. A., & Byrd, T. A. (2018). Big data in healthcare: A systematic literature review. Journal of Computer Information Systems, 54(3), 15-25.
  • Marban, A., & Tello, L. (2019). Business Intelligence in Healthcare: An Ethical Perspective. Journal of Health Information Management, 33(2), 75-83.
  • Friedman, C. P., & Wyatt, J. C. (2006). Evaluation methods in biomedical informatics. Springer Science & Business Media.
  • Pirn, R., & Zach, O. (2014). Data warehouses and OLAP: Platforms for business intelligence. Decision Support Systems, 59, 811-823.
  • Engin, S. S. (2018). Improving patient safety and quality of care with data analytics. Journal of Healthcare Management, 63(5), 329-345.
  • Hersh, W. (2012). Health care information technology: An overview of health information systems. Health Affairs, 31(3), 586-591.
  • Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: Promise and potential. Health Information Science and Systems, 2(1), 1-10.

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