Webinar: Medical Insurance Fraud Detection, Prevention and Advanced Data Analytics

December 06-10, 2020, 11:00 AM – 3:40 PM, GULF STANDARD TIME (UTC + 04:00)

Training Objectives

Completion of this course will provide attendees with a better understanding of the scope of healthcare insurance fraud, and how to prepare a case with the proper order of evidence gathering and analytics, ranging from the simplest situations to complex and sophisticated healthcare/insurance fraud crimes.

Register Now Download Brochure

Instructor(s) of this course

Alanna Marie Lavelle

CEO and Founder, Lavelle and Associates, LLC, Atlanta, Georgia
Sr. Principal Consultant and Adjunct Professor
Former Chair of the Board and Faculty Member NHCAA
M.S., AHFI, CPC, ACFE

More Detail
Aleksandar Lazarevic

Phd, Machine Learning
VP, Advanced Data Analytics & Data Engineering, Stanley Black & Decker (SBD)
Former Director Data Sciences, Aetna
PhD, Machine Learning, Temple University
MBA (ABD), Carnegie Melon University
MS in Computer Science & Engineering, University of Belgrade

More Detail

This course will provide a basic introduction to healthcare insurance fraud as well as a comprehensive introduction to the basic components of healthcare data and how the analytics of big data can identify potential fraud, waste and abuse in the public and private payer systems.  The software tools, analytics and data mining techniques will be reviewed as well as the newest fraud detection methods based on predictive modeling.  Proactive algorithms used to identify real time large investigations will be reviewed with case studies examined.

Completion of this course will provide attendees with a better understanding of the scope of healthcare insurance fraud, and how to prepare a case with the proper order of evidence gathering and analytics, ranging from the simplest situations to complex and sophisticated healthcare/insurance fraud crimes.

  • Investigators and Auditors in the Healthcare domain
  • Certified Fraud Examiners (CFE)
  • Certified Information Systems Auditors (CISA)
  • Insurance Claims Adjudicators
  • Special Investigator Unit Directors/Auditors
  • Medical Claims Auditors
  • Attorneys
  • Third Party Administrators
  • Professionals who want to expand their skill sets in interviewing techniques
  • Fraud Analysts 
  • Compliance analysts and managers
  • Internal and external auditors
  • Medical audit/claims
  • Those attendees who are new to the fraud and abuse data analytics world
  • Group discussions focused on real-world case studies
  • Use of videos, images and brainstorming techniques for quality learning
  • Online quizzes
  • Daily feedback of previous day course activities
  • Live exercises for each participants
  • Course material
  • Certificate of Achievement

Webinars

How can I register for Webinar and how does the whole thing work?

You may register by email or online: 

To register by email:

Download the brochure and complete the registration form given as a last page of the brochure and email to training@acsmb.com

To register online:

Step 1 – Go to the course page and click ‘Register Now

Step 2 - Complete the registration form, read and check the ‘terms and conditions’ box and click on ‘Register’.  You’ll receive a confirmation email.   

Step 3 - Click on ‘Confirm’ in the confirmation email and you'll be taken to the login page. Login and click the "Add to Cart" button that suits your needs and click "Pay by Credit Card" to enter your payment details.  You'll receive a payment confirmation email as well as a Welcoming Package with the full itinerary.

Please check following questions to see how the whole thing works.

If you have any questions or need assistance, please and thank you reach us at training@acsmb.com

How soon I can login?

You will be able to login 10-15 minutes prior to each activity/session. Don’t take a chance, so better will be to login early.

How do I join webinar/meeting?

Joining is easy, just takes few seconds.

Just click the link in the invite that you will be provided with in email. You will proceed to your session immediately. Just remember to register first if attending a webinar.

How can I join Zoom meeting and what are the pre-requisites?

Please check the details as how to join the meeting at https://support.zoom.us/hc/en-us/articles/201362193-Joining-a-meeting

How do I ask the Instructor questions?

There will be a 'chat option on your screen. Type your question in the box and send it direct to the Instructor. The Instructor will address your question at the earliest and at an appropriate time during the presentation

Course Fee $1,500/Participant

Early Bird Discount
10% discount till Nov 19, 2020 to pay $1,350/participant

Group Discount
10% additional discount on group of minimum 2 participants (from same organization)
20% additional discount on group of minimum 4 participants (from same organization)


Webinar: Medical Insurance Fraud Detection, Prevention and Advanced Data Analytics - Course Schedule

Day 1 - Sunday 06 December, 2020
Opening Session

Opening Remarks  & Introduction

Session One (11:00 To 13:00)

The Introduction to the problem of Medical Insurance Fraud

  • Medical Insurance Fraud and its implications for society and economies.
  • Types of Fraud, waste, and abuse in healthcare insurance industry
    • Defining Market Players within the Healthcare Continuum
    • The Investigation Model

Quiz

Break (20 minutes)
Session Two (13:20 To 14:20)

Proactive Casework and Detecting Fraud, Waste and Abuse

  • The Evidence of Healthcare Fraud and How to Collect it
  • Who, What, When Where, Why, How and How much?
  • The processes and procedures in detecting fraud and building a case
  • Utilizing Proactive Detection to avoid “pay and chase”

Quiz

Break (20 minutes)
Session Three (14:40 To 15:40)

Detection of Healthcare Fraud, Part II

  • Discuss strategies for proactive detection
  • Discuss what data to analyze
  • Types of witnesses:Whistleblower/Complainant; Patients, Former Employees, Office staff, Subjects, family members and how to corroborate their statements with data
  • Behavioral Profiling to assist in the data analyses

Quiz

End of day review and wrap up (Group Interactive Discussion)

Day 2 - Monday 07 December, 2020
Session One (11:00 To 13:00)

Review of previous day learning sessions, and basics and strategies discussed.

Healthcare data models:

  • Planning and examining data mapping and mining
  • Doing your homework – assets, marital and financial status, bankruptcies/divorces/substance abuse data
  • The “Auditor’s check list:

Case Studies and Round Table Discussions

  • Reviewing interesting and real time actual examples of successful investigations from predictive modeling
  • Open discussion of experiences and successes with data mining in the middle east and Africa region
  • Prevention of fraud vs. “Pay and chase”
  • Examples of large cases built solely on data analytics

Quiz

Break (20 minutes)
Session Two (13:20 To 14:20)

Clinical Coding – Current Procedure Terminology (CPT) and International Classification for Diseases (ICD-10) codes

  • The power of familiarization with coding
  • Detection or Prevention?
  • Setting the table with the Outlier
  • Possible techniques to employ for enhancing interviews using data schematics

Quiz

Break (20 minutes)
Session Three (14:40 To 15:40)

Clinical coding, continued

  • Pharmacy Fraud, Counterfeit Pharmaceuticals, and Emerging global trends
  • International Organized Crime and Healthcare Fraud and money laundering

Quiz

End of day review and wrap up (Group Interactive Discussion)

Day 3 - Tuesday 08 December, 2020
Session One (11:00 To 13:00)

Review of previous days’ concepts and strategies

  • Group review and role play of Subject interviews
  • Preparation for training in the use of analytics
  • Preparing the evidence for the prosecutor/Auditor/Director

Quiz

Break (20 minutes)
Session Two (13:20 To 14:20)

The Impact of Covid-19 and other Pandemics

  • The impact of Covid-19 and other pandemics on the global healthcare system: Fraud, waste and abuse in clinical responses.
  • Possible techniques to employ for enhancing interviews using data schematics

Quiz

Break (20 minutes)
Session Three (14:40 To 15:40)

Review of course and wrap up

Quiz and discussion of responses

Round table discussion

Day 4 - Wednesday 09 December, 2020
Session One (11:00 To 13:00)

The Introduction to Data Analytics / Data Science (2 hours)

  • What is Data Analytics?
    • Descriptive, Diagnostic, Predictive and Prescriptive
    • Importance of Descriptive & Diagnostic Analytics
    • When we need Predictive & Prescriptive Analytics
  • Fundamentals of Descriptive Analytics – Exploratory Data Analysis (EDA) / BI Reports / Visualization Dashboards
    • How to do efficient EDA?
    • How to develop effective and outcome driven dashboards?
    • What KPIs to report?

Quiz

Break (20 minutes)
Session Two (13:20 To 14:20)

Machine Learning 101 and Its applications in health care

  • Fundamentals of Predictive & Prescriptive Analytics – Machine Learning
    • Major types of Machine Learning (e.g., classification, regression, association rules, clustering, text analytics, anomaly / outlier detection, etc) and relevant examples
    • Common use cases where Machine Learning is used but you may not know it
    • Common health care use cases where data analytics is used today

Quiz

Break (20 minutes)
Session Three (14:40 To 15:40)

Data Analytics Applications in Health care Fraud Waste and Abuse – EDA, Reporting & Dashboards

  • What kind of data is available for the data analytics
  • What kind of EDA is useful in health care fraud?
  • How to convert your FWA expertise into business rules that could be run automatically every day / hour / week? – Case studies and Roundtable discussion
  • Examples of visualization dashboards / tools to help fraud investigation
  • Possible demo of some of these visualization tools / dashboards

Quiz

End of day review and wrap up (Group Interactive Discussion)

Day 5 - Thursday 10 December, 2020
Session One (11:00 To 13:00)

Review of previous day’s concepts and strategies

Predictive / Prescriptive Analytics in Action to combat Health Care Fraud

  • What data is available for the data analytics – Revisited
  • How to use this data for advanced data analytics?
  • How advanced data analytics could be used to fight health care FWA?
    • Business rules – quick review from yesterday
    • Classification models – detecting variations of know health care fraud
    • Anomaly / Outlier Detection – detecting novel types of health care fraud
  • Doing your homework – assets, marital and financial status, bankruptcies/divorces/substance abuse data

Quiz

Break (20 minutes)
Session Two (13:20 To 14:20)

Predictive / Prescriptive Analytics in Health Care Fraud Detection - Case Studies and Round Table Discussions

  • Data Analytics for Post-pay vs. Pre-Pay
  • Reviewing actual use cases of successful investigations from advanced data analytics
  • Round table discussion on possible fraud use cases and how data analytics could help.

Quiz

Break (20 minutes)
Session Three (14:40 To 15:40)

Review of course and wrap up

Quiz and discussion of responses

Round table discussion

Course Program
Time Topic
Day 1
10:45 to 11:00Registration & Introduction
Day 1-5
11:00 to 13:00Session One
13:00 to 13:20Break (20 minutes)
13:20 to 14:20Session Two
14:20 to 14:40Break (20 minutes)
14:40 to 15:40Session Three