PhD Day Faculty of Economics and Business Administration 25/05/2012

PhD Day Faculty of Economics and Business Administration 25/05/2012

STIJN BAERT

BAS VAN DER KLAAUW

GIJSBERT VAN LOMWEL

THE EFFECTIVENESS OF OCCUPATIONAL DOCTORS

AND SPECIALISTS IN THE REDUCTION OF

SICKNESS ABSENTEEISM AMONG SELF-EMPLOYED

Baert, van der Klaauw, van Lomwel (2012) 2

WHY THE ANSWER MAY BE “YES”

Moral hazard in public sickness insurance is found among

employees

Higher sick leave benefits lead to higher sick leave durations (Johansson &

Palme, 2005)

Gatekeeping by physicians is found to be important to reduce

sick leave among them

Postponing certificate requirement led to higher sick durations in SE (Hesselius et al., 2005)

Stricter regulations for certification led to lower sick durations in NO (Markussen, 2010)

ARE OCCUPATIONAL DOCTORS AND SPECIALISTS

EFFECTIVE IN REDUCING SICK LEAVE DURATIONS

AMONG SELF-EMPLOYED?

RESEARCH QUESTION


WHY THE ANSWER MAY BE “NO”

The evidence for employees may not be generalised to the self-employed

Self-employed: financial motives to keep absence durations as short as possible

Self-employed: more satisfied and involved with their jobs (Blanchflower and Oswald, 1998)

Self-employed: need for achievement, love of independence, optimism (Parker, 2004)

Private instead of public health cover

ARE OCCUPATIONAL DOCTORS AND SPECIALISTS

EFFECTIVE IN REDUCING SICK LEAVE DURATIONS

AMONG SELF-EMPLOYED?

RESEARCH QUESTION


Overview

1. Institutional settings and data

2. Econometric model

3. Results

4. Conclusion


Private insurance system

In the Netherlands, sickness insurance for the self-

employed is only available from private insurance

companies

We analyse database of major private Dutch insurance

company

Two importance modalities of insurance contract:

Deferment period: time period between falling sick and start of

benefit payment

Insured income

Active case management in order to enhance recovery

rates

Intake interview and monitoring by case workers

Intervention: medical track and labour track

1 | Institutional settings and data


Intervention: medical track and labour track

Medical track

Occupational doctors (physicians)

Second opinion

Further medical treatment

Labour track

Occupational specialists (work study practitioners)

Ergonomic advise

Coaching



Data selection (1)

All sickness claims (11872) between January 2009 and

December 2011.

Durations until (i) recovery, (ii) medical track and (iii) labour

track

From the start of the deferment period (daily precision)

Censored if sick leave had not been terminated at 31 December 2011.

For each claim: wide range of individual characteristics

Exclusion of ...

Maternity claims (958) and claims with a missing diagnosis type (215).

Claims with missing explanatory variables (31)

Claims with non-positive or inconsistent durations (18)



Data selection (2)

Distinction between 9588 physical and 1062

psychological claims

Patterns of recovery differ by type of disease


Figure: survival function for recovery

0 200 400 600 800 10000

0.2

0.4

0.6

0.8

1Physical claimsPsychological claims

Analysis time (days)

Surv

ival


Data selection (3)

Distinction between 9588 physical and 1062

psychological claims

Patterns of inflow into the intervention tracks differ by type of

disease


0 200 400 600 800 10000

0.2

0.4

0.6

0.8

1Physical claimsPsychological claims

Analysis time (days)

Surv

ival

Figure: survival function for labour track


Double selection problem

Problem 1: correlation between unobserved determinants of

recovery and intervention

Recovery and intervention may be determined by the same

unobservables

This may lead to a spurious relationship

Problem 2: dynamic selection

To evaluate the effect of intervention, the self-employed should not

recover before moment of start of intervention

They must therefore have relatively adverse unobserved characteristics

This may bias the estimated intervention effect towards zero

Solution: Timing of Events approach (Abbring & van den Berg, 2003)

2 | Econometric model


Timing of Events approach

Treatment (1): medical track

Treatment effect (1): effect of medical track on recovery rate

afterwards

Treatment (2): labour track

Treatment effect (2): effect of labour track on recovery rate

afterwards

Use time variation in treatments in order to capture

treatment effects



Econometric framework

r: index recovery; m: index medical track and l: index labour

track

𝜽: hazard rates

t: elapsed durations since start job search

λ: baseline hazards (piecewise constant)

x : vector of observables; v: unobservables (discrete distribution)


Econometric framework


Constant treatment effect model3 | Results

Econometric frameworkConstant treatment effect model

Estimation results treatment effects

Physical claims Psychological claims

Medical track:

Constant 𝜹m,0 -0.59*** (0.05) 0.13 (0.36)

Labour track: Constant 𝜹l,0 -0.78*** (0.09) 0.06 (0.23)


Extended model3 | Results

Econometric frameworkExtended model



Medical

track:

Constant

Early intervention

Middle late

intervention

-0.62***

0.11

0.08

(0.06)

(0.08)

(0.06)

-0.06

0.47**

0.59***

(0.36)

(0.20)

(0.18)

Labour

track:

Constant

Early intervention

Middle late

intervention

-0.76***

0.12

0.10

(0.10)

(0.23)

(0.13)

0.18

-0.09

0.05

(0.27)

(0.20)

(0.15)


Sensitivity analysis 1: delay start of durations

3 | Results

Econometric frameworkExtended model



Medical

track:

Constant

Early intervention

Middle late

intervention

-0.63***

0.09

0.03

(0.06)

(0.08)

(0.06)

-0.06

0.54**

0.57***

(0.36)

(0.21)

(0.21)

Labour

track:

Constant

Early intervention

Middle late

intervention

-0.76***

0.00

-0.03

(0.10)

(0.22)

(0.12)

0.21

-0.10

0.12

(0.28)

(0.18)

(0.16)


Sensitivity analysis 2: gender heterogeneity

3 | Results

Econometric frameworkOther dimensions effect heterogeneity



Medical

track:

Constant

Female

-0.56***

0.06

(0.05)

(0.09)

0.24

-0.48*

(0.36)

(0.27)

Labour

track:

Constant

Female

-0.78***

0.01

(0.09)

(0.14)

0.04

-0.07

(0.23)

(0.25)


Sensitivity analysis 3: tough occupations

3 | Results

Econometric frameworkOther dimensions effect heterogeneity



Medical

track:

Constant

Tough occupation

-0.60***

0.05

(0.08)

(0.07)

0.14

0.09

(0.35)

(0.23)

Labour

track:

Constant

Tough occupation

-0.46***

-0.48***

(0.11)

(0.10)

0.31

-0.40*

(0.27)

(0.23)


Conclusion

Only stable positive effect of early and middle late

intervention by occupational doctors for psychological

claims

All other forms of intervention have a neutral or negative

effect

Self-employed have every interest in keeping absence durations as

short as possible

Occupational doctors and specialists may advise longer sick-leaves

than necessary (Hesselius et al., 2005)

Occupational doctors and specialists may be unable to distinguish

shirkers from truly sick (Carlsen and Nyborg, 2009)

4 | Conclusion

Documents

PhD Day Faculty of Economics and Business Administration 25/05/2012