|Home > RNJ > 2011 > May/June > Use of the Functional Independence Measure for Outcomes Measurement in Acute Inpatient Rehabilitation|
Use of the Functional Independence Measure for Outcomes Measurement in Acute Inpatient Rehabilitation
Assessment of functional status is a major responsibility for professionals practicing in rehabilitation facilities. Functional assessment tools have been created to meet this need. One of the most widely used tools is the Functional Independence Measure (FIM). Data from the FIM are used to examine patient outcomes for several purposes. This article explores the rationale for use of the FIM as an outcomes measure and research regarding the validity, reliability, responsiveness, and utility of this tool. Limitations of this instrument, future research needs, and implications for rehabilitation professionals also are discussed.
Advances in science and technology have improved survival resulting from once-fatal diseases and injuries, which has led to an increasing number of people living with chronic disease and disability. These people often need the services of rehabilitation professionals to help them return to the community as independently as possible. The complexity of the disability and the presence of comorbidities often necessitate an inpatient program. Inpatient rehabilitation facilities (IRFs) admit patients with a wide variety of conditions including stroke, burns, brain and spinal cord injury, multiple trauma, cardiac conditions, pulmonary disease, amputations, and fractures. The goal of IRF programs is to help patients gain as much independence as possible in activities of daily living (ADLs) or to self-direct care when necessary (Cohen & Marino, 2000).
Acute care facilities focus on improving health, and IRFs focus on improving independence. To measure this improvement, rehabilitation professionals rely on functional assessment tools to determine a patient’s abilities to perform a variety of physical and cognitive tasks (Black, 1999). Functional assessment was defined in 1970 as a “systematic and objective measure of a person’s level of function in a variety of domains” (Lawton, 1971, p. 466). A patients’ functional status drives his or her entire rehabilitation program. Assessment of a patients’ premorbid functional status (usually determined by self-report), functional needs (the level of function needed to attain for safe discharge), and status upon admission provide data to set realistic rehabilitation goals and create a treatment plan to help meet those goals. Function is measured continuously to determine a patients’ progress toward goals and the need to modify goals to reflect progress.
Goals are used to develop the plan of care, and data from functional assessment tools are used to predict patient needs and determine length of stay (LOS; Black, Soltis, & Bartlett, 1999). Functional assessment scores are used to plan budgets (Black, 1999) and staffing levels and help determine equipment and resource needs. Insurance companies use functional scores to determine patient eligibility for IRF admission. They also use admission and ongoing functional status reports to determine the LOS for which they will pay. Medicare uses diagnosis, age, functional status, and comorbidities to determine the payment an IRF will receive for each patient.
Functional assessment tools are used to determine outcomes measurement (Black, 1999). Patients and their families participate in goal setting and recognize that goal attainment means discharge. Outcomes are not only important to patients and families, but to IRFs as well (Black). IRFs use the scores generated by these tools to compare patient outcomes to the same diagnosis over time. These outcomes help determine the effectiveness of process improvement initiatives, evidence-based practice, and new technology (Black). Patients have a choice regarding where to seek their rehabilitative care; the number of patients who meet or exceed their functional goals is a valuable marketing tool for an IRF (Black).
Regulatory agencies require IRFs to demonstrate outcomes. The Commission for Accreditation of Rehabilitation Facilities (CARF) requires outcomes to be monitored and shared with stakeholders. The availability of outcomes information such as discharge destination and the number of people who achieve their predicted outcome allows prospective patients to learn about a facility’s ability to serve people with the same diagnosis and determine if the program will meet their needs and preferences (CARF, 2009). The Centers for Medicare and Medicaid Services (CMS) includes the attainment of outcomes in its IRF admission criteria; if rehabilitation admission is to be considered, there must be a reasonable expectation of measurable improvement (CMS, 2009).
Functional Assessment Tools
Many functional assessment tools are used today. The Berg Balance Scale (Berg, Wood-Dauphinee, Williams, & Gayton, 1989), which is used to measure balance, and the 6-Minute Walk Test (Guyatt et al., 1985), used to determine oxygen needs while ambulating, are examples of tools used by physical therapists. Some functional assessment tools are system specific and used by multiple disciplines; for example, the Manual Muscle Testing (Brass, Loushin, Day, & Iaizzo, 1996) and Glasgow Coma Scale (Teasdale & Jennett, 1974) are used by physicians, nurses, and therapists. The Barthel Index (Mahoney & Barthel, 1965) and the Functional Independence Measure (FIM; Uniform Data System for Medical Rehabilitation, 1996) are examples of more global ADL assessment tools. The Barthel Index is designed to measure what a patient “can do.” This index has 10 items (feeding, transfer from bed and back, grooming, toileting, bathing, dressing, bowel continence, bladder continence, walking/wheelchair, and stairs) and uses a 0–100 scoring system, with 100 representing total independence and 0 representing dependence (Mahoney & Barthel; Dittmar & Gresham, 1997). This tool has been considered by some to be too simple and not responsive enough to determine rehabilitation outcomes (van der Putten, Hobart, Freeman, & Thompson, 1999). Although rarely used in the United States, the Barthel Index commonly is used in European rehabilitation facilities (Black, 2007).
The FIM was created to develop a universal language for describing function and outcomes and to address weaknesses of the Barthel Index; today the FIM is one of the most widely used tools in the United States (Black, 2007; Ottenbacher, Hsu, Granger, & Fiedler, 1996). The FIM was developed in 1984 at the State University of New York at Buffalo. It underwent refinement after years of trials and was released to rehabilitation professionals in 1987 with instructions and definitions. In 1988 the Uniform Data System for Medical Rehabilitation (UDSMR), also based at the State University of New York at Buffalo, was created and became the national repository for FIM data for subscribing rehabilitation programs. In 1996 Version 5 of the FIM Guide was released with an 18-item (Table 1), 7-level ordinal scale, with 1 indicating dependence and 7 indicating independence. The tool is designed to measure “burden of care,” or “the type and amount of assistance required for a person with a disability to perform basic life activities” (Deutsch, Braun, & Granger, 1996, p. 268). In addition, UDSMR offered educational programs on FIM scoring and credentialing examinations for its subscribers to ensure consistency in scoring and validity and reliability of data submitted to the database. The FIM was designed to be used by any discipline including physiatrists, nurses, physical therapists, occupational therapists, and speech-language pathologists (Black).
In 2001 the FIM was acquired by CMS for the IRF Prospective Payment System (PPS) and was incorporated into the Inpatient Rehabilitation Facility Patient Assessment Instrument (IRF-PAI). Beginning in 2002, CMS required an IRF-PAI be completed for all Medicare patients who were admitted to an IRF. The IRF-PAI is electronically transmitted to CMS when a patient is discharged and the scores are used for calculation of payment (CMS, 2002). This mandate has led to the FIM being the most widely used global functional assessment tool.
To validate the use of any tool as an outcome measure, it must be proven to be valid (its ability to test the behavior of interest), reliable (consistency between raters and each time it is administered), and responsive (able to detect a clinically significant change). As the most commonly used functional assessment tool, FIM has been the subject of many research studies. There is a significant body of research on the reliability, validity, and responsiveness of the FIM, which likely is the reason the FIM was chosen by CMS to calculate payment.
The FIM can be used by a variety of disciplines, and multiple raters often contribute to each assessment; interrater reliability (the consistency between two or more raters) must be considered. The interrater reliability of the FIM has been well studied (Chau, Daler, Andre, & Patris, 1994; Deutsch et al., 1996; Hamilton, Laughlin, Fiedler, & Granger, 1994; Ottenbacher et al., 1996). In a study of 89 IRFs, researchers found that when clinicians are trained and competency tested, Kappa coefficients range between .69 (memory) and .84 (bladder management; Hamilton et al.). In another study in France the weighted Kappa coefficient for the total FIM was .91 (95% CI, .82–1.0), suggesting that multiple raters were consistent in their scoring (Chau et al.). A study by Ottenbacher and colleagues (1996) found the FIM mean interrater reliability level to be .915–.925 at the 95% confidence level. Interrater reliability across different raters with varying educational levels and professional backgrounds also was examined. The median interrater reliability value was .95, suggesting that professional discipline did not influence FIM scoring (Ottenbacher et al.).
The FIM is designed to be measured at different points in time to determine current status and functional gain, so the tool must be considered to have intrarater reliability. Stineman and colleagues (1997) examined intrarater reliability—the chance that a rater will obtain the same result when observing the same item at different times—and determined that the FIM motor items, in most cases, met or exceeded minimum psychometric properties across stroke and spinal-cord-injury impairment groups. In another study by Ottenbacher and colleagues (1994), intrarater reliability and stability of the FIM were examined and results indicated high agreement within and between raters. Pollak, Rheault, and Stoecker (1996) determined that evidence supported test-retest reliability of the FIM.
The validity of the FIM, or its ability to measure the things institutions believe it measures, has been questioned. FIM was created to measure the “burden of care,” so Dodds and colleagues (1993) examined changes in FIM scores based on clinical factors. When a person was older and had more comorbidities, FIM scores were lower. Concerns have been raised regarding the validity of the FIM in people older than 80 years of age. In a 1996 study by Pollak and colleagues, the authors noted their study “demonstrated evidence for the construct validity of the FIM as a measure of burden of care” in people older than age 80. One of the ways facilities use FIM to determine functional gains achieved during a rehabilitation program is by calculating FIM change per day (discharge score minus the admission score divided by LOS). In 1994 Linacre and colleagues studied FIM ratings from admission and discharge of more than 14,000 patients. This research demonstrated the FIM instrument functions the same at both admission and discharge and concluded that such comparisons are valid.
As an outcomes measure, the FIM must be reliable, valid, and responsive, or able to detect change in function. A 1990 study by Granger and colleagues determined the FIM had high precision, or the ability to detect meaningful change. In another study by Dodds and colleagues (1993), patients in all impairment groups demonstrated significant change in FIM scores from admission to discharge. Stineman and colleagues (1996) examined FIM items for floor and ceiling effects because these items are unlikely to contribute to predictive value. A ceiling effect is an undesirable measurement outcome that occurs when the dependent measure puts an artificially low ceiling on how high a participant may score, leading to clusters of scores near the upper limit of the data. A floor effect occurs when there are clusters of scores near the lower limit. The researchers pointed out that items with floor effects on admission that may be clinically useful are activities for which a large increase in functional ability might be expected—a logical focus for clinicians. The opposite is true for items showing ceiling effects. This study showed that in acute rehabilitation facilities there were very small floor and ceiling effects for most items and for most patients. The researchers indicated that floor and ceiling effects would likely be different for other settings such as outpatient or long-term care (Stineman et al.). The FIM instrument has been found to be responsive to change in functional abilities in stroke patients and is not prone to ceiling effects (Dromerick, Edwards, & Diringer, 2003). A study in stroke patients revealed that FIM is sensitive enough to capture minimal changes in functional abilities and has been found to be both a valid and reliable measure of ADL functioning in the stroke population (Kwon, Hartzema, Duncan, & Min-Lai, 2004).
In comparison with other functional assessment measures, the FIM was determined to be least biased when compared to other tools. When compared to the Barthel Index and Katz Index, the FIM scored highest in reliability, validity, and responsiveness, providing the best measure of disability (Cohen & Marino, 2000). The FIM has been found to be the most valid, reliable, and responsive global functional assessment tool that can be expressed as a summated rating scale because it exceeds the minimum psychometric properties (Stineman et al., 1996).
An advantage to using the FIM as an outcome tool is the ability to administer this tool both in person and via self-report. Because outcomes measurement is required by CARF, facilities collect FIM data on patients postdischarge to determine if functional gains were maintained. Facility personnel may conduct these assessments or hire a for-profit agency to complete the assessment and provide quarterly reports. To determine the reliability of self-reported scores, FIM scores collected in person were compared to self-reported scores. A study found that for those without cognitive deficits, self-reporting is reliable with correlation ¨ratings of 0.828 (Grey & Kennedy, 1993). When patients have cognitive deficits, proxy data also were found to be reliable and have high agreement for the total FIM score and the motor FIM score but lower for the cognitive FIM score when compared to scores assigned by clinicians (Segal, Gillard, & Schall, 1996).
As mentioned earlier, facilities use functional assessment as a predictor of LOS and resource needs. In a 1994 study, Heinemann and colleagues demonstrated that the motor subscore of the FIM was an accurate predictor of LOS. The FIM score and the estimated hours of care required were well correlated (Disler, Roy, & Smith, 1993). In a comparison study of the FIM, Sickness Impact Profile, and the SF-36 Health Functioning, the FIM was the most accurate predictor of minutes and type of assistance and supervision needed (Deutsch et al., 1996). The FIM also has been determined an accurate predictor of discharge disposition (Granger, Hamilton, & Fiedler, 1992; Oczkowski & Barreca, 1993; Wilson, Houle, & Keith, 1991). The FIM has been modified since its incorporation into the IRF-PAI. Definitions for eating, bladder management, and bowel management were changed, but reliability has remained strong (Granger, Deutsch, Russell, Black, & Ottenbacher, 2007).
Despite literature supporting the validity, reliability, responsiveness, and utility of the FIM, some limitations exist. Before 2002 there was one data repository to which facilities could subscribe—UDSMR—for FIM data collection and comparison. Since 2002, three separate databases have been available. UDSMR (www.udsmr.com) continues to serve approximately 70% of the industry as a data repository and also operates the CMS hotline for FIM scoring questions. eRehabData (www.erehabdata.com) was created by the American Medical Rehabilitation Providers Association and serves approximately 30% of the industry. These organizations neither share nor publish their subscriber lists, so facilities do not know who they are comparing themselves against. Inpatient Rehabilitation Validation and Entry (IRVEN) is the CMS site for IRF-PAI transmission and is free to IRFs; IRVEN users do not have analysis or comparison capabilities. These separate databases do not affect an IRF’s ability to examine outcomes over time, but they do limit an IRF’s ability to compare itself to other IRFs. However, these comparisons must be done with caution because all IRFs are not the same. Some IRFs comprise units with 10–20 beds located within a larger hospital. Others are freestanding rehabilitation hospitals with 100 or more beds. Freestanding facilities are likely to have more resources than hospital-based units and are more likely to treat hundreds of patients with the same diagnosis each year. The differences in the numbers of patients with a specific diagnosis should be considered when IRFs are using their chosen database to compare against those of other facilities.
The purpose of the FIM has shifted over time. Before 2002 the FIM was used to determine personal and facility outcomes and predict resource needs and LOS. Since 2002 it also has become the basis for reimbursement. To maximize reimbursement, many facilities have changed their methods of data collection and hired IRF-PAI coordinators to oversee the process. To capture the most dependent score, more raters, including nursing assistants, are being used. These assistants contribute to scoring through their documentation because they directly assist patients with certain tasks (e.g., toileting, bathing, etc.). Another change since 2002 is the training requirement. The FIM is dependent on clinicians performing the assessment (Cavanagh, Hogan, Gordon, & Fairfax, 2000). To attain interrater reliability, considerable training and education must occur (Hamilton et al., 1994). CMS encourages facilities to train staff on IRF-PAI scoring but does not require it; as a result, there are no uniform educational programs or competency exams. UDSMR and eRehabData offer training sessions and credentialing and competency exams, but they are not standardized. Without this standardization, facility-to-facility comparison may not be valid. The change in methods, the changes to and numbers of raters, and the potential lack of training threaten FIM data reliability.
Many practice changes have been implemented since most of these studies were conducted. For example, some facilities have implemented fall-reduction programs and no-lift policies, which must be considered when scoring because they may artificially lower FIM scores. A patient may be independent in the room with ambulation and transfer just before discharge, but he or she must be supervised at night as part of the facility’s fall-reduction policy. This policy would lower the FIM score to a 5 because CMS guidelines dictate the score reflects the activities a patient can perform, not the things we think he or she can do. The use of clinical judgment to determine a patient’s individualized care and treatment plan must also be considered. For example, a patient may have two stairs to climb to enter his or her home and no stairs once inside, so the therapist chooses to set the stair goal to be independent with three stairs. Because the patient only has three stairs, LOS is short, the patient has other functional goals (e.g., car transfer, longer ambulation distance, etc.), and the physical therapist may choose to stop working on stairs after the patient is independent with one rail up/down three steps. This clinical judgment limits a patient’s ability to attain an FIM score higher than 2 because the guidelines state that for a score higher than 2, a patient must be able to climb 12–14 stairs. Some facilities, however, insist that patients try the entire flight necessary to score stairs. These policies may compromise the validity of interfacility comparison.
Reliability also is a concern. Interrater comparisons in some of the cited studies were based on two raters; many facilities generally use more than two raters. Nurses working different shifts, physical therapists, occupational therapists, and speech-language pathologists are likely to complete sections of the IRF-PAI and FIM. More studies are needed to examine the effect of multiple raters and their education and training on the reliability of FIM data.
Responsiveness of the FIM also has been questioned (Cavanagh et al., 2000). A study by Wallace, Duncan, and Lai (2002) concluded that responsiveness can be affected by timing of the assessment and phase of rehabilitation during which it is determined. The scoring guidelines raise questions about the responsiveness of the tool. For example, to score walk any higher than 2, a patient must walk 150 feet. Consequently, a patient who on admission walks 10 feet with maximal assistance and on discharge walks 100 feet with supervision scores a 2 for both admission and discharge. This patient can now walk 10 times the distance and requires less assistance, but the FIM gain would be 0.
Scoring is further complicated by the “household exception” score of 5 for walk/wheelchair and stairs. This exception allows the clinician to score a patient as a 5 when he or she is independent with or without a device but cannot walk/wheel the required 150 feet (they must advance a minimum of 50 feet) or climb the required 12–14 stairs (they must climb 6–8 steps). In all other scoring categories, a score of 5 means a patient required supervision or cueing for safety or set-up of equipment. So for the FIM items of walk/wheelchair and stairs, the scoring guidelines contain two level 5s. When analyzing FIM data for outcomes purposes, there is no way to determine if the person is independent with a limited distance or number of stairs or if he or she can walk/wheel or climb longer distances with supervision. This makes a difference to discharge planners and families.
Responsiveness also has been questioned regarding bowel and bladder management. A patient who has accidents requiring assistance to change clothing and linen every day would be scored as a 1. If this same patient became continent, used a urinal at night due to frequency and managed the urinal independently, but spilled the urine the night before discharge when emptying the urinal, he would score a 1 as well (the FIM change is 0 despite true functional gain). This lack of responsiveness indicates FIM score alone does not always reflect a patient’s abilities.
In 2002 CMS changed the definition of eating, bladder, and bowel. CMS also added new items to score: bladder frequency of accidents, bowel frequency of accidents, distance walked, and distance in wheelchair. IRFs are mandated to complete the IRF-PAI, and they use the FIM imbedded in the PAI for outcomes purposes. An additional consideration when using FIM for outcomes measurement is that only one study has looked at the validity, reliability, and responsiveness of the FIM since its incorporation into the IRF-PAI.
Veterans Administration (VA) hospitals have seen an increase in rehabilitation services since 2001. These facilities are not under PPS and may choose to use another tool for outcomes measurement and documentation of functional outcomes. If the VA chooses to use and report FIM data, Version 5 scoring guidelines would be used, not those put forth by CMS (Uniform Data System for Medical Rehabilitation, 1996, 1999). These two guidelines are different, and the differences must be considered when comparing outcomes published in the literature. The loss of a single national data repository also is an issue. Although subscribers were never publicized, there was only one FIM data repository, UDSMR. Today, national data are spread across two main databases that are not consistent in outcomes analysis.
Despite its limitations, the FIM is recognized as the rehabilitation industry’s most reliable, valid, and responsive functional assessment tool (Stineman et al., 1996). Because the FIM now is mandated by CMS, it is likely to remain the most used functional assessment tool in the United States. Multiple studies demonstrated its validity, reliability, and responsiveness prior to its inclusion in the IRF-PAI in 2002. Future research needs to explore these areas in light of the continually changing healthcare environment and changes in the tool itself.
IRFs need to invest time and resources to ensure that all clinical staff members whose documentation will be used to determine FIM scores are adequately educated and can demonstrate competency. Facilities must have clear policies regarding when clinicians can use their judgment to stop working on a particular functional skill, or whether they should always encourage patients to attempt the distance required for higher FIM scores. Such policies will increase consistency within facilities and allow for valid and reliable internal comparisons.
The rehabilitation industry needs to work toward a common universal language. Because patients commonly transition between levels of care (acute rehabilitation, outpatient therapy, home care, long-term acute care, and skilled nursing), facilities need to have the capacity to communicate patients’ functional abilities and goals. Currently, various types of facilities have different functional assessment tools; the Minimum Data Set (MDS) in skilled nursing facilities, the Outcome and Assessment Information Set (OASIS) in home care, and the IRF-PAI all assess different functional items and use different tools to do so. In the Deficit Reduction Act of 2005, Congress required CMS to establish a demonstration program to develop a standardized patient assessment instrument across all postacute care sites to measure functional status and other factors during the treatment and at discharge from each provider (CMS, 2006). The project has developed a uniform assessment instrument, Continuity Assessment Record and Evaluation (CARE), which currently is being tested. The CARE tool includes a core set of items and is shorter than the OASIS and MDS. This common language will allow a smoother transition for patients served.
The FIM is the most widely used instrument to measure outcomes in medical rehabilitation units and hospitals in the United States. Rehabilitation providers, including rehabilitation nurses, need to be experts at both scoring and understanding the output from this instrument. Rehabilitation professionals must consider that the instrument itself does not completely reflect patients’ true functional abilities, and should consider reporting other ¨functional descriptors (e.g., distance walked) in addition to FIM scores and be critical consumers of research containing FIM data. Because the tool is not used outside of the rehabilitation setting, rehabilitation professionals will need to convert FIM data into layman’s terms when sharing it with patients and stakeholders and when publishing outcomes results.
The need for rehabilitation services is likely to increase considering the aging baby boomer generation and ongoing military conflicts (in addition to the further advancement of medical science). Consumers will be looking for quality facilities to provide their rehabilitative services. Their choice will not be influenced only by marketing, but also by their primary physician and insurance company. Rehabilitation facilities must be able to demonstrate their worth though patient outcomes. It is only through the demonstration and publication of outcomes that rehabilitation professionals can demonstrate the vital role that rehabilitation facilities and professionals play in improving the lives of patients and their families.
About the Author
Michele Cournan, DNP RN CRRN ANP-BC, is the director of education and resources at Sunnyview Rehabilitation Hospital in Schenectady, NY. Address correspondence to her at firstname.lastname@example.org.
Berg, K., Wood-Dauphinee, S., Williams, J. I., & Gayton, D. (1989). Measuring balance in the elderly: Preliminary development of an instrument. Physiotherapy Canada, 41, 304–311.
Black, T. (1999). Outcomes: What’s all the fuss about? Rehabilitation Nursing, 24(5), 188–189, 191.
Black, T. (2007). Chapter 19: Outcome measurement and performance improvement. In K. Mauk, (Ed). The specialty practice of rehabilitation nursing: A core curriculum (4th ed.). Glenview, IL: Association of Rehabilitation Nurses.
Black, T. M., Soltis, T., & Bartlett, C. (1999). Using the Functional Independence Measure instrument to predict stroke rehabilitation outcomes. Rehabilitation Nursing, 24(3), 109–114, 121.
Brass, T. J., Loushin, M. K., Day, J. W., & Iaizzo, P. A. (1996). An improved method for muscle force assessment in neuromuscular disease. Journal of Medical Engineering Technology, 20, 67–74.
Cavanagh, S. J., Hogan, K., Gordon, V., & Fairfax, J. (2000). Stroke-specific FIM models in an urban population. Journal of Neuroscience Nursing, 32(1), 17–21.
Centers for Medicare and Medicaid Services. (2002). IRF Patient Assessment Instrument. Retrieved January 30, 2011, from www.cms.hhs.gov/InpatientRehabFacPPS/04_IRFPAI.asp.
Centers for Medicare and Medicaid Services. (2006). Deficit reduction act. Retrieved January 30, 2011, from www.cms.hhs.gov/demoprojectsevalrpts/.
Centers for Medicare and Medicaid Services. (2009). Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2010. Retrieved January 30, 2011, from http://220.127.116.11/register/2009/may/06/E9-10078.pdf.
Chau, N., Daler, S., Andre, J. M., & Patris, A. (1994). Inter-rater agreement of two functional independence scales: The Functional Independence Measure (FIM) and a subjective uniform continuous scale. Disability Rehabilitation, 16(2), 63–71.
Cohen, M. E., & Marino, R. J. (2000). The tools of disability outcomes research functional status measures. Archives of Physical Medicine and Rehabilitation, 81(2), S21–S29.
Commission on Accreditation of Rehabilitation Facilities. (2009). Medical rehabilitation standards manual. Tuscon, AZ: CARF International.
Deutsch, A., Braun, S., & Granger, C. (1996). The functional independence measure (FIMSM Instrument) and the functional independence measure for children (WeeFIM® Instrument): Ten years of development. Critical Reviews in Physical Medicine and Rehabilitation Medicine, 8(4), 267–281.
Disler, P. B., Roy, C. W., & Smith, B. P. (1993). Predicting hours of care needed. Archives of Physical Medicine and Rehabilitation, 74(2), 139–143.
Dittmar, S., & Gresham, G. (1997). Appendix A: Description and display of selected functional assessment and outcome measures in physical rehabilitation. In Functional assessment and outcome measurement for the rehabilitation healthcare professional (pp. 90–138). Gaithersburg, MD: Aspen.
Dodds, T. A., Martin, D. P., Stolov, W. C., & Deyo, R. A. (1993). A validation of the Functional Independence Measurement and its performance among rehabilitation inpatients. Archives of Physical Medicine and Rehabilitation, 74(5), 531–536.
Dromerick, A., Edwards, D., & Diringer, M. (2003). Sensitivity to changes in disability after stroke: A comparison of four scales useful in clinical trials. Journal of Rehabilitation Research & Development, 40(1), 1.
Granger, C. V., Cotter, A. S., Hamilton, B. B., Fiedler, R. C., & Hens, M. M. (1990). Functional assessment scales: A study of persons with multiple sclerosis. Archives of Physical Medicine and Rehabilitation, 71, 870–875.
Granger, C. V., Deutsch, A., Russell, C., Black, T., & Ottenbacher, K. J. (2007). Modifications of the FIM instrument under the inpatient rehabilitation facility prospective payment system. American Journal of Physical Medicine and Rehabilitation, 86(11), 883–892.
Granger, C. V., Hamilton, B. B., & Fiedler, R. C. (1992). Discharge outcome after stroke rehabilitation. Stroke, 23(7), 978–982.
Grey, N., & Kennedy, P. (1993). The Functional Independence Measure: A comprehensive study of clinician and self-ratings. Paraplegia, 31(7), 457–461.
Guyatt, G. H., Sullivan, M. J., Thompson, P. J., Fallen, E. L., Pugsley, S. O., Taylor, D. W., et al. (1985). The 6-minute walk: A new measure of exercise capacity in patients with chronic heart failure. Canadian Medical Association Journal, 132, 919–923.
Hamilton, B. B., Laughlin, J. A., Fiedler, R. C., & Granger, C. V. (1994). Interrater reliability of the 7-level Functional Independence Measure. Scandinavian Journal of Rehabilitation Medicine, 26(3), 115–119.
Heinemann, A. W., Linacre, J. M., Wright, B. D., Hamilton, B. B., & Granger, C. V. (1994). Measurement characteristics of the Functional Independence Measure. Topics in Stroke Rehabilitation, 1(3), 1–15.
Kwon, S., Hartzema, A. G., Duncan, P. W., & Min-Lai, S. (2004). Disability measures in stroke: Relationship among the Barthel Index, the Functional Independence Measure, and the Modified Rankin Scale. Stroke, 35(4), 918–923.
Lawton, M. P. (1971). The functional assessment of elderly people. Journal of the American Geriatric Society, 19(6), 465–481.
Linacre, J. M., Heinemann, A. W., Wright, B. D., Granger, C. V., & Hamilton, B. B. (1994). The structure and stability of the Functional Independence Measure. Archives of Physical Medicine and Rehabilitation, 75, 127–132.
Mahoney, F. I., & Barthel, D. W. (1965). Functional evaluation the Barthel Index. Maryland State Medical Journal, 14, 61–65.
Ottenbacher, K. J., Hsu, Y., Granger, C. V., & Fiedler, R. C. (1996). The reliability of the functional independence measure: A quantitative review. Archives of Physical Medicine and Rehabilitation, 77(12), 1226–1232.
Ottenbacher, K. J., Mann, W. C., Granger, C. V., Tomita, M., Hurren, D., & Charvat, B. (1994). Interrater agreement and stability of functional assessment in the community-based elderly. Archives of Physical Medicine and Rehabilitation, 75(12), 1297–1301.
Oczkowski, W. J., & Barreca, S. (1993). The Functional Independence Measure: Its use to identify rehabilitation needs in stroke survivors. Archives of Physical Medicine and Rehabilitation, 74(12), 1291–1294.
Pollak, N., Rheault, W., & Stoecker, J. L. (1996). Reliability and validity of the FIM for persons aged 80 years and above from a multilevel continuing care retirement community. Archives of Physical Medicine and Rehabilitation, 77(10), 1056–1061.
Segal, M. E., Gillard, M., & Schall, R. R. (1996). Telephone and in-person proxy agreement between stroke patients and caregivers for the Functional Independence Measure. American Journal of Physical Medicine and Rehabilitation, 75(3), 208–212.
Stineman, M. G., Shea, J. A., Jette, A., Tassoni, C. J., Ottenbacher, K. J., Fiedler, R., et al. (1996). The Functional Independence Measure: Tests of scaling, assumptions, structure, and reliability across 20 diverse impairment categories. Archives of Physical Medicine and Rehabilitation, 77(11), 1101–1108.
Stineman, M. G., Jette, A., Fiedler, R., & Granger, C. V. (1997). Impairment-specific dimensions within the Functional Independence Measure. Archives of Physical Medicine and Rehabilitation, 78, 636–643.
Teasdale, G., & Jennett, B. (1974). Assessment of coma and impaired consciousness. A practical scale. Lancet, 13(2), 81–84.
Wallace, D., Duncan, P. W., & Lai, S. (2002). Comparison of the responsiveness of the Barthel Index and the motor component of the Functional Independence Measure in stroke. The impact of using different methods for measuring responsiveness. Journal of Clinical Epidemiology, 55(9), 922–928.
Wilson, D. B., Houle, D. M., & Keith, R. (1991). Stroke rehabilitation: A model predicting return home. Western Journal of Medicine, 154(5), 587–590.
Uniform Data System for Medical Rehabilitation. (1996). Guide for the uniform data set for medical rehabilitation. Buffalo, NY: State University of New York.
Uniform Data System for Medical Rehabilitation. (1999). The FIMware® user guide and self-guided training manual, Version 5.20. Buffalo, NY: UDSMR.
van der Putten, J. J., Hobart, J. C., Freeman, J. A., & Thompson, A. J. (1999). Measuring change in disability after inpatient rehabilitation: Comparison of the responsiveness of the Barthel Index and the Functional Independence Measure. Journal of Neurology, Neurosurgery, and Psychiatry, 66(4), 480–484.
Rehabilitation Nursing is pleased to offer readers the opportunity to earn nursing contact hours for its continuing education articles by taking a posttest through the ARN Web site. The posttest consists of questions based on this article, plus several assessment questions (e.g., how long did it take you to read the article and complete the posttest?). A passing score of 80% on the posttest and completion of the assessment questions yield one nursing contact hour for each article.
To earn contact hours, go to www.rehabnurse.org/education/cearticles.html. (You may also go to www.rehabnurse.org → Education → RNJ Online CE.) Once there, you may read the article again or go directly to the posttest assessment by selecting "Purchase CE Test."
Between May 1, 2011, and June 30, 2011, contact hours for this article will be free for ARN members who complete the posttest and evaluation. After June 30, 2011, regular pricing will apply.
The Association of Rehabilitation Nurses is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center’s Commission on Accreditation (ANCC-COA).