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Measuring outcomes and monitoring progress in the era of evidence-based clinical practice

Published online by Cambridge University Press:  20 December 2019

Robyn L. Tate
Robyn L. Tate*
Affiliation:
John Walsh Centre for Rehabilitation Research, Kolling Institute of Medical Research, Faculty of Medicine and Health, The University of Sydney, Australia
*
Email: robyn.tate@sydney.edu.au
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Abstract

Health outcome measurement is a growth industry. Thousands of behavioural assessment instruments, developed for neurological populations alone, are available for diagnosis, prediction and evaluation of interventions. The task of selecting the best instrument for the purpose at hand is thus a daunting one for the clinician and researcher. Fortunately, there are guides that make the task easier. This presidential address covers three interrelated themes that inform assessment in neurorehabilitation: First, it reviews current concepts and the status of behavioural assessment in neurorehabilitation. It then examines evidence-based clinical practice as applied to assessment of function, along with methods to benchmark the scientific quality of assessment instruments. Finally, the article considers the need to move beyond outcome measurement in the neurorehabilitation setting.

Keywords

Measurementevidence-based assessmentInternational Classification of Functioning, Disability and HealthCOSMINsingle-case methodsneurorehabilitation
Type
Presidential address
Information
Brain Impairment , Volume 20 , Issue 3 , December 2019 , pp. 276 - 288
Copyright
© Australasian Society for the Study of Brain Impairment 2019 

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References

Cieza, A., Geyh, S., Chatterji, S., Kostanjsek, N., Üstün, B., & Stucki, G. (2005). ICF linking rules: An update based on lessons learned. Journal of Rehabilitation Medicine, 37, 212–218.CrossRefGoogle ScholarPubMed
Coenen, M., Cieza, A., Freeman, J., Khan, F., Miller, D., Weise, A., & Kesselring, J. (2011). The development of ICF Core Sets for multiple sclerosis: Results of the International Consensus Conference. Journal of Neurolology, 258, 1477–1488.CrossRefGoogle ScholarPubMed
Evans, J. J., & Krasny-Pacini, A. (2017). Goal setting in rehabilitation. In Wilson, B. A., Winegardener, J., van Heugten, C. M., & Ownsworth, T. (Eds.). Neuropsychological rehabilitation. The international handbook (pp. 49–58). Abingdon, Oxon: Routledge.Google Scholar
Finger, M. E., Escorpizo, R., Glässel, A., Gmünder, H. P., Lückenkemper, M., Chan, C., … Cieza, A. (2012). ICF core set for vocational rehabilitation: Results of an international consensus conference. Disability and Rehabilitation, 34(5), 429–438.CrossRefGoogle ScholarPubMed
Geyh, S., Cieza, A., Schouten, J., Dickson, H., Frommelt, P., Omar, Z., … Stucki, G. (2004). ICF core sets for stroke. Journal of Rehabilitation Medicine, Suppl. 44, 135–141.CrossRefGoogle ScholarPubMed
Grill, E., Strobi, R., Müller, M., Quittan, M., Kostanjsek, N., & Stucki, G. (2011). ICF core sets for early post-acute rehabilitation facilities. Journal of Rehabilitation Medicine, 43(2), 131–138.CrossRefGoogle ScholarPubMed
Honan, C. A., McDonald, S., Tate, R., Ownsworth, T., Togher, L., Fleming, J., … Ponsford, J. (2019). Outcome instruments in moderate-to-severe adult traumatic brain injury: Recommendation for use in psychosocial research. Neuropsychological Rehabilitation, 29(6), 896–916.CrossRefGoogle Scholar
Hunsley, J., & Mash, E.J. (2007). Evidence-based assessment. Annual Review of Clinical Psychology, 3, 29–51.CrossRefGoogle ScholarPubMed
Laxe, S., Zasler, N., Selb, M., Tate, R., Tormos, J. M., & Bernabeu, M. (2013). Development of the International Classification of Functioning, Disability and Health core sets for traumatic brain injury: An international consensus process. Brain Injury, 27(4), 379–387.CrossRefGoogle Scholar
Manolov, R., Moeyaert, M., & Evans, J. J. (2015). Resources and guidelines for analysing SCED data. Retrieved 25 August, 2019 from www.ub.edu/gcai/soft/Software_resources_for_applied_researchers_April2015.pdf.Google Scholar
McDonald, S., Anderson, V., Ponsford, J., Tate, R., Togher, L., Morgan, A., … Murdoch, B. (2012). Moving ahead: A new centre of research excellence in brain recovery, focusing on psychosocial reintegration following traumatic brain injury. Brain Impairment, 13(2), 256–270.CrossRefGoogle Scholar
Mokkink, L. B., Terwee, C. B., Patrick, D. L., Alonso, J., Stratford, P. W., Knol, D. L., … de Vet, H. C. (2010). The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: An international Delphi study. Quality of Life Research, 19(4), 539–549.CrossRefGoogle Scholar
Mokkink, L. B., de Vet, H. C. W., Prinsen, C. A. C., Patrick, D. L., Alonso, J., Bouter, L. M., & Terwee, C. B. (2018). COSMIN Risk of Bias checklist for systematic reviews of patient-reported outcome measures. Quality of Life Research, 27(5), 1171–1179.CrossRefGoogle ScholarPubMed
Pfaff, A., & Tate, R. L. (2004, December). Manual for the Modified Oxford Post-Traumatic Amnesia Scale (MOPTAS). Unpublished manuscript, Brain Injury Rehabilitation Unit, Liverpool Hospital, Sydney, Australia.Google Scholar
Rosenkoetter, U., & Tate, R. L. (2018). Assessing features of psychometric assessment instruments: A comparison of the COSMIN checklist with other critical appraisal tools. Brain Impairment, 19(1), 103–118.CrossRefGoogle Scholar
Schellingerhout, J. M., Verhagen, A. P., Heymans, M. W., Koes, B. W., de Vet, H. C., & Terwee, C. B. (2012). Measurement properties of disease-specific questionnaires in patients with neck pain: A systematic review. Quality of Life Research, 21(4), 659–670.CrossRefGoogle ScholarPubMed
Scherer, M. J., Federici, S., Tiberio, L., Pigliautile, M., Corradi, F., & Meloni, F. (2012). ICF core set for matching older adults with dementia and technology. Ageing International, 37(4), 414–440.CrossRefGoogle Scholar
Spoorenberg, S. L. W., Reijneveld, S. A., Middel, B., Uittenbroek, R. J., Kremer, H. P. H., Wynia, K. (2015). The Geriatric ICF core set reflecting health-related problems in community-living older adults aged 75 years and older without dementia: Development and validation. Disability and Rehabilitation, 37(8), 2337–2343.CrossRefGoogle ScholarPubMed
Tate, R. L. (2004). Assessing support needs for people with traumatic brain injury: The Care and Needs Scale (CANS). Brain Injury, 18(5), 445–460.CrossRefGoogle Scholar
Tate, R. L. (2010). A compendium of tests, scales and questionnaires: The practitioner’s guide to measuring outcomes after acquired brain impairment. Hove, UK: Psychology Press.Google Scholar
Tate, R. L. (2014). Measuring outcomes using the International Classification of Functioning, Disability and Health (ICF) model, with special reference to participation and environmental factors. In Levin, H., Shum, D., & Chan, R. (Eds.), Understanding traumatic brain injury: Current research and future directions (pp. 163–189). Oxford: Oxford University Press.Google Scholar
Tate, R. L., Godbee, K., & Sigmundsdottir, L. (2013) A systematic review of assessment tools for adults used in traumatic brain injury research. NeuroRehabilitation, 32, 729–750.CrossRefGoogle ScholarPubMed
Tate, R. L., & Perdices, M. (2008). Applying the International Classification of Functioning Disability and Health (ICF) to clinical practice and research in acquired brain impairment. Brain Impairment, 9(3), 282–292.CrossRefGoogle Scholar
Tate, R. L., & Perdices, M. (2019). Single-case experimental designs for clinical research and neurorehabilitation settings: Planning, conduct, analysis and reporting. Abingdon, UK: Routledge.CrossRefGoogle Scholar
Tate, R. L., Perdices, M., Pfaff, A., & Jurjevic, L. (2001). Predicting duration of posttraumatic amnesia (PTA) from early PTA measurements. Journal of Head Trauma Rehabilitation, 16, 525–542.CrossRefGoogle ScholarPubMed
Tate, R. L., Perdices, M., & Wakim, D. (in press). Integrating routine clinical interventions with single-case methodology: Parallels, differences and bridging strategies. Brain Impairment.Google Scholar
Tate, R. L., Simpson, G. K., Lane-Brown, A. T., Soo, C. A., de Wolf, A., & Whiting, D. (2012). Sydney Psychosocial Reintegration Scale (SPRS-2): Meeting the challenge of measuring participation in neurological conditions. Australian Psychologist, 47, 20–32.CrossRefGoogle Scholar
Tate, R. L., Wakim, D., Sigmundsdottir, L., & Longley, W. (2018). Evaluating an intervention to increase meaningful activity after severe traumatic brain injury: A single-case experimental design with direct inter-subject and systematic replication. Neuropsychological Rehabilitation. doi: 10.1080/09602011.2018.1488746.CrossRefGoogle Scholar
Terwee, C. B., Mokkink, L. B., Knol, D. L., Ostelo, R. W. J. G., Bouter, L. M., & de Vet, H. C. W. (2012). Rating the methodological quality in systematic reviews of studies on measurement properties: a scoring system for the COSMIN checklist. Quality of Life Research, 21(4), 651–657.CrossRefGoogle ScholarPubMed
Wearne, T., Anderson, V., Catroppa, C., Morgan, A., Ponsford, J., Tate, R., … McDonald, S. (2018). Psychosocial functioning following moderate-to-severe pediatric traumatic brain injury: Recommended outcome instruments for research and remediation studies. Neuropsychological Rehabililitation. 1–15. doi: 10.1080/09602011.2018.1531768.Google ScholarPubMed
World Health Organization (WHO). (2001). ICF. The International Classification of Functioning Disability and Health. Geneva: WHO.Google Scholar