File:Healthcare Analytics in Navy Medicine vol. 3, issue 4 (IA HealthcareAnalyticsVol03No04THEMERiskAdjustmentFINAL).pdf

Focus on Risk Adjustment
An Introduction to the MHS Risk Adjustment Model
Geof Hileman, FSA, and Robert Opsut, PhD

Experienced healthcare analysts know that apparent differences in cost or utilization measures can be caused by many diverse factors. For example, a group of seven year-old girls is likely to have much lower average health care costs than a group of 62 year-old retirees. Similarly, two groups with similar demographics but different levels of disease burden will exhibit very different patterns of cost and utilization. One of the major challenges in conducting analyses of healthcare cost and use data is properly adjusting for demographic and health status differences in the underlying populations. This article provides an introduction to risk adjustment in order to assist the reader in better understanding its application in the context of financial adjustment (e.g., capitation payments) and non-financial uses (e.g., population cohort management).

Focus on Risk Adjustment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
Skills and Methods—Building a New Risk Adjustment Model. 3
Data and Information Systems —New Risk Adjustment Data
in M2 and MDR . 4
New Knowledge —Noted Publications. 5
What’s Coming Up. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Tips and Tricks—The Goal Seek Feature in Excel . 6
Knowledge Sources. 8