M7: Flashcards
Process of inspecting, cleaning, transforming, interpreting, and modeling data to discover trends, patterns and other information that can be used to support benefit plan decisions and changes
Data Analytics
Statistical technique used to forecast future behavior by analyzing historical and current data
Predictive Modeling
To quantify risk/costs for individuals and groups in health plans
Uses of predictive modeling
Involves outcomes that are partly due to chance
Regression to the mean
How intensively plans use physician visits and hospitals
Consumption
What plan sponsors in a self-funded arrangement contract are called, often either with a TPA or insurance carrier
Administrative Services Only (ASO)
Health plan trends show there has been increased enrollment and
savings in this type of account
Health Savings Accounts (HSAs)
Health plan trends show there has been increased participation in this type of health plan
High Deductible Health Plans (HDHPs)
Visualization Layer
Analytics solutions
Data collected in spreadsheets and databases
White space data
The number of levels in the Healthcare Analytics Adoption Model
Eight
Level 3 of the Healthcare Analytics Adoption Model
Automated Internal Reporting
This ensures a plan has been set up properly
Transitional audit
Audit procedures associated with plan enrollments
Operational Plan Audits
Suggested frequency of administrative plan audits
Every 3 to 4 years if it is the same plan sponsor
Typical cost of a plan audit
$25,000 to $50,000
Definition of a plan’s disease burden
Health Status
Level 7 in the Healthcare Analytics Adoption Model
Clinical Risk Intervention and Predictive Analytics
Metadata repository
Vendor provides repository with analytics solutions
Plan sponsors assume risk and liability for uncertain health care
costs
Self-funded plans
Why do companies choose self-funded health insurance plans over fully insured plans?
Over the years, organizations have steadily moved from fully insured plans to self-insured plans to have the opportunity to lower health care costs and to be able to have more flexibility in plan design.
Study Guide, Module 7, Page 17, Learning Outcome 4.1
What are the differences between the types of plan audits?
a. Transitional audit – ensures a plan has been set up appropriately when moving from one carrier to another
b. Operational audit – looks at procedures associated with enrollment such as card processing and customer standards
c. Reinsurance audit – discovers charges that should have been paid by the reinsurance carrier, but were not
Study Guide, Module 7, Page 20, Learning Outcome 4.10
What is the difference between predictive modeling and data analytics?
Predictive modeling is a statistical technique used for forecasting purposes such as future outcomes. Data analytics uses a process to inspect, clean, transform, and model data to discover trends that can aid in benefit plan decisions.
Study Guide, Module 7, Page 6, Learning Outcomes 1.1 and 1.2
Variables that can most likely influence future results
Predictors
