Identifying predictors of early non-recovery in a compensation setting: The Whiplash Outcome Study
Introduction
Whiplash Associated Disorders (WAD) are the most common injury type sustained following motor vehicle crashes27 and as such constitute a large proportion of compensation scheme costs in jurisdictions where compensation is available. The incidence of WAD has increased over the past 30 years and is likely to be at least 300 per 100,000 inhabitants in some countries.17 The number of claims for compensation also varies amongst countries and compensation schemes, reports have been as high as 600 per 100,000 inhabitants.8
The Bone and Joint Decade 2000–2010 Task Force on Neck Pain and its Associated Disorders recently reported that recovery from WAD is protracted with only half those affected reporting no neck symptoms 1 year after the motor vehicle crash.18 This is consistent with the findings of an Australian Study where only 50% of the study population had recovered at the time of the Study's 2-year follow-up.25 Measuring recovery from WAD is inconsistent, with only a small number of studies using a validated measurement instrument19 such as the Functional Rating Index25 and the Neck Disability Index.28 Studies that have used proxies for recovery, typically claim finalisation have reported higher recovery rates.30
Previous research has been contradictory with respect to determinants of delayed recovery. One systematic review found that age, gender, initial pain intensity and radicular symptoms were predictors of outcome,9 whilst another review agreed that high initial pain intensity was predictive of outcome but found age and gender were not.26 More recently, the best evidence synthesis of The Bone and Joint Decade 2000–2010 Task Force on Neck Pain and its Associated Disorders concluded that recovery is slower in those WAD sufferers with higher symptom severity and that post-injury psychological distress and passive coping was prognostic of poor recovery.7
A large proportion of people with WAD obtain treatment and intervention through a compensation process where there is mounting evidence to suggest that being part of that process is associated with poorer outcomes.12, 15, 2 Identifying those who are least likely to recover as early as possible within that process becomes increasingly important so resources may be directed appropriately.
In New South Wales (NSW), Australia, motor accident insurance is compulsory and is provided on a “fault-basis”, for those who have been injured as a result of the fault of another person. Some important features of the NSW Scheme include; provisions for early notification and treatment through speedy and simplified accident notification and provisional liability provisions, and a threshold to access common law damages (non-economic loss payments) which is determined by an objective medical assessment process. Claims for whiplash do not typically meet the threshold.
The Whiplash Outcome Study (WOS) is based in NSW, where claims for WAD are a significant component of the NSW Motor Accidents Scheme with 45% of all claims involving a whiplash injury, contributing 27% of the total claims cost in that Scheme.21
This paper describes those people with WAD who had not recovered within 3 months following their crash and aims to identify potential predictors of poorer health and non-recovery. In particular, the approach is to identify data which, if collected at claim notification, could assist in the development of screening processes and informing targeted interventions that can be applied by Insurers and Compensation Scheme policy makers.
Section snippets
Study design and population
The Whiplash Outcome Study is a prospective cohort study in which participants were eligible if they sustained a whiplash injury and lodged a claim for compensation with a large private NSW based insurer between November 2007 and June 2009. Participants completed baseline health measures within 3 months of sustaining their injury. This paper presents a cross-sectional analysis of this cohort study.
Eligible participants had sustained a whiplash injury which was coded in accordance with the
Population and recruitment
A total of 7179 claims were lodged with a NSW based private insurer during the study period, from November 2007 to June 2009, of that 3323 (46%) were whiplash injury and of those 1289 (38%) met the study selection criteria. Claims were notified to the insurer in a mean (standard deviation) of 27 (19.4) days after the crash.
Of those that met the selection criteria, 639 (50%) agreed to receive information and an invitation to participate in the study. Of the 639 postal questionnaires sent, 326
Recovery and non-recovery
Recovery in this study was defined as a score of less than or equal to 25 on the FRI with 23.0% of the study population meeting this definition on receipt of the baseline questionnaire.25 Of the 246 participants, 3 did not complete the FRI at baseline, therefore they were not allocated to a group. All other participants were allocated to a recovered group (n = 56) or a non-recovered group (n = 187) and analysed as two independent groups (Table 3).
Health measures
Overall, whiplash had a significant impact on the
Health outcomes
The objective of this study was to identify potential predictors of poorer health and non-recovery following WAD in a compensation setting as early as possible following claim notification. Information collected by insurers and claims handlers at claim notification rarely includes information about a person's health. Nevertheless this information is used to inform “risk” screening practices where risk typically represents risk of prolonged duration and cost, and prolonged duration is a proxy
Discussion
Whiplash injuries had a significant negative effect on this population with 77% of the participants unrecovered at 3 months post-injury. Overall their physical and mental health was well below that of the Australian population (Fig. 1) and 38% of the working population were unable to continue in their pre-injury capacity.
Pain catastrophising was associated with poorer health, and the helplessness subscale was the most predictive of disability levels and worse physical and mental health on all
Conclusion
Regardless of the health outcome measures used in this study, the helplessness subscale of the PCS was the strongest predictor of disability and poorer health and as such interventions aimed at minimising helplessness, would be useful in reducing the persistence of pain and disability. In all these useful predictors of outcome accounted for more than 60% of the variance in disability. In contrast, the insurer model only predicted 1%.
Including additional information at claim notification,
Conflict of interest statement
Petrina Casey was an employee of Insurance Australia Group (IAG) when the study was planned and implemented.
Role of funding source
Funding was received by Insurance Australia Group to assist in data collection which was carried out independently from them. This funding ceased in July 2009. IAG has had no involvement in the design, analysis or reporting of the study.
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2016, Pathology and Intervention in Musculoskeletal RehabilitationCourse of recovery for whiplash associated disorders in a compensation setting
2015, InjuryCitation Excerpt :An index score is generated with a range of scores from zero (no disability) to 100 (severe disability) [6]. Suggested cut off scores for the FRI are; ≤25 (no disability – recovered); >25–50 (moderate disability); and >50–75 (severe disability) which has been used previously [1,6]. Pain catastrophising was measured by the Pain Catastrophising Scale (PCS).
Associations with duration of compensation following whiplash sustained in a motor vehicle crash
2015, InjuryCitation Excerpt :Accordingly, researchers remain critical of using claim closure as a proxy for recovery as the relationship has not been sufficiently established [16,17]. The appropriate recovery metric, health outcome data, is rarely routinely collected within the compensation insurance context; rather, insurers collect data in order to assess insurance risk, which is usually claim duration and claim cost [18], and typically referred to as complexity. Therefore, identifying predictors of time to claim closure may be of more practical use to insurers and claims handlers where interventions aimed at minimising claim duration and claim cost may be implemented.