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Research Reports |
AM Jette, PT, PhD, is Director, Health and Disability Research Institute, School of Public Health, Boston University, 580 Harrison Ave, 4th Floor, Boston, MA 02218 (USA)
SM Haley, PT, PhD, is Associate Director, Health and Disability Research Institute, School of Public Health, Boston University
W Tao, BS, is Graduate Research Associate, Health and Disability Research Institute, School of Public Health, Boston University
P Ni, MD, MPH, is Research Assistant Professor, Health and Disability Research Institute, School of Public Health, Boston University
R Moed, MBA, is President, CRE Care, LLC, Boston, Mass
D Meyers, MBA, is National Director of Trends and Outcomes, HealthSouth Outpatient Services, HealthSouth Corporation, Birmingham, Ala
M Zurek, PT, is Vice President of Clinical Quality, HealthSouth Outpatient Services, HealthSouth Corporation
Address all correspondence to Dr Jette at: ajette{at}bu.edu
Submitted April 24, 2006;
Accepted November 29, 2006
 | Abstract |
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Method: This was a prospective study with a convenience sample of 1,815 patients with spine, lower-extremity, or upper-extremity impairments who received outpatient physical therapy in 1 of 20 outpatient clinics across 5 states. The authors conducted an evaluation of the number of items used and amount of time needed to complete the CAT assessment; evaluation of breadth of content coverage, item exposure rate, and test precision; as well as an assessment of the validity and sensitivity to change of the score estimates.
Results: Overall, the AM-PAC-CAT's Basic Mobility scale demonstrated excellent psychometric properties while the Daily Activity scale demonstrated less adequate psychometric properties when applied in this outpatient sample. The mean length of time to complete the Basic Mobility scale was 1.9 minutes, using, on average, 6.6 items per CAT session, and the mean length of time to complete the Daily Activity scale was 1.01 minutes, using on average, 6.8 items.
Background and Conclusion: Overall, the findings are encouraging, yet they do reveal several areas where the AM-PAC-CAT scales can be improved to best suit the needs of patients who are receiving outpatient orthopedic physical therapy of the type included in this study.
| Introduction |
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 TopAbstract Introduction MethodResultsDiscussion and ConclusionsReferences |
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A CAT is programmed to first present an item from the mid-range of a predefined item bank of outcome questions and then directs subsequent questions to the patient's most appropriate level based on his or her previous responses. By having comprehensive item banks available for each outcome domain of interest, the CAT algorithm selects only the items that are needed to provide a score estimate based on a predetermined number of items or a predetermined level of measurement precision. This allows for fewer items to be administered to each patient while gaining accurate information regarding an individual's placement along an outcome continuum.5 The development of comprehensive and methodologically sound item banks for each outcome of interest is a prerequisite to the development of psychometrically adequate CAT platforms that have clinical or research utility.
Item response theory (IRT) is both a theoretical framework and a collection of quantitative techniques used to construct outcome instruments, to scale responses to individual test items, and to equate scores, as well as to identify item bias and to facilitate CAT.3,6 With IRT, items are calibrated on the same scale that is used to measure a patient's functional ability. As such, the items are inherently linked to the scale both in terms of ability and the amount of information that an item provides at some point along the scale. In a CAT application, items are selected based on maximum information near the individual's estimated level of ability, thus avoiding the administration of items that are too easy or too difficult. This property of IRT supports an efficient selection of items during a CAT administration. In essence, the CAT software is programmed to select the items that provide optimal information, thus leading to a precise and efficient estimate of the patient's ability.7,8 This feature of CAT and IRT methods creates important flexibility in administering tests in a dynamic and tailored approach for each patient.
Although CAT applications for health care have been recommended for nearly a decade2,5,9 and a major set of papers on the subject was published in 2000,7,10,11 the literature has been limited largely to either position papers,4,12–14 data simulations,1,15–19 or small-scale prospective research demonstrations.17,18,20
If CAT applications are going to become widely accepted as a means of monitoring health care outcomes, prospective evaluations should become more readily available in the clinical literature. To our knowledge, no previous study has evaluated the prospective use of CAT in health care environments. Building on our previous work,21–23 in this pilot study we prospectively evaluated the practical and psychometric adequacy of the Activity Measure for Post-Acute Care (AM-PAC) "item bank" and CAT assessment platform (AM-PAC-CAT) when applied within orthopedic outpatient physical therapy settings. Our evaluation consisted of 3 components: (1) a practical evaluation that included test efficiency of the CAT (ie, number of items used and amount of time needed to complete the CAT assessment); (2) a psychometric evaluation, including content range coverage, item exposure rate (IER), test precision, and person fit; and (3) an assessment of the validity and sensitivity to change of the score estimates derived by the AM-PAC-CAT.
In this study, we evaluated the Basic Mobility and Daily Activity scales of the AM-PAC-CAT.24 Our intent was to identify areas where the prototype AM-PAC-CAT instrument was working well and where the CAT could be improved to enhance its utility for use in outpatient rehabilitation and related clinical settings.
| Method |
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TopAbstractIntroductionMethodResultsDiscussion and ConclusionsReferences |
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We developed an initial pool of AM-PAC items based on input from measurement and content experts, suggestions from several focus groups of people with disabilities, and a comprehensive literature review. Some items were modified from existing functional instruments, but adapted for difficulty or assistance response categories included in the AM-PAC. We framed the activity questions in a general fashion without specific attribution to health, medical conditions, or disabling factors. The AM-PAC data are collected by self-report, either through self-administration or when administered either by a clinician or by a trained data collector.
The Daily Activity scale item bank encompasses 65 distinct personal care and instrumental activities of daily living tasks. The Basic Mobility domain contains 120 basic physical activities such as bending, walking, carrying, or climbing stairs. Based on factor analytic work and IRT analyses,21,23 Basic Mobility and Daily Activity scale domains were identified and confirmed. A third AM-PAC domain—applied cognitive activity—was not included because it was judged by the clinical sites participating in this study as not relevant to this patient population.
The IRT modeling of the items was conducted using the generalized partial credit model (GPCM).26 The GPCM uses 2 parameters—item difficulty and discrimination—in estimating item locations and person scores and makes no assumptions regarding the similarity of item response categories across items. Adequate levels of reliability of individual items and validity of the AM-PAC have been established and have been reported previously.21,27
We developed a CAT version of the AM-PAC instrument (the prototype AM-PAC-CAT instrument) and have conducted a preliminary evaluation in samples of patients in post–acute care settings.24 The CAT software includes options for item selection, score estimation using the expected a posteriori (EAP) estimator method, and stopping rules based on the number of items or level of precision.
In this study, we set a stop rule of administering no more than 7 items to each patient based on the participating clinic's desire to keep patient (and clinic staff) burden to an absolute minimum. We also used a content balancing algorithm that allowed AM-PAC items to be selected based on both content specifications and maximum information function for the first 3 items of the Basic Mobility scale and the first 4 items of the Daily Activity scale.28
The content balancing algorithm ensured that content chosen within the CAT item selection procedure was not limited to only one content aspect of the scale. For example, the first 3 items of the Basic Mobility scale were an item from each of the 3 major content areas: (1) bend/lift/reach/carry/ items, (2) mobility items, and (3) transfer items. Likewise, the CAT was programmed to select an item with the most information from one of each of the 4 Daily Activity scale content areas: (1) dressing items, (2) meal items, (3) grooming and hygiene items, and (4) instrumental activity items. Subsequent items in both scales then were selected based on maximum information at each iterative step.
Estimated AM-PAC scores for each subject in the sample were converted to norm-based scoring, which is a simple linear translation that expresses scores as deviations from a measure of central tendency. In this study, we used a mean of 50 and a standard deviation of 10. By using norm-based scoring instead of the more traditional 0–100 scale, as we raise the ceiling or lower the floor of a scale in the future by adding and calibrating new items, the placement (and scoring) of the item thresholds in relation to the average does not change. We based the CAT algorithms used in this study on software developed at the Health and Disability Research Institute, Boston University.
Subjects
Subjects for this study, conducted in 2005, consisted of a convenience sample of 1,815 patients with spine, lower-extremity (LE), or upperextremity (UE) impairments who received outpatient physical therapy in 1 of 20 outpatient clinics across 5 states that were operated by HealthSouth's Outpatient Division Inc.
Background characteristics of the study sample, by major impairment grouping, are shown in Table 1. The sample was predominantly female, with a mean age between 46.8 and 51.4 years.
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Subject demographic information, acuity level, surgical status, and major impairment were all available from administrative data collected routinely by each outpatient clinic. Reliability and validity data on these administrative data elements were not available. Acuity was defined as the number of days from the onset of the condition for which therapy was being sought to the admission visit to the physical therapy clinic. Payer source was defined as the primary source of payment for that physical therapy episode of care. Spine impairments included impairments of the cervical, thoracic, or lumbosacral region of the spine. Upper-extremity impairments included conditions of the shoulder, elbow, hand, or wrist. Lower-extremity impairments were conditions of the hip, knee, foot, or ankle.
Data Analysis
To evaluate the practical utility of the AM-PAC-CAT, we assessed the CAT's efficiency, which was defined as the number of CAT items administered per assessment and the amount of time taken to complete the CAT. In the psychometric evaluation, we assessed the content range of each scale item pool, IER, test precision, and model fit in this sample. We also evaluated scale score validity and sensitivity to change over the episode of care.
Content range coverage assessed how well the AM-PAC item bank captured the range of physical functioning experienced by the subjects in each Activity Limitation scale content domain. We examined potential ceiling effects (ie, the point at which subjects received the highest score) and floor effects (ie, the point at which subjects received the lowest possible score).
The IER identified which AM-PAC items were administered more often in the CAT application. Item exposure rate was defined as the ratio of the total number of times an item was administered over the total number of test occasions in a CAT study. Plots of the IER against item difficulty levels were constructed to detect possible relationships between frequencies of items being selected and their difficulty levels. The IER is influenced by the difficulty and discrimination of items, the distribution of ability of the patients, what other similar items are in the item bank, and the specific content balancing specifications developed for each scale.29,30
Test precision was examined in this sample using the test information function (TIF). The TIF is a summary of information provided by individual items in the instrument and identifies where along an underlying scale that items have their best level of discrimination and measurement precision. Although the ideal for a CAT instrument is equal measurement precision (small standard errors of measurement) at all levels of ability, there is likely to be some variability of measurement precision for a certain group of people depending on their level of ability on the scale. The location on the scale where the test information curve peaked indicates the portion on an ability scale best measured by that instrument. When the test information is peaked at around the same range on the scale as the patients' peak of ability distribution, the instrument is assumed to "fit" the population being measured.
Test information function values are closely related to the calculation of standard error (SE) of the person ability estimates. Specifically, the SE of the person ability estimate is inversely proportional to the TIF value: SE=1/square root(TIF). To illustrate the precision levels of CAT scores at different ability levels, we also calculated the average SE of estimates for people at different score ranges. Confidence intervals (CIs) of the estimates were generated by multiplying the SE by a z score corresponding to certain confidence level.
To assess sample fit to the CAT model, we estimated the degree to which the subjects' responses to items met the hierarchical assumptions of the fixed calibrations used in the CAT for the Basic Mobility and Daily Activity scales. For any IRT scale, an important assumption is that item difficulty locations on the underlying functional scale are similar for all people and that these locations have a predetermined hierarchy that applies to most individuals. To test this assumption, we used a standardized log-likelihood statistic (lz) for polytomous items to test for person fit.31 The empirical distribution of the log-likelihood statistic is reasonably close to a standardized normal distribution, so we calculated the percentage of administrations (both at admission and discharge) in which lz exceeded an alpha level of .05.
Validity of CAT score estimates was assessed using construct validation techniques. To provide evidence for construct validity of the AM-PAC-CAT scales, we compared AM-PAC-CAT scores between subjects with less than 35 acuity days (the median) and subjects with more than 35 acuity days and between subjects who had postsurgery treatment and those who had not. We hypothesized that earlier treatment following the onset of a condition and treatment after surgery would be associated with more improvement on both AM-PAC outcome scales.
Sensitivity to change was examined using one-sample dependent t tests to determine whether the increase in AM-PAC-CAT scores between admission and discharge from therapy were significantly greater than zero. In addition, we calculated the minimal detectable change (MDC) and the MDC proportion. The MDC is considered the minimal amount of change that is not likely to be due to measurement error. It is one of the more common distributional-based change indexes, which can be used to identify reliable changes in function, strength (force-generating capacity), and walking efficiency.32 The MDC can be reported at different confidence levels. We chose to report both the MDC68 and MDC90 confidence levels in this article. The MDC proportion was calculated as the proportion of people scored equal to or above MDC. In calculating the MDC, we used test-retest reliability estimates on the short-form AM-PAC from our earlier work.27
| Results |
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TopAbstractIntroductionMethodResultsDiscussion and ConclusionsReferences |
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Content Coverage
The mean Basic Mobility scale scores at the admission and discharge visits, for the total sample and by impairment group, are listed in Table 2. The mean admission score of the total group was 63.3, and the mean discharge score of the total group was 68.7, an average increase of 5.4 units. When broken down into the 3 impairment groups, the UE group had the highest Basic Mobility scale scores and the LE group had the lowest scores in both admission and discharge sessions.
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Construct Validity
If both AM-PAC scales discriminated properly, we expected to see greater increases in basic mobility and daily activity for those subjects who were below the median level of acuity compared with those who were above the median level and for those who received postsurgical treatment compared with those who did not receive postsurgical treatment. As hypothesized, the data presented in Table 7 revealed that there were statistically significant differences in level of improvement in the Basic Mobility scale as a function of a subject's acuity level and his or her surgical status. The Daily Activity scale discriminated across acuity subgroups, but the difference was not statistically significant for the surgical status subgroups.
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Among the 3 impairment groups, the LE impairment group experienced the highest Basic Mobility scale mean score increase (8.32 units), followed by the spine impairment group (4.83 units) and then by the UE impairment group (2.78 units). The Daily Activity scale also detected significant mean score increases for the total sample (3.9 units) and by each impairment group. Among the impairment groups, the UE impairment group experienced the highest mean Daily Activity scale score increase (5.65 units), followed by the LE impairment group (3.69 units) and then the spine impairment group (2.89 units).
For the Basic Mobility scale, 60% of the patient episodes exceeded the MDC68 and 49% exceeded the MDC90. For the Daily Activity scale, 50% of the patient episodes exceeded the MDC68 and 42% exceeded the MDC90. The proportion of patients who exceeded the MDC varied across impairment groups is shown in Tables 2 and 3.
| Discussion and Conclusions |
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TopAbstractIntroductionMethodResultsDiscussion and ConclusionsReferences |
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The present study is the first attempt, to our knowledge, to prospectively evaluate the psychometric utility of 2 CAT-based Activity Limitation outcome scales within an actual clinical setting for the purpose of monitoring functional outcomes. This evaluation included an assessment of the scale distributions and content coverage, particularly their ceiling and floor effects; CAT selection of items from the underlying item pool; precision of the test; and construct validity and sensitivity to change, along with an examination of how well the item banks fit this sample of patients receiving outpatient orthopedic physical therapy services. Overall, the findings are encouraging, yet they do suggest areas for improvement that would advance measurement in this sample.
The AM-PAC-CAT's Basic Mobility scale demonstrated excellent psychometric properties when applied in this outpatient rehabilitation sample. The frequency distributions were roughly normally distributed, with no floor effects and only modest ceiling effects (10% at discharge). Although the Basic Mobility scale was sensitive to change in all 3 impairment groups, it was most sensitive to change among those subjects with primary LE and spinal impairments. The effect size level for the Basic Mobility scale was 0.34 for subjects with UE impairments, but an effect size level of 0.91 was achieved for subjects with LE impairments. The greatest proportion of subjects exceeding the Basic Mobility scale MDC (66.1%) was seen in those with LE impairments. The Basic Mobility scale worked least well for subjects with UE impairments, which makes clinical sense when one considers that people with UE conditions are less likely to experience mobility limitations in the types of activities measured by this scale.
The Basic Mobility scale also discriminated well among subjects as a function of their acuity level and their postsurgical status. Among a pool of 120 items, the CAT relied primarily on 21 Basic Mobility scale items. While the CAT relied most frequently on those items in the upper half of the Basic Mobility scale, the distribution of the higher-end items was roughly even across the upper half of the scale. Considering that the AM-PAC was designed for patients in post–acute care inpatient and outpatient settings, one would expect the items used in an outpatient sample to be selected from the upper half of the item bank. Based on the TIF of the most frequently used CAT items, analyses revealed that the greatest measurement precision occurred when a person's Basic Mobility scale score was between 50 and 60, with less precision being achieved above and below this range. It is clear that new items located at the upper (better functioning) end of the Basic Mobility scale could help reduce ceiling effects and improve measurement precision.
The AM-PAC-CAT's Daily Activity scale demonstrated less adequate psychometric properties than the Basic Mobility scale in this outpatient sample. Analyses revealed several areas where the Daily Activity scale is in need of revision and improvement to best suit the needs of people in orthopedic outpatient settings. The frequency distributions of the Daily Activity scale scores revealed the negatively skewed distributions for subjects in each impairment group on admission to and at discharge from physical therapy care. There was a substantial ceiling effect in the Daily Activity scale scores for all 3 impairment groups, especially in the LE impairment group where the ceiling was reached by 32.3% of the subjects on admission and by 62.6% of the subjects at discharge. The Daily Activity scale discriminated among subjects as a function of their acuity status and detected significant mean score increases in function for all 3 impairment groups.
Despite the shortcomings of the Daily Activity scale, the group effect sizes achieved were substantial: the range was from 0.42 for spine impairments to 0.60 for UE impairments. The Daily Activity scale was most sensitive to change among those subjects with UE impairments, which also makes clinical sense because UE impairments are the type of condition most likely to affect personal care and performance of instrumental activities of daily living. Among a pool of 65 Daily Activity scale items, the CAT relied primarily on 15 items, which were predominantly located in the upper end of the item pool. The TIF curve for the items most frequently selected by the CAT on the Daily Activity scale revealed that these items provided less information for the subjects with Daily Activity scale scores above 60 units. For improved measurement precision at higher levels of functioning, particularly for improving the precision of individual score estimates, these findings suggest that the Daily Activity scale needs revision and addition of new items to make the scale more useful for outpatients of the type seen in this study.
An important advantage of CAT methodology, in contrast to traditional fixed-form measurement approaches, is the ability to readily update and improve the item bank as well as the CAT algorithms as problems are identified. Based on the results of this study, our research group has developed new questionnaire items for the Basic Mobility and Daily Activity scale item banks and has tested them, along with the existing AM-PAC-CAT scales, within a new sample of outpatients receiving physical therapy services. We are currently examining these new items in an IRT analysis to determine whether they fit the Basic Mobility or Daily Activity outcome scales, have content advantages over current items, and have locations on these outcome scales that fill in the content gap identified in the current study. Once these new IRT analyses are completed, the new items will be incorporated into the next revision of the Basic Mobility and Daily Activity scale item bank and CAT programs. In this sense, CAT outcome instruments can be viewed as dynamic, with the potential for continuous updating and improvement.
One of the concerns over using CAT-based outcome instruments is whether restricting the number of items administered to a patient (a maximum of 7 items in this study) could diminish the sensitivity of the instrument to change. With regard to this issue, it was encouraging to note that the effect sizes observed using the AM-PAC-CAT were comparable to those observed in similar types of patients followed with more traditional fixed-form functional outcome tools. For example, in this study, we observed an effect size of 0.91 with the AM-PAC Basic Mobility scale when used with patients with LE impairments. This finding compares with an effect size of 0.94 at 4 weeks for the Activities of Daily Living Scale in subjects with knee impairments,33 an effect size of 0.93 for the Lysholm Knee Rating Scale, and an effect size of 0.81 that was observed on the Physical Function scale of the 36-Item Short-Form Health Status questionnaire (SF-36) when applied in a sample of outpatients with knee impairments.35 In our study, the average AM-PAC-CAT Basic Mobility scale effect size was 0.62 in subjects with spinal impairments, which compares with an effect size of 0.70 that was observed on the Physical Function scale of the SF-36 when applied in a sample of outpatients with cervical and lumbar impairments.36 Future studies will be directed at evaluating the extent to which adding more than the 7 items per scale may improve upon the levels of sensitivity observed in this study.
Limitations
There are several limitations to the pilot study that should be noted. The first is that the subjects were a convenience sample of outpatients drawn from 20 outpatient practices. As with any convenience sample, we have no way of determining the extent to which these subjects represent the populations served by these clinics.
The reader also should note that only those subjects who completed both admission and discharge AM-PAC-CATs were eligible for our analyses. Securing discharge CATs in these busy clinical practices was a problem. Although the sample for this paper consisted of only 38% of all subjects who had completed the admission AM-PAC-CAT, those subjects who completed an admission AM-PAC-CAT but not a discharge AM-PAC-CAT were very similar to those who completed both instruments. Subjects who completed only the admission AM-PAC-CAT versus subjects who completed both admission and discharge AM-PAC-CATs were slightly younger (mean age=48 years versus 50 years), were more likely to have a spinal impairment (36% versus 32%), and were less likely to be receiving postsurgical treatment (24% versus 28%). The mean Basic Mobility and Daily Activity scale scores for patients who completed only the admission AM-PAC-CAT were 62.7 and 56.5, not statistically different from the mean scores of 62.9 and 56.8 for the final sample. Finally, we used test-retest estimates from an earlier study of the AM-PAC that was done with both inpatients and outpatients who were receiving post–acute care.27 The ideal approach would have been to derive test-retest estimates from a sample of subjects from orthopedic outpatient settings. We were unable to do so in this study, so we used the estimates from our earlier work. These methodological limitations should be kept in mind when interpreting our findings.
Implications
We believe that contemporary measurement methods such as IRT and CAT methodology present an exciting innovation that has the potential to transform the way in which patient-based outcome assessments are conducted within and across health care settings. The National Institutes of Health, for example, has recently included CAT approaches as part of their Roadmap and has funded major multi-year CAT projects to develop clinical research applications14 designed to ensure more uniformity in outcome endpoints used for clinical trials. Because CAT assessments provide an accurate, real-time measurement of outcomes, the CATs can readily be used to track patient-reported outcomes to clinical interventions, making them attractive for use in quality-monitoring systems applied across various clinical settings.37
We believe that the advantages of CAT-based instruments are likely to be maximized when applied across various post–acute care settings where the breadth of the CAT-based instrument will be of maximum advantage. For instance, when used to monitor patient outcomes across inpatient rehabilitation, nursing home, and home health care settings, the sensitivity of the AM-PAC-CAT has been shown to be superior to traditional setting-specific instruments such as the Functional Independence Measure.38,39
Future CAT development should include work that attempts to balance the utility of generating scores for groups of patients (as was done in this study) with a desire by clinicians to use these CAT assessments as a source of usable information for individual treatment planning and specific patient monitoring. Past efforts that have tried to use group-level outcome assessment tools for individual patient assessment have largely been disappointing.40 The problem is that group-level instruments yield imprecise and insensitive scores for individual patients. This problem might be solved using CAT methodology.2
In theory, it is possible to generate CAT item selection algorithms that would select items to be administered to a patient from the relevant underlying item pool based on clinical considerations as well as on maximizing information for the CAT estimate. Computerized adaptive testing methodology allows the user to yield reliability estimates at the level of the individual person, thus facilitating the selection of a sufficient number of items for longitudinal assessment of individual change over time. An example of how this individual patient approach using a CAT version of the Pediatric Evaluation of Disability Inventory was recently published.32 A challenge to developing CAT applications that are useful at the individual patient level in rehabilitation is to provide sufficient information at the patient level while minimizing patient response burden so that CATs remain feasible to use in clinical practice.
If CAT outcome instruments such as the AM-PAC-CAT are shown to be beneficial for widespread application and use, a future challenge will be to develop effective and efficient methods to disseminate these innovations. It is essential not only that information about contemporary outcome instruments is communicated accurately and efficiently, but also that potential users understand what these instrument can offer and have the skill to appropriately implement them to assess functional outcomes. Without careful attention to dissemination and training, health care professionals may not know how to use these innovative tools and, consequently, outdated ordinal-scaled measures are likely to remain the outcome measurement norm for years to come.
To accomplish this challenge, new dissemination methods will need to be developed and implemented beyond the traditional methods of professional conference presentations and publication in scholarly journals.41 Funding mechanisms will need to be developed that will support these dissemination tasks at every level. Future users must be provided with the software needed to apply, analyze, and interpret CAT-based outcome instruments. This may require the development of continuing education seminars or high-quality technical assistance vehicles to assist rehabilitation professionals and organizations in their understanding, application, and interpretation of contemporary outcome measurement tools. Accreditation or professional organizations might be able to play a crucial role in this dissemination approach, facilitating the dissemination process.
In addition, efforts need to be taken to ensure that future generations of clinicians are appropriately trained through the development of didactic courses and professional curricula on contemporary outcomes measurement. Specific courses on modern measurement technology can be incorporated into professional curricula as a new basic science in professional (entry-level) health professions education. To accomplish this challenge will require efforts to educate faculty in the science of contemporary outcome measurement so that they have the skill to develop and deliver these courses to their future students. All of these dissemination steps are necessary to ensure that future generations of clinicians are familiar with and skilled in the application of contemporary outcomes measurement. Once developed and fully tested, these contemporary outcome instruments need to be widely disseminated and incorporated into clinical practice and research to improve our understanding of the effectiveness of health care interventions.
| Footnotes |
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This study was approved by the Institutional Review Board of Boston University.
This study was supported by HealthSouth Corporation's Outpatient Division. It also was supported, in part, by an Independent Scientist Award (K02 HD45354-01) to Dr Haley.
Dr Jette, Dr Haley, and Mr Moed have stock interest in CRE Care, LLC, which distributes the Activity Measure for Post-Acute Care products.
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TopAbstractIntroductionMethodResultsDiscussion and ConclusionsReferences |
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This article has been cited by other articles:
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  A. M Jette Invited Commentary Physical Therapy, July 1, 2008; 88(7): 851 - 853. [Full Text] [PDF]
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D. Deutscher, D. L Hart, R. Dickstein, S. D Horn, and M. Gutvirtz Implementing an Integrated Electronic Outcomes and Electronic Health Record Process to Create a Foundation for Clinical Practice Improvement Physical Therapy, February 1, 2008; 88(2): 270 - 285. [Abstract] [Full Text] [PDF]
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R. L Craik Till We Meet Again Physical Therapy, July 1, 2007; 87(7): 830 - 832. [Full Text] [PDF]
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D. L Hart On "Prospective Evaluation of the AM-PAC-CAT..." Jette et al. Phys Ther. 2007;87:385 398. Physical Therapy, May 1, 2007; 87(5): 609 - 611. [Full Text] [PDF]
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