Positive recovery for low-risk injuries screened by the short form - Örebro musculoskeletal pain screening questionnaire following road traffic injury: evidence from an inception cohort study in New South Wales, Australia

Road traffic injury (RTI) is a major public health problem worldwide, contributing to a large burden of mortality, disability and economic loss. According to the World Health Organisation Global status report on road safety, RTI claims over 1.2 million lives and costs governments nearly 3% of the GDP [1]. In Australia fatal RTIs is decreasing [2], however non-fatal RTIs and their associated costs remain significant. The 2015 Australian Institute of Health and Welfare on serious injuries due to road traffic crashes shows from 2001 to 2010, there was an average annual increase of 0.9% (from 141.6 to 146.6 per 100,000 population) [3]. In 2010, the Bureau of Infrastructure, Transport and Regional Economics estimated the social cost of road crashes to Australia was $17.85 billion in 2006, equivalent to approximately 1.7% of the total GDP [4]. Large proportion of the costs was associated with factors such as injury treatment and rehabilitation, disability and loss of productivity.

Prognosis of musculoskeletal disorders following injury is essential in determining appropriate treatment and care. People with poor prognosis often undergo unnecessary care and treatment, which contribute to significant personal, economic and social burden associated with the condition [5, 6]. In the area of musculoskeletal health care, there is increasing interest in developing and applying prognostic screening tools to stratify patients into risk levels of recovery to direct appropriate level of care. Essentially, those with higher risk should receive more comprehensive care than those with lower risk. To date there is evidence that stratified care has improved outcomes using condition specific tools. For instance, use of the Keele STarT Back Screening Tool to provide stratified treatment for patients with low back pain has demonstrated clinical and cost effectiveness in the UK [7]. Similarly, the short form Orebro Musculoskeletal Pain Screening Questionnaire (SF-OMPSQ) [8] was used to direct appropriate care for workers with soft tissue injury, demonstrating clinically significant improvements in outcomes such as disability and sustained return to work [9]. The SF-OMPSQ covers concept areas found to be associated with recovery, including self-reported level of pain, self-perceived function/disability, distress, fear avoidance and recovery expectation [8]. These concept areas are also among the priority measures for inclusion recommended for future prognostic studies for whiplash injury [6]. Recently, Rebbeck and colleagues conducted a randomised trial [10] to evaluate stratified care for people with whiplash associated disorder using a validated clinical prediction rule [11]. In addition to these studies, there are many prognostic tools to identify the risk of non-recovery early after presentation for specific musculoskeletal injuries such as whiplash [12‐15], idiopathic neck pain [16, 17], low back pain [18], musculoskeletal pain and knee osteoarthritis patients [19, 20]. To date however, there have been no studies that have evaluated a tool that accurately stratifies risk across common musculoskeletal injuries following a road traffic crash.

For clinicians, it is more acceptable and more likely to be used if a single validated prognostic tool could stratify risk of non-recovery across common musculoskeletal injuries. Given the positive outcome from the use of the SF-OMPSQ to drive care for injured workers and its recommendation in recent published models of care [21], we investigated the application of the SF-OMPSQ to stratify risk of non-recovery for people with musculoskeletal injuries after RTI. Specifically, we aimed to examine differences in recovery, return to work and health related quality of life between low and high-risk of poor recovery people with common musculoskeletal injuries (neck, low back and lower limb) at 6 months after RTI.

Our study investigated differences in recovery, return to work and health related quality of life at 6 months following a RTI between low and high-risk of non-recovery groups stratified by the SF-OMPSQ. We found statistically significant higher proportion of recovery and returning to work in the low-risk than the high-risk group. In the occupational injury setting, the Work Injury Screening and Early intervention (WISE) study showed positive outcomes from the application of the SF-OMPSQ in identifying and directing appropriate care and treatment for injured workers based on their identified risk level [9]. Our results, from an inception cohort study, indicated that the SF-OMPSQ is a promising generic tool to identify people at risk of poor recovery among those with musculoskeletal injury to the neck (whiplash), lower back or lower limb after a RTI. The SF-OMPSQ would not only work in the occupational injury setting but also in the cohort traumatic RTIs and across a number of common musculoskeletal injuries.

The significant differences in the SF-12 physical and mental summary component scales at baseline between risk group show that the SF-OMPSQ would also well discriminate people with poorer quality of life when they were identified as being at high-risk of non-recovery. This discriminative ability of the tool would be used by clinician to direct appropriate type and amount of care by the level of risk identified. Over time, the greater extent of improvements in physical scores (between baseline and 6 months after the injury) in the low-risk than those in the high-risk group across all injury groups suggest that regardless of body part injured, people with musculoskeletal pain after an RTI could be managed similarly using a stratified care model; more care would be directed to those identified at higher risk of non-recovery.

The strength in our study is that it demonstrated some promising properties of the SF-OMPSQ for RTIs. However, room for improvement of the tool still exists. In the low-risk of non-recovery group in our study, there were still large proportions of participants, who did not recover and similarly some of those with high-risk, who did recover. This suggests that a group with a medium risk of non-recovery may exist. In fact, a number of risk stratification tools for musculoskeletal injuries have medium level of non-recovery in addition to the common low and high-risk levels, such as the clinical prediction rule for whiplash injuries [14] or the Keele STarT Back Screening Tool for low back pain [7]. The identification of medium risk group would minimise the likelihood of missing out people who should have a more comprehensive care if they were stratified into the low-risk group.

Our study also has limitations. Participants’ recovery, return to work and/or health related quality of life would be influenced by other factors such as the medical care and treatment that they received following their injuries. At this stage, we are limited in the data collected from the study questionnaires. In the design of the original study, linked data on health service utilisation and hospitalisation for all participants will be available [22]. These additional data would allow us to conduct further analyses adjusting for health and hospital service utilisation. While we conducted multi-variable analyses when comparing the recovery and return to work outcomes to adjust for potential confounders, we were limited in variables/participants’ characteristics included in our questionnaires. Therefore, there was potential for residual confounding due to unmeasured factors such as personal coping skills, family circumstances, employer characteristics, working conditions, readiness/intent to return to work scales. The observed results for health-related quality of life were also potentially confounded due to measured factors, since they were not adjusted for in the analysis. Another limitation was the bias due to loss to follow-up and missingness in the data, which would influence our observed associations.

Despite limitations, results from our study provided some important implications for practice and further research. The tool was administered by trained interviewers, who were research nurses at study recruitment sites, within 28 days of the crash. In this and the WISE study, the tool was administered in a clinical or primary setting. It was demonstrated that the tool was better in these setting compared to the data from participants from the general public. The tool would potentially be tested by other users, such as an insurer case manager, for reliability and validity compared to clinicians. Another aspect is the time frame for the tool to be administered. A window of time between four and 6 weeks from the time of crash would be considered appropriate. Once the risk of poor recovery is identified, there would be time for intervention before the condition/pain would become chronic (i.e. lasting for 3 months or more). For patients identified as high-risk, they would be referred to specialist for further examination and appropriate care.

For future research, in addition to the study to identify threshold for medium risk group based on the SF-OMPSQ score, there should be studies to compare use of the SF-OMPSQ and other risk stratification tools. For instance, the SF-OMPSQ would be compared with the clinical prediction rule to stratify risk of non-recovery among whiplash injuries or the SF-OMPSQ would be compared with the Keele STarT Back Screening Tool to identify risk levels for patients with low back pain. In addition, a randomised trial similar to the WISE study for RTIs with care and treatment directed by the use of the SF-OMPSQ score would also be desirable.

Our study provides evidence that the SF-OMPSQ could be used as a prognostic tool for early identification of people with risk of non-recovery following RTI. Consistently across common musculoskeletal injuries (including neck, lower back and lower limb), individuals identified to be at low-risk were more likely to recover and return to work. Further research is needed to compare the SF-OPMSQ and other prognostic tools for its reliability and validity; and also to examine its feasibility to apply in the hospital and primary health care settings, and then to drive appropriate level of care according to the level of risk identified.