Factors associated with return-to-work and health outcomes among survivors of road crashes in Victoria

2010 vol. 34 no. 2 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH 153© 2010 The Authors. Journal Compilation © 2010 Public Health Association of Australia

Factors associated with return-to-work and

health outcomes among survivors of

road crashes in Victoria

Michael FitzharrisAccident Research Centre, Monash University, Victoria, and Monash South Africa, Ruimsig, South Africa

Diana BowmanMelbourne School of Population Health, Melbourne University and Accident Research Centre, Monash University, Victoria

Karinne LudlowFaculty of Law, Monash University, Victoria

The social and economic cost of

traffic-related injury in Australia

h a s b e e n e s t i m a t e d t o b e

$15 billion annually, with lost productivity

and workplace disruption representing

23% of this economic cost, second only to

vehicle repairs (27%).1 As an expression of

social reintegration, return to work (RTW)

is perceived to be a key milestone in the

rehabilitation of the injured patient.2

There is a significant body of literature

examining rates and factors associated with

RTW among injured populations. Much of

this literature has, however, focused on a

particular type of injury such as traumatic

brain injury,3 spinal cord injury4,5 and lower

extremity injury.6 Among inclusive studies,

RTW rates range from 60-90%, one to two

years following major trauma.2,7-10 Younger

age, higher educational level, higher pre-

injury income and positive social support

have been associated with improved RTW

outcomes.2,6,9,11 Indicators of injury severity

(e.g. length of stay) and disability associated

with traumatic brain injury (TBI), spinal cord

injury (SCI) and orthopaedic trauma are

associated with lower rates of RTW.2,6,9,11-13

Studies that have examined the nature of

‘work’ indicate that ‘blue collar’ or manual

workers have slower RTW rates than their

‘white collar’ counterparts.2,6,13,14

Submitted: May 2009 Revision requested: July 2009 Accepted: November 2009Correspondence to:Dr Michael Fitzharris, Accident Research Centre, Monash University, Victoria, Australia 3800. Fax: +61 3 9905 4363; e-mail: [email protected]

Abstract

Objective: To explore the relationships

between injury, disability, work role

and return-to-work outcomes following

admission to hospital as a consequence of

injury sustained in a road crash.

Design and setting: Prospective cohort

study of patients admitted to an adult

trauma centre and two metropolitan

teaching hospitals in Victoria, Australia.

Participants were interviewed in hospital,

2.5 and eight months post-discharge.

Participants: Participants were 60

employed and healthy adults aged 18 to

59 years admitted to hospital in the period

February 2004 to March 2005.

Results: Despite differences in health

between the lower extremity fracture and

non-fracture groups eight months post-

crash the proportions having returned

to work was approximately 90%. Of

those returning to work, 44% did so in a

different role. After adjustment for baseline

parameters, lower extremity injuries were

associated with a slower rate of return to

work (HR: 0.31; 95%CI: 0.16-0.58) as was

holding a manual occupation (HR: 0.16;

95%CI: 0.09-0.57). There were marked

differences in physical health between and

within the injury groups at both follow-up

periods.

Conclusions: These results demonstrate

that both injury type and severity and

the nature of ones occupation have a

considerable influence on the rate and

pattern of return to work following injury.

Further, persisting disability has a direct

influence on the likelihood of returning to

work. The implications of these findings

and the types of data required to measure

outcome post-injury are discussed.

Key words: accidents, disability,

pain, quality of life, wounds, injuries,

compensation.

Aust NZ J Public Health. 2010; 34:153-60

doi: 10.1111/j.1753-6405.2010.00500.x

There is a rich body of injury outcomes

research conducted in Australia though

most utilise mixed injury cause samples to

examine recovery after head injury15,16 or the

incidence and determinants of acute stress

disorder17 and post-traumatic stress disorder

(PTSD).18-20 Few studies have specifically

examined RTW outcomes for survivors of

traffic crashes.21,22

In a recent study using a mixed injury cause

sample presenting to adult major trauma

centres in the state of Victoria, Gabbe et al.23

reported on disability and RTW outcomes

for a sample of orthopaedic trauma patients.

By 12-months post-injury, 84% of non-

compensable patients (60% fell; 8.6% struck

by object; 6.6% motorcyclist; 6.2% cyclist;

0.8% pedestrian; 0.4% vehicle occupant;

16.7% ‘other cause’) had RTW in contrast

to 67% for Transport Accident Commission

(TAC) compensable patients (53.5% vehicle

occupant; 27.3% motorcyclist; 11.1%

pedestrian; 5.8% cyclist; 2.2% ‘other cause’).

The compensable group were reported to

have, on average, lower physical health and

mental health than the non-compensable

group despite adjusting for age, head injury

status, injury severity and discharge status.

Despite a number of caveats, particularly

surrounding comparability of the two

groups with respect to mechanism, the

Article Injury

154 AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH 2010 vol. 34 no. 2© 2010 The Authors. Journal Compilation © 2010 Public Health Association of Australia

authors concluded that “our study adds to the evidence that

compensation schemes may impede recovery from injury” (p 17).

The implications of this finding is critical to explore as the TAC

provides no-fault insurance for those injured in road crashes in

Victoria under the provisions of the Transport Accident Act 1986.24

Specifically, the likely confound between injury type, persistent

disabilities and RTW must be considered. This is examined among

a group of individuals injured in road crashes in Victoria, all of

whom were eligible for TAC compensation.

This paper expands on previously reported findings21 by

Fitzharris et al.21 The study of 62 patients admitted to hospital

specifically excluded those with moderate or severe head injury

and spinal cord injury due to well stated rehabilitation challenges

associated with these injuries.5,16,25 In elaborating on these findings,

the aim of this paper is to explore the relationships between injury

type, disability, work role and RTW rates.

MethodsThe method of the study is described in detail elsewhere.21 We

summarise the key points below.

Participants and settingPatients aged 18 to 59 years admitted to a Victorian adult

Level 1 Trauma Centre and two metropolitan teaching hospitals

following involvement in a road traffic crash were eligible for the

study. Recruitment was conducted in the period February 2004 and

March 2005 inclusive. Eligible patients were those admitted for a

period greater than 24 hours with a Glasgow Coma Scale (GCS)

≥13.26 Exclusion criteria were: a) the presence of an Abbreviated

Injury Severity (AIS) score of 3 or higher (‘serious’) head, spinal,

or vertebral column injury;27 b) crashes involving a fatality; c) burn

injuries resulting from a vehicle fire; d) post-traumatic amnesia

(PTA) ≥24 hours; e) pre-existing cognitive impairment; f) deliberate

self-harm; g) history of psychosis; h) illicit drug dependence; i)

occupants of a stolen vehicle; and j) medically unfit to provide

informed consent. Non-English speakers and those residing outside

of Victoria were excluded due to budgetary constraints.

Recruitment and assessment proceduresConsecutive admissions were screened for eligibility and

patients were approached when medically appropriate to seek

participation. A full description of the study was provided and

once informed consent was gained the first of three interviews (T1,

within 14 days; T2, 6-8 weeks; T3, 6-8 months) was conducted.

Seventy-four patients consented to the study and 68 interviews

were conducted (91.8%), with six patients lost to interview due

to discharge, withdrawal of consent while one interview was

abandoned due to discomfort. Of the 68 participants who completed

the in-patient interview (T1), 64 completed T2 at approximately

two months post-crash (94% retention), and 62 completed T3 at

approximately eight months post-crash (91% retention). Those lost

to follow-up were due to failure to return the questionnaire booklet

(n=3); moved residence (n=2); and one deceased in a subsequent

motor vehicle crash. Non-responders at T3 (n=6) were more likely

to be male (n=5; 83.6%) than female (n=1, 16.7%), and were

marginally younger than the overall sample.

Assessment Measures – an extensive questionnaire and

psychometric tests were used. The interview included demographic

questions, factors related to and perceptions of the crash,

occupational and social functioning and pre-existing health, while

the T2 and T3 interviews focused on the same health outcomes

with temporally specific items replacing those focused on ‘acute’

responses. The number of weeks post-crash that patients RTW was

noted at both T2 and T3 with this information validated using pay

slips, time sheets and/or personal diaries.

Injuries were coded according to the Abbreviated Injury Scale

(AIS), 1998 revision, and the Injury Severity Score (ISS) was

calculated.27,28 The injury event, diagnosis and management were

coded as per the International Statistical Classification of Diseases

and related Health Problems 10th Revision – Australian modification

(ICD-10-AM) coding system.29 The Glasgow Coma Scale (GCS)26

was obtained from paramedic and hospital medical records. Pre-

crash employment occupation was coded according to the Australian

Standard Classification of Occupations (ASCO).30

Two health measures used are reported here. The SF-3631 is a

measure of general health status and quality of life, providing eight

domain scores as well as a physical (PCS) and mental component

summary score (MCS). Administration of the SF-36 at T1 focused

on ‘before the crash’ while at T2 and T3 the reference time was

‘since the crash’. The Alcohol Use Disorders Identification Test

(AUDIT)32 was used to assess harmful alcohol consumption and

was completed at T1 with reference made to ‘prior to the crash’

and at T3 with reference being ‘since the crash’.

Data analysisThe sample was divided into patients with lower extremity

fractures (LEF) and those without (non-LEF) given the well-

reported difference in RTW outcomes between these two goups.6

The lower extremity fracture group is defined by ICD-10-AM codes

S32 (bony pelvis), S72 (femur), S82 (lower leg) and S92 (ankle and

foot). Comparisons between the patient groups were made using

Fishers Exact test, chi-square tests and Repeated Measures ANOVA’s

where appropriate. Z-scores were used to compare the SF-36 scores

of the sample with Australian norms (18-64 years, employed), while

comparisons within and between the injury groups were made using

the non-parametric repeated measures Wilcoxon Signed Ranks Test

and independent samples Mann-Whitney U test respectively;33 these

were used as SF-36 data is non-normally distributed. Univariate

logistic regression34 was used to determine the association between

RTW and SF-36 scores, which were modelled linearly. As the time

to RTW was recorded and not all patients RTW by the T3, the

Kaplan-Meier survival analysis plot was used to describe the rate

of RTW with the Log Rank Test to determine differences between

the two groups. A Cox proportional hazards model was used to

examine the rate of RTW for the injury groups while adjusting for

demographic and injury factors.34 Analysis was performed using

STATA v.8.35 Statistical significance was set at p≤0.05. University

and Hospital Ethics Committees of the participating institutions

approved the research.

Fitzharris, Bowman and Ludlow Article


ResultsOf the 62 patients who completed the T3 interview, 60 form the

basis of analysis. As we are concerned with RTW outcomes it was

necessary to exclude one patient not employed at the time of the

crash and one patient who failed to note their RTW date.

Patient demographicsDemographic, road user type and baseline injury details are

presented in Table 1. Approximately two-thirds of the LEF group

were male compared to half in the non-LEF group while age,

marital status, area of residence and GCS were similar between the

two groups. There were approximately equal numbers of drivers

and passengers in the two groups however all the motorcyclists in

the sample sustained a LEF. The mean length of stay (LOS) was

significantly longer and the mean ISS was significantly higher

for the lower extremity fracture group compared to the non-LEF

group (p≤0.05). Of the 14 patients admitted to rehabilitation, all

had sustained a lower extremity fracture, of which seven were

drivers of motor vehicles.

Injury outcomes and characteristics of the LEF and non-LEF groups

Table 2 presents the nature of injuries sustained between the two

injury groups. Six participants in the LEF group sustained bilateral

lower extremity injuries, while all dislocations, sprains and strains

of joints of the lower leg were associated with lower extremity

fractures. With respect to injuries in other regions, a higher

proportion of patients in the non-LEF group (53.5%) sustained

fractures of the upper extremity compared to patients in the LEF

group (26.7%)(p≤0.05), while a slightly higher proportion of

patients in the LEF group sustained a concussive injury (p=0.07).

There were no other differences evident.

Health outcomes

SF-36 Health Status compared to Australian norms

Pre-injury and follow-up SF-36 MCS scores for both injury

groups did not differ from normative scores for employed

Table 1: Demographic, injury severity measures and selected psychological health outcomes of the lower extremity facture (LEF) and non lower extremity (non-LEF) fracture groups.

Characteristic Non-LEF (n=30) LEF (n=30)

% Male 50% (15) 66.7% (20)

Roaduser Driver 40% (12) 36.7% (11)Passenger 10% (3) 6.7% (2)Motorcyclist Nil 43.3% (13)Bicyclist 46.7% (14) 6.7% (2)Pedestrian 3% (1) 6.7% (2)

Marital status

Married / living with partner 53.3% (16) 63.3% (19)

Age (years)

Mean (SD) 37.9 (11.2) 35.4 (13.1)

Range, Median 19.9-58.8, 38.4 19.0-56.2, 31.3

Rural residence 20% (6) 16.7% (5)

Glasgow Coma Scale (GCS) (%) GCS 15 83.3% (25) 70% (21)GCS 14 13.3% (4) 23.3% (7)GCS 13 3.3% (1) 6.7% (2)

Length of Stay (days)

Mean (SD)a 4.8 (4.7) 7.1 (3.7)*

%>7 days 20% (6) 36.7% (11)

Range 2-25, 3 2-17, 6.5

Injury Severity Score (ISS)

Mean (SD)a 8.0 (6.9) 12.9 (9.1)a

Range, Median 1-29, 5 4-41, 10

% Major Trauma: ISS>15 10% (3) 23.3% (7)

Separation type (%) Home 100% (30) 53.3% (16)Rehabilitation / private Nil 46.7% (14)

Maximum Abbreviated Injury Scale score for injuries in non lower extremity body regions

No injury Nil 13.3% (4)MAIS 1-2 (minor, moderate) 66.7% (20) 63.3% (19)MAIS 3-5 (serious, 33.3% (10) 23.3% (7) severe critical)

Notes: a) p≤0.05

Table 2: Principal injuries of the sample.

Injury (ICD-10-AM) LEF Non-LEF (n=30) (n=30) % (n) % (n)

Fracture of lower extremity, including pelvis 100% (30) N/AFracture of lower leg 56.7% (17) N/AFracture of femur 26.7% (8) N/AFracture lumbar spine pelvisa 20% (6) N/AFracture of ankle and foot 10% (3) N/AFracture of upper extremityb 26.7% (8) 53.3% (16)Fracture of forearm 30% (9) 10% (3)Fracture of shoulder upper arm 13.3% (4) 20% (6)Fracture hand wrist 3.3% (1) 10% (3)Fracture of ribs sternum & thoracic spine 30% (9) 20% (6)Concussive injury, LOC<30 min; 23.3% (7) 6.7% (2) unspecifiedTraumatic injury of lung 20% (6) 10% (3)Fracture of skull and facial bones 16.7% (5) 3.3% (1)Dislocation, sprain, strain joint ligaments 23.3% (7) Nil lower legc

Injury of eye and orbit 6.7% (2) 6.7% (2)Other & unspecified injury of neck 3.3% (1) 6.7% (2)

Notes: a) All pelvic fractures; b) p≤0.05 c) All associated with lower extremity-pelvis injury;

20

2530

3540

4550

5560

Pre T2 T3 Pre T2 T3

M en ta l C om ponen t S um m ary S c o re P hy s ic a l C om ponen t S um m ary S c o re

No n L E F 9 5 % C IL E F 9 5 % C IA u st n o rm s 9 5 % C I

SF-3

6 su

mm

ary

scor

e

T im e

Figure 1: MCS and PCS scores for LEF and non-LEF injury groups, with Australian norms for employed adults aged 18-64 years.

Injury Return-to-work and health outcomes for road crash survivors


Australian adults (Figure 1).36 For the non-LEF group, the

pre-injury PCS score did not differ from norms, however was

significantly lower at T2 (p≤0.05) and again equivalent at T3

indicating improved physical health. For the LEF group, the

pre-injury PCS score was higher than Australian norms but

significantly lower at both T2 and T3.

SF-36 health status within and between the injury groups

Compared to pre-crash (56.8), the T2 mean PCS score for the

LEF group was 30.2 (46.9% reduction; p≤0.05) and 43.1 at T3

(24% reduction; p≤0.05). For the non-LEF group, the mean PCS

score was 54.9 at baseline, 42.3 at T2 (22.9% reduction; p≤0.05)

and 52.1 at T3 (5% reduction; p≤0.05); hence the improvement

from T2 to T3 was statistically significant (23% increase; p≤0.05).

While the baseline PCS scores between the injury groups were not

statistically different, at T2 and T3 PCS scores were lower for the

LEF group compared to the non-LEF group (p≤0.05).

Disaggregation of the PCS summary score indicated a

significantly lower physical functioning and the role physical sub-

domain scores at T2 and T3 for the LEF group compared to the

non-LEF group. There was no difference on general health domain

scores at either follow-up time or body pain at T2, however the

bodily pain score for the LEF group was lower (worse) than for

the non-LEF group at T3 indicating a difference in recovery.

There was little change in the overall MCS scores from pre-injury

scores and the pattern was similar for both injury groups. However,

examination of the four sub-domain scores that form the composite

MCS score indicates a significantly lower social functioning SF-36

MCS domain score for the LEF group compared to the non-LEF

group at T2 (44.2 vs. 70.8; p≤0.05) and T3 (75.0 vs. 89.6; p≤0.05),

indicating on-going and significant impact on social activities;

indeed, the non-LEF group score was similar to their pre-injury

score (88.3) and this was not the case for the LEF group (90.8). In

addition, the vitality score was lower for the LEF group compared

to the non-LEF group at T3 (57.3 vs. 67.7; p≤0.05).

Alcohol use Alcohol consumption decreased in the non-LEF group

(Pre: 5.5, 95%CI: 3.8–7.2; Post: 3.9, 95%CI: 2.4–5.3) and

increased in the LEF group following the crash (Pre: 6.4, 95%CI:

4.7–8.0; Post: 7.3, 95%CI: 4.8–9.9); this differential change was

statistically significant (p≤0.05), as was the difference at T3

(p≤0.05, Bonferroni correction).

Occupation and Return-to-Work outcomesTable 3 presents the key occupation and RTW outcomes for

the two injury groups. Using the ASCO system30 the number

of patients holding managerial, administration or professional

positions and clerical or sales and service occupations was

similar. There were more trades-people in the LEF group (20%)

than in the non-LEF group (10%) (Table 3). Most patients were

employed on a full-time basis with a small number being part-time

employed or students supplementing their income with part-time

or casual work. By T3, approximately equal numbers had RTW

(approximately 90%) while seven (11.6%) had yet to RTW by T3

(3 non-LEF; 4 LEF).

Of the seven patients yet to RTW (4 LEF, 3 non-LEF), four (3

LEF, 1 non-LEF) stated they were no longer employed at T3 as a

consequence of injuries sustained. Of the four LEF patients yet to

RTW at T3, three were male, three were motorcyclists and one was

a driver, two had an ISS >15; two were admitted to rehabilitation,

and all were tradespeople or manual workers. Of the non-LEF

patients (3) yet to RTW, all were female, all were discharged home,

all had an ISS<15, and there was one driver, one cyclist and one

passenger and one was in a trade or manual occupation.

Analysis shows that at T3 SF-36 PCS and MCS scores were

associated with whether a patient had RTW (p≤0.05) but this was

not the case for the variable indicating lower extremity injury;

this indicates that by eight months post-crash persisting disability

is critical in whether a patient RTW or not. Tradespeople were

less likely to have RTW by T3 than professional and clerical

occupational groups (p≤0.05).

Despite the similar proportion of patients having RTW by T3,

there was a significant difference in the rate of RTW. As shown in

both Table 3 and Figure 2 the median time to RTW for non-LEF

group patients was three weeks post-discharge (95th % CI: 2-4

weeks), and 12 weeks (95th % CI: 5.7-18.3 weeks) for patients in

the LEF group (p≤0.05), reflecting the slower rate of RTW. Figure

2 reflects the finding that seven patients were yet to RTW by T3.

Approximately half the patients RTW in the same role while

13 patients (43.3%) in the non-LEF group stated their salary had

suffered as a consequence of the crash in contrast to 17 patients

(56.7%) in the LEF group.

Table 3: Occupation and return-to-work outcomes.

Characteristic Non-LEF LEF (n=30) (n=30)

Pre-injury occupation Manager/Administration/Professional 66.7% (20) 60% (18)Clerical, Sales & Service 23.3% (7) 20% (6)Trades and related 10% (3) 20% (6)

Pre-injury employment profile Full time employed 73.3% (22) 76.7% (23)a

Full time work; self-employed 10% (3) 6.7% (2)Part-time / casual 6.7% (2) 6.7% (2)Student (+ part-time/casual work) 10% (3) 10% (3)

Return-to-work outcome at T3

Returned to work 90% (27) 83.3% (25)

Unable to work 10% (3) 13.3% (4)

Returned to work / unable to study 0% (0) 3.3% (1)

Time to return to work (post discharge acute hospital)*

Median (weeks) 3 12

95% CI (weeks) 2–4 5.7–18.3

Role on return-to-work at T3

Same role 53.3% (16) 46.7% (14)

Different role (part-time, lighter duties, 36.7% (11) 40% (12) new role)

No longer employed 3.3% (1) 6.7% (2)

Yet to RTW 6.7% (2) 6.7% (2)Salary suffered as consequence of crash 43.3% (13) 56.7% (17)

Notes: a) 1 also studying; *p≤0.05



Modelling time to RTWThe Cox proportional hazards model was used to assess

occupational, injury and demographic factors associated with

the RTW rate (Table 4). Patients in the LEF injury group RTW

at a rate 69% slower than those in the non-LEF group controlling

for factors noted in Table 4 (HR: 0.31; 95%CI: 0.16-0.58). The

maximum AIS score (MAIS) of injuries sustained in other body

regions was included to adjust for this potentially confounding

influence. Those with MAIS 3-5 injuries in regions other than

the lower extremity RTW at a rate 56% slower than those with

minor (MAIS1) or no injury (HR: 0.42, CI: 0.20-0.88, p=0.02).

The model was adjusted for pre-crash health and these factors

were associated with the rate of RTW. Patients holding a trade and

related occupation pre-crash had a significantly slower RTW rate

than both professional workers (HR: 0.31, CI: 0.16-0.58, p=0.003)

and clerical, sales and service workers (HR: 0.22, CI: 0.06-0.81,

p=0.02). There was no difference in the RTW rate between the

clerical and professional occupation groups.

Time spent in rehabilitation was unable to be assessed as only

patients with lower extremity fractures were admitted to another care

facility post-discharge from the treating hospital. This is clearly related

to injury type and impacts upon RTW outcomes. Marital status and

gender was not associated with RTW rate in this sample.

DiscussionIn this study of healthy employed adults admitted to hospital

following injuries sustained in traffic crashes – all of whom were

covered by the TAC no-fault compensation scheme – we set out

to explore the relationships between injury type, disability, work

role and RTW outcomes.

Among this relatively small, yet representative sample of admitted

patients within the context of the eligibility criteria,21 those with

lower extremity fractures experienced a longer length of stay

and higher mean ISS than those without such fractures. Of those

patients requiring in-patient rehabilitation, all had sustained a lower

extremity fracture. Despite pre-injury physical health, as measured

by the SF-36, being equal to or better than Australian norms, at 2.5

months post-crash physical health was impaired for both injury

groups though remained impaired only for the LEF group at eight-

months post-crash. The extent of impairment in physical health was

greater among the LEF group at both follow-up times compared to

the non-LEF group. For mental health, there appeared to be little

change from pre-injury scores, however, disaggregation of the MCS

indicated significantly impaired social functioning at both follow-up

times for the LEF group compared to the non-LEF group as well

as impaired vitality eight-months post-crash.

Despite these differences in health, there was no difference in the

proportion of those having RTW eight-months post-crash with the

proportions being 86% and 90% for the LEF and non-LEF group

respectively. On-going impairments in health were associated

with the failure to RTW eight-months post-crash as was having a

manual (trade) occupation. Of those that did RTW, 44% returned

in a different role and there was little difference between the injury

groups. There were however significant differences in the RTW rate,

or time taken to RTW. After adjustment for baseline parameters and

potential confounding variables, having sustained a lower extremity

injury was associated with a significantly slower RTW rate as was

the nature of one’s occupation and the severity of injuries sustained

in body regions other than the lower extremity.

The implications of the results reported here are simple: both

injury type and severity and the nature of one’s occupation have an

influence on the rate and pattern of return-to-work following injury,

reflecting earlier research.2,6,9,11-13 Further, persisting disability has

a direct influence on the likelihood of returning to work. Clearly

disability and RTW are not mutually exclusive outcomes.

The findings reported here highlight a number of key issues with

respect to measuring outcome following injury. First, the component

summary scores (i.e. PCS and MCS) are reductionist and do not in

themselves necessarily reveal the extent of impairments experienced

across sub-domains – indeed they are by definition summary

measures. This point can be evidenced by the disaggregation of

the MCS score that showed social functioning being significantly

poorer among those with lower extremity fractures eight-months

post-crash. It is interesting to reflect that among this group alcohol

intake was significantly higher – and indeed increased from pre-

crash levels – than the non-lower extremity group whose alcohol

intake actually reduced from pre-crash levels.

Table 4: Factors associated with time to return-to-work.

Factor HR 95th% CI p Lower-Upper

Lower Extremity 0.31 0.16–0.58 <0.001 Fracture (LEF)

Age 0.98 0.95–1.00 0.07

MAIS for non-lower extremity injuries (Reference category AISO/1)

MAIS 2 0.70 0.34–1.44 0.4

MAIS 3-5 0.42 0.20–0.88 0.02

Occupation (Reference category Prof, Managers & Admin)

Clerical, Sales 0.84 0.39–1.83 0.7 & Service

Trades and related 0.19 0.06–0.57 0.003

SF-36 pre-injury 1.06 1.01–1.12 0.01 PCSSF-36 pre-injury 1.03 1.00–1.07 0.05 MCS

0.25

0.50

0.75

1.00

Prop

ortio

n ye

t to

RTW

1 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34T im e to R e turn to W o rk s inc e d is c harg e - we e ks

No n -L E F G ro u pL E F G ro u p

Figure 2: Kaplan-Meier survival plot of proportion of patients RTW by time since discharge.



The second point to be made is whether the dichotomous

outcome of RTW is a sufficient indicator of a successful outcome

post-injury. The findings reported here highlight the problematic

nature of using a dichotomous yes/no RTW outcome as there were

clear differences in the rate of RTW as well as in the pattern of

RTW. Certainly in the field of occupational injury, RTW measures

are common and as Krause et al.37 note, RTW measures serve to

define the burden of occupational injury for society and individuals

directly affected by occupational injury, as well as determining

the efficacy and cost-effectiveness of intervention programs and

policies in assisting in the maintenance of occupational roles. The

specific RTW index used is a matter of debate, with Butler et al.

suggesting that first RTW is not a useful measure of RTW38 due

to multiple patterns of RTW. Indeed, Harris et al.39 recognised this

point when conducting a meta-analysis of 129 studies seeking to

examine the influence of workers compensation schemes (33%

included litigation) on outcome post-surgery by specifically

excluding outcome scores measuring time-to-RTW. Harris et al.

noted that RTW ‘…outcome is influenced by confounding factors

such as job characteristics and social factors’ (p 1645). In their

review, the likelihood of an unsatisfactory outcome was reported

to be three times higher among compensated patients than the

uncompensated patient. In discussing these results four possible

scenarios were considered: 1) psychological factors related to

the injury; 2) factors associated with the at times adversarial

compensation process itself; 3) the notion of secondary gain where

benefit is derived from ‘assuming the sick role’, though this impact

was considered to be small; and 4) tertiary gain – to the benefit

of a third party. However, it may prove that RTW rates and RTW

patterns might prove useful for those injured in non-work related

traffic crashes given the disconnect between the injury event (and

thus eligibility for TAC coverage) and employment.

This discussion of how to best measure outcome post injury

is important as it reflects on the perceived success or failure of

schemes designed for those injured and seeking rehabilitation,

benefit or redress. In this vein fundamental differences between

the eligibility and operation of fault-based and no-fault

compensation schemes as well as differences in the mechanisms

and patterns of occupational injury and traffic crash related injury

must be recognised. As a counter to the negative impact of the

workers compensation scheme on outcomes noted above,39 the

transformation of the fault-based compensation scheme in the

province of Saskatchewan, Canada, to a no-fault scheme was

associated with improved outcomes among those involved in traffic

crashes,40 with the suggestion being this result might be associated

with less opportunity for financial gain and less exposure to the

adversarial tort system, particularly with respect to compensation

claims for pain and suffering.39

In this study, all patients were covered by the TAC no-fault

system. It is important to note that the TAC scheme provides

coverage only for those involved in traffic crashes and acts as a

no-fault scheme that supplements, rather than replaces, the tort

system. However, for a claim in the courts to be pursued, the

injured person must have suffered a serious disability. The findings

of this study can be interpreted in either a positive fashion or a

negative fashion – that 90% had returned to work eight-months

after sustaining a serious injury is positive, however, it remains

the case that a proportion remained out-of-work, that some RTW

faster than others, and for those that did return to work, only half

did so in the same role. These results highlight the complexity of

defining a successful outcome and indicate that multiple measures

are required to measure a successful recovery following injury.

By extension, evaluating the value of compensation systems in

promoting successful outcomes is equally complex.

While the findings reported here have served as the basis to

explore issues in defining and measuring outcome post-injury they

are in themselves important. Clearly a subset of patients experience

persistent disability and problems in RTW. The study has strengths

with respect to its prospective design and high retention rates.

However, the scale of the study is small and the generalisability

of the findings is limited. Those with serious head and spinal

cord injury were deliberately excluded as were children and older

adults. There are unique issues with these groups from structural

anatomical injury through to re-integration with schooling and

ageing. Using administrative datasets, the target sample represents

43% of those admitted to Victorian hospitals due to road injury.21

The issue of secondary gain among those yet to RTW requires

acknowledgement, however that injury type and occupation is

associated so strongly with both the likelihood and the rate of

RTW the influence of secondary gain seems small. The role of

private income protection must be considered within this context

in future studies. While an attempt was made to examine a range

of factors associated with RTW, due to the small sample size it was

not possible to include a larger range of socio-economic factors

that might influence the RTW rate.

A larger and more inclusive study is required to test findings

reported here, however the extensive nature of the multi-

dimensional data required represents a formidable challenge

requiring multi-centre co-operation. A study that utilises the

World Health Organization (WHO) International Classification of

Functioning, Disability and Health (ICF)41 measure supplemented

by a psychological test battery covering depression and anxiety

disorders42 to compare health outcomes of those injured in

the course of their occupation and in road crashes, and hence

covered by different compensation schemes (fault-based, no-

fault, litigation) would be able to appropriately examine factors

associated with short and long-term post-injury outcomes. This

type of study design would permit an assessment of the value of

the various forms of compensation and modes of assistance and

recourse open to the injured patient.

ConclusionsDespite persistent levels of disability the RTW outcome was

close to 90% eight-months post-crash and expectedly the rate of

RTW differed for manual workers and those with lower extremity

injuries. This paper highlights that despite apparent high levels

of patients returning to work, a substantial proportion did so in a

different role while approximately one-tenth were yet to return-



to-work eight months post-crash. Also expected, though still

important to document, was the finding that persistent disability

was associated with the inability to RTW. In elaborating on these

findings, it is suggested that it is important to remain wary about

reductionist measures when considering outcomes and it is crucial

to distinguish between occupational injury and traffic-related

injury; this is particularly pertinent with respect to RTW outcomes

when used to consider the efficacy of different compensation

schemes. The assessment of outcome post-injury is complex

and requires consideration of multiple dimensions of health and

social resources available to those injured. The WHO ICF41 offers

one such framework and in combination with psychological test

batteries is highly recommended.

AcknowledgementsThe data collected here was done so as part of the first author’s

PhD candidature at Monash University under the supervision of

Professor Brian Fildes, Dr Judith Charlton and Professor Claes

Tingvall. During this time Michael Fitzharris was a Research Fellow

in the Department of Trauma Surgery, The Alfred, the National

Trauma Research Institute and the Department of Emergency

Medicine, Southern Health. The authors gratefully acknowledge

the significant contribution of each participant as well as that of

the treating nursing and medical staff of the hospitals involved.

The authors wish to thank Professor Thomas Kossmann, Professor

Johannes Wenzel and Dr Pam Rosengarten for supporting the study.

Thanks also to Louise Niggemeyer RN, Manager, Trauma Registry,

The Alfred, Michelle Srage RN & Claire Sage RN, Trauma Care-

Coordinators, The Alfred, and Meg Lindsay RN, Southern Health,

for vital support without which this research would not be possible.

Michael Fitzharris acknowledges the financial contribution of the

MUARC Foundation and Monash University for providing stipend

funding and the MUARC Doctoral Students Research Fund (DSRF)

for supporting this research activity. The views expressed are those

of the authors and do not necessarily represent those of Monash

University, the Accident Research Centre, the MUARC Foundation,

Alfred Health or Southern Health.

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Documents

Factors associated with return-to-work and health outcomes among survivors of road crashes in Victoria