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An independent licensee of the Blue Cross and Blue Shield Association. U7430b, 2/11 Impact of Employee Health on Workers’ Compensation 10/6/2017 Brian Caveney CMO, BCBSNC

Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

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Page 1: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

An independent licensee of the Blue Cross and Blue Shield Association. U7430b, 2/11

Impact of Employee Health

on Workers’ Compensation

10/6/2017

Brian Caveney

CMO, BCBSNC

Page 2: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

$Lifestyle Behaviors

What’s the Connection?

2

Page 3: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Why are Health Care Costs Rising?

Aging population

Population growth

New technology

Prescription drugs (new + price)

Defensive medicine

Government mandates

Hospital consolidation

Lifestyle-related conditions

Redundancy, inefficiency, ineffectiveness6.5%

Health care costs

rising

annually*

*“Medical cost trends 2007-2017,” PricewaterhouseCoopers LLP. www.pwc.com (Accessed Feb.6 2017).

Page 4: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

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Page 5: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Medical costs are the

“tapeworm of American

economic competitiveness”

Warren Buffet, 5/6/2017

5

Page 6: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based
Page 7: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

A Bigger Bite of Income

Percent change in middle-income households’ spending on basic needs(2007-2014)

Page 8: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Stress & Anxiety

F.A.T.

SleepPhysicalMental

Health factors

Medical& Rx Job

factors

Economy

Finances

Home life

Personal issues

Page 9: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Employee health status

Healthy9%

At Risk27%

Chronic Low Risk 48%

ChronicHigh Risk

8%Complex

8%

Risk Flow

Page 10: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

An independent licensee of the Blue Cross and Blue Shield Association. U7430b, 2/11

IT’S NOT THAT EASY

Poor employee health =

increased costs from

medical bills, more

sick days and lower

productivity.

“Insanity: Doing the

same thing over and

over again and

expecting different

results.”

– Albert Einstein

For years, employers

have been doing the

same things to try and

change employee

behaviors like direct

mail, payroll stuffers

and worksite posters.

Solution? Change

employee behavior –

eat better, get more

exercise, take their

prescription drugs and

utilize preventive care

10

Page 11: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

“If we could give every individual

the right amount of nourishment

and exercise, not too little and

not too much, we would have

found the safest way to health.”

Hippocrates, circa 370 BC

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Page 12: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

© www.popular-pics.com

Page 13: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Male and Female Differences

Page 14: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Obesity in America

Page 15: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Odds of Incurring an Acute Sprain or Strain

1

2.22

3.79

1.49

0

0.5

1

1.5

2

2.5

3

3.5

4

BMI < 25 BMI 25 - 30 BMI 30 - 40 BMI > 40

odds ratio

Source: Pollack et al. A J Epi 166(2) 2007

Obesity’s Impact on WC Claims

Page 16: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Ostbye, T. et al. Arch Intern Med 2007;167:766-773

Mean Indemnity Claims Costs, Medical Claims Costs, and Number of Lost Workdays per Claim

by Body Mass Index (BMI) Category

11x

7x

13x

Normal

BMI

Page 17: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Relationship between BMI and Workers’ Comp Costs

Copyright © 2017 American College of Occupational and Environmental Medicine 17

Source: Chenoweth, David H.; Rager, Robin C.; Haynes, Robert G. Relationship Between Body Mass Index and Workers’ Compensation Claims and Costs: Results From the North Carolina League of Municipalities Database. Journal of Occupational and Environmental Medicine. 57(9):931-937, September 2015. doi: 10.1097/JOM.0000000000000506

Page 18: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Cost Differences in Diabetes and Pre-diabetes

18

Source: 2017 Internal BCBSNC Data – commercial BoB

Page 19: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Source: © Castlight Health 2017: http://www.castlighthealth.com/pdf/Castlight-Report-Opioid-Crisis-

In-Workforce-web.pdf

Page 20: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Where do they get the Opioids?

• An estimated 52

million Americans

have used prescription

drugs for non-medical

purposes 54.2%Free from friend or relative

16.6%Bought/took from friend or relative

18.1%One doctor

5%Other

5.7%Bought/took from relative5.5%

Free from friend or relative

3.1%More than one doctor

2.2%Other

1.9%Drug

dealer or stranger

0.2%Bought on the

internet

3.9%Drug dealer or stranger

1.9%More than one doctor

0.3%Bought on the internet

81.6%One doctor

Source: Link: http://www.drugabuse.gov/related-topics/trends-

statistics/infographics/popping-pills-prescription-drug-abuse-in-america, 2011

Page 21: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

High Risk

Moderate - HighRisk

Moderate Risk

Low Risk

Identification of Patients at Risk

Risk Stratification Algorithm is based on:

1. Number of prescriptions filled in the last 90 days

2. Morphine Equivalent Dose

3. Front end platform based risk assessment

Total Members

Total Members 2, 513, 930

Non Users 1,989,138 (79%)High Risk

3 or more fills in 90 day period with more than a 120 MED

10,229(1%)

Moderate-High Risk3 or more fills in a 90 day period with an MED of less

than 120

75,064(3%)

Moderate Risk2 fills in a 90 day period with an MED of less than

120

82,443(3%)

Low Risk1 fill in a 90 day period

357,056(14%)

Page 22: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Correlations to Dx and Use

HIGH RISK COMPARED TO NON-USERS

ODDS RATIO (p<.001)

Spondylosis and other back problems

5.3

Substance Related and Addictive Disorders

4.6

Sleep-Wake Disorders 2.2

Depressive Disorders 1.7

Headache 2.1

Anxiety Disorders 1.5

HIGH RISK COMPARED TO NON-USERS

ODDS RATIO (p<.001)

Substance Abuse Services 4.5

Anesthesia 4.2

ER 3.2

Mental Health Services 2.3

Surgery 2.0

OP Surgery 1.3

Predictors: Diagnoses

Predictors: Utilization

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Page 23: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Opioid Use Management

.

Prevention/Education Control/Limit Use Addiction treatment

• Provider education on portal• 100% Coverage for

alcohol/drug screening• Quarterly letters to providers

sharing potential abuse• Screening during case

management enrollment

• 24 hour phone line• Network of Substance

abuse professionals and facilities

• Medication Assisted Therapy Coverage

• TROSA substance abuse recovery center funding

• PA/QL on all extended release opiates

• Drug testing in pain management/substance abuse treatment (medical policy)

• Pharmacogenetic testing for drug metabolism (medical policy)

• Claims edits

Page 24: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Opioid Considerations

• STOP Act in North Carolina

• Standing order for Naloxone

• Fraud, Waste & Abuse Investigations

• Out of state marketing efforts

• Take Back Boxes

• Network expansion

• Drug costs

• EAP programs

• Drug Free Workplace Program

• “Goldman Sachs thinks the opioid crisis is so bad it’s

affecting the economy” © cnbc.com 7/6/2017

Page 25: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Mental Health & Substance Use Disorders

25

Source: Kamal, Cox & Rousseau. Costs and Outcomes of Mental Health and Substance Use

Disorders in the US. JAMA August 1, 2017.

http://jamanetwork.com/journals/jama/fullarticle/2646703

Page 26: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Employees

Health

plan

Cafeteria planningFacilities

Mgmt

Occ

healthSafety

HR / Benefits

Operations

Disability

Legal

Create an Integrated Strategy

FoodFacilities

Page 27: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

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Page 28: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

TWH® Hierarchy of Controls

28Source: https://www.cdc.gov/niosh/twh/letsgetstarted.html

Page 29: Impact of Employee Health on Workers’ Compensation · Risk Moderate - High Risk Moderate Risk Low Risk Identification of Patients at Risk Risk Stratification Algorithm is based

Think about your employees’ total health

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