How to Adapt Data Analytics for Data-Driven Decision Making

September 20, 2017

Introduction

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Jim Paugh, SVP

Deborah has worked closely with theCenters for Medicare and MedicaidServices (CMS) as the first reporting agentparticipating in beta testing. She alsoworked with CMS and congressional staffadvocating for transparency andimprovements in the MSP program.

Deborah Watkins, CEO

Jim has an extensive background withinworkers’ compensation insurance from safetyand loss control to claim management andconsulting to underwriting and claimanalytics. He has developed many KeyPerformance Indicators for use by regulators,carriers and Fortune 500 employers as well asassociated predictive models for claimcomplexity, case management and provideroutcomes.

During her tenure at Gould & Lamb, the company received the 2010Oracle Titan Award and Gartner 1to1 CRM Silver Award for technologyimplementation of an enterprise analytics platform.

Deborah has worked in major roles for group health, workers comp andgroup benefit insurance companies. She participated in the FederalMedicare + Choice pilot program, the precursor for Medicare AdvantageC plans and is recognized for excellence in medical claims managementand return to work outcomes.

She has a Master’s in Healthcare Leadership (MBA/MPH) from BrownUniversity and a Master of Science in Nursing. She is a past boardsecretary for the National Association of Medicare Set AsideProfessionals (NAMSAP).

He formerly held leadership positions with Deloitte Consulting, VeriskAnalytics and Paradigm Management Services. In these positions, hemanaged and worked on projects for predictive modeling in workers’compensation for a $2B underwriter, one of the first claims complexitymodels for a large national carrier and reserving application for anational third-party administrator. Other project work included, WCand liability claim reviews, medical malpractice regulatory audits anddashboard development work for an actuarial firm and carrier.

Objectives

Discuss

Introduction to the ever changing world

of data analytics

Understand

How Workers’ Compensation Data

MiningCan Yield Important

and Actionable Information

Learn

How to Develop Key Performance

Indicators/Metrics

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MONEYBALL AND SABERMETRICS Indicators of Offensive Success

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Traditional Measure Moneyball Measures

• Batting Average• Home Runs• Pitching Wins• Stolen Bases• RBI’s

• On-Base %-age• Slugging %-age• 100 pitch count

>65% Strikes <58% Strikes

Expected Future Runs Scored in an inning given certain conditions. (1961-77 data set)

The Moneyball Impact

Moneyball changes the way baseball teams evaluate performance for draftees and veteran talent

Moneyball allows teams to focus on value-talent vs. “proto-typical” talent

Moneyball changed the balance of power allowing smaller market teams to compete at the highest levels.

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Changing the Outcomes.Years from Last World Series Championship

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1970 1980 1990 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Years since last win

18.6

39.7 Years

18.6 Years

39.7 Years

Who’s Next:Longest current World Series championship droughts

Seasons Team Last championship won Last World Series appearance

• 68 Cleveland Indians 1948 2016• 56 Texas Rangers Never (franchise began 1961) 2011• 55 Houston Astros Never (franchise began 1962) 2005• 48 Milwaukee Brewers Never (franchise began 1969) 1982• 48 San Diego Padres Never (franchise began 1969) 1998• 40 Seattle Mariners Never (franchise began 1977) never• 37 Pittsburgh Pirates 1979 1979• 33 Baltimore Orioles 1983 1983• 32 Detroit Tigers 1984 2012• 30 New York Mets 1986 2015

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Risk Management

1. How do you measure & quantify risk?

2. Haven’t we been using analytics for years? Is there anything new here?

3. Isn’t analytics already built into the Enterprise Risk Management (ERM) function?

4. Can analytics help with financial statements and reporting?

5. What role can analytics play in meeting regulatory requirements?

Questions Taken From Deloitte® Risk Angles

Example of Using Data Analytics

100%

8%

94%

71%

71%

66%

0% 20% 40% 60% 80% 100%

MSA delays/ precludes settlement (subjective report, notquanitified)

Confidence in Adjuster Competence with MSP Compliance

No tracking method to monitor risk compliance

Lack of Centralized Program

Fragmented Vendor Utilization (More than a single MSAvendor is used)

Outsource CMS Section 111 Reporting

SURVEY RESULTS

We randomly, confidentially surveyed 36 payers about Medicare Secondary Payer Compliance

Risk Management Process

Identify Risk: No tracking method to

monitor MSP Compliance Risk

Examine Risk Management

Techniques: Consider use of Data analytics

Select Risk Management

Technique: Integrated Data Analytics risk

management platform

Implement Data Analytics approach

Measure & Monitor Data Analytics

Approach & Outcomes

How to Develop Key Performance Indicators/Metrics

Most Measure for KPIs: Average (Mean)

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Easy to calculate, useful as “rule of thumb”but offers little insight into problem solving

Other Measurements: Mode

Median

Standard Deviation 1,2,3

Counts

Relationships/Ratios

Modeling Variables

Easy to calculate, but dives deeper showing opportunities

How to Develop Key Performance Indicators/Metrics

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Financial(Money)

Activity-Based(Work)

TotalRatio

Category1

Category2

Categoryn

Category3

ADJUSTER

POLICY HOLDER

INJURY TYPE

NETWORK SIC INDUSTRY &

CLASS CODES

NEW/RENEW

CLAIM

LEGAL/LITIGATION

LOSS CONTROL

UNDERWRITING

PRICING AUDIT

Red-Flag(Work)

Financial Performance KPI’s

1) Premium-to-surplus Ratio2) ALAE3) ULAE4) Loss Ratio5) Premium Growth6) Written to Earned Premium7) Reserve Development Ratio8) Recurring Revenue to Equity9) Recurring Revenue / EE10) Underwriting Leverage11) Operating Ratio12) UW Expense Ratio

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Activity-based KPIs

1. Cycle Times2. Payment Days3. Claim Durations4. Cancel/Reinstate5. Pre/post loss

inspections6. UW Inspections7. Inventory Load

1. Policy Apps2. Claims3. Matters4. Inspections

8. Re-work - Incomplete apps

9. Declinations

10. Lapses and Attrition11. Collections12. Audit Adjustments13. Sales Volume/Growth14. Commission Ratio15. Sales

Targets/Commitments16. Blocking Ratio17. Reserve Adjustments18. Open/Re-Open/Closed19. Subrogation20. Litigation Ratio21. Litigation payout ratio22. Compliance

Ratio/Penalty

23. News Worthy Incidents24. Scheduled CR/DR 25. Claim Ratio26. Claim Complexity Ratio27. Payment Accuracy28. RX / Opioid / MEDD29. Claim Re-assignments30. Delay and Denial Rates31. Payroll Changes32. Validation

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“RED” Flags as potential measures

• Every vendor provides RED flags as a way to garner referral business.

• The goal is to “validate” these truisms through analytics.

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http://www.ohiobwc.com/basics/guidedtour/generalinfo/empgeneralinfo22.asp

http://www.untied.com/feature/redflag.pdf

1. Number of days worked and amount of salary inconsistent with occupation;

2. Injured worker disputes average weekly wage due to additional income (i.e., per diem and/or 1099 income);

3. Cross-outs, white-outs and erasures on documents;

4. Injured worker files for benefits in a state other than principle location of the alleged industrial injury or occupational disease;

5. Injured worker-listed occupation is inconsistent with employer’s stated business;

Claimant

1. Injured worker does not recall having received the billed service;

2. Provider’s medical reports read almost identically even though they are for different patients with different conditions;

3. Much higher health-care costs than expected for the allowed injury type;

4. Frequency of treatments or duration of treatment period is greater than expected for allowed injury type, especially for older (non-catastrophic) claims;

5. Frequent billing in older (non-catastrophic injury) claims;

Medical Provider

1. Representation letter received within a few days of the incident.

2. Attorney consistently deals with same medical providers.

3. Attorney consistently willing to compromise for low dollar amounts.

4. Attorney is single practitioner with offices in several cities.

5. First notice of claim comes from attorney or medical clinic

Attorney

1. Continued pain or increased pain 3 months post injury

2. Injured Worker referred to a Pain Management Program

3. Injured Worker referred for spine surgery

4. Injured Worker has seen 2 or more care providers for same diagnosis or symptoms

5. Pain mediation is prescribed by more than one medical provider

Chronic Pain

Case Management Associates, Inc.

HEDIS® NQF 0052 Low Back Pain: Use of Imaging

• Use of imaging studies for low back pain: percentage of members with a primary diagnosis of low back pain who did not have an imaging study (plain x-ray, MRI, CT scan) within 28 days of the diagnosis.

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A higher rate represents better performance

US Averages

HEDIS® 0052: Colorado Example

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Opportunity

A higher rate represents better performance

50 California health plans scored from 61 to 90, with 2/3 below High Performance Level of 84.1.

Use of Imaging Studies: Proxy

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This measures hospitals with Outpatients with low back pain who DID NOT have an MRI without trying recommended treatments first such as physical therapy.

Use of imaging studies for low back pain: percentage of members with a primary diagnosis of low back pain who did not have an imaging study (plain x-ray, MRI, CT scan) within 28 days of the diagnosis.

HEDIS®Outpatient Imaging Efficiency Measure

Health Plans Hospitals

A higher rate represents better performance

Not exactly the same measures, but looks for use/overuse

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Proxy for HEDIS® Low Back Imaging

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A higher rate represents better performance

Opportunity:50 points

This measures hospitals with Outpatients with low back pain who DID NOT have an MRI without trying recommended treatments first such as physical therapy.

BEST

WORST

Making Data Actionable

• Defining Data Elements –

• Structured Data (numbers, formatted text)

• Unstructured Data ( text or free-form)

– Name variations: USA, U.S.A., America, United States, United States of America, US, U.S., not to mention typos.

• Care Bridge Approach to Data

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Data in Action

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Precise Data - Surgery

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Precise Data - Drug

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Data Analytics Dashboard

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Drill Down

MSA KPIs

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Carrier Company Nurse Adjuster

Opioids State Attorney Surgery

1.3

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1.5

6.6

0

1

2

3

4

5

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7

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Overall Moderate Severe Catastrophic

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DX Grouping

Day

Overall Moderate Severe Catastrophic

Word Count: “Therapy” vs Claim Cost

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Word Cloud: Services to Claim Cost

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Develop Action Plans for

Outcomes

Identify those that Impact Outcomes

Budget Performance

Staffing Demographics•Hours•Rating•Vendor Mgmt

Compare Treatment Guidelines and UR

Policy, Premiums and Markets

Perform Running Analyses

Identify Strongest Univariates and other Data Elements

Examine Time Periods and Counts

Claim Outcome Measures Claim Operations Measures

Key Performance Indicators

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It’s All About Outcomes

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Date of

Injury

30

MD VisitsDC VisitsRX Fills

MD_RX FillsRX ChangesMD Changes

MD VisitsDC VisitsRX Fills

MD_RX FillsRX ChangesMD Changes

Wage ReplacementWaiting Period Impact

AWWCo-Morbidities

Stay at WorkRepeat Ratio

Disability RatioCase Load Ratio by Complexity

New Data SourcesNew Outcomes for All

New Measures

New Tools & Methods

60“Window of

Suggestibility”

DAYS

References

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Thank You!

Deborah Watkins, CEOP: + 1(888) 434-9326 Ext. 101deborah@carebridgeinc.com

Jim Paugh, SVPP: + 1(888) 434-9326 Ext. 102

jim@carebridgeinc.com

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Care Bridge International, Inc9040 Town Center ParkwayLakewood Ranch, FL 34202

www.carebridgeinc.com