Outcome Measurement in Rehabilitation

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 topic.

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 the health condition interaction with contextual personal and environmental factors to define 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 a r condition, RMOs should be chosen as a combination to reflect these constructs.^1,2 Of note, RMOs are distinct from AHRQ Structural measures, that define system capacity, Process Measures, that reflect provider actions to improve care,⁴ and implementation outcome measures, that define implementation success.⁵

RMOs are used for multiple reasons, that include

• Tracking changes in functioning at an individual as well as population level,
• Serving as a common language that can be understood by all rehab professionals, patients and families, as well as insurance companies that influence health provision,
• Providing feedback for improving clinical rehabilitation interventions, and
• Answering research specific questions. Furthermore, 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 several psychometric properties, including

• 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 commonly used 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).⁶

Relevance to Clinical Practice

Outcome measures across levels of care – Historical context and current status

One of the most studied and validated rehabilitation outcome measure used in Inpatient Rehabilitation Facilities was 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) using 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).⁷

This FIM^® is a great example of RMO’s application for assessing performance outcomes to calculate reimbursement. The UDSMRprogram 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 were 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^® was also used to estimate participation and associated caregiver impact. General Burden of Care (BoC) guidelines indicated that FIM^® ratings of 60 and 80 equated to 4 and 2 hours of BoC daily assistance, respectively, while 100+ scores indicated 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.⁷

The post-acute rehabilitation outcomes assessment was measured by the AlphaFIM^®, with 4 motor and 2 cognitive tasks, on the 1-7 FIM^® scale. Other variants included the SigmaFIM^TM for most pre-acute institutional and post-acute community settings, the AcuteFIM^TM for acute discharge planning, and the WeeFIM^® and the WeeFIMII^® for children aged 0-7, and infants^,to adolescents, respectively.⁷

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.⁸

Choosing RMOs for your clinical practice

There are hundreds of outcome measures. While they can be classified based upon criteria (Rehabilitation Measures Database | Shirley Ryan AbilityLab) such as assessment type, anatomic structure, and diagnosis to make the choice more streamlined, determining a feasible set of metrics for clinical use is herculean task. Many research outcome measures are often difficult to implement in clinical practice, and many clinical measures are insufficient to answer research questions.

The choice of a feasible set of RMOs should hence be based upon a combination of psychometric characteristics, clinical population of interest, the level of care (inpatient vs outpatient, SNF vs acute), as well as implementation feasibility, related to resources such as time, equipment, funding, and training.^1,2 For aiding the clinician in decision making, this section is not intended to be exhaustive, but rather provide the reader with recognition of RMOs used clinically and develop an understanding of how to best incorporate these into clinical practice.

The universally accepted WHO ICF framework has been used to describe common research and clinical outcome measures (including bedside tests) , under the three functioning domains of body structure/function (impairments), activity (limitations), and participation(restriction), with a focus on feasibility Please also note that many measures often assess and overlap across domains, especially between body structure/function and activity categories.

Body Structure/Function RMOs – to assess impairments

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

Strength

• Hand-Held Dynamometry provides biomechanical quantification with specialized equipment needed.
• Manual Muscle Test is more qualitative but also more feasible, as specialized equipment is not needed.
• Population specific measures also exist, with an example being is the International Standards for Neurological Classification of Spinal Cord Injury (SCI) – ASIA Impairment Scale).⁶

Spasticity/Spasms

• (Modified) Ashworth Spasticity Scale is a bedside qualitative measure of spasticity.
• Penn Spasm Frequency Scale is a bedside qualitative measure of spasms.⁶

Pain – Multiple patient-reported outcome measures (PROM) exist.

• Numeric Pain Rating Scale is a simple Likert scale that is easy to administer, but subject to several biases.
• Pain Catastrophizing Scale and the Brief Pain Inventory are measures linking pain to its impact on emotion or/and functioning.
• West-Haven-Yale Multidimensional Pain Inventory measures chronic pain.
• STarT Back Screening Tool, and the Shoulder Pain and Disability Index (SPADI) are examples of pathology specific tools.⁶

Aphasia – Common outcome measures include

• Western Aphasia Battery
• Boston Naming test
• Reading Comprehension Battery for Aphasia- 2nd Edition, and
• Aphasia Communication Outcome Measure (ACOM).⁶

Aerobic Capacity/Endurance

• The 6 Minute Walk Test is an excellent quantitative measure of sub-maximal aerobic capacity
• RPE (Rating of Perceived Exertion) is a standard PROM of “how hard” an activity is. The Borg RPE is a 6 (no exertion) to 20 (Maximal exertion) scale,⁹ commonly used to guide progression of intensity and duration of cardiovascular rehabilitation.
• Biomechanical measures include the Maximal Oxygen Uptake: VO2max and VO2peak.⁶

Activity RMOs – to assess limitations

Activities of daily living (ADLs), upper extremity (UE) functioning and dexterity

• Parkinson’s Disease Activities of Daily Living Scale is a pathology specific ADL RMOs,⁶
• Commonly used UE functioning measures for stroke¹⁰ 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.⁸
• The Quick Disabilities of Arm, Shoulder & Hand, QuickDASH is a patient-reported measure of UE function, mostly used for musculoskeletal impairments.⁶
• Box and Block Test measures Gross upper limb dexterity
• Purdue Pegboard Test measures Gross upper limb dexterity and fine finger dexterity
• Nine-Hole Peg Test measures fine finger dexterity
• The Action Research Arm Test sequentially evaluates dexterity from the most to least difficult (subscales: Grasp, Grip Pinch, and Gross Movement).
• Jebsen Hand Function Test assesses hand function ability for ADLs.⁶

Lower extremity (LE) functioning, Balance and Fall risk

• Rivermead Mobility Index (RMI) is a commonly accepted PROM for LE functioning with a ceiling effect.
• Additional measures evaluating active function include
  • 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.¹¹
• Static balance
  • A simple bedside test is the Romberg test, originally developed to screen for sensory impairment.
  • The Berg Balance Scale (14 items) is a more in-depth measure.
• Dynamic balance and fall risk – Commonly used objective measures include
  • Dynamic Gait Index
  • Functional Gait Assessment
  • Four Step Square Test (step over objects forward, sideways, and backwards)
  • Timed Up and Go test.
  • Tinetti Falls Efficacy Scale – this is a patient reported measure of activity related fear of falls from imbalance.
  • The Floor Transfer Test, requiring adults to sit down on the floor and then stand up is an objective (time) measure of fall risk as well.
  • Instrumented and non-instrumented Dynamic Visual Acuity Tests and the Gaze Stabilization Test⁶ assess vestibular contribution to impaired balance.

Cognition, Attention and Working Memory

• Mini-Mental State Examination is one of the commonest standard bedside measures
• Saint Louis University Mental Status Exam is also commonly used and was 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.
• Walking While Talking Test assessed divided attention during motor tasks, especially in the elderly.⁶
• Objective and subjective measures of executive function include
  • Executive Function Performance Test (simple cooking, telephone use, medication management, and bill payment), tested in the Stroke and Multiple Sclerosis (MS) populations
  • Behavior Rating Inventory of Executive Function – Parent Questionnaire, is designed for evaluating children.⁶
• Inattention or neglect
  •  Behavioral Inattention Test can be used as a screen
  • Motor-free Visual Perception Test, validated primarily for learning disabilities, but used commonly in stroke population⁶ can be used for in-depth evaluation.

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 RMOs¹²

Participation RMOs – to assess restrictions

Quality of Life Measures, QOL

• Generic (examples)
  • Goal Attainment Scale, that minimizes the gap between patient goals set and met,
  • Medical Outcomes Short-Form Health Survey, SF-36, designed originally for head and neck cancers
  • Short Form 12 item (version 2) Health Survey, designed originally for Parkinson’s Disease
• Impairment related (examples)
  • Incontinence Quality of Life Scale, tested in MS and overactive bladder, and
  • Sexual Interest and Satisfaction Scale, designed for SCI and modified for traumatic brain injury (TBI)
• Pathology-specific (examples)
  • SCI-QoL Self-care.⁶

Social Integration and Limitations

• Common examples of pathology specific measures include
  • Community Integration Questionnaire designed for TBI
  • Stroke Impact Scale
  • Disability Rating Scale/ Disability Scale (Vestibular Disorders).
• The Measurement of Quality of the Environment assesses the role of environmental factors.
• Activity Card Sort can be administered by therapy in the inpatient setting to patients to better understand their social-recreational approach to set therapy goals.
• ICF-based Participation measure for post-acute care can be used to follow outpatient and home participation.⁶
• QoL PROMS for cost-effectiveness: EQ5D is a PROM incorporating five dimension, namely, mobility, self-care, usual activities, pina/discomfort, and anxiety/depression that can be covered to a utility score ranging from 0 to 1, that can then be used to calculate cost-utility for an intervention, such as for prosthetic devices in the elderly.¹⁵

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.¹³

For limb loss, the data element set can 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 also understand patient-perceived improvement with device use. Examples include the Prosthesis evaluation questionnaire (PEQ) developed in the 1990s, Locomotor capabilities index in the 2000s, and the Prosthetic limb users survey (PLUS) in the 2010s.¹⁴

For tracking outcomes related to arthritis, the data set should 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.⁶

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

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,¹⁶ 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.¹⁷ Also of interest is the relatively new approach of identifying measures most applicable for robot guided therapy for the upper extremity¹⁸ and the lower extremity.¹⁹

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 1/3^rd 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,²⁰ 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.²¹ 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 2005,²² 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 2014.²³ Section GG is the latest national-level outcome measure reflective of this need.

AI is improving rehabilitation by helping teams predict risks earlier and track recovery more accurately. Machine-learning models can analyze clinical data, function scores, and patient-reported outcomes to identify early those who might experience functional delays and complications.²⁴ In spinal cord injury rehabilitation, AI was used to predict discharge Functional Independence Measure (FIM) scores and motor outcomes.²⁵ In stroke rehabilitation, AI was used to estimate patient-reported outcomes such as mobility, self-care, and participation,²⁶ and arm–hand capacity using Action Research Arm Test (ARAT) performance.²⁷ Overall, AI supports personalized care, but workflow integration of these tools is still evolving.

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. Examples of objective and subjective measure include the Gross Motor Function Measure, developed for Cerebral Palsy and Down’s Syndrome,²⁸ and the parent reported Pediatric Quality of Life Inventory (PEDS-QL),²⁹ 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 can be used to create a feasible RMO set to improve evidence-based clinical practice.³⁰

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).³¹

References 

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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

Prateek Grover, MD, PhD, MHA. Outcome Measurement in Rehabilitation. 9/1/2022

Author Disclosures

Prateek Grover, MD, PhD, MHA
Amputee Coalition, Contracted with Penn State, Medical Director
HMP Global, Honorarium, Panelist, Presenter
So Every Body Can Move, Non-remunerative Positions of Influence, Medical & Research Advisory Board Member
American Academy of PM&R, Non-remunerative Positions of Influence, HPPA member, Chair Amputee Rehabilitation Community Group
American Congress of Rehabilitation Medicine, Non-remunerative Positions of Influence, Member, Board of Governors; Chair, Policy & Legislation Committee