Methods and tools used by healthcare professionals to identify barriers to return-to-work for workers with upper extremity conditions in Australia

Abstract

Introduction

Healthcare professionals, including hand therapists, are frequently called upon to identify barriers to return-to-work for workers with upper extremity injuries. However, the methods and tools used to assess barriers to return-to-work remain unknown. Results from these assessments can be used to direct appropriate interventions for those who may be at risk of a prolonged work absence.

Methods

The purpose of this study was to identify the tools and methods used by healthcare professionals to assess barriers to return-to-work for workers with upper extremity conditions. A total of 596 Australian healthcare professionals responded to an open-ended question regarding the tools/methods they use to identify barriers to return-to-work. All responses were coded and analysed descriptively. Differences between professional disciplines were recorded.

Results

Healthcare professionals nominated 59 types of tools and methods that they use to identify barriers to return-to-work for workers with upper extremity conditions in their clinical practice. The most favoured method was clinical interviewing. Other commonly used tools were clinical measures, e.g., strength, and a return-to-work risk-factor screening tool validated on musculoskeletal diagnoses, the Orebro Musculoskeletal Screening Questionnaire.

Discussion

Healthcare professionals use a variety of methods and tools to identify barriers to return-to-work for workers with upper extremity conditions. Generally, they favoured subjective methods. Future research is needed to develop or validate assessment tools designed to identify barriers to return-to-work for workers with upper extremity conditions. In the absence of upper extremity specific screening tools, hand therapists should consider the biopsychosocial framework when evaluating barriers to return-to-work.

Keywords

Assessment work disability occupational health workers’ compensation risk factors

Introduction

The majority of serious workers’ compensation claims in Australia involve the upper extremity.¹ Research has found that workers with a work-related upper extremity condition return to some form of work at least once after diagnosis of their conditions; however, a first return does not necessarily mark the end of work disability. Among workers absent at least once, 26% report a second injury-related absence.² In the Australian workers’ compensation setting (similar to insurance agencies internationally), healthcare professionals (HCPs), including hand therapists, are expected to identify barriers to work resumption and recommend strategies to overcome these barriers.^3,4

Evidence from a systematic review and a Delphi study of experts indicated that prognostic factors for return-to-work for workers with upper extremity conditions are largely influenced by psychosocial factors.^5,6 A cross-sectional study of workers with upper extremity disorders and a workers’ compensation claim found that a combination of ergonomic and psychosocial factors (including feelings of being overwhelmed by pain, low confidence in problem solving, high ergonomic risk and other non-pain-related symptoms) contributed twice as much towards a poorer outcome than pain alone.⁷ In a prospective cohort study of 91 workers, Opsteegh et al.⁸ examined prognostic factors for return-to-work following any type of hand surgery. They found a number of prognostic variables for a delayed return-to-work including pain, post-traumatic stress disorder symptoms and the accident occurring at work. All of these studies point towards a multidimensional paradigm for understanding the reasons for prolonged or multiple work absences for workers with upper extremity conditions. This was highlighted by Feuerstein in 2000,⁹ who then discussed the importance of a multifactorial screening approach for determining return-to-work in workers with upper extremity conditions and using this to improve work-related outcomes. Thus, supporting the emerging paradigm to identify early risk factors associated with a delayed return-to-work using the biopsychosocial model.^1,3,4,10 This has been advocated by the World Health Organisation and adopted by various workers’ compensation and health-related agencies.^1,3,4,10 When modifiable biopsychosocial risk factors are recognized early in the injury trajectory, appropriate interventions can theoretically be implemented to facilitate a successful earlier return to employment and improve disability-related outcomes. However, what is unknown is whether HCPs implement biopsychosocial tools and methods to identify barriers to return-to-work for workers with upper extremity conditions in their clinical practice?

Assessment methods and tools (either objective, clinician-directed or patient reported) can be used to evaluate barriers to return-to-work. Shaw et al.¹¹ categorized the various assessment tools and methods with respect to their delivery/format: (i) patient questionnaires, (ii) semi-structured clinical interviews, (iii) worksite evaluations, (iv) clinician’s overall impressions and clinical opinion, (v) objective measurements and (vi) data from administrative resources. More recently, researchers have developed various screening questionnaires, based on the biopsychosocial model, that have the potential to identify barriers to return-to-work and thereby facilitate recovery for workers with back pain and general musculoskeletal disorders.^12–15 These tools, usually in the format of patient questionnaires or structured interviews, allow clinicians to screen workers to identify risk factors for a prolonged work absence. Based on this, clinicians can then discuss these risk factors with the key return-to-work stakeholders and devise an intervention plan to facilitate a safe and speedy return to meaningful employment. However, these types of screening tools are yet to be validated in workers with upper extremity conditions.¹⁶ Another tool, the ‘flags method’ has also been popularized as a method for identifying psychosocial barriers to return-to-work in the literature.^15,17–19 Although not validated specifically on workers with upper extremity, it has been implemented in workers’ compensation jurisdictions, including some in Australia.²⁰

Research question and study purpose

The research question was: which methods and/or specific tools are currently being utilized by HCPs to identify return-to-work barriers for workers with upper extremity conditions (e.g., carpal tunnel syndrome, lateral epicondylalgia and rotator cuff pathology) and injuries (e.g., fractures, tendon repairs and mutilating traumas)? Thus, the purpose of this study was to explore the types of assessment tools and methods most frequently used by Australian HCPs in their current clinical practice to identify barriers to return-to-work for workers with upper extremity conditions.

Methods

This paper reports on the responses from a section of a larger cross-sectional survey administered to Australian return-to-work stakeholders.²¹ Only HCPs involved in the management of workers with work-related injuries completed the section of the survey regarding assessment tools used to identify barriers to return-to-work. Detailed information on the other sections of the survey can be found elsewhere.²¹ The surveys were completed between August 2013 and January 2014.

Development of the survey

The survey was piloted prior to distribution. Participants of the pilot round were stakeholders with various roles in the return-to-work process and over 10 years’ experience managing workers with upper extremity conditions. Modifications were made to the survey content and format. This included wording of the questions. Following this, the questionnaire was distributed to another 10 return-to-work stakeholder representatives to establish reliability between the electronic and hardcopy. They completed each format of the questionnaire with a minimum of 24 h between each. The formats were found to be reliable and, thus, interchangeable.²¹

This paper summarises the data from an open-ended question that was included in the survey: ‘What assessment tools or methods do you use in your practice to identify barriers to return-to-work?’ Respondents were able to list one or more assessment tools or methods that they use in their clinical practice when dealing with workers with upper extremity conditions. Examples of common conditions provided were carpal tunnel syndrome, lateral epicondalgia, wrist tendinopathies and rotator cuff pathology. Ethical approval was received from the School of Health and Rehabilitation Sciences, The University of Queensland (2012SHRS_OT007). Completion of the surveys was voluntary.

Sampling strategy and dissemination

Distribution of the questionnaire to the HCPs was through various gatekeeper organizations (refer to Acknowledgements), using an online survey platform (SurveyMonkey®) and hard copy surveys distributed at key stakeholder events and conferences. In addition, the survey was disseminated by the ‘RTW Matters’ online newsletter (www.RTWmatters.org). This newsletter is disseminated nationally to HCPs, employer representatives and insurer claims advisors and case managers. Gatekeeper organisations and the ‘RTW Matters’ newsletter were asked to distribute the survey with two reminders being sent at two-weekly intervals.

A ‘snowball’ dissemination strategy was used.^22,23 This allowed respondents to forward the electronic survey on to other HCPs that manage patients with upper extremity conditions who may not be affiliated with a gatekeeper association. This dissemination strategy was selected as snowball dissemination methods have been advocated as a valid, unbiased method to access hidden populations of participants that may not be affiliated with ‘seed’ gatekeeper associations, thus ensuring a more representative sample.^22,23 The electronic survey portal remained open to receive completed surveys for a one-month period until no further surveys were received (i.e., the portal closed in February 2014). After the one-month period of no surveys being received, the portal was closed and the respondent population was considered to be adequately exhausted.^22,23 Hardcopy responses were later entered into SurveyMonkey® by a person external to the study.

Data analysis

Descriptive statistics were used to detail the demographic data of the participants (Table 1). To analyse the data from the open-ended question, we first coded the responses into categories of assessment tools. Due to the number of tools and methods, we grouped similar tools into logical categories determined by the researchers. For example, different variations of Functional Capacity Evaluations (FCEs) were combined into one category. Then using an iterative process, categories were refined to create a final list. We collapsed different types of similar overall assessment methods into one category that best described the tools. Any ambiguous or unfamiliar tools were discussed between the authors to gain consensus on the tool’s categorization. When particular protocols for functional or psychological evaluations were not specifically described, it was assumed that these methods were not objective or validated instruments due to lack of explicit description regarding the methods. Hence, these responses were recorded as tools under ‘semi-structured clinical interviews’. For example, when HCPs stated, ‘assess function’ or ‘functional assessment’ these were described as ‘functional assessments – not specified’ and ‘assess psychological state” or “general psychological evaluation’, these were coded as ‘psychological evaluation – not specified’. Also on occasion, participants nominated strategies (e.g., pain management or exercise program) instead of an assessment tool. These responses (n = 156) were not considered valid responses detailing an assessment tool or method and hence were not coded. Frequencies for each of the categorized tools/methods were calculated for the overall HCP group and for each discipline.

Table 1.

Demographics characteristics of the healthcare professionals.

		HT	PT	OT	Surgeons	OP	EP	Psychologists	Nurse	Other	Total
% (n)		26.8 (160)	21.0 (125)	18.1 (108)	12.2 (73)	7.5 (45)	7.2 (43)	4.0 (24)	2.3 (14)	0.7 (4)	596
Number of assessment tools nominated	Mean	3.1	2.8	3.3	1.7	2.2	2.7	2.8	1.9	3.3	2.7
	Range	0–8	0–12	0–10	0–6	1–5	0–6	1–10	0–6	1–7	0–12
	SD	1.7	1.7	1.9	1.3	1.1	1.4	2.3	1.7	2.9	1.7
% Workers managed that are workers’ compensation (%)	0–25%	25.6	41.6	21.2	19.2	15.6	14.0	16.7	42.9	50.0	155
	26–50%	30.0	25.6	19.4	37.0	6.7	18.6	8.3	21.4	0.0	144
	51–75%	25.6	15.2	23.1	23.3	8.9	9.3	8.3	14.3	0.0	114
	>75%	18.8	17.6	36.1	20.5	68.9	58.1	66.7	21.4	50.0	183
Gender (%)	Female	90.6	63.2	89.8	6.8	15.6	55.8	87.5	92.9	100.0	395
Gender (%)	Male	9.4	36.8	10.2	93.2	84.4	44.2	12.5	7.1	0.0	201
Age (%)	21–29	13.8	29.6	20.4	0.0	0.0	55.8	4.2	7.1	0.0	107
	30–39	41.3	28.0	29.6	23.3	11.1	25.6	29.2	0.0	25.0	174
	40–49	26.3	23.2	34.3	31.5	13.3	11.6	25.0	14.3	25.0	151
	50–59	15.6	12.8	13.0	31.5	31.1	7.0	25.0	14.3	25.0	106
	60 or older	3.1	4.8	2.8	13.7	51.1	0.0	16.7	42.9	25.0	58
State (%)	ACT	1.8	1.6	4.6	2.7	6.6	0.0	4.2	14.3	25.0	19
	NSW	27.5	70.4	26.9	21.9	11.1	81.4	10.0	28.6	75.0	225
	NT	0.6	0.0	2.7	0.0	0.0	2.3	8.3	0.0	0.0	7
	QLD	28.1	18.4	37.0	40.8	22.2	9.3	20.8	7.1	0.0	164
	SA	7.0	2.4	10.2	9.6	13.3	0.0	20.8	0.0	0.0	39
	TAS	4.4	1.6	0.0	2.7	2.2	2.3	0.0	0.0	0.0	8
	VIC	22.5	4.0	15.7	12.3	24.4	0.0	4.2	50.0	0.0	86
	WA	9.4	1.6	11.1	5.5	48.9	4.6	0.0	0.0	0.0	39
	Other	–	–	–	–	–	–	–	–	–	9

ACT: Australian Capital Territory; NSW: New South Wales; NT: Northern Territory; QLD: Queensland; SA: South Australia; TAS: Tasmania; VIC: Victoria; WA: Western Australia; HT: hand therapists; PT: physiotherapists; OT: occupational therapists; OP: occupational physicians; EP: exercise physiologists.

Results

In total, 752 HCPs completed the questionnaire, of which 596 respondents provided valid responses that could be coded for analysis. These included hand therapists (i.e., occupational therapists or physiotherapists practising in hand therapy) (26.8%), physiotherapists (21%), occupational therapists (18.1%), surgeons (i.e., hand surgeons, orthopaedic surgeons, plastic surgeons, neurosurgeons) (12.2%), occupational physicians/general practitioners (7.5%), exercise physiologists (7.2%), psychologists/counsellors (4%), nurses (2.3%) and other HCPs (including social workers and speech pathologists working in occupational rehabilitation) (0.7%). The characteristics of the HCPs are described in Table 1.

A total of 59 assessment tools and/or methods were reported by the HCPs. Each HCP nominated a median of two assessment tools or methods (range: 0–12). The frequency of each of the categorized assessment tools nominated by each discipline can be viewed online as a supplementary file.

Overall, a mix of assessment methods was nominated, including clinician’s overall impression and clinical opinion (e.g., interviews, discussions, clinical reasoning), semi-structured interviewing (e.g., insurer specific checklists), objective measurement (e.g., functional capacity evaluations), worksite evaluations and patient-rated questionnaires (e.g., disabilities of the arm, shoulder and hand (DASH)).

Table 2 lists the 10 highest responses from each HCP discipline and the responses from all of the groups combined. The majority of the stakeholders indicated that they use subjective methods, i.e., their own overall impression and clinical opinion to inform their clinical judgments. The most favoured method by all stakeholders combined was clinical interviewing and history received directly from the worker (40.4%). This was the favoured method by surgeons, occupational physicians, occupational therapists and psychologists (64.4% 54.8%, 47.2% and 41.7%, respectively). However, physiotherapists and exercises physiologists favoured the Orebro Musculoskeletal Pain Questionnaire (OMPQ) (46.4% and 48.8%, respectively) and hand therapists favoured strength assessments (e.g., grip strength) (57.5%). An online Appendix (Table 3) includes responses from all HCP disciplines.

Table 2.

Most common assessment tools nominated by the healthcare professionals.

Ranking	Hand therapists	Occupational therapists	Physiotherapists	Surgeons	Occupational physicians/GPs	Exercise physiologists	Psychologists	All groups
1	Strength testing (57.5%)	Interviewing/history taking (47.2%)	OMPQ (46.4%)	Interviewing/history taking (54.8%)	Interviewing/history taking (64.4%)	OMPQ (48.8%)	Interviewing/history taking (41.7%)	Interviewing/history taking (40.4%)
2	Range of movement/goniometry (39.4%)	Strength testing (31.4%)	Interviewing/history taking (29.6%)	Physical clinical examination (30.1%)	Meeting/discussion with stakeholders (33.3%)	Interviewing/history taking (44.2%)	OMPQ (33.3%)	Strength testing (26.8%)
3	Interviewing/history taking (31.3%)	ROM/goniometry (29.6%)	ROM/goniometry (20%)	Meeting/discussion with stakeholders (12.5%)	Physical clinical examination (24.4%)	Meeting/discussion with stakeholders (20.9%)	Meeting/discussion with stakeholders (29.2%)	OMPQ (24%)
4	DASH/quick DASH (23.1%)	FCE (26.9%)	Strength testing (17.6%)	Strength testing (12.5%)	Documentation from stakeholders (13.3%)	Questionnaires- not specified (18.6%)	DASS (25%)	ROM/goniometry (21.8%)
5	FCE (17.5%)	Meeting/discussion with stakeholders (25%)	Manual muscle testing (17.6%)	None (12.5%)	Worksite assessment (13.3%)	Functional assessment - not specified (14.0%)	Psychological evaluation (20.8%)	Meeting/discussion with stakeholders (16.1%)
6	Worksite assessment (16.9%)	Worksite assessment (21.2%)	Physical clinical examination (16.8%)	Meeting/discussion with stakeholders (10.9%)	Flags model (13.3%)	FCE (14.0%)	Clinical reasoning/experience (16.7%)	FCE (15.3%)
7	Pain severity scale (16.9%)	OMPQ (19.4%)	FCE (16.8%)	Radiology and test results (9.6%)	OMPQ (11.1%)	FACTORWEB (14.0%)	Flags model (12.5%)	Physical clinical examination (13.9%)
8	Sensibility tests (16.9%)	Pain Severity Scale (17.6%)	Functional assessment not specified (16.8%)	Range of movement/goniometry (9.6%)	DASS (11.1%)	Physical clinical examination (11.6%)	Pain severity scale (12.5%)	DASH/quick DASH (11.9%)
9	Functional assessment not specified (15.0%)	DASH/quick DASH (17.6%)	Pain severity scale (11.2%)	Worksite assessment (8.2%)		DASS (11.6%)	FACTORWEB (12.5%)	Functional assessment not specified (11.7%)
10	Physical clinical examination (10.6%)	Functional assessment not specified (13.9%)	Questionnaires not specified (10.4%)	Subjective examination not specified (8.2%)		Worksite assessment (11.6%)		Pain severity scale (11.4%)

GP: general practitioners; OMSQ: Orebro Musculoskeletal Pain Questionnaire; DASH: disabilities of the arm, shoulder and hand; FCE: Functional Capacity Evaluation; ROM: Range of Movement; DASS: Depression Anxiety Stress Scale.

Discussion

Overall, HCPs favoured subjective methods (such as clinical interviewing and semi-structured interviews) to inform their own impressions of barriers for return-to-work. The most common subjective method was the use of clinical interviewing (40.4%) which was preferred by occupational therapists, surgeons, occupational physicians and psychologists. This method was the second most favoured method for physiotherapists and exercise physiologists. Subjective assessments were most likely nominated, as they are a routine part of a clinical appointment. They are also able to capture factors that are not purely biological in nature (e.g., the context of the injury, such as timing of injuries, previous interventions). This allows psychosocial factors (such as, observed and reported psychological state and exploration of workplace issues) to be explored by probing and discussing issues and concerns with the worker. Clinical interviewing is also an essential component of clinical reasoning used by HCPs in diagnosis. Therefore, it is not surprising that this was the favoured method used to identify barriers to return-to-work. Furthermore, clinical reasoning is a higher level function that often combines information obtained from multiple sources, such as interviewing and objective measures, to make decisions and recommendations.²⁴ Therefore, it is also possible that HCPs did not nominate clinical reasoning as frequently as the other methods, as they nominated a battery of tools, including clinical interviewing, to inform their clinical reasoning and recommendations for intervention.

Hand Therapists identified strength testing and goniometry as their primary tools to assess barriers to return-to-work in their practice. These tools are important objective measures to monitor progress for recovery, but focus on the biological impairment itself, which has equivocal evidence for their relationship with earlier return to work. For example, grip strength has not been found to be a strong prognostic variable for return-to-work following carpal tunnel release.⁴ Interestingly, using a clinician’s overall impression or clinical opinion to guide identification of return-to-work barriers, such as, clinical interviewing, was nominated by only 30% of this group. However, clinical interviewing is a key part of the hand therapy session.²⁵ It might be possible that hand therapists focused on the objective biological impairment measures, as these are validated and standardised instruments frequently used in their practice, but still engage routinely in clinical interviewing. Furthermore, standardised and valid measures, such as grip strength and range of movement testing, are favoured by insurance agencies in Australia as documented in the Clinical Framework for Delivery of Health Services in Australian compensable settings.^26–29

Physiotherapists and exercise physiologists preferred use of the OMPQ to identify barriers. Interestingly, the OMPQ was designed as a screening tool to identify psychosocial barriers in patients with low back pain, not upper extremity diagnoses.³⁰ Their selection of this tool as a favoured method may reflect their experience that this tool can be generalized across various musculoskeletal conditions. It’s utility is also advocated by various Australian insurance agencies (including workers’ compensation insurers).^26,27,31,32

Interestingly, fewer HCPs nominated work-related assessment tools such as worksite assessments and functional capacity evaluations to identify barriers to return-to-work, despite these being key services provided by return-to-work intervention providers (such as, occupational therapists).³³ Although functional capacity evaluations and worksite evaluations are commonly used to facilitate return-to-work, Gross and Battie³⁴ found that functional performance was indeed a weak predictor for workers’ compensation claim closure and recovery for workers with upper extremity conditions. Perhaps, through focusing on functional capacity and workplace issues, clinicians may ignore the psychological or social factors that may also pose as barriers in the return-to-work process. Further research needs to be conducted to specifically establish the benefit of worksite assessments and FCEs for workers with upper extremity conditions.

It is not surprising that the various self-report patient questionnaires are not commonly used. The tools that were nominated were often directed at assessing discrete barriers to return-to-work, such as pain catastrophizing or fear avoidance beliefs questionnaires. While it is feasible that these psychological factors are barriers to an early return to work, there is limited evidence for their validity to assess workers with upper extremity conditions. Therefore, they are probably best used in a battery of assessments to examine psychosocial functioning or in isolation when specific concerns are raised through clinical interviewing. Recommendations have also been made that a staged process to assess psychosocial barriers to recovery and return-to-work should be conducted when a worker does not return to work at two weeks or later for other musculoskeletal conditions.^11,19

Surprisingly, the DASH and its short version were nominated by 11.9% of respondents. Although not specifically designed as a tool to identify barriers to return-to-work, the DASH contains an optional work module which can be used to assess the impact of an upper extremity condition on work participation.³⁵ Besides the DASH questionnaire, most other upper extremity questionnaires (e.g., Constant score, Patient Rated Wrist (and Hand) Evaluation (PRWHE), Upper Extremity Index (UEFI), Shoulder Pain and Disability Index (SPADI)) focus on impairment and activity restriction and may contain only a single item on ability to participate in work.

There are several plausible explanations for the variation in tools and methods nominated by the HCPs. First, there are no known validated tools designed to specifically screen for barriers to return-to-work for workers with upper extremity conditions. Therefore, it is possible that HCPs default to using tools that they have the greatest familiarity in their clinical practice, in the hope of gaining some insight regarding the potential barriers for return-to-work. Second, HCPs may expect that by identifying barriers to recovery, such as pain or physical restrictions, barriers to return-to-work will also be revealed. Third, perhaps HCPs do not understand what constitutes a barrier for return-to-work and are therefore unsure how to assess them. Finally, the HCPs in this study may feel it is not part of their role or scope of practice to assess barriers for return-to-work.

Clinical implications for hand therapists

The literature strongly supports the use of a biopsychosocial framework for understanding barriers to return-to-work, which extends to workers with upper extremity conditions.^3,6,10,36 However, the concept that there are barriers to work resumption that extend beyond physical ability, relating to psychological, social and environmental factors has been poorly discussed in the hand therapy literature.¹⁶ Unfortunately, although specific tools to assess biopsychosocial barriers to return-to-work based on prognosis studies for some musculoskeletal conditions exist,^12–14 these have not yet been developed explicitly for, or validated on, workers with upper extremity conditions.¹⁶ In the absence of validated tools, hand therapists should: (i) use methods or a battery of assessment tools that assess biological, psychological, social and work-related barriers (or refer to members of a multidisciplinary team (e.g., psychologists, medical doctors) to assess risk factors outside of their scope of practice); (ii) consider the perspectives of the key return-to-work stakeholders involved in the patient’s return to work; and (iii) use this information to guide their own clinical judgement and recommendations for return-to-work. Ultimately, if specific tools become available that have been validated, or developed, specifically for workers with upper extremity conditions, these should be used to inform practice.

Limitations of this study

One limitation of the study was that we could not estimate the total population of potential respondents who may have been sent the survey. The reasons for this are three-fold: first, we used a snowball dissemination method and therefore some respondents may not be affiliated with a gatekeeper association; second, the number of total members of each of the professional associations was not always publically available or was not revealed by the association to the researchers; and third, respondents may be members of multiple associations but were asked to only complete the survey once even if they received multiple invitations.

Another limitation of this study was that we were unable to obtain an equal number of participants from each HCP discipline for our sample. However, this is most probably a reflection of the relative proportion of these HCPs who actually work with upper extremity patients. Hand therapists formed the largest group. It is also likely that some of the respondents who nominated themselves as an occupational therapist or a physiotherapist may also work in the hand therapy field. In Australia, there are currently over 600 members of the Australian Hand Therapy Association, so it is not surprising that many were interested in being involved in this study as it has a direct impact on their management of injured workers. Also we investigated the type of assessment tools that the different HCPs from various disciplines used; however, we did not directly question the rationale behind the utility of each specific tool. The survey method did not lend itself to adequate exploration of this. A future qualitative study (either through interviews or focus groups) in which HCPs are required to discuss the processes they use to identify barriers to return-to-work and explain the reasoning behind the selection of particular assessment tools would be a preferred method to yield this information. This would also allow clarification behind some of the nominated methods such as ‘functional assessment – not specified’ or ‘psychological evaluation – not specified’.

It is also important to consider that HCPs may use other assessment tools and methods that they did not report using the format of an open-ended question on a questionnaire. It is possible that there was a reporting bias with HCPs only reporting the assessment tools that were most frequently used in their practice or those that were front-of-mind. Regardless, it is still plausible to consider that the assessment methods and tools nominated were likely to be those used most frequently and hence, more favoured tools.

Conclusions

Australian HCPs use a variety of tools and methods to identify barriers to return-to-work when managing workers with upper extremity conditions and injuries. Overall, HCPs favoured subjective methods, such as clinical interviewing. However, hand therapists frequently nominated physical impairment based testing, such as grip strength and goniometry. It is recommended that hand therapists consider the importance of assessing for psychosocial contributors for prolonged work absences. Further research is needed to develop or validate assessment tools for identifying barriers to return-to-work specifically for workers with upper extremity conditions and injuries. Such tools would assist hand therapists and other HCPs and could be used to direct appropriate interventions for those workers who may be at risk of a delayed or poorer work outcome.

Footnotes

Acknowledgements

The authors would like to acknowledge the following organizations for disseminating the survey: Australian Hand Therapy Association, Queensland Hand Surgery Society, Australian Lawyers Alliance, Australian Shoulder and Elbow Society, Australian Society for Surgery of the Hand, Occupational Therapy Australia, Australian and New Zealand Society of Occupational Medicine, Australian Faculty of Occupational and Environmental Medicine, Australian Rehabilitation Providers Association, RTW Matters, Queensland Law Society, QComp and Self Insurers Association (Australia). We would like to thank Bertrand Koh for assistance with data management. This study was generated and included as part of the first author Susan Peters’ doctoral thesis.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was partially supported by a research grant from the Australian Hand Therapy Association.

References

Safe Work Australia. The cost of work-related injury and illness for Australian employers, workers and the community, 2012–2013. Canberra: Safe Work Australia, www.safeworkaustralia.gov.au/sites/SWA/about/Publications/Documents/940/cost-of-work-related-injury-and-disease-2012-13.docx.pdf (2015, accessed 9 August 2016).

Baldwin

Butler

. Upper extremity disorders in the workplace: costs and outcomes beyond the first return to work. J Occup Rehabil 2006; 16: 303–323.

Workcover Victoria. Clinical framework for the delivery of health services. Victorian workcover authority, Melbourne, Victoria: Victorian WorkCover Authority, 2012.

Workcover Queensland. Realising the health benefits of work detailed information State of Queensland (Work Cover Queensland)., https://www.worksafe.qld.gov.au/injury-prevention-safety/health-and-wellbeing-at-work/health-and-wellbeing/realising-the-health-benefits-of-work/realising-the-health-benefits-of-work-detailed-information (2015, accessed 9 August 2016).

Peters SE, Hines S, Coppieters MW, et al. Prognostic factors for return-to-work following carpal tunnel release: a systematic review. Joanna Briggs Institute Library Syst Rev 14: 9.

Peters SE, Johnston V, Ross M, et al. Expert consensus on facilitators and barriers to return-to-work following surgery for non-traumatic upper extremity conditions. A Delphi study. J Hand Surg (European). Epub ahead of print 20 June 2016.

Shaw

Feuerstein

Lincoln

. Ergonomic and psychosocial factors affect daily function in workers' compensation claimants with persistent upper extremity disorders. J Occup Environ Med 2002; 44: 606–615.

Opsteegh

Reinders-messelink

Schollier

. Determinants of return to work in patients with hand disorders and hand injuries. J Occup Rehabil 2009; 19: 245–255.

Feuerstein

Huang

Haufler

. Development of a screen for predicting clinical outcomes in patients with work-related upper extremity disorders. J Occup Environ Med 2000; 42: 749–761.

10.

World Health Organization. The burden of musculoskeletal conditions at the start of the new millenium. Geneva, Switzerland: World Health Organization, http://apps.who.int/iris/bitstream/10665/42721/1/WHO_TRS_919.pdf. (2003, accessed 9 August 2016).

11.

Shaw

van der Windt

Main

. Early patient screening and intervention to address individual-level occupational factors (“Blue Flags”) in back disability. J Occup Rehabil 2009; 19: 64–80.

12.

Linton

Nicholas

MacDonald

. Development of a short form of the Örebro Musculoskeletal Pain Screening Questionnaire. Spine 2011; 36: 1891–1895.

13.

Shaw

Reme

Pransky

. The pain recovery inventory of concerns and expectations: a psychosocial screening instrument to identify intervention needs among patients at elevated risk of back disability. J Occup Environ Med 2013; 55: 885–894.

14.

Hill

Dunn

Lewis

. A primary care back pain screening tool: identifying patient subgroups for initial treatment. Arthritis Rheum 2008; 59: 632–641.

15.

Gray

Adefolarin

Howe

. A systematic review of instruments for the assessment of work-related psychosocial factors (Blue Flags) in individuals with non-specific low back pain. Man Ther 2011; 16: 531–543.

16.

Peters SE, Ross M and Johnston V. Improving work-related outcomes following upper extremity injury: current concepts, methodological challenges and considerations for future research. Open Orthop. Epub ahead of print 16 March 2016.

17.

Kendall

NAS

Linton

Main

. Guide to assessing psychosocial yellow flags in acute low back pain: risk factors for long-term disability and work loss, Wellington, New Zealand: Accident Rehabilitation and Compensation Insurance Corporation, 1997.

18.

Leerar

Boissonnault

Domholdt

. Documentation of red flags by physical therapists for patients with low back pain. J Manipulative Physiol Ther 2007; 15: 42–49.

19.

Nicholas

Linton

Watson

. Early identification and management of psychological risk factors (“Yellow Flags”) in patients with low back pain: a reappraisal. Phys Ther 2011; 91: 737–753.

20.

Workcover Western Australia. Using the flags model: a practical guide for GPs. In: The clinical framework for health care delivery, http://gpsupport.workcover.wa.gov.au/content/uploads/sites/2/2015/07/UsingTheFlagsModel_A_PracticalGuideForGPs_FinalAcess.pdf (2015, accessed 7 August 2016).

21.

Peters SE. Factors influencing return-to-work following upper extremity surgery. PhD thesis, The University of Queensland, Australia, https://espace.library.uq.edu.au/view/UQ:396027/s4216049_Thesis_final_20160708.pdf. (2016, accessed 9 August 2016).

22.

Sadler

Lee

Lim

. Recruitment of hard-to-reach population subgroups via adaptations of the snowball sampling strategy. Nurs Health Sci 2010; 12: 369–374.

23.

Matthew

Heckathorn

. Sampling and estimation in hidden populations using respondent-driven sampling. Sociol Methodol 2004; 34: 193–240.

24.

Ajjawi

Higgs

. Learning to reason: a journey of professional socialisation. Adv Health Sci Educ 2008; 13: 133–150.

25.

Pitts

Willoughby

Morgan

Clinical reasoning and problem solving to prevent pitfalls in hand injuries. In: Cooper

(ed). Fundamentals of hand therapy: clinical reasoining and treatment guidelines for common diagnoses of the upper extremity, 2nd ed. St Louis: Elsevier Mosby, 2014, pp. 87–102.

26.

Traffic Accident Commission. Standard outcome measures, www.tac.vic.gov.au/providers/clinical-resources/outcome-measures (2016, accessed 9 August 2016).

27.

Workcover New South Wales. Practice guidelines, https://www.workcover.nsw.gov.au/workers-compensation-claims/medical-professionals/allied-health-practitioners/practice-guidelines (2016, accessed 9 August 2016).

28.

Workcover Queensland. Allied health providers: State of Queensland (WorkCover Queensland), https://www.worksafe.qld.gov.au/service-providers/allied-health-providers (2016, accessed 9 August 2016).

29.

Worksafe Victoria. Clinical framework for the delivery of health services, www.worksafe.vic.gov.au/__data/assets/pdf_file/0006/3885/clinical-framework.pdf (2012, accessed 9 August 2016).

30.

Johnston

. Orebro Musculoskeletal Pain Screening Questionnaire. Aust J Physiother 2009; 55: 141–141.

31.

Australian Government (Department of Veterans Affairs). Heads of Workers' Compensation Authorities & Heads of Compulsory Third Party: Biospsychosocial injury management, www.hwca.org.au/documents/HWCA%20HCTP%20-%20Biopsychosocial%20Injury%20Management%20Paper.pdf (2011, accessed 9 August 2016).

32.

Western Australia Workcover. Musculoskeletal injuries, http://gpsupport.workcover.wa.gov.au/applied-resources-for-gps/musculoskeletal-injuries/ (2015, accessed 9 August 2016).

33.

Roberts-Yates

. Examining the role of rehabilitation in the South Australian Workers' compensation system. Aust J Rehabil Counselling 2003; 9: 82–101.

34.

Gross

Battie

. Does functional capacity evaluation predict recovery in workers compensation claimants with upper extremity disorders? J Occup Environ Med 2006; 63: 404–410.

35.

Kennedy

Beaton

Solway

. Disabilities of the arm, shoulder and hand (DASH). The DASH and QuickDASH outcome measure user’s manual, 3rd edn. Toronto, ON: Institute for Work and Health, 2011.

36.

Burton AK, Kendall NAS, Pearce BG, et al. Management of upper limb disorders and the biopsychosocial model. Norwich, UK: Health and Safety Executive, www.hse.gov.uk/research/rrpdf/rr596.pdf (2008, accessed 9 August 2016).