| Literature DB >> 27473747 |
Nieke A Elbers1, Alex Collie2, Sheilah Hogg-Johnson3, Katherine Lippel4, Keri Lockwood5, Ian D Cameron5.
Abstract
BACKGROUND: Involvement in a compensation process following a motor vehicle collision is consistently associated with worse health status but the reasons underlying this are unclear. Some compensation systems are hypothesised to be more stressful than others. In particular, fault-based compensation systems are considered to be more adversarial than no-fault systems and associated with poorer recovery. This study compares the perceived fairness and recovery of claimants in the fault-based compensation system in New South Wales (NSW) to the no-fault system in Victoria, Australia.Entities:
Keywords: Claimants; Compensation systems; Injury; Motor vehicle crash; Procedural justice
Mesh:
Year: 2016 PMID: 27473747 PMCID: PMC4966779 DOI: 10.1186/s12889-016-3331-3
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Comparison of the Victorian and NSW compensation scheme design
| NSW motor accidents scheme | Victoria transport accident scheme | |
|---|---|---|
| Scheme structure and administration | ||
| 1. Legislation | Motor Accidents Compensation Act | Transport Accident Act |
| 2. What type of law governs the scheme: no-fault, hybrid, common law? | Hybrid. Mainly fault. Injured people have to prove that somebody else was at-fault. People can lodge a no-fault claim regardless of fault up to $5000. | Hybrid. Mainly no-fault. Injured people can claim regardless of fault. People with serious injury have access to common law, which is fault-based. |
| 3. Is the compensation scheme mechanism-based or disability-based? | Mechanism-based (injury resulting from motor vehicle/land-based transport accident) | |
| 4. How does the compensation system interact with other societal structures? | Both systems purchase healthcare from national publicly funded and private healthcare systems. Both have involvement with legal systems for dispute resolution. | |
| 5. Is the insurance compulsory? How is the scheme funded? | Compulsory insurance. Funded by annual insurance premiums paid by motor vehicle owners as part of registration. | |
| 6. Does the jurisdiction insure through private carriers or a state insurance fund? | 7 Third party private insurance companies (profit) | 1 First party state government compensation agency (non-profit) |
| Scheme eligibility | ||
| 7. Is liability assessment a feature of the scheme? | Yes. Liability is assessed within 3 months after claim lodgement | No. Coverage is accepted for all transport accident related injuries. |
| 8. What proportion of the total transport injury population is covered by the scheme? How is the total transport injury population defined? | The transport injury population are those who are injured in a transport accident that occurred in the state under investigation (respectively Victoria or NSW) AND anyone traveling in a vehicle registered by that particular state (respectively Victoria or NSW) in any part of Australia | |
| 9. Which injuries and afflictions are covered and which are not? Are mental health claims covered? | All injuries arising from the transport accident are covered including mental injury. | |
| 10. What is the time frame to lodge a claim? | The fault-based claim has to be lodged within 6 months post-injury | The no-fault claim has to be lodged within 12 months post-injury |
| Medical assessments | ||
| 11. Who conducts the medical assessments? What is the role of the physician in injury certification and fitness for work? | Medical assessments are conducted by doctors assigned by the insurance company or assigned by the injured person’s lawyer. For disputed medical assessments there is an independent medical assessment service | <18 months: assessments are conducted by injured person’s general practitioner. |
| Scheme benefits and entitlements | ||
| 12. What benefits are paid for? | Compensation can be paid for medical and rehabilitation services, past (i.e. between injury and claim settlement) and future (i.e. after claim settlement) income replacement, travel, and household support, legal services, and pain and suffering | No-fault benefits include medical and rehabilitation services, income replacement, travel, and household support. Legal costs related to disputes (protocol disputes and Victorian Civil Appeals Tribunal) are reimbursed. |
| 13. What is the level of income benefits/loss of wages? Are there caps on the wages earned? | Loss of wages involves 100 % of previous/future salary. Capped at $4,412 net weekly earning (2014). Payments are tax-free, provided certain conditions are met. | The claimant has to cover the first 5 working days before compensation of loss of earnings commences. |
| 14. What is the duration and frequency of payments? | Treatment is paid as long as it is reasonable and necessary. Usually paid on an as incurred basis. Loss of income comprises 100 % of pre-injury earnings. Capped at $4,412 net weekly earning (2014). Loss of past and future income reimbursements are paid as a lump sum at claim settlement. Periodic financial hardship payment can be paid. | Treatment is paid as long as it is reasonable and necessary. Usually paid on an as incurred basis. Income benefits for no-fault claims are limited to 3 years from the accident unless they have a permanent impairment level of at least 50 %. Income benefits are paid fortnightly. Claims do not formally close. |
| Scheme Changes | ||
| 15. Has the compensation scheme undergone any significant changes during the study period? | No changes during the study period. | The claims process changed in October 2013. The main changes with respect to perceived fairness were an easier claims form and faster approval of services. Also a joint medical examination process was introduced reducing the number of medical assessments. |
Table is based on information derived from the Transport Accident Act [33] and Motor Accidents Compensation Act [34] and checked by policy makers of both schemes. We used the format developed by Clay et al. [35] adapted for motor vehicle injury insurance schemes
Fig. 1Flowchart of participants
Sample characteristics, claim factors, health and work status
| Demographic variables | NSW ( | VIC ( | χ2 or t (df) |
|
|---|---|---|---|---|
| N (%), M (SD) | N (%), M (SD) | |||
| Age | 54.59 (14.36) | 45.79 (16.27) | 3.88 (180) | < .001 |
| Gender (male) | 52/98 (53 %) | 58/84 (69 %) | 4.84 | .028 |
| Country of birth (Australia) | 67/98 (68 %) | 61/84 (73 %) | 0.39 | .531 |
| Socio-economic status (high) | 46/98 (47 %) | 51/84 (61 %) | 3.45 | .063 |
| Education (high) | 25/98 (26 %) | 26/83 (31 %) | 0.75 | .386 |
| Marital status (married) | 54/98 (55 %) | 44/82 (54 %) | 0.04 | .846 |
| Injury (whiplash/soft tissue) | 39/98 (40 %) | 15/84 (18 %) | 10.43 | .001 |
| Hospital (admitted) | 43/98 (48 %) | 54/84 (64 %) | 7.57 | .006 |
| Time since the accident (12 months) | 54/98 (55 %) | 41/84 (49 %) | 0.72 | .397 |
| Claim factors | ||||
| Lawyer | 66/98 (67 %) | 11/84 (13 %) | 54.54 | < .001 |
| Medically assessed | 53/98 (54 %) | 8/83 (10 %) | 39.73 | < .001 |
| Number of assessments | 1.66 (1.02) | 2.29 (1.38) | −1.47 (58) | .148 |
| Dispute process | 2/98 (2 %) | 1/84 (1 %) | - |
|
| Claim status (settled/inactive) | 25/98 (26 %) | 38/84 (45 %) | 7.78 | .005 |
| Previous claim | 31/98 (32 %) | 13/84 (16 %) | 6.44 | .011 |
| Fault (at-fault) | 0/98 (0 %) | 14/79 (18 %) | 18.86 | < .001 |
| Health and work status | ||||
| Health | ||||
| Pre-injury (good-excellent) | 88/96 (92 %) | 81/83 (98 %) | 2.96 | .085 |
| Post-injury (good-excellent) | 43/92 (47 %) | 56/84 (67 %) | 7.09 | .008 |
| Not working due to the accidenta | 12/98 (12 %) | 15/84 (18 %) | 1.13 | .288 |
Notes. Socio-economic status (low = 1–5 versus high = 6–10), education (low-medium versus high; high is defined as undergraduate, bachelor and postgraduate), marital status (married/de facto versus single/divorced/separated), type of injury (whiplash/soft tissue injury versus other), at-fault (totally at fault versus not at all at fault/partially at fault), health (poor/fair versus good/very good/excellent)
aat time of interview
Fairness perceptions about the claims process, claims management, medical assessments, lawyer involvement, and dispute process
| Claims process | NSWa | VICa | χ2 |
|
|---|---|---|---|---|
| It is easy to fill out forms | 45/97 (46 %) | 62/80 (78 %) | 17.75 | < .001 |
| It is easy to support claim | 50/97 (52 %) | 70/82 (85 %) | 23.00 | < .001 |
| Claim duration is acceptable | 44/96 (46 %) | 70/84 (83 %) | 27.13 | < .001 |
| Compensation received so far is fair | 45/98 (46 %) | 60/81 (74 %) | 14.50 | < .001 |
| Overall claim process is fair | 44/96 (46 %) | 70/83 (84 %) | 28.54 | < .001 |
| Claims management | ||||
| The claims manager… | ||||
| takes views/feelings into account | 39/96 (39 %) | 62/82 (76 %) | 22.05 | < .001 |
| manages claim objectively | 41/96 (42 %) | 78/84 (93 %) | 50.29 | < .001 |
| uses correct information | 43/96 (45 %) | 75/82 (92 %) | 43.11 | < .001 |
| provides information | 44/96 (46 %) | 71/83 (86 %) | 30.56 | < .001 |
| explains procedure | 33/96 (34 %) | 64/79 (81 %) | 38.15 | < .001 |
| communicates timely | 39/95 (41 %) | 66/84 (79 %) | 25.88 | < .001 |
| is polite | 66/96 (67 %) | 78/82 (95 %) | 19.90 | < .001 |
| is respectful | 63/96 (64 %) | 78/84 (93 %) | 19.58 | < .001 |
| approves treatment needed | 56/98 (57 %) | 76/82 (93 %) | 28.84 | < .001 |
| approves treatment promptly | 51/98 (52 %) | 68/82 (83 %) | 19.01 | < .001 |
| approves other services promptly | 37/98 (37 %) | 49/73 (67 %) | 14.43 | < .001 |
| Medical assessments | ||||
| The medical assessor… | ||||
| provided information | 26/52 (50 %) | 3/8 (38 %) | - | - |
| explained procedure | 27/52 (52 %) | 5/8 (63 %) | - | - |
| examined unbiased | 21/52 (40 %) | 3/8 (38 %) | - | - |
| was polite | 35/52 (67 %) | 6/8 (75 %) | - | - |
| was respectful | 35/52 (67 %) | 5/8 (63 %) | - | - |
| Number of assessments was acceptable | 34/53 (64 %) | 7/8 (88 %) | - | - |
| Lawyer involvement | ||||
| The lawyer… | ||||
| provided information | 57/66 (86 %) | 8/10 (80 %) | - | - |
| explained procedure | 57/66 (86 %) | 8/10 (80 %) | - | - |
| communicated timely | 55/66 (83 %) | 8/10 (90 %) | - | - |
| was polite | 64/66 (97 %) | 11/11 (100 %) | - | - |
| was respectful | 61/66 (92 %) | 11/11 (100 %) | - | - |
| The lawyer made the process easier | 56/66 (85 %) | 8/11 (73 %) | - | - |
| Dispute process | ||||
| Decision maker … | ||||
| provided information | 0/2 (0 %) | 1/1 (100 %) | - | - |
| explained procedure | 0/2 (0 %) | 1/1 (100 %) | - | - |
| communicated judgment | 0/2 (0 %) | 1/1 (100 %) | - | - |
| was polite | 2/2 (100 %) | 1/1 (100 %) | - | - |
| was respectful | 2/2 (100 %) | 1/1 (100 %) | - | - |
| Dispute process was stressful | 2/2 (100 %) | 1/1 (100 %) | - | - |
Notes. The answer scale to all justice questions was strongly agree, agree, neither agree nor disagree, disagree, strongly disagree, which was dichotomised into strongly disagree, disagree, neither agree nor disagree versus agree, strongly agree
acolumn displays the number of participants that strongly agreed/agreed with the statement divided by the total number of participants that answered the question
- = The number of participants is too small to conduct further analyses
Predictors overall fairness of the compensation process
| Independent variables | Overall fairness claims process | |||||||
|---|---|---|---|---|---|---|---|---|
| Model 1 | Model 2 | |||||||
| AOR | CI |
| AOR | CI |
| |||
| Age | 0.99 | 0.97, | 1.01 | .21 | 1.00 | 0.97, | 1.02 | .73 |
| Gender | 0.75 | 0.38, | 1.48 | .41 | 0.79 | 0.37, | 1.68 | .54 |
| Country of birth | 0.91 | 0.44, | 1.87 | .79 | 0.87 | 0.38, | 1.97 | .73 |
| Socio-economic status | 1.84 | 0.95, | 3.56 | .07 | 1.38 | 0.65, | 2.94 | .41 |
| Education | 0.58 | 0.28, | 1.21 | .15 | 0.46 | 0.20, | 1.06 | .07 |
| Marital status | 2.11 | 1.09, | 4.06 | .03 | 1.69 | 0.81, | 3.55 | .16 |
| Injury | 0.43 | 0.19, | 0.94 | .04 | 0.65 | 0.26, | 1.60 | .35 |
| Hospital admission | 0.73 | 0.36, | 1.49 | .38 | 1.08 | 0.48, | 2.45 | .85 |
| Time after injury | 1.04 | 0.54, | 1.99 | .91 | 1.08 | 0.48, | 2.44 | .86 |
| Medical assessment | 0.31 | 0.12, | 0.78 | .01 | ||||
| Lawyer involvement | 0.33 | 0.13, | 0.81 | .02 | ||||
| Claim status | 1.71 | 0.68, | 4.32 | .26 | ||||
| Previous claim | 1.66 | 0.68, | 4.03 | .26 | ||||
Notes: Model 1 Nagelkerke R2 = .111; Model 2 Nagelkerke R2 = .339
Multiple logistic regression analysis, modelling the probability that the process was considered fair (versus not fair/neutral). The first model includes demographic and injury details. The second model adds the claim factors. ‘At-fault’ was not included because this variable only applies to the Victorian sample. There was no multicollinearity
Coding: Gender (0 = Male; 1 = Female); Country of birth (0 = Other; 1 = Australia); Socio-economic status (0 = Lower; 1 = Higher); Education (0 = Low/Medium; 1 = High); Marital status (0 = Single/Divorced; 1 = Married); Injury (0 = Other; 1 = Whiplash/soft tissue injury); Hospital admission (0 = No; 1 = Yes); Time after injury (0 = 12 months; 1 = 24 months). Medical assessment (0 = No; 1 = Yes); Lawyer involvement (0 = No; 1 = Yes); Claim status (0 = Pending; 1 = Settled); Previous claim (0 = No; 1 = Yes); Overall fairness claims process (0 = not fair/neutral, 1 = fair). Reference category = 0
Predictors of health post-injury
| Health post-injury | ||||||||
|---|---|---|---|---|---|---|---|---|
| Model 1 | Model 2 | |||||||
| Independent variable | OR | CI |
| AOR | CI |
| ||
| Fairness claims process | 2.78 | 1.45, | 5.33 | .002 | 2.83 | 1.40, | 5.71 | .004 |
| Age | 1.01 | 0.99, | 1.04 | .23 | ||||
| Gender | 0.91 | 0.45, | 1.83 | .78 | ||||
| Country of birth | 1.00 | 0.48, | 2.12 | .99 | ||||
| Socio-economic status | 1.12 | 0.57, | 2.20 | .74 | ||||
| Education | 0.88 | 0.42, | 1.88 | .75 | ||||
| Marital status | 0.90 | 0.46, | 1.79 | .77 | ||||
| Injury | 1.35 | 0.57, | 3.16 | .49 | ||||
| Hospital admission | 2.04 | 0.97, | 4.26 | .06 | ||||
| Time after injury | 0.62 | 0.32, | 1.20 | .16 | ||||
| Health pre-injury | 6.15 | 1.09, | 34.61 | .04 | ||||
Note: Model 1 Nagelkerke R2 = 0.08; Model 2 Nagelkerke R2 = 0.16
Multiple logistic regression analysis, modelling the probability of good or excellent health (versus fair or poor health). Model 1 explores the unadjusted association between the overall fairness perception and health. Model 2 adjusts for demographic, injury variables, and pre-injury health. There was no multicollinearity
Coding: Overall fairness claims process (0 = disagree/neutral; 1 = agree); Gender (0 = Male; 1 = Female); Country of birth (0 = Other; 1 = Australia); Socio-economic status (0 = Lower; 1 = Higher); Education (0 = Low/Medium; 1 = High); Marital status (0 = Single/Divorced; 1 = Married); Injury (0 = Other; 1 = Whiplash/soft tissue injury); Hospital admission (0 = No; 1 = Yes); Time after injury (0 = 12 months; 1 = 24 months); Health pre-injury (0 = Poor; 1 = Good); Health post-injury (0 = poor/fair, 1 = good/excellent). Reference category = 0