• Define raw data in health care.
• Explain four types of raw data currently being used in health care settings.
• Explain how raw data are collected and analyzed.
• Use current best practices from peer-reviewed literature to show how raw data are transformed into meaningful information.
• Evaluate the effect of data analysis on performance and QI.
Health care organizations are often complex systems that comprise a wide array of services. For example, the modern hospital is a complex system including outpatient services, surgery centers, pharmacies, and other essential services. Managed care organizations are another complex system that consists of a diversified network of doctors, specialists, hospitals, and outpatient services. These complex organizations need managers with a strong understanding of analytics to ensure the organizations are meeting the needs of their stakeholders. Modern health care organizations need to be able to transform raw data into meaningful information that can help guide decisions.
In this assignment, consider the types of data used for QI in a complex health care system such as a managed care organization or hospital system.
• Determine four types of raw data and the sources of such data.
• Detail how raw data are collected, analyzed, and transformed into meaningful information.
• Discuss how the transformed data are evaluated and applied to decisions related to quality and performance approval.
The ability of health care organizations to gather and store data has improved greatly due to the advancement of technology and health information systems. These data can be used to help improve quality and reduce risk. However, many organizations struggle to identify what datasets are most important and how to analyze, interpret, and validate the data. Furthermore, to be effective, data need to be transformed into meaningful action plans. Collected and stored data are not useful to a health care organization until they are properly analyzed and put into action. Health care organizations need to have the processes in place to securely gather and store important data, as well as analyze, interpret, and validate those data. Finally, a successful health care organization should have the ability to transform important data into working protocols, policies, and procedures that improve quality and reduce risk.
After reviewing the Vila Health scenario in regard to the need for improving data analysis at the hospital system, develop an academic paper addressing the following:
• What types of internal data and datasets are most valuable to the organization for quality assurance in risk reduction?
• What types of external data and datasets are most valuable to the organization for quality assurance in risk reduction?
• What are the best practices most commonly used in the field to securely store and access important data, based on accepted industry best practices?
• What are the tools and approaches that will be used to analyze, interpret, and validate the data?
In addition, develop 5 to 10 recommendations for how the organization can use the data to develop a meaningful quality assurance plan, based on current literature, best practices, and accepted industry trends.
Pay attention to the critical elements that form part of the grading criteria for this assignment:
• Explain types of internal data and datasets that are most valuable to the organization for quality assurance in risk reduction.
• Explain types of external data and datasets that are most valuable to the organization for quality assurance in risk reduction.
• Determine best practices most commonly used in the field to securely store and access important data, based on accepted industry best practices.
• Discuss tools and approaches appropriate for the analysis, interpretation, and validation of data.
• Develop appropriate recommendations for how an organization can use data to develop a meaningful quality assurance plan, based on current literature, best practices, and accepted industry trends.