Healthcare Fraud: Auditing and Detection Guide, 2nd Edition

Detection Model

Exhibit 20.1 begins with the concept of detection. Detection is the discovery of clues within the data. This book is all about finding the anomaly. The model reflects taking segmented market pieces and blending them into one data source for seamless analysis. Any anomalies will be noted and will feed the detection table for future analysis. This output is then evaluated for either response or follow-up investigations.

Exhibit 20.1 Detection Model

The following sample case flow is an actual case with hypothetical names.

Sample Case: Dr. Healer

Case History

Who: Dr. Healer, MD

What: Radio host for a program called Medicine Man; skilled healer with nontraditional practices

When: Growing practice over the last five years

Why: ?

Where: Five walk-in clinic services

Data Set

Billing data: High percentage of complicated visits; Dr. Healer generated bills while traveling in Europe.

Recent claim data: Visits to chiropractors, acupuncturists, massage therapists, nutritionists, and personal trainers at a gym billed under Dr. Healer’s tax ID number and under MD current procedural terminology (CPT) visit codes.

Staff issues: Dr. Foreign, staff physician, an unlicensed doctor, was on staff for $5 per hour; Dr. Gone continued to bill out of this clinic, although he no longer was associated with the clinic.

Dr. Healer Statement

“I am just a caring doctor getting ...