Medicare Cost Analysis

Group 8

Ganesh, Rafael, Zhuang

Outline

• Introduction

• Business Objectives

• Exploratory Analysis

• Unsupervised Learning

• Supervised Learning

• Predictive Modeling

• Recommendations

Part OneIntroduction01

What’s Medicare?

• Medicare is the federal health insurance program for people who are 65 or older and certain younger people with disabilities

2013 Medicare Facts

• Accounted for 14% of the federal budget • Represented 20% of total national health spending • Covered 54 million beneficiaries• Benefit payments totaled $583 billion

Source: Kaiser Family Foundation - https://kaiserfamilyfoundation.files.wordpress.com/2014/07/7305-08-the-facts-on-medicare-spending-and-financing.pdf

• Submitting false statements• Billing for services or supplies not furnished• Billing for services not medically necessary

Sources of Medicare Fraud and Abuse

Business Objectives

Finding similarities among medical procedures (Clustering)

Discovering consistency among charges (Classification – Decision Tree & Logistic Regression) m

Predicting cost of a procedure in a given state (Predictive Modeling)

Data Description

Hospital Data

3 million rows

Columns- State- Procedure- Cost ……

Medicare Provider Data

9 million rows

Columns- Demographics- Specialty- Patient Distribution ……

Part TwoExploratory Analysis02

Average Medicare Payments$1,068

$281$218

Submitted Allowed Actual Payment

Med

icar

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Most Frequent ProceduresFr

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ncy

Avg.

Med

icar

e Pa

ymen

t Per

Pro

cedu

re

- Broken Ankle- Broken thigh- Correction of Bunion

- Removal of plaque and insertion of stent- Transplantation of donor heart

Costliest ProceduresFr

eque

ncy

Avg.

Med

icar

e Pa

ymen

t Per

Pro

cedu

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- Removal of plaque and insertion of stent- Transplantation of donor heart- Transplantation of donor liver

State wise Procedure Frequency

State wise Procedure Payment

Part ThreeData Analysis03

Unsupervised Learning – Clustering

• Best Clustering - 3 Clusters

• Important attributes: - Average cost - Patient age - Patient race - Disease type - Provider type

Unsupervised Learning – Clustering

• Business question: Are costs of different procedures in different states consistent with the national average?

• Input: - State - Procedure - Average Cost - Number of Services

Supervised Learning – Decision Tree & Logistic Regression

Decision Tree - Result

Procedure: AnestheticNo. of Services: >369,366

Decision Tree - Result

Procedure: Surgical TreatmentsDrug Administration: N

Decision Tree - Result

Procedure: Removal of Leg Plaque, Balloon Dilation…No. of Providers: < 4No. of Services: < 400

Decision Tree - Result

Procedure: Cardiac Surgeries No. of Providers: < 4No. of Services: < 400

• Business question: How much will a procedure cost in a given state?

Predictive Modeling – Linear Regression

Linear Regression Coefficients

• Business question: How much will a procedure cost in a given state?

• Higher the number of services, lower the expected cost• Higher the number of providers, lower the expected cost• Procedures without drug have higher expected cost than the ones with drug

administration

Predictive Modeling – Linear Regression

Recommendations

RecommendationsAddressing procedure cost differential between states: Increase physician enrollment in states with lower representation to increase competitiveness of physician availability.

RecommendationsAddressing potentially improper billing of commonly “abused” procedures: Institute more stringent rules for procedures known to be most common and expensive via expanded review edits.

Costly and Frequent Procedures:- Plaque removal in leg artery- Balloon Dilation- Surgery equipped with Endoscopy