Data-Based and Analytical Decision Making in Case Management

Data-Based and Analytical Decision Making in Case Management 

This course will provide an overview of innovative ways that data are being applied to improve healthcare costs, quality, and outcomes. You will begin with a broad perspective of what experts are calling the “data revolution” in healthcare, or the “age of big data,” and dive into what this means from a technology perspective. Following this, you will learn how data are being applied in ways never before seen by payers and providers to drive healthcare improvement through an analytic approach. Next, you will dig into the topic a bit more and go down to the micro level of healthcare data application within the payer setting. You will examine the different ways in which data are helping payers to improve overall population health, manage healthcare costs, and inform the creation of innovative pilot programs. Finally, you will learn about the application of healthcare data from the Case Management perspective within the payer setting. An overview will be provided about member case management selection, the intersection of healthcare data and member preference, and how data are being used to inform best practices through medical necessity criteria and clinical guidelines. This course is intended for all case managers and care coordinators with payer organizations.

$19.95

Hours: 1.50
REL-PI-0-DBADM

Certificates

Certificates provided by accrediting body (1 Match)

Commission for Case Manager Certification

1.0 HOURS


This program has been pre-approved by The Commission for Case Manager Certification to provide 1.00 hours of continuing education credit to CCM® board certified case managers.

Course Details

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 will be transparent in disclosing if any commercial support, sponsorship or co-providership is present prior to the learner completing the course.
Course Delivery Method and Format
Asynchronous/Online Distance Learning; please see certificate details for specifics on delivery format.
Relias has a grievance policy in place to facilitate reports of dissatisfaction. Relias will make every effort to resolve each grievance in a mutually satisfactory manner. In order to report a complaint or grievance please contact Relias.
If you require special accommodations to complete this module, please contact Relias Support by completing the web form (https://www.relias.com/help) or by using the chat functionality.
All courses offered by Relias, 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.
Reference herein to any specific commercial product, process, or service by trade name, trademark, service mark, manufacturer or otherwise does not constitute or imply any endorsement, recommendation, or favoring of, or affiliation with, Relias, LLC.
All characteristics and organizations referenced in the following training are fictional. Any resemblance to any actual organizations or persons living or dead, is purely coincidental.
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.
Accommodations
If you require special accommodations to complete this module, please contact Relias Customer Support here.