Agenda Day One

Presenter(s): Sreenivas (Si) Konda, Ph.D

• Basic statistics (means/medians/variance/standard error of estimates);
• Test of significance and their interpretation (p values; R²; F, Chi-sq, and t-tests; ROC curves);
• Hypothesis testing and interpretation of ANOVA results;

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• Introduction to R;
• Review of data examples;
• Data visualization and exploration;
• Graphical applications in R.

Materials: Prescription Cost Dataset

Software:  R

 

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Presenter(s): Ian Duncan, FSA, CSPA, FCA, FCIA, FIA, MAAA

• Introduction to medical claims;
• Introduction to prescription drug claims;
• Introduction to clinical values and their interpretation;

Introduction to medical algorithms (e.g. how to identify members with a condition from claims data; how to distinguish between claims generated by different provider and service types, for example).

Materials: Lecture notes; Chapter 1; Health Care Dataset; Sample EMR data

Software: R

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Presenter(s): Sreenivas (Si) Konda, Ph.D

• Linear Regression Models (LM)
• Generalized Linear Models (GLM)
• Bootstrap, K-fold Cross-validation (CV)

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Materials: Lecture notes
Medicare dataset

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Presenter(s): Ian Duncan, FSA, CSPA, FCA, FCIA, FIA, MAAA

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Presenter(s): Nhan Huynh, MS

Materials:  Lecture notes
Dataset

The CMS Hospital Readmission Reduction Program (HRRP) applies a penalty (reduced DRG reimbursement) to those hospitals whose readmissions exceed a benchmark. Hospitals have an incentive to apply case management to patients at high risk of readmissions.   Using patient level data with more specific patient information (with 13 explanatory variables) we will build logistic regression models for readmissions and compare with the industry standard LACE index. In addition, for practical implementation purposes will apply an   economic model to determine the optimal level of intervention.

Chapter 20

Medicare Dataset

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