Nathan Kleinman, PhD Senior Research Analyst and Consultant Human Capital Management Services

Nathan Kleinman, PhDSenior Research Analyst and Consultant

Human Capital Management ServicesAdjunct Assistant Professor, College of Business

University of Wyoming

Introduction to Employer Health Benefit

Data Types and Uses

2006 HCMSGroup. All rights reserved.04/20/23

Introduction to Employer Health Benefits DataIntroduction to Employer Health Benefits Data

Types of Employer Benefits & Data

Levels of Data Granularity

Examples of Employer Data

The Need for Data Integration

Data Uses– Business Management– Research


Types of Employer

Benefits & Data

Types of Employer

Benefits & Data


Types of Employer Benefits & DataTypes of Employer Benefits & Data

Demographics, Salary, Job Type, etc.

– Birth Date– Gender– Hire Date– Race– Salary– Exempt Status– Full-time/Part-time Status– Job Type– Job Title– Etc.



Health Benefits

– Health Insurance (HMO, PPO, Indemnity)– Prescription Drugs (Brand vs. Generic, Tiers)– Dental– Vision– Etc.



Health Risk Appraisals

– May include questions about:• Height

• Weight

• Blood pressure

• Smoking status

• Alcohol consumption

• Exercise

– May be required to get lower health insurance premium or in conjunction with gym membership

– May be administered by corporate doctor or may be self-report



Health-related Absence

– Sick Leave– Short-term Disability – Long-term Disability– Workers’ Compensation

– Family & Medical Leave Act (FMLA)



Other Absence

– Vacation– Paid Time Off (PTO)– Holidays– Floating Holidays– Military leave– Bereavement leave– Others



Productivity, Performance

– Population examples• Profit per store

• Graduates per professor

– Person-level examples• Self-report productivity surveys

• Manager performance reviews

• Widgets produced, calls answered, boxes moved per day


Levels of Data GranularityLevels of Data Granularity


Levels of Data GranularityLevels of Data Granularity

Population– Each record summarizes data for many people

Person– One record per person

Leave– Example: One record per sick leave episode or disability leave of absence– Possibly several records per person

Transaction, Payment– Example: One record per medical service or prescription– Example: One record per disability leave payment– Many records per person


Employer Data ExamplesEmployer Data Examples


Data Examples – Health Insurance ClaimsData Examples – Health Insurance Claims

IDPAT

GENDRELA-TION

PAT BIRTH DT

SERVICE DATE

ICD9 CODE

PROC CODE BILLED ALLOWED INELIG DEDUCT COINSUR COPAY PAID PAID DT

0500792 F E 5/15/1955 11/5/2001 46500 99213 $66 $66 $0 $0 $0 $15 $34 11/30/20010500792 M D 10/3/1985 10/14/2001 84210 73140 $28 $28 $0 $0 $0 $0 $8 11/30/20010500792 M D 10/3/1985 10/14/2001 84210 29125 $76 $76 $0 $0 $0 $0 $60 11/30/20010500792 M D 10/3/1985 10/14/2001 84210 7100 $347 $347 $0 $0 $0 $0 $347 10/31/20010500792 M D 10/3/1985 10/18/2001 71944 99213 $98 $98 $0 $0 $0 $15 $34 11/30/20010500792 M S 9/4/1957 12/4/2001 46600 99213 $66 $66 $0 $0 $0 $15 $34 12/31/20010500792 M D 10/3/1985 10/2/2001 46590 99213 $67 $67 $0 $0 $0 $15 $34 10/31/20010500792 F E 5/15/1955 10/30/2001 72310 72052 $171 $171 $0 $0 $0 $0 $63 11/30/20010500792 F E 5/15/1955 10/25/2001 00068 93000 $55 $55 $0 $0 $0 $0 $28 11/30/20010500792 M D 10/3/1985 10/14/2001 84210 9000 $105 $105 $0 $0 $0 $0 $105 10/31/20010500792 M D 10/3/1985 10/14/2001 84210 9000 $188 $188 $0 $0 $0 $50 $138 10/31/20010500792 F E 5/15/1955 10/26/2001 00068 80053 $40 $40 $0 $0 $0 $0 $12 11/30/20010500792 F E 5/15/1955 10/25/2001 00068 99396 $150 $150 $0 $0 $0 $15 $92 11/30/20010500792 M D 10/3/1985 10/14/2001 84210 99283 $158 $158 $0 $0 $0 $0 $64 11/30/20010500792 F E 5/15/1955 2/2/2002 72910 99213 $66 $66 $0 $0 $0 $15 $34 2/28/20020500792 F E 5/15/1955 1/22/2002 24290 84443 $118 $118 $0 $0 $0 $0 $17 1/31/20020500792 F E 5/15/1955 1/22/2002 24290 99213 $66 $66 $0 $0 $0 $15 $34 2/28/20020500792 M S 9/4/1957 1/25/2002 00068 99215 $137 $137 $0 $0 $0 $15 $99 2/28/20020500792 F E 5/15/1955 1/22/2002 24290 85651 $26 $26 $0 $0 $0 $0 $4 1/31/20020500792 F E 5/15/1955 10/25/2001 00068 80061 $64 $64 $0 $0 $0 $0 $13 1/31/20020500792 F E 5/15/1955 10/25/2001 00068 80050 $187 $187 $0 $0 $0 $0 $40 1/31/20020500792 F E 5/15/1955 1/28/2002 72100 72141 $1,395 $1,395 $0 $0 $0 $0 $1,042 2/28/20020500792 F E 5/15/1955 10/25/2001 00068 85651 $26 $26 $0 $0 $0 $0 $4 1/31/20020500792 M S 9/4/1957 5/16/2002 00068 85025 $33 $33 $0 $0 $0 $0 $8 5/31/20020500792 M S 9/4/1957 5/16/2002 00068 80053 $50 $50 $0 $0 $0 $0 $11 5/31/20020500792 M D 10/3/1985 3/25/2002 71946 99214 $125 $125 $0 $0 $0 $15 $61 4/30/2002


Data Examples – Prescription Drug ClaimsData Examples – Prescription Drug Claims

IDPAT

GENDRELA-TION

PAT BIRTH DT RX NUM FILL DT NDC CODE DRUG NAME

REFILL NUM QTY

DAYS SUPPLY COPAY PAID BILLED

0034450 2 1 8/29/1965 006424704 9/30/2003 00062535601 TERAZOL 3 1 20 3 $15 $22 $370034450 2 4 6/13/1995 006474847 5/26/2003 00026853110 CIPRO HC 0 10 7 $15 $54 $690034450 2 1 8/29/1965 006941196 7/2/2003 64731082001 DUET 0 30 30 $18 $0 $180034450 2 1 8/29/1965 006941196 9/4/2003 64731082001 DUET 2 30 30 $18 $0 $180034450 2 1 8/29/1965 006941196 8/4/2003 64731082001 DUET 1 30 30 $18 $0 $180034450 2 1 8/29/1965 006424704 9/20/2003 00062535601 TERAZOL 3 0 20 3 $15 $22 $370034450 2 1 8/29/1965 006947977 8/22/2003 00149071001 MACROBID 0 14 7 $15 $12 $270034450 2 1 8/29/1965 006835577 11/21/2001 00062190315 ORTHO TRI-CYCLEN 0 28 28 $10 $21 $310034450 2 1 8/29/1965 006949807 9/4/2003 00062535601 TERAZOL 3 0 20 3 $15 $22 $370034450 1 3 5/9/1998 006947155 8/15/2003 63304097004 AMOXICILLIN 0 200 10 $5 $14 $190034450 1 3 5/9/1998 006949884 9/5/2003 00006071131 SINGULAIR 0 30 30 $15 $65 $800034450 2 4 6/13/1995 006815044 8/6/2001 63395010110 FLOXIN OTIC 0 10 15 $10 $45 $550034450 2 4 6/13/1995 006849062 1/29/2002 00029604955 AMOXIL 0 150 10 $10 $7 $170034450 1 3 5/9/1998 006865072 10/22/2002 00085112802 CLARITIN 1 30 30 $15 $82 $970034450 1 3 5/9/1998 006822946 9/19/2001 00085112802 CLARITIN 0 30 30 $10 $71 $810034450 1 3 5/9/1998 006822946 11/10/2001 00085112802 CLARITIN 1 30 30 $10 $71 $810034450 1 3 5/9/1998 006822946 2/1/2002 00085112802 CLARITIN 2 30 30 $10 $73 $830034450 1 3 5/9/1998 006822947 9/19/2001 00085119701 NASONEX 0 17 25 $10 $43 $530034450 1 3 5/9/1998 006849681 1/31/2002 00029604959 AMOXIL 0 100 10 $10 $2 $120034450 1 3 5/9/1998 006865072 4/17/2002 00085112802 CLARITIN 0 30 30 $10 $81 $910034450 2 1 8/29/1965 006829411 7/18/2002 00088109047 ALLEGRA-D 4 60 30 $25 $47 $720034450 2 1 8/29/1965 006829411 9/21/2002 00088109047 ALLEGRA-D 5 60 30 -$25 -$47 -$720034450 2 1 8/29/1965 006829411 9/21/2002 00088109047 ALLEGRA-D 5 60 30 $25 $47 $720034450 2 1 8/29/1965 006829411 10/5/2002 00088109047 ALLEGRA-D 5 60 30 $25 $47 $720034450 2 1 8/29/1965 006775676 9/18/2001 00062190315 ORTHO TRI-CYCLEN 9 28 28 $10 $21 $310034450 2 1 8/29/1965 006775676 10/22/2001 00062190315 ORTHO TRI-CYCLEN 10 28 28 $10 $21 $310034450 2 1 8/29/1965 006775676 8/30/2001 00062190315 ORTHO TRI-CYCLEN 8 28 28 $10 $21 $310034450 2 1 8/29/1965 006827079 10/10/2001 00029608012 AUGMENTIN 0 20 10 $10 $63 $73


The Need for Data IntegrationThe Need for Data Integration


The Problem of Separate SilosThe Problem of Separate Silos

Human Resource

Data

Workers’ Comp Data

Health Care Data

Disability Data

Productivity Data

Sick Leave Data

Drug Data


Cost Shifting from One Benefit Silo to AnotherCost Shifting from One Benefit Silo to Another

Total Cost Balloon

$$$

Hokey Corporate Benefits Manager


Integrated Information Eliminates SilosIntegrated Information Eliminates Silos

Workers’Compensation

Data

Drug Data

HRData

Sick Leave Data

Productivity Data

Disability Data

Integrated Person-Centric

Database

Medical Insurance Data


Uses of Employer DataUses of Employer Data


Business ManagementBusiness Management


Sample Employee Total Compensation Analysis(A Days Pay for a Days Work)

Sample Employee Total Compensation Analysis(A Days Pay for a Days Work)

Insurance, 10.2%

PTO, 4.2%

Training, 2.9%

Retirement, 11.8%

Taxes, 4.8%

Wages, 70.1%


Sample Integrated Health Benefits Trend AnalysisSample Integrated Health Benefits Trend Analysis

Adjusted for Inflation

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd 4th 1st 2nd 3rd

2002 2003 2004 2005

Ave

rag

e C

ost

per

Em

plo

yee

Employee Medical Employee Drug Dependent Medical Dependent Drug STD LTDWC Sick Leave

39% Increase


Integrated Benefits ManagementAd Hoc Pareto Analysis

Analytic Finding:

14 percent of the workers used 80 percent of the total health benefits claim cost.

Analytic Finding:

14 percent of the workers used 80 percent of the total health benefits claim cost.

8.6%

8.6%

27.6%

35.2%

14% 80%

EMPLOYEESTOTAL HEALTH CLAIMS COST

Non-Pareto Workers

86%

Non-ParetoCosts20%

WC Medical

STD/LTD

WC Indemnity

Group Health

Non-Pareto

Pareto

Pareto Group

WC Ind.

WC Med.GH

STD/LTD

Source: OCI Research Group


Person-Centric/Human Capital Approach

The Type of People Using Health Benefits

Cost per Person

% of LTD STD WCI WCM GHMAll

Benefits% of Total

People People $ $ $ $ $ $ Cost

Benefits-Centric/Medical Approach

No Disability Claims

90% 0 0 0 48 504 551 26%

With DisabilityClaims

10% 1,290 1,912 5,399 3,361 3,391 15,352 74%

Integrated Disability and Total Benefits Management

The Type of Health Benefits People Use

LTD3%

STD4%

WCI10%

WCM9%

GHM74%

Medical Managed

Care

Source: OCI Research Group


Increases in LTD Claims Rate From a 10% Increase in each Variable

0.070%

0.324%

0.452%

0.768%

0.833%

0.543%

0.001%

0.003%

-15.000% -10.000% -5.000% 0.000% 5.000% 10.000% 15.000% 20.000%

Suspensions

FMLA Claims

Medical Insurance Costs

STD Claims

West Region

East Region

POS Medical Plan

WC Claims

1.310%

1.791%

4.121%

14.418%

Sick Leave

Female

WC Wait Period

Age

-5.538%

-1.958%

-13.208%

Exempt

Pay for Performance

STD Wait Period


$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

$80,000

$90,000

1st Quintile 2nd Quintile 3rd Quintile 4th Quintile 5th Quintile

Av

era

ge

Co

st

pe

r E

mp

loy

ee

Employee Medical Employee Drug Dependent MedicalDependent Drug WC Medical WC IndSTD LTD Sick Leave

High Risk Group5% of Employees

Moderate Risk Group15% of Employees

Low Risk Group80% of Employees

Sample Integrated Health Benefits Pareto Analysis with Dependent Costs

Sample Integrated Health Benefits Pareto Analysis with Dependent Costs

Quintile Avg. Cost Cost Range Medications

1 $1,000 $0-$4000 3

2 $5,000 $4000-$10,000 5

3 $15,000 $10,000-$25,000 10

4 $30,000 $25,000-$40,000 12

5 $75,000 $40,000-$450,000 16

Average Cost: $2,000


Pareto 1st and 5th Quintile Utilization Comparative AnalysisPareto 1st and 5th Quintile Utilization Comparative Analysis

Time Period 10/1/04 – 9/30/05

1st Quintile (N=16,000)

5th Quintile (N=200)

Ratio of 5th to 1st

Percent Change 5th to

1st

Number of Diagnoses per person 3.0 20.6 6.9 587%

Number of Providers per person 2.5 19.5 6.1 514%

Number of Medications per person 3.3 16.4 5.0 397%

Number of Tests per person* 4.6 42.8 9.3 830%

*MRI, Radiology, Lab Procedures and ER Procedures


Time Period 7/1/04 – 6/30/05

$169

$297

$1,1

27

$3,2

38

$973

$705 $2

,869

$5,9

79

$15,

783

$49,

576

$1,0

01

$2,5

85

$4,0

64

$2,9

98

$3,7

64

$8 $14

$355

$325

$9,1

37

$293

$938 $2

,918

$9,5

13

$33,

728

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000


Ave

rag

e C

ost

per

Em

plo

yee

Metabolic Concurrent Medical Drug WC Income Replacement

High Risk Group52 Employees

Moderate Risk

Low Risk Group

Average Cost per Employee: $6,969

Quintile Population Avg. Cost Cost Range Medications1 571 (63.9%) $2,176 $0-$4,659 52 185 (20.7%) $6,703 $4,672-$9,803 93 86 (9.6%) $14,443 $9,851-$23,923 114 39 (4.4%) $31,858 $23,972-$48,673 155 13 (1.5%) $97,178 $50,020-$210,677 13

Diabetes/Cardio Metabolic Integrated Disease Pareto Analysis

Diabetes/Cardio Metabolic Integrated Disease Pareto Analysis


Integrated Cost ProfileMental and Nervous Claimants

Integrated Cost ProfileMental and Nervous Claimants

Productivity Loss Cost$4,300

Administrative Cost$854

Other Medical Cost$2,933

WC Cost$1,867

Disability Cost$18,010

3,637 People over 2 years

Mental & Nervous ICD9s$854

Total Health & Productivity Cost $28,818

(3% of Total)


Health Benefits Cost Shifting Analysis

Analysis comparing WC costs for HMO and Traditional Health Care Plans

# of Employees WC CostsTraditional Health Plan 18,000 $ 850HMO 4,000 $1,200

Potential Savings: $1.4M annually ($350 per employee)


ResearchResearch


Cost of Bipolar DisorderCost of Bipolar Disorder


Descriptive ComparisonEmployees with Bipolar Disorder vs. Employees without Bipolar Disorder

Descriptive ComparisonEmployees with Bipolar Disorder vs. Employees without Bipolar Disorder

Variable

Employees with Bipolar Disorder (N=761)

Employees without Bipolar Disorder (N=229,145)

Mean Mean DifferenceAge (at index date) 41.16 40.41 0.75 *Tenure (at index date) 10.63 9.76 0.86 *Percent Female 54.40% 44.48% 9.92% *Percent Married 46.15% 55.98% -9.83% *Percent White 83.53% 65.08% 18.45% *Percent Black 9.12% 21.26% -12.15% *Percent Hispanic 4.12% 7.96% -3.84% *Percent Exempt 21.16% 27.33% -6.17% *Percent Full-time 89.09% 85.70% 3.39% *Annual Salary $47,351 $48,468 -$1,117Zipcode 1st Digit = 0 18.79% 12.46% 6.33% *Zipcode 1st Digit = 1 22.34% 15.43% 6.91% *Zipcode 1st Digit = 2 18.79% 14.15% 4.64% *Zipcode 1st Digit = 3 14.06% 22.54% -8.48% *Zipcode 1st Digit = 4 3.29% 5.34% -2.05% *Zipcode 1st Digit = 5 0.13% 0.68% -0.55% *Zipcode 1st Digit = 6 2.76% 3.00% -0.24%Zipcode 1st Digit = 7 5.78% 9.59% -3.81% *Zipcode 1st Digit = 8 4.60% 4.30% 0.30%Zipcode 1st Digit = 9 9.46% 12.44% -2.98% ** Statistically significant difference (p<0.05)


Comparison of Annual Cost per PersonComparison of Annual Cost per Person

Bipolar vs. Non-bipolar vs. Other Mental Disorders vs. No Mental Disorders

Comparison of Annual Cost1 per Person$5

,492

$2,4

96

$489 $9

75

$118 $413

$9,9

83

$1,6

32

$630

$408

$307

$10

$159

$3,1

47

$3,6

98

$1,2

52

$503

$580

$28

$208

$6,2

68

$1,2

37

$496

$353

$255

$6 $163

$2,5

10

$0

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

Medical PrescriptionDrug

Sick Leave Short-termDisability

Long-termDisability

Workers'Compensation

Total Cost

Adj

uste

d2 A

nnua

l Cos

t per

Per

son

Bipolar Employees(N=761)

Employees without Bipolar(N=229,145)

Other Mental Disorder Employees(N=26,776)

Employees without Other Mental Disorders(N=185,802)

1 Costs are measured during the year following each person's index date. For bipolar patients, the index date is the date of the first bipolar diagnosis in 2001. For other mental patients,

the index date is the date of the first mental disorder diagnosis (non-bipolar) in 2001. For all other population groups, the index date is the average index date from the bipolar employee group.2 Costs shown are adjusted using regression modeling and controlling for age, tenure, gender, marital status, race, exempt status, full-time/part-time status, salary, and location.


Comparison of Annual Absence Days per PersonComparison of Annual Absence Days per Person

Bipolar vs. Non-bipolar vs. Other Mental Disorders vs. No Mental Disorders

Comparison of Annual Absence Days1 per Person

5.2

11.0

1.4 1.3

18.9

3.3 3.2

0.10.7

7.4

5.06.0

0.3 0.8

12.2

2.7 2.7

0.1 0.6

6.1

0

2

4

6

8

10

12

14

16

18

20

Sick Leave Short-term Disability Long-term Disability Workers'Compensation

Total Days

Adj

uste

d2 A

nnua

l Day

s pe

r P

erso

n

Bipolar Employees(N=761)

Employees without Bipolar(N=229,145)

Other Mental Disorder Employees(N=26,776)

Employees without Other Mental Disorders(N=185,802)

1 Days are measured from leaves begun during the year following each person's index date. For bipolar patients, the index date is the date of the first bipolar diagnosis in 2001.

For other mental disorder patients, the index date is the date of the first mental disorder diagnosis (non-bipolar) in 2001. For all other population groups, the index date is

the average index date from the bipolar employee group.2 Days shown are adjusted using regression modeling and controlling for age, tenure, gender, marital status, race, exempt status, full-time/part-time status, salary, and location.


Real Productivity Output While at Work

0

5

10

15

20

25

30

Bipolar DisorderEmployees

(N=59)

Employees withoutBipolar Disorder

(N=27,574)

Other Mental DisorderEmployees (N=1,382)

Employees withoutMental Disorders

(N=25,268)

Healthy Employees (N=18,179)

Study Population

Un

its P

roce

ssed

Per

Ho

ur

Wo

rked

0

5

10

15

20

25

30

Mean Adjusted Units Processed Per Hour 95% Confidence Upper Limit 95% Confidence Lower Limit

1 Productivity output measurements come from real worker output data. This data provides the number of units processed

(units of work performed) and number of hours worked for each employee on a daily basis.2 Productivity output measurements are taken during the year following the employee's index date. For bipolar patients, the index

date is the date of the first bipolar diagnosis in 2001. For other mental disorder patients, the index date is the date of the first mental

disorder diagnosis (non-bipolar) in 2001. For other employees, the index date is the average index date from the bipolar employee group.

3 The populations in this study were restricted to those employees with productivity data. Outliers were removed (>4 standard deviations).4 Productivity output measurements shown are adjusted using regression modeling and controlling for age, tenure, gender,

marital status, race, exempt status, full-time/part-time status, salary, and location. Differences in adjusted units processed per hour

between population groups are not statistically signifcant (p>0.05). 5 Employees were defined to be "healthy" if they had less than $500 in medical costs paid by their employer, no short- or long-term

disability costs, and no workers' compensation disability costs during the year after their index date.


Real Annual Productivity OutputReal Annual Productivity Output

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

Bipolar DisorderEmployees

(N=59)

Employees withoutBipolar Disorder

(N=27,574)

Other Mental DisorderEmployees (N=1,382)

Employees withoutMental Disorders

(N=25,268)

Healthy Employees (N=18,179)

Study Population

Un

its P

roce

ssed

Per

Yea

r

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

Mean Adjusted Units Processed Per Hour 95% Confidence Upper Limit 95% Confidence Lower Limit

1 Productivity output measurements come from real worker output data. This data provides the number of units processed

(units of work performed) for each employee on a daily basis.2 Productivity output measurements are taken during the year following the employee's index date. For bipolar patients, the index

date is the date of the first bipolar diagnosis in 2001. For other mental disorder patients, the index date is the date of the first mental

disorder diagnosis (non-bipolar) in 2001. For other employees, the index date is the average index date from the bipolar employee group.

3 The populations in this study were restricted to those employees with productivity data. Outliers were removed (>4 standard deviations).4 Productivity output measurements shown are adjusted using regression modeling and controlling for age, tenure, gender,

marital status, race, exempt status, full-time/part-time status, salary, and location. Differences in adjusted units processed per year between

bipolar employees and employees without bipolar, employees without mental disorders, and healthly employees are statistically signifcant (p<0.05). 5 Employees were defined to be "healthy" if they had less than $500 in medical costs paid by their employer, no short- or long-term

disability costs, and no workers' compensation disability costs during the year after their index date.


Annual Medical Cost per Person by Major Diagnostic Category (during the year following each person's index date1)

$0

$400

$800

$1,200

$1,600

$2,000

BLO

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CIR

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CO

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Ann

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Bipolar Employees Employees without Bipolar Other Mental Employeees Employees without Mental

1 For bipolar patients, the index date is the date of the first bipolar diagnosis in 2001. For other mental patients, the index date is the date of the first mental disorder diagnosis (non-bipolar) in 2001. For all other population groups, the index date is the average index date from the bipolar employee group.


Annual Medical Cost per Person by Specific AHRQ Disease Category(during the year following each person's index date 1)

$147

$242

$129

$101

$50

$50

$48

$44 $5

6

$15

$19

$21

$17

$16

$116

$11

$47

$9

$24

$28

$31

$17

$17

$15

$10

$166

$27

$288

$102

$96

$83

$123

$81

$62

$44

$39

$29

$17

$0

$15

$87

$0

$40

$0

$11 $2

1

$26

$11

$14

$13

$9

$0

$100

$200

$300

$400

$500

Affe

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ost

per

Per

son

Bipolar Employees Employees without Bipolar Other Mental Employeees Employees without Mental

$1,5

99

1 For bipolar patients, the index date is the date of the first bipolar diagnosis in 2001. For other mental patients, the index date is the date of the first mental disorder

diagnosis (non-bipolar) in 2001. For all other population groups, the index date is the average index date from the bipolar employee group.


Average Benefit Cost for Employees with Bipolar Disorder by Medical and Drug Cost Quintile

Average Benefit Cost for Employees with Bipolar Disorder by Medical and Drug Cost Quintile

1 The 761 employees with bipolar disorder were ranked according to their total medical and drug cost during the year following their index date. After begin ranked, the

employees were grouped into five quintile groups such that the total medical and drug cost for each quintile group summed to 20 percent of the overall total medical and drug cost.2 For bipolar patients, the index date is the date of the first bipolar diagnosis in 2001.

Average Benefit Cost for Employees with Bipolar Disorder

by Medical and Drug Cost Quintile1,2

$346

$1,1

44

$2,8

21 $7,1

43

$6,9

85

$870 $3

,476 $7

,528

$16,

203

$52,

365

$436

$1,0

39

$1,2

49

$1,7

57

$892

$770 $1

,857

$2,1

44

$2,3

96 $5,0

36

$263

$15

$125

$0 $1,0

58

$335

$741

$612

$560

$629

$365

$813 $1

,901

$7,5

70

$3,6

51

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000


Ave

rag

e C

ost

Bipolar Medical Cost Concurrent Conditions Medical Cost Bipolar-related Drug CostOther Drug Cost Workers' Compensation Medical Cost Sick Leave CostCosts Due to Other Lost Time

Avg. Cost $3,385 N=469 (61.6%)

Avg. Cost $9,084 N=151 (19.8%)

Avg. Cost $16,380N=83 (10.9%)

Avg. Cost $35,630N=40 (5.3%)

Avg. Cost $70,616N=18 (2.4%)

Nathan Kleinman, PhD Senior Research Analyst and Consultant Human Capital Management Services

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