Aligning Technology with Workers Compensation Results

Aligning Technology with Workers Compensation Results

James R. Jones CPCU, AIC, ARMExecutive Director

Katie School InsuranceIllinois State University

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Katie School Project Researchers

Michael R. Williams, Ph.D.Professor of MarketingIllinois State University

Team of academic researchers

James R. Jones, CPCU, AIC, AIS, ARMExecutive Director - Katie School of InsuranceIllinois State University


Katie School of Insurance Research (link to survey)

Corporate Systems sponsored research project to determine the effects of

technology on claim practices

http://katie.cob.ilstu.edu/WorkingPapers/WORKERS%20COMP%20SURVEY%20ver%20final%20for%20Carriers%20TPAs%20Brokers.doc


Research Hypotheses

• Automation has significant potential to facilitate improved results in the Workers’ Comp claim management process.

• Limited automation improvements have been implemented to-date – and those that have are focused on very specific areas, e.g. medical cost management.

• The impediments to major automation-supported business process changes are significant.

The objective was to determine the current and potential effect of technology on improving workers comp claim results


Research Focus

• Why research automation impacts on Workers’ Comp claims?

— Continued economic challenge for this line of business (Subject of many reform efforts)

— The potential for significant savings (both loss and admin costs)

— Current archaic technology

• Research Participants— Insurance carriers with Net Written Premium exceeding $10

million in workers compensation coverage

— Fortune 1000 companies

— Third party administrators (Top 20)

• Why research both carriers/TPA’s and their customers?

— Holistic view

— Determine the differences and assess the implication


Research Methodology

• Literature search

• Phase 1: Qualitative research and analysis— In-depth interviews

— Preliminary survey

• Phase 2: Quantitative research— Credible results based on survey response

• Phase 3: Analysis of research results

Building on previous research and

adding to the body of industry knowledge


RESPONSE CREDIBILITY

• 426 distinct organizations comprised the sample pool— Top 201 Workers Compensation Carriers [distinct entities]

— Top 25 TPAs

— 200 Work Comp Buyers- random sample from Fortune 1000

• 108 organizations responded with completed instruments— Response Rate of 25.4 percent

— 52 Carriers for 25.9 percent Response Rate

— 9 TPAs for a 36 percent Response rate

— 47 W C buying organizations for 23.5 percent response rate

• High Representation and Statistical Confidence— Points of Pain: 95% CI +/-.40

— Usefulness of Technology: 95% CI +/-.55

— Utilization of Technology: 95% CI +/-.75

— Benefits from Technology: 95% CI +/-.35

— Obstacles to Implementation: 95% CI +/-.55


CARRIER RESPONSE CREDIBILITY

• 4 Tier Categories based on WC NPW— Tier 1: NPW = $300,000,000 to $1,500,000,000

— Included 18 entities; 8 Respondents for 44.4% Response Rate

— Tier 2: NPW = $100,000,000 to $299,000,000— Included 42 entities; 8 Respondents for 19.0% Response Rate



• High Representation and Statistical Confidence— Points of Pain: 95% CI +/-.60— Usefulness of Technology: 95% CI +/-.70— Utilization of Technology: 95% CI +/-.80— Benefits from Technology: 95% CI +/-.40— Obstacles to Implementation: 95% CI +/-.60


TPA RESPONSE CREDIBILITY

• Sample included Top 25 TPAs on basis of Administration Claims Paid for the year 2002

— Did not categorize by tier due to small sample

• 9 responses received for overall = 36% Response Rate

• 6 responses received from top-ten = 60 % Response Rate

• Confidence Intervals not applicable


BUYER RESPONSE CREDIBILITY

• 5 Tier Categories based on Annual Revenues— Tier 1: Revenues = $15,000,000,000 to $30,000,000,000

— Included 40 entities; 9 Respondents for 22.5% Response Rate

— Tier 2: Revenues = $5,000,000,000 to $14,000,000,000— Included 40 entities; 9 Respondents for 22.5% Response Rate



— Tier 5: Revenues = Under $1,500,000,000— Included 40 entities; 10 Respondents for 25.0% Response Rate

• High Representation and Statistical Confidence— Points of Pain: 95% CI +/- .55— Usefulness of Technology: 95% CI +/- .90— Utilization of Technology: 95% CI +/-1.10— Benefits from Technology: 95% CI +/- .60— Obstacles to Implementation: 95% CI +/- .70


Key Findings

• Respondent perceptions vary according to respondent type and size.

• Automation can mitigate points of pain and enable significant improvements.

• There is a gap between perceived usefulness and current level of utilization.

• The gap is less for mature technologies and significantly larger for emerging technologies.


Key Findings

• Rising medical costs have achieved “critical status” – outdistancing any other issue.

• Interestingly, the technology that specifically targets this cost driver, medical bill automation, is not only the most “used” technology, it is also perceived as the most “useful”.

• Given that the critical status of this issue, the implications is that existing solutions must be augmented with new solutions to resolve the issue in its current form.


Key Findings

• Technologically sophisticated respondents are not perceiving the same levels of benefit/value as the less technologically sophisticated.

• Strong correlation between perceived benefit and emerging technologies.

• The obstacles to implementation of technology may not be as burdensome as once thought.


Identifying the Key Points of Pain


Points of Pain

0123456789

10

Rising MedicalCosts

GettingWorkers Back

to Work

Lack of DataStandards

EstablishingAccurateReserves

SystemDoesn'tMeasureWhat's

Important Rising medical costs scored significantly higher than all other “points of pain”

Reaching “critical” status – for every type and size of respondent


Technology Assessment

Usefulness Scoring

Utilization Scoring


Technology Assessment

Thirty different technologies were assessed.

These technologies had been identified and validated in the qualitative research.


Substantial Variation in Both Usefulness and Utilization

7.56

5.995.54

8.39

7.18 7.326.74

7.57 7.4

4.97 4.97

5.56

7.48

8.18

7.276.82

7.33

6.016.51

5.014.46

7.446.87

7.23

6.176.71

6.33 6.52 6.36 6.42

5.68

4.07

3.47

6.29

4.92 4.98

4.21

5.03 4.79

2.33 2.232.68

4.57

5.22

4.253.79

4.26

2.813.18

1.6

0.97

3.9

3.133.43

2.34 2.542.05 2.01

1.58 1.43

0

1

2

3

4

5

6

7

8

9

Custom

er loss reporting

Integrated with service bureaus (e.g. IS

O)

Autom

ated claims assignm

ent

Autom

ated medical bill review

Real tim

e interface with nurse case m

anager

Autom

ated forms and letter generator

Autom

ated bill payments to claim

ants

Data conversion

Integrated incident intake and reporting

Autom

ated assignment to case m

anager

Reserving (according to autom

ated rules-basedguidelines)

Cash m

anagement

Electronic paym

ent and reconciliation processes

Tim

ely and accurate detailed loss analysis

Ad hoc exception reports

Electronic docum

ent managem

ent (paperless files)

Electronic D

ata Integration (ED

I)

Autom

ated delivery of e-mails on com

p laws

Autom

ated claims triage

Electronic legal bill audit

Autom

ated rules engine that assists with decision-

making)

Ability to provide loss/risk forecasting (loss

triangles)

Docum

ent scanning and imaging

Autom

ated reserve tracking

Total cost of risk analysis

Loss prevention report & exposure m

apping

Autom

ated fraud indicators

Best practices library

Autom

ated adjustor scorecard

Electronic subm

ission of medical bill by provider

Percived Usefulness

Actual Utilization Estimate


0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

10.00 Automated Med Bill Processing

Loss Analysis

Data conversion

Cust. Loss Reporting

Electronic Payment

Loss Forecasting

Integrated Intake Reporting

EDI

Automated forms and letters

Ad hoc Exceptions Reports

Perceived Usefulness of Technology

The Top 10


Utilization of Technologies

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

10.00 Automated Med Bill Review and Processing

Timely,Detailed Loss Analysis

Customer Loss Reporting

Data Conversion

Integrated Incident Intake and Reporting

Automated Forms and Letter Generator

Electronic Data Integration

Automated Reserve Tracking

Real Time Interface with Nurse CM

Ad hoc Exceptions Reports

The Top 10


Gap Between Usefulness and Utilization

1.88 1.922.07 2.1

2.26 2.342.53 2.54 2.61 2.64 2.74

2.88 2.91 2.96 3.02 3.03 3.073.2

3.33 3.41 3.49 3.543.74 3.8 3.83

4.17 4.284.51

4.784.99

0

1

2

3

4

5

Mature Technologies

Emerging Technologies


Gap Between Usefulness and Utilization

1.88 1.922.07 2.1

2.26 2.342.53 2.54 2.61 2.64 2.74

2.88 2.91 2.96 3.02 3.03 3.073.2

3.33 3.41 3.49 3.543.74 3.8 3.83

4.17 4.284.51

4.784.99

0

1

2

3

4

5

Emerging Technologies

The increasing gap indicates increasing potential of achieving value and benefit.

The largest tier of carriers showed a much higher utilization of the emerging technologies

than did any other group.


Difference in Perceived Usefulness and Actual Utilization (By Largest Differences)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Technology

GA

P

Automated claims triage

Electronic legal bill audit

Automated rules engine that assistswith decision-making)

Ability to provide loss/ risk forecasting(loss triangles)

Document scanning and imaging

Automated reserve tracking

Total cost of risk analysis

Loss prevention report & exposuremapping

Automated fraud indicators

Best practices library

Automated adjustor scorecard

Electronic submission of medical bill byprovider


Claims Technology – Outcomes & Benefits Assessment


Desired Outcomes

• Increase in Productivity of Claims Reviews and Audits

• Reduced Loss Costs

• Improved Return-to-Work

• Reduced Administrative Expenses

• Reduced Frequency and Severity of Losses

• Reduction in Claim Settlement Times


0.02.04.06.08.0

10.012.014.016.018.020.0

Less than5%

5 to 10 % 11 to 15%

16 to 20%

21 to 25%

26 to 30%

Over 30%

Improvement

Per

cen

t A

ttai

nin

g

Overall Carriers

Increase in Productivity of Claims Reviews and Audits Due to Technology


0.0

5.0

10.0

15.0

20.0

25.0

30.0

Less than 5 % 5 to 10 % 11 to 15 % 16 to 20 % 21 to 25 % 26 to 30 %

Extent of Improvement

Per

cen

t A

ttai

nin

g

Overall

Carriers

Reduced Loss Costs Due to Technology


0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

Less than5 %

5 to 10 % 11 to 15 % 16 to 20 % 21 to 25 % 26 to 30 %

Improvement

Pe

rce

nt

Att

ain

ing

Overall

Carriers

Improved R-T-W Due to Technology


0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

Less than 5%

5 to 10 % 11 to 15 % 16 to 20 % 21 to 25 % 26 to 30 % Over 30 %


Per

cen

t A

ttai

nin

g

Overall

Carrier

Reduced Administrative Expenses


0.0

5.0

10.0

15.0

20.0

25.0

Less than 5%

5 to 10 % 11 to 15 % 16 to 20 % 21 to 25 % 26 to 30 % Over 30 %


Per

cent

Att

aini

ng

Overall

Carrier

Reduced Frequency and Severity of Losses


0.0

5.0

10.0

15.0

20.0

25.0

Less than 5%

5 to 10 % 11 to 15 % 16 to 20 % 21 to 25 % 26 to 30 % Over 30 %


Per

cent

Atta

inin

g

Overall

Carrier

Reduction in Claim Settlement


Importance of Improvements Required to Address Points of Pain

0.00

2.00

4.00

6.00

8.00

10.00

Mea

n

Reduce Frequency and Severity

Improve Reserve Accuracy

Improve Customer Satisfaction

Reduce Loss Costs

Improve R-T-W

More Timely Incident Reporting

More Accurate Med. Provider Payment

More Accurate Claim Info.

Better Reporting of Reserve Changes


• Return-to-work

• Loss forecasting accuracy,

• Settlement time

• Timeliness in payments to providers

What’s Not Getting Measured

Measurement is affected by what the system can measure, which is often a

function of the size of the organization


Barriers and Obstacles


• Level of investment to immediate payback (5.35)

• Lack of information on resulting benefits (5.11)

• Legacy systems and processes (5.07)

• Turnover in claims personnel (4.76)

• Lack of data standardization (4.66)

Obstacles in Implementing Technology

MODEL ONE

TECHNOLOGICAL SOPHISTICATION

3002001000

40

30

20

10

0

Observed

Linear

LogarithmicCla

im r

evie

w p

rod

uct

ivit

y140120100806040200

40

30

20

10

0

TECHNOLOGICAL SOPHISTICATION

Cla

im r

evie

w p

rod

uct

ivit

y

MODEL TWO

LEGEND

Observed Values

Linear Relationship

Curvilinear Relationship

Relationship Between Technology and Outcomes(More Technology Doesn’t Necessarily Mean Better Results)


Positive Relationship Between New Technology and Outcomes

D13 D14 D15 D16 D17 D18

Incr

ease

d p

rod

uct

ivit

y o

f cl

aim

rev

iew

s/au

dit

s

Red

uce

d a

dm

inis

trat

ive

exp

ense

s

Red

uce

d lo

ss c

ost

s

Imp

rove

d r

etu

rn-t

o-

wo

rk r

esu

lts

Red

uce

d f

req

uen

cy a

nd

se

veri

ty o

f lo

sses

Red

uct

ion

in t

ime

to

sett

le c

laim

s

2 Integrated incident intake and reporting c4 Automated claims assignment to adjuster c7 Integrated with service bureaus (eg. ISO) X13 Best practices library (Sharing of cost-saving practices) X c X c X14 Electronic document management ( paperless files) X17 Electronic Data Integration (EDI) X19 Electronic submission of medical bill by provider X X20 Automated fraud indicators X21 Ad hoc exception reports (generates reports to defined exception)

22 Electronic legal bill audit X25 Automatic adjuster scorecard card (Customized adjuster activity analysis) X26 Total cost of risk analysis X

LEGEND: X = signif icant at .10 or better; c = nearing statistical signif icance

Claims Technology Technology Competencies

OUTCOMES REALIZED


Conclusions

• There is significant potential for improved results based on leveraging underutilized technologies.

— The potential ranges from 5% to 40% increase in productivity and from 2% to 20% in loss cost reductions.

• It is critical to benchmark and measure practices that will contribute to improving results.

• Effective implementation and system integration of systems will help reduce the gaps.

Documents

Aligning Technology with Workers Compensation Results