Author(s): Prateek Grover, MD, PhD, MHA
Originally published: August 4, 2017 Last updated: September 1, 2022
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Overview and Description

An Outcome Measure is a qualitative or quantitative measurement of outcome,1 for rehabilitation interventions,2 and are referred to as Rehabilitation Measure of Outcome (RMO) in this article.

RMOs are vital to the practice of evidence-based rehabilitation medicine. Given the plethora of RMOs used, the World Health Organization International Classification of Functioning, Disability and Health, (WHO ICF)3 serves as a useful framework to understand RMO applications  The ICF describes how the health condition interaction with contextual personal and environmental factors to describe functioning as a combination of structure and function (impairments), activity (limitations), and participation (restriction).3 Hence, to comprehensively characterize the outcome of rehabilitation interventions for any health condition, RMOs must be defined for each of these domains and contextual factors.1,2 

Of note, RMOs are distinct from AHRQ Structural measure, that define system capacity, and Process Measures, that reflect what a provider does to improve care.4

RMOs are used for multiple reasons. They help track changes in functioning at an individual as well as population level. They establish a common language that can be understood by all rehab professionals, patients and families, as well as insurance companies that influence health provision. They help provide feedback for improving clinical rehabilitation interventions, as well as answering research specific questions. While Clinician-assessed measures focus on changes in impairments and activities, Patient-reported outcome measures (PROM) help focus on how well the aforementioned domain improvements translate into participation.1

Core attributes of an RMO include validity (answer the question asked), reliability (measurement independent of measurer), sensitivity (ability to detect change), and generalizability (avoidance of floor or ceiling effects). The most accepted RMOs are also easy to implement (feasibility) and communicate.2 The smallest change detected by an RMO that is not the result of measurement error is defined as the Minimal Detectable Change (MDC). How small a change detected by the RMO is clinically important is defined as the Minimal Clinically Important Difference (MCID).5

The choice of an RMOs should be based upon not only upon the established aforementioned characteristics, but also the population of interest, the level of care (inpatient vs outpatient, SNF vs acute), and the domain and/or context of functioning. While choosing an outcome measure, it is also important to take into consideration the limitations to implementation, related to resources such as time, equipment, funding, and training.1,2 Accordingly, many research outcome measures are often difficult to implement in clinical practice, and many clinical measures are insufficient to answer research questions.

Relevance to Clinical Practice

Outcome Measures Across Levels of Care

The most studied and validated rehabilitation outcome measure used in Inpatient Rehabilitation Facilities is the Functional Independence Measure, abbreviated FIM®. The FIM® was developed in 1987 by UDSMR to address the limitations of the Barthel Index. and was endorsed by the American Academy of Physical Medicine and Rehabilitation and the American Congress of Rehabilitation Medicine. This outcome measure helped incorporate functional severity into the Prospective Payment System (PPS) per the Centers for Medicare and Medicaid Studies diagnosis-related group (CMS DRG) criteria. It is a global measure of the Burden of Care (BoC), assessing 13 motor and 5 cognitive tasks, on a 1 (Dependent) to 7 (Independent) ordinal scale, with scores ranging from 18 (lowest) to 126 (highest).6

This FIM® is a great example of a RMO’s application for assessing performance outcomes to calculate reimbursement. The UDSMR program evaluation model (PEM) was designed to address the pay-for-performance Medicare reimbursement model in 2006. Of the 5 measures for IRF facilities compared nationwide, three are FIM® based, namely Discharge FIM®, FIM gain = FIM® (discharge-admission), and FIM efficiency = FIM® gain/length of stay, Community discharge rate, and Acute Care transfer rate being the other two.

FIM® can also be used to estimate participation and associated caregiver impact. General BoC guidelines indicate that FIM® ratings of 60 and 80 equate to 4 and 2 hours of BoC daily assistance, respectively, while 100+ scores indicate no BoC. The FIM® scale is non-linear, with equal weighting for intervals 2-3, 3-4, 4-5 and 5-6, while intervals 1-2 and 6-7 are weighted 3 times as much as the prior intervals. The modified independent and independent levels help avoid the ceiling effect.6

The post-acute rehabilitation outcomes assessment can be measured by the AlphaFIM®, with 4 motor and 2 cognitive tasks, on the 1-7 FIM® scale. Other variants include the SigmaFIMTM for most pre-acute institutional and post-acute community settings, the AcuteFIMTM for acute discharge planning, and the WeeFIM® and the WeeFIMII® for children aged 0-7, and infants, to adolescents, respectively.6

While FIM continues to be used in several parts of the world, it was replaced in the US by Section GG in 2017. This measure has been demonstrated to have similar pattern as FIMs using conceptually similar transfer and self-care items for comparison.7

Outcome Measures Across the Functioning Continuum

The purpose of this section is not to list all measures, but to provide the reader with recognition of RMOs used clinically and develop an understanding of how to best incorporate these into clinical practice. Hence, common research and clinical outcome measures have been presented within the WHO ICF framework, under the body structure/function, activity, and participation domains. Bedside tests used for tracking the course of the specific functioning parameters have also been included in the description. Please also note that many measures often assess and hence overlap multiple domains, especially between body structure/function and activity categories.

Body Structure/Function RMOs

Examples for Neuro-musculo-skeletal and Cardio-Pulmonary Systems are presented below.

  • Strength: While Hand-Held Dynamometry can be used for biomechanical quantification, much more ubiquitous metrics include the qualitative bedside Manual Muscle Test, as well as population specific measures such as the International Standards for Neurological Classification of Spinal Cord Injury (SCI) – ASIA Impairment Scale).5
  • Spasticity/Spasms: Bedside measures of spasticity and spasms include the (Modified) Ashworth Spasticity Scale and the Penn Spasm Frequency Scale, respectively.5
  • Pain: Multiple subjective measures are available, the simplest being the Numeric Pain Rating Scale. Measure linking pain to its impact on emotion or/and functioning include the Pain Catastrophizing Scale, and the Brief Pain Inventory, respectively. Chronic pain can be addressed by the West-Haven-Yale Multidimensional Pain Inventory. Pathology specific examples include the STarT Back Screening Tool, and the Shoulder Pain and Disability Index (SPADI).5
  • Aphasia: Common outcome measures include the Western Aphasia Battery, Boston Naming test, Reading Comprehension Battery for Aphasia- 2nd Edition, and the Aphasia Communication Outcome Measure (ACOM).5
  • Aerobic Capacity / Endurance: The 6 Minute Walk Test is an excellent objective measure of sub-maximal aerobic capacity, which the RPE (Rating of Perceived Exertion) is a standard subject-reported measure of “how hard” an activity is. The Borbg RPE is a 6 (no exertion) to 20 (Maximal exertion) scale,8 which is commonly used to guide and progress intensity and duration in cardiovascular rehabilitation. Biomechanical measures include the Maximal Oxygen Uptake: VO2max and VO2peak.5

Activity RMOs

  • Activities of daily living (ADLs), upper extremity (UE) functioning and dexterity
    • ADL RMOs have been defined for specific pathologies, such as the Parkinson’s Disease Activities of Daily Living Scale.5
    • Commonly used UE functioning measures for stroke 9 include the Fugl-Meyer Assessment, Action Research Arm Test, Box and Block Test, Chedoke Arm and Hand Activity Inventory, Wolf Motor Function Test and ABILHAND. Computerized adapted testing (CAT) is recommended for patient reported outcome measures.7
    • The Quick Disabilities of Arm, Shoulder & Hand, QuickDASH is a patient-reported measure of UE function, mostly used for musculoskeletal impairments.5
    • Gross upper limb dexterity is measured by the Box and Block Test, and the Purdue Pegboard Test measure. The latter also measures fine finger dexterity, along with the Nine-Hole Peg Test. The Action Research Arm Test sequentially evaluate dexterity from the most to least difficult (subscales: Grasp, Grip Pinch, and Gross Movement).
    • Jebsen Hand Function Test assesses hand function ability for ADLs.5
  • Lower extremity (LE) functioning, Balance and Fall risk
    • A commonly accepted PROM for LE functioning identified based upon psychometric criteria is the Rivermead Mobility Index (RMI), which does show a ceiling effect.
    • Additional measures evaluating active function included the Brain Injury Community Rehabilitation Outcome, Climbing Stairs Questionnaire, Human Activity Profile, Lower Extremity Functional Scale, Nottingham Extended ADL Index, Sickness Impact Profile, Stroke Impact Scale.10
    • A simple bedside test of static balance is the Romberg test, originally developed to screen for sensory impairment. The Balance – Berg Balance Scale (14 items) is a more in-depth measure.
    • Commonly used objective measures of dynamic balance and fall risk include the Dynamic Gait Index, Functional Gait Assessment, Four Step Square Test (step over objects forward, sideways, and backwards), and the Timed Up and Go test.
    • A patient reported measure of activity related fear of falls from imbalance is the Tinetti Falls Efficacy Scale. The Floor Transfer Test, requiring adults to sit down on the floor and then stand up can be used as an objective (time) measure of fall risk as well. Metrics for vestibular contributors to impaired balance include the Instrumented and non-instrumented Dynamic Visual Acuity Tests and the Gaze Stabilization Test.5
  • Cognition, Attention and Working Memory
    • Standard bedside measures include the Mini-Mental State Examination and the Saint Louis University Mental Status Exam, designed for dementia screening.
    • The Cognistat Cognitive Assessment is a more in-depth measure, evaluating multiple domains in addition to alertness, orientation, attention and memory, such as language, construction and calculation and executive skills.
    • Divided attention during motor tasks, especially in the elderly, can be assessed by the Walking While Talking Test.5
    • Objective and subjective measures of executive function include the Executive Function Performance Test (simple cooking, telephone use, medication management, and bill payment), tested in the Stroke and Multiple Sclerosis (MS) populations, and the Behavior Rating Inventory of Executive Function – Parent Questionnaire, designed for evaluating children, respectively.5
    • Inattention or neglect can be tracked by the Behavioral Inattention Test and evaluated more in-depth by the Motor-free Visual Perception Test, validated primarily for learning disabilities, but used commonly in stroke population.5
    • Efforts to design patient-reported outcome measures for cognitive impairments while limited, are underway. As an example, chronic stroke patients undergoing cognitive rehab indicated that cognitive gaps, decreased attention, emotion, and fatigue were major ongoing concerns, and that such cognitive deficits were harder to accept compared with physical deficits. Such insight can be used to design and validate appropriate RMOs11

Participation RMOs

  • Quality of Life Measures, QOL: These PROMs can be generic such as the Goal Attainment Scale, that minimizes the gap between patient goals set and met, the Medical Outcomes Short-Form Health Survey, SF-36, designed originally for head and neck cancers, and the Short Form 12 item (version 2) Health Survey, designed originally for Parkinson’s Disease; impairment related such as the Incontinence Quality of Life Scale, tested in MS and overactive bladder, and the Sexual Interest and Satisfaction Scale, designed for SCI and modified for traumatic brain injury (TBI); or pathology-specific such as the SCI-QoL Self-care.5
  • Social Integration and Limitations: Common examples of pathology specific measures include the Community Integration Questionnaire designed for TBI, Stroke Impact Scale, and the Disability Rating Scale/ Disability Scale (Vestibular Disorders). The Measurement of Quality of the Environment assesses the role of environmental factors. In the inpatient setting, the Activity Card Sort can be administered by therapy to patients to better understand their social-recreational approach to set therapy goals. Outpatient and home participation can be followed by the ICF-based Participation measure for post-acute care, as discussed in the section on settings of care.5

Defining Outcome Measure Core Dataset for Your Practice

A combination of RMOs discussed in the preceding sections can be used by institutions for designing and utilizing standard data element sets for comprehensive functional evaluation of common neurorehabilitation diagnoses such as stroke, SCI, TBI, MS, and PD. As an example, a common battery for comprehensive stroke outcome assessment could include Barthel Index and Section GG self-care section to measure activities of daily living, Fugl-Meyer for assessment of motor function, Berg Balance Assessment for balance, and Western Aphasia Battery for speech and language function assessment.12 For limb loss, the data element set could include generic measures such as the 6MWT and the TUG, as well as amputee specific measures such as the Amputee mobility predictor (AMP) for patients with or without the use of a prosthesis (AMPPRO and AMPnoPRO respectively), comprised of 21 tasks over 4 categories of sitting balance, simple mobility, standing balance and gait and functional activities. The Comprehensive high-activity mobility predictor (CHAMP) can be included for high level performers. PROMs should be included to understand patient-perceived improvement with device use. These have been developed and studies published over the past 3 decades, such as the Prosthesis evaluation questionnaire (PEQ) in the 1990s, Locomotor capabilities index in the 2000s, and the Prosthetic limb users survey (PLUS) in the 2010s.13

For tracking outcomes related to arthritis, thedata element setshould include elements specific to the anatomic location. Functioning limitations related with low back with/(out) leg pain, and with neck pain can be tracked by the Oswestry Disability Index, and the Neck Disability Index, respectively. Peripheral joint dysfunction has been assessed by measures such as the Shoulder Pain and Disability Index (SPADI), and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). The latter was designed for the hip and knee diagnoses, including replacements, but has been used for back pain and other rheumatologic diagnoses as well.5

Table I. Examples of Rehabilitation Measure of Outcome (RMO)

Outcome-Measurement-in-Rehabilitation-Table-IDownload

Cutting Edge/ Unique Concepts/ Emerging Issues

Clinically administered (objective) measures are subject to interrater variability. To minimize this source of error, and improve the preciseness of measurement, biomechanical measures are gaining prominence. These measures could be developed using kinematic (movement) and kinetic (force) techniques. An example is the Symmetry in external work (SEW) measure,14 that uses activity data from sensors embedded in soles and has applications for ADLs and mobility activities.

It is interesting to note the trend toward developing the WHO ICF itself as an outcome measure.15 Also of interest is the relatively new approach of identifying measures most applicable for robot guided therapy for the upper extremity16 and the lower extremity.17

PROMs in the Post-IRF setting are often difficult to obtain, even with Computerized Adaptive Testing (CAT).  A study involving a CAT version of the Community Participation Indicators (CAT-CPI) found only 21% agreement to complete the survey at 4 weeks (more likely younger with higher perceived satisfaction with care), with 1/3rd completion rate (more likely longer LOS and greater FIM® cognition at discharge). While most clinicians will find it easier to use validated outcome measures, if novel design for a specific population is the aim, both demographic and functional parameters should be included,18 and a psychometrician should be part of the study team.

Another issue to consider is the need to better unify functional assessment across the rehabilitation levels of care, since acute RMOs (e.g. FIM®) and post-acute RMOs (e.g. Minimum Data Set, MDS) may not translate well across the gap.19 While efforts have been ongoing for over a decade, such as a project to integrate the FIM® (acute) with the MDS-PAC (post-acute care) described by the RAND Corporation in 2005,20 similar initiatives are now gaining significant traction, driven by the standardized data reporting requirements of the IMPACT (Improving Medicare Post-Acute Care Transformation) Act of 2014.21 Section GG is the latest national-level  outcome measure reflective of this need.

Gaps in Knowledge/ Evidence Base

Pediatric Outcome measures are a distinct group, with focus on growth related domains. While comprehensive description is out of scope for this chapter, a brief overview is presented in this paragraph. Excellent examples of objective and subjective measure include the Gross Motor Function Measure, developed for Cerebral Palsy and Down’s Syndrome,22 and the parent reported Pediatric Quality of Life Inventory (PEDS- QL),23 respectively. There are also RMOs specifically designed to study rare disorders. While this seems daunting, adopting the functioning approach to clearly define the research question (such as mobility evaluation in Rett’s Syndrome) and utilizing technology (such as an activity monitor) to derive valid, reliable, and clinically meaningful insight is vital for improving clinical practice.24

Clinician determined outcome measures of body structure/function and activity don’t always correlate well with PROMs. In order to provide comprehensive care that incorporates both provider and patient perspectives, the optimal approach is to (a) utilize RMOs from both categories, and (b) understand correlations between the two categories. An illustration of this concept is a stroke related hemicraniectomy study that found longitudinal improvements in all clinician reported measures and PROMs, and a correlation between clinician-reported Modified Rankin Scale (mRS) and PROM EuroQol quality of life index (EQ-5D).25

References 

  1. Braddom’s Physical Medicine and Rehabilitation, 5th Edition, Editor Cifu D.X, © Elsevier 2016.
  2. Wade DT, Outcome measures for clinical rehabilitation trials: Impairment, function, quality of life, or value? Am J Phys Med Rehabil 2003;82(Suppl): S26–S31.
  3. Towards a Common Language for Functioning, Disability and Health – The International Classification of Functioning, Disability and Health, World Health Organization, Geneva, 2002.
  4. Types of Health Care Quality Measures | Agency for Healthcare Research and Quality (ahrq.gov), retrieved from https://www.ahrq.gov/talkingquality/measures/types.html#:~:text=Process%20Measures.%20Process%20measures%20indicate%20what%20a%20provider,example%3A%20The%20percentage%20of%20people%20receiving%20preventive%20services
  5. Rehabilitation Measurement Datatbase, © 2010 Rehabilitation Institute of Chicago, developed by Rehabilitation Institute of Chicago, Center for Rehabilitation Outcomes Research, Northwestern University Feinberg School of Medicine Department of Medical Social Sciences Informatics group, retrieved from org
  6. Uniform Data System for Medical rehabilitation 2012, The FIM® Instrument: Its Background, Structure, and Usefulness, retrieved from http://www.udsmr.org/Documents/The_FIM_Instrument_Background_Structure_and_Usefulness.pdf
  7. Li C-Y, Mallinson T, Kim H, Graham J, Kuo Y-F, Ottenbacher KJ, Characterizing Standardized Functional Data at Inpatient Rehabilitation Facilities, Journal of the American Medical Directors Association, 2022, ISSN 1525-8610, https://doi.org/10.1016/j.jamda.2022.02.003.
  8. Borg G, Borg’s Perceived Exertion and Pain Scales, 1st Ed, Publisher: Human Kinetics, 1998.
  9. Alt Murphy M, Resteghini C, Feys P, Lamers I. An overview of systematic reviews on upper extremity outcome measures after stroke. BMC Neurol. 2015 Mar 11;15:29.
  10. Ashford S, Brown S, Turner-Stokes L. Systematic review of patient-reported outcome measures for functional performance in the lower limb. J Rehabil Med. 2015 Jan;47(1):9-17.
  11. Patchick EL, Horne M, Woodward-Nutt K, Vail A, Bowen A, Development of a patient-centred, patient-reported outcome measure (PROM) for post-stroke cognitive rehabilitation: qualitative interviews with stroke survivors to inform design and content. Health Expect. 2015 Dec;18(6):3213-24.
  12. Sullivan JE, Crowner BE, Kluding PM, Nichols D, Rose DK, Yoshida R, Pinto Z.G. Outcome measures for individuals with stroke: process and recommendations from the American Physical Therapy Association neurology section task force. Phys Ther. 2013 Oct;93(10):1383-96.
  13. Agrawal V. Clinical Outcome Measures for Rehabilitation of Amputees – A Review. Phys Med Rehabil Int. 2016; 3(2): 1080.
  14. Agrawal V, Gailey R, O’Toole C, Gaunaurd I, Dowell T. Symmetry in external work (SEW): a novel method of quantifying gait differences between prosthetic feet. Prosthet Orthot Int. 2009; 33: 148-156.
  15. Kohler F, Connolly C, Sakaria A, Stendara K, Buhagiar M, Mojaddidi M. Can the ICF be used as a rehabilitation outcome measure? A study looking at the inter- and intra-rater reliability of ICF categories derived from an ADL assessment tool. J Rehabil Med. 2013 Sep;45(9):881-7.
  16. Sivan M, O’Connor RJ, Makower S, Levesley M, Bhakta B. Systematic review of outcome measures used in the evaluation of robot-assisted upper limb exercise in stroke. J Rehabil Med. 2011 Feb;43(3):181-9.
  17. Geroin C, Mazzoleni S, Smania N, Gandolfi M, Bonaiuti D, Gasperini G, Sale P, Munari D, Waldner A, Spidalieri R, Bovolenta F, Picelli A, Posteraro F, Molteni F, Franceschini M, Italian Robotic Neurorehabilitation Research Group. Systematic review of outcome measures of walking training using electromechanical and robotic devices in patients with stroke. J Rehabil Med. 2013 Nov;45(10):987-96.
  18. Wong AW, Heinemann AW, Miskovic A, Semik P, Snyder TM, Feasibility of computerized adaptive testing for collection of patient-reported outcomes after inpatient rehabilitation. Arch Phys Med Rehabil. 2014 May;95(5):882-91.
  19. Glenny C, Stolee P, Comparing the Functional Independence Measure and the interRAI/MDS for use in the functional assessment of older adults: a review of the literature, BMC Geriatr. 2009; 9: 52.
  20. Buchanan JL, Andres P, Haley SM, Paddock SM, Young DC, Zaslavsky A, Final Report on Assessment Instruments for a Prospective Payment System, Prepared for the Centers for Medicare and Medicaid Services, Rand Health 2005, retrieved from https://www.rand.org/content/dam/rand/pubs/monograph_reports/2005/MR1501.pdf
  21. SNF Quality Reporting Program (Impact Act 2014), CMS.gov, retrieved from https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-IMPACT-Act-2014.html
  22. Gross Motor Function Measure, retrieved from www.canchild.ca/en/measures/gmfm.asp
  23. Pediatric Quality of Life Inventory (PEDS- QL), retrieved from http://www.pedsql.org/
  24. Downs J, Leonard H, Jacoby P, Brisco L, Baikie G, Hill K. Rett syndrome: establishing a novel outcome measure for walking activity in an era of clinical trials for rare disorders. Disabil Rehabil. 2015;37(21):1992-6.
  25. Kelly ML, Rosenbaum BP, Kshettry VR, Weil RJ. Comparing clinician- and patient-reported outcome measures after hemicraniectomy for ischemic stroke. Clin Neurol Neurosurg. 2014 Nov;126:24-9.

Original Version of the Topic

Armando Miciano, MD, David Berbrayer, MD, Ram Abhishek Sharma, MD. Measurement of Outcomes. 5/5/2016

Previous Revision(s) of the Topic

Prateek Grover, MD, Denise Holt, M.S., CCC-SLP. Outcome Measurement in Rehabilitation. 8/4/2017

Author Disclosures

Prateek Grover, MD, PhD, MHA
Nothing to Disclose