Course Code: REL-PI-0-DBADM
Hours: 1.5
Type: Online Course
Content Expiration Date: 3/31/2021
Learning Objectives:
Discuss the background and implications of big data in healthcare.
Describe how data are utilized by case managers within different areas of the payer setting to improve care outcomes.
Summarize how data plays a part in the application of medical necessity criteria and evidence-based guidelines.
Explain how data has the potential to revolutionize healthcare and the challenges associated with bringing this to fruition.
Outline:
Section 1: Introduction A. About This Course B. Learning Objectives Section 2: An Introduction to Healthcare Data A. Testing Your Existing Knowledge B. An Introduction to Healthcare Data C. What is “Big Data” In Healthcare? D. Where Data Comes From: General Data Realms E. Four Sources of Healthcare Data F. Where Data Comes From: Specific Data Sources G. Four Steps of Healthcare Data Analytics H. How Providers are Utilizing Data I. How Payers are Utilizing Data J. How Patients are Utilizing Data K. How Pharmaceutical Industries are Utilizing Data L. Data Challenges and Future Rewards M. Data Sourcing, Storage, Quality, and Veracity N. Data Sharing and Transparency O. Needed Infrastructure P. The Need for Privacy Q. Potential Future Benefits R. Meet Anna S. Summary Section 3: Data-Based Decision Making in the Payer Setting A. Applying and Utilizing Data in the Payer Setting B. Area 1: Care Quality and Member Outcomes C. Area 2: Member Engagement and Preventive Programs D. Area 3: Chronic Conditions and High Utilizers E. Area 4: Fraud, Waste, and Abuse F. Area 5: The Provider Network G. Data-Based Case Management H. Achieving Case Management Goals I. Identification for Case Management Services J. Critical Measurements During the Case Management Process K. Outcome Measures as a Benchmark L. Suggested Measures in Case Management/Care Coordination M. Case Management Performance Measures N. Utilization Benchmarks and Best Practice Identification O. Utilization Reviews and Data-Based Guided Care P. Identifying Fraud, Waste, and Abuse Q. Data Measurements for Medical Necessity Adherence R. Medical Necessity Criteria and Scope S. Review T. Summary Section 4: Detailed Application of Data in Decision Making A. Common Areas of Data within Case Management B. Outcome and Utilization Measures for Case Management C. Driving Better Care through Data D. Exploring Medical Necessity Guidelines E. Medical Necessity Guidelines are Evidence-Based F. Clinical Pathways to Guide Decisions with Data G. The Benefits of Data-Based Decision Making H. Review I. Summary Section 5: Conclusion A. Summary B. Congratulations! C. Course Contributors D. Resources E. References
Instructor: Danyell Jones
Danyell Jones is a recognized leader in the healthcare industry with more than 10 years of diverse experience at the executive level. Ms. Jones has been published in a number of leading healthcare industry magazines and journals, and has been responsible for the development and execution of training programs for some of the nation’s largest Managed Care, Insurer, Provider, and Health System organizations.
Disclosure: Danyell Jones has declared that no conflict of interest, Relevant Financial Relationship or Relevant Non-Financial Relationship exists.
Target Audience:
The target audience for this course is: Advanced, Intermediate level Social Workers; Case Managers; Nurses; in the following settings: All Healthcare Settings.
Relias Learning will be transparent in disclosing if any commercial support, sponsorship or co-providership is present prior to the learner completing the course.
Relias Learning has a grievance policy in place to facilitate reports of dissatisfaction. Relias Learning will make every effort to resolve each grievance in a mutually satisfactory manner. In order to report a complaint or grievance please contact Relias Learning at support@reliaslearning.com.
All courses offered by Relias Learning, LLC are developed from a foundation of diversity, inclusiveness, and a multicultural perspective. Knowledge, values and awareness related to cultural competency are infused throughout the course content.
To earn continuing education credit for this course you must achieve a passing score of 80% on the post-test and complete the course evaluation.
Course Delivery Method and Format
Asynchronous Distance Learning with interactivity which includes quizzes with questions/answers, and posttests.