US Healthcare Analytics Market – A Quick Snapshot by Sutherland Global Services

US Healthcare Analytics Market – A Quick Snapshot

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Current Healthcare Environment Fraud, Waste & Abuse in Healthcare Fraud, Waste & Abuse Perpetrators

Current Healthcare Fraud Systems

Current Healthcare Fraud Operations

• Far more sophisticated – organized,

• Most current detection systems act

• Limited to third-party systems and

patient, sharing of rules • Leveraging multiple channels

(providers & facilities) at the same time • Continuously evolving fraud strategies

on claim level data alone

rules

• Investigations limited to individual

• No real proactive steps taken to

members, providers, and facilities

combat fraud, waste, and abuse

• Focus on rule-based approaches

• Inefficiencies driven by amount of

(linear and limited to known

data and disparate sources

schemes)

The National Health Care Anti-Fraud Association (NHCAA) estimates conservatively that 3% of all healthcare spending or USD 70 Bn is lost to healthcare fraud each year (100 times credit card estimates)

Other estimates by the government and law enforcement agencies place the loss due to healthcare fraud at as high as 10% of US annual health care expenditure or a staggering USD234 Bn each year

Source: SAS, News articles, SGS analysis

www.sutherlandglobal.com May 9, 2014

Trend in Healthcare Fraud Management The Current Special Investigative Unit (SIU) Standard – “Pay and Chase” Claim Receipt & Data Integration

Adjudication Integration / Claim Edits

Adjudication Processing

Claim Payment

Fraud Detection & Alert Generation

Alert Triage & Case Management

Moving analytics and fraud detection upstream in the claims lifecycle to become proactive Vs “Pay and Chase”

Step 1: Pre-Payment Fraud Detection Claim Receipt & Data Integration

Adjudication Integration / Claim Edits

Adjudication Processing

Fraud Detection & Alert Generation

Alert Triage & Case Management

Claim Payment

Step 2: Pre-Adjudication Fraud Detection Claim Receipt & Data Integration

Source: SAS, News articles, SGS analysis

Adjudication Integration / Claim Edits Fraud Detection & Alert Generation

Adjudication Processing

Claim Payment

Alert Triage & Case Management

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Fraud Analytics Using a Hybrid Approach for Fraud, Waste & Abuse Detection Enterprise Data

Providers

Suitable for Unknown Patterns

Suitable for Complex Patterns

Rules

Anomaly Detection

Predictive Models

Social Network Analysis

Detect individual and aggregated abnormal patterns vs. peer groups Examples: • Ratio of € to procedure exceeds norm • # of procedures / providers exceeds norm • # of patients from the surrounding area exceeds norm

Predictive assessment against known fraud cases

Knowledge discovery through the associative link analysis

Examples:

• Like upcoding behavior as known fraud provider

• Provider association to known fraud

Members Rules to filter fraudulent claims and behaviors

Facilities

Claims

Examples: • Upcoding / correct coding

Referrals

Fraud Flags

Financials

3rd Party Data

Suitable for Associative Link Patterns

Suitable for Known Patterns

• Value of charges for procedure exceeds threshold • Daily provider billing exceeds possible

• Predicted diagnosis does not match actual

• Linked members with like suspicious behaviors

• Like provider / network growth rate (velocity)

• Suspicious referrals to linked providers

Hybrid Approach Proactively applies a combination of all four approaches at member, provider, facility, and network levels Source: SAS, News articles, SGS analysis

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Enterprise Fraud Management – Overview, Major Players & Market Size Estimates Enterprise Fraud Management • Enterprise Fraud Management (EFM) is a software supporting the detection, analysis and management of fraud across users, accounts, products, processes, and channels • EFM solutions monitor and analyze user activity and behavior at the application level, as opposed to the system, database or network level, and watch what transpires inside and across accounts using any channel available to a user • These solutions also analyze behavior among related users, accounts or other entities, looking for organized criminal activity, fraud rings, corruption or misuse

Major Players in Healthcare EFM Detica, Verizon, SAS, Memento, Intellinx Ltd., Knowledge Solutions, ARGO, IBM

Key Takeaway in Enterprise Fraud Management in Healthcare • ‘Healthcare Fraud, Waste & Abuse’ market is estimated at USD1.4 Bn in 2011 and expected to grow at a CAGR of ~7% to reach USD1.7 Bn in 2014. – Healthcare Claims Recovery Audit, one of the main services in the industry, is estimated at around ~USD450 Mn in 2011, and has the potential to double or triple in the years to come • According to the National Health Care Anti-fraud Association, every USD2 Mn invested by private health insurers in fighting healthcare fraud returns USD17.3 Mn in recoveries, court-ordered judgments, plus bogus claims that were not paid and other anti-fraud savings

• According to HHS, every USD1 spent on Medicare fraud prevention would stop USD10 in fraud Source: SAS, News articles, SGS analysis

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Master Data Management & Business Intelligence and Analytics – Market Dynamics Master Data Management – Health Care 

Health care is changing, both in terms of patient treatment and the government’s role in regulation and reimbursement. This makes the use of data, business intelligence, and analytics tools even more important A typical regional hospital organization can have 200+ healthcare applications, multiple versions of systems, and many “hidden” departmental applications. In such cases, Master Data Management for the enterprise as a whole can be a daunting task



Healthcare Master Data Management – Market Size

Healthcare Business Intelligence & Analytics – Market Size

USD Mn

200

~180

180 160 140 120 100 80

1,000

~70

MDM practices typically involve using data quality, profiling, matching, and other tools. MDM is relatively new, but will be the key in improving business intelligence , given its ability to improve quality and consistency of data before it reaches data warehouses

800 700 600



600

500 400 300

200

100

2008 2013 Business Intelligence & Analytics – Health Care 

~878

900

2009

2013

Large healthcare organizations are using business intelligence and analytics tools – as a standard part of their financial and administration process – to streamline billing, manage financial performance, allocate staff and equipment, better manage patients as they move through the organization, and uncover revenue opportunities Increased focus on the financial performance management, labor productivity, cost control, and analysis of billing, payments, bed occupancy rates, and patient treatment will drive growth in Business Intelligence and Analytics

Source: SAS, News articles, SGS analysis

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End of Presentation