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Descriptive Data Analysis Examining How Standardized Assessments Are Used to Guide Post–Acute Discharge Recommendations for Rehabilitation Services After Stroke

Marghuretta D. Bland, Michelle Whitson, Hilary Harris, Jeff Edmiaston, Lisa Tabor Connor, Robert Fucetola, Alexandre Carter, Maurizio Corbetta, Catherine E. Lang
DOI: 10.2522/ptj.20140347 Published 1 May 2015
Marghuretta D. Bland
M.D. Bland, PT, DPT, NCS, MSCI, Program in Physical Therapy, Department of Neurology, and Program in Occupational Therapy, Washington University. Mailing address: Program in Physical Therapy, Washington University, 4444 Forest Park, Campus Box 8502, St Louis, MO 63108 (USA).
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Michelle Whitson
M. Whitson, PT, MHS, MA, MBA, Barnes Jewish Hospital Rehabilitation Services, St Louis, Missouri.
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Hilary Harris
H. Harris, MSPT, Barnes Jewish Hospital Rehabilitation Services.
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Jeff Edmiaston
J. Edmiaston, MS, CCC-SLP, Barnes Jewish Hospital Rehabilitation Services.
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Lisa Tabor Connor
L.T. Connor, PhD, MSOT, Department of Occupational Therapy, MGH Institute of Health Professions, Boston, Massachusetts.
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Robert Fucetola
R. Fucetola, PhD, Department of Neurology, Washington University.
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Alexandre Carter
A. Carter, MD, PhD, Department of Neurology, Washington University.
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Maurizio Corbetta
M. Corbetta, MD, Department of Neurology and Department of Radiology, Washington University.
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Catherine E. Lang
C.E. Lang, PT, PhD, Program in Physical Therapy, Department of Neurology, and Program in Occupational Therapy, Washington University.
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Abstract

Background Use of standardized assessments in acute rehabilitation is continuing to grow, a key objective being to assist clinicians in determining services needed postdischarge.

Objective The purpose of this study was to examine how standardized assessment scores from initial acute care physical therapist and occupational therapist evaluations contribute to discharge recommendations for poststroke rehabilitation services.

Design A descriptive analysis was conducted.

Methods A total of 2,738 records of patients admitted to an acute care hospital with a diagnosis of stroke or transient ischemic attack were identified. Participants received an initial physical therapist and occupational therapist evaluation with standardized assessments and a discharge recommendation of home with no services, home with services, inpatient rehabilitation facility (IRF), or skilled nursing facility (SNF). A K-means clustering algorithm determined if it was feasible to categorize participants into the 4 groups based on their assessment scores. These results were compared with the physical therapist and occupational therapist discharge recommendations to determine if assessment scores guided postacute care recommendations.

Results Participants could be separated into 4 clusters (A, B, C, and D) based on assessment scores. Cluster A was the least impaired, followed by clusters B, C, and D. In cluster A, 50% of the participants were recommended for discharge to home without services, whereas 1% were recommended for discharge to an SNF. Clusters B, C, and D each had a large proportion of individuals recommended for discharge to an IRF (74%–80%). There was a difference in percentage of recommendations across the clusters that was largely driven by the differences between cluster A and clusters B, C, and D.

Limitations Additional unknown factors may have influenced the discharge recommendations.

Conclusions Participants poststroke can be classified into meaningful groups based on assessment scores from their initial physical therapist and occupational therapist evaluations. These assessment scores, in part, guide poststroke acute care discharge recommendations.

In the acute care setting, the median length of stay for people with stroke is 3 days.1 Rehabilitation clinicians often see a patient only once for an acute care evaluation, and a key responsibility is to screen for sensorimotor, cognitive, and language deficits. Despite the challenges of patient-, clinician-, and facility-specific barriers,2–9 use of standardized assessments across the continuum of care is continuing to grow through multiple efforts.10–13 A goal of standardized assessment is to objectively quantify deficits of impairment, activity limitations, and participation restrictions to assist rehabilitation clinicians in determining patient prognosis, appropriate interventions, and the need for additional services.4,5,13–16 It is assumed that standardized assessments completed during the initial evaluation will help clinicians in determining these factors; however, research has not shown that this is the case.

The aim of this study was to examine if standardized assessment scores from initial acute care physical therapist and occupational therapist evaluations systematically contribute to discharge recommendations for poststroke rehabilitation services. After initial evaluation of patients in our acute care facility, physical therapists and occupational therapists make one of the following discharge recommendations: (1) home with no services, (2) home with services, (3) inpatient rehabilitation facility (IRF), or (4) skilled nursing facility (SNF). If the standardized assessments, which measure key impairments and activity limitations, systematically contribute to discharge recommendations, we would expect patterns or groupings of patients based on the severity of the deficits. For example, patients with no deficits to minimal deficits would likely be grouped together and would most often receive the recommendation to go home with no services, whereas those with severe deficits would be grouped together and would most likely receive the recommendation for discharge to an SNF. Patients with mild to moderate deficits would be somewhere between these groups and would receive a recommendation of home with services or IRF. As standardized assessments become more routinely administered, the results of this study will provide information on the next step: examining how standardized assessments shape and guide rehabilitation clinical practice.

Method

Participants

This study utilized a convenience sample of 2,738 patient records stored in the Brain Recovery Core database and additional variables collected in the Cognitive Rehabilitation Research Group database from January 2010 through March 2013.10,17 All participants had a primary diagnosis of stroke or transient ischemic attack (TIA).18 Each participant provided informed consent to have his or her stroke rehabilitation data stored and used for research. The Washington University Human Research Protection Office approved the databases and studies using de-identified data.

Participants averaged 0 days between onset of stroke to admission to the acute care hospital. Once a patient is admitted to the acute care hospital and is medically stable, rehabilitation services for physical therapy and occupational therapy are ordered, usually within 24 hours of admission. The acute care physical therapist evaluation is completed, on average, within 4 days (median=1 day) of admission, and the occupational therapist evaluation is completed, on average, within 3 days (median=1 day) of admission. The recommendation for discharge services for this analysis originated from the initial physical therapist and occupational therapist evaluations. The recommendations for discharge services from speech-language pathologists were not included; participants with stroke or TIA were referred for speech-language pathology therapy only if they screened positive for a language deficit (by an occupational therapist), screened positive for a swallowing deficit (by nursing staff), or met the criteria for further determination of subtle higher-level cognitive deficits (based on the occupational therapy screening battery).19 Typical initial evaluations at an acute care hospital for patients poststroke take an average of 20 minutes for physical therapy and 39 minutes for occupational therapy.19 Discharge recommendations were made by the physical therapists and occupational therapists during the initial evaluation but could be revised at any time. In our review of the records, ≤5% of the discharge recommendations made from the initial physical therapist or occupational therapist evaluation were changed prior to patient discharge; thus, the discharge recommendation made as part of the initial evaluation was used for the analysis. Finally, only patient records where the physical therapist and occupational therapist made the same discharge recommendation for future services were used for the analysis. Arguably, the need for a specific discharge service has greater credence when both the physical therapist and occupational therapist make the same recommendation. Figure 1 shows a flowchart of all records screened (N=4,613) and how the final sample (n=2,738) was achieved.

Figure 1.
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Figure 1.

Participant records utilized from the Brain Recovery Core database. Of the initial 4,613 patients poststroke who consented to participate, 2,738 participants were included in the analysis. PT=physical therapist, OT=occupational therapist, IRF=inpatient rehabilitation facility, SNF=skilled nursing facility.

Variables Assessed

At the acute care hospital, clinicians completed a standardized initial evaluation on all participants poststroke.10,19 The assessments completed in this evaluation are part of a required standardized battery of tests that encompass the sensorimotor, cognitive, and language domains and that are completed across the continuum of care. The assessments were chosen to meet the needs of each discipline (physical therapy, occupational therapy, and speech-language pathology) and each service (acute, inpatient, outpatient). In addition, assessments had to be clinically useful for the entire spectrum of stroke severities. The following variables along with the construct being assessed from the initial acute care physical therapist and occupational therapist evaluations were: upper and lower extremity Motricity Index scores of the affected limb to assess paresis,20,21 light touch on the palm of the hand and the dorsum of the foot of the affected limb to assess somatosensation,22,23 Berg Balance Scale score to assess static and dynamic balance,24,25 10-m walk speed to assess gait speed for those participants who could walk without hands-on assistance,26–29 Short Blessed Test score to screen for dementia or other cognitive impairment,30 Trail Making Test A and B scores to assess for visual scanning and attention,31,32 Unstructured Mesulam total score to assess neglect,33–35 15-item Boston Naming Test score to screen for aphasia,36–38 and scores for Functional Independence Measure items (gait assist, grooming, lower body dressing, and toileting) to assess assistance required for activities of daily living.28,39–41 In addition, data for other demographic variables that could affect the recommendation for discharge services were collected: age, race, sex, and availability of help at home.

Data Analysis

We used IBM SPSS version 21 (IBM Corporation, Armonk, New York) for all statistical analyses, and the criterion for statistical significance was set at P<.05. The independent variables came from the initial physical therapist or occupational therapist evaluations archived in the Brain Recovery Core clinical database. As with most clinical databases, the majority of variables were present for most participants, but some data were missing. Across the 2,738 participants and 15 variables, 32% (13,230/41,070) of the data were missing. To limit the introduction of selection bias and loss of information and efficiency, multiple imputation was utilized to account for the missing data.42–48 Multiple imputation allows for missing values to be replaced through statistical algorithms that capitalize on the case and group observed values and variability.46,47,49–52 Previous analysis of data from the Brain Recovery Core database53 has shown that clinical data were missing at random (ie, missing values were not systematically different from those without missing values).42,44–46,49,51,54 To account for the uncertainty in missing data, multiple imputation utilized multiple imputed data sets as opposed to a single data set.52 Ten imputations were run, producing 10 imputed data sets of the assessment variables. The decision to run 10 imputations was based on concepts from previous studies suggesting that 10 imputations can provide sufficient efficiency of the estimate.42,44,50,51

The next step was a K-means clustering algorithm run on each of the 10 imputed data sets to examine if participants could be categorized into relatively homogeneous groups based on their initial assessment scores. The K-means method partitioned participants into a cluster if their respective variables (assessment scores) were closest in distance to the center (overall mean) of that particular cluster compared with the other clusters.55 The variables used in the analysis included the impairment- and activity-level assessments listed previously, plus the demographic variables of age, race, sex, and help at home. Because a K-means cluster analysis expects the number of clusters to be specified prior to the analysis, 2-, 3-, 4-, and 5-cluster solutions were explored. Although each solution was statistically feasible, the 4-cluster solution was ultimately chosen to align with clinical constructs (4 discharge recommendations are commonly made).43,55–57 Each analysis assigned participants to a particular cluster and defined that cluster based on the assessment and demographic variables analyzed. Once the K-means cluster analysis was run on each of the 10 imputed data sets, the results were combined. Using the most common cluster assignment (mode) across the 10 imputations, each participant was partitioned into his or her final cluster. In addition, each imputation produced 4 slightly different clusters; therefore, the cluster center for each of the 4 clusters was averaged across all 10 imputations, creating the final cluster centers. Both within-imputation and between-imputation variance also were calculated to help with the interpretation of the analysis.48,50,52

Finally, the results of the cluster analysis (ie, relatively homogeneous groups based on the independent variables) were compared with the therapy discharge recommendations for future rehabilitation services. The percentage of people assigned to each discharge recommendation within each cluster was calculated. Percentages were compared across clusters using a chi-square analysis. We anticipated that the cluster that centered on minimal or no deficits would have a high percentage of participants referred to home with no services. In contrast, the cluster that centered on the more severe deficits across the sensorimotor, cognition, and language domains might have the highest percentage of participants referred to an SNF. Clusters that centered on participants with mild to moderate deficits might have greater percentages of participants recommended to go home with services or to an IRF.

Role of the Funding Source

Funding was provided by the Barnes Jewish Hospital Foundation and the Washington University McDonnell Center for Systems Neuroscience.

Results

Figure 1 presents a flow chart of how the 2,738 participants were identified. Of these, 490 participants (18%) were recommended by both physical therapists and occupational therapists to discharge home without services, 261 (10%) to discharge home with services (home health or outpatient), 1,727 (63%) to discharge to an IRF, and 260 (10%) to discharge to an SNF.

The K-means cluster analysis produced 4 distinct clusters: A, B, C, and D. Table 1 presents the pooled final cluster centers (mean and standard deviation of cluster center for A, B, C, and D across the 10 imputations) and parameter estimates of the imputations. Cluster A contained the youngest participants, with a final cluster center for age of 58 years. Cluster A had those with the least amount of impairment on the standardized assessment battery, with the center defined as affected upper and lower extremity Motricity Index scores of 84 and 86 (out of 100 points), respectively; modified independence or supervision on functional activities; and a negative screen for dementia and neglect. These results are contrasted with cluster D, which contained the oldest patients (final cluster center of 69 years) and had the greatest amount of impairment, with the center defined as affected upper and lower extremity Motricity Index scores of 38 and 42 (out of 100 points), respectively; maximal assist required on functional tasks; and positive screens for severe dementia and neglect. Overall, cluster A was least impaired based on assessment scores, followed by clusters B, C, and D, which was the most impaired. In addition, the greatest proportion of the sample was allocated to cluster A (n=901), followed by cluster B (n=814), cluster C (n=686), and cluster D (n=337).

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Table 1.

K-Means Cluster Analysisa

Assignment of participants to the 4 clusters was compared with the actual discharge recommendations made by the clinicians (home without services, home with services, IRF, or SNF). Figure 2 shows the discharge recommendation percentages across all 4 clusters, expressed as the percentage per cluster (Fig. 2A) and as a percentage of the whole sample (Fig. 2B). In cluster A, 50% of the participants were recommended to go home without services, whereas 1% were recommended to go to skilled nursing. Clusters B, C, and D each had a large proportion of individuals recommended to go to IRF (74%–80%). There was a difference in percentage of recommendations across the clusters (χ2=1334, P<.001) that was largely driven by the differences between cluster A and clusters B, C, and D. The data in Figure 2 indicate that assessment results (severity based on sensorimotor, cognitive, and language deficits) and demographic variables were partially steering discharge recommendations. To check that multiple imputation did not alter the results, the analysis was re-run on the nonimputed data. The resulting clusters and comparison with discharge recommendations were similar.

Figure 2.
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Figure 2.

Recommendation for future rehabilitation services across all 4 clusters. (A) Summary of discharge recommendation as a percentage of each cluster. (B) Summary of discharge recommendation as a percentage of the whole sample. Discharge recommendations include: home without services, home with services, inpatient rehabilitation facility (IRF), or skilled nursing facility (SNF).

Discussion

This study provides new information about the contributions of standardized assessment scores to the postacute discharge rehabilitation service recommendations made by physical therapists and occupational therapists for people poststroke. Through the use of a K-means clustering algorithm, standardized assessment scores from initial evaluation plus demographic variables were used to divide participants into 4 meaningful clusters. These 4 clusters represent different levels of stroke severity characterized by sensorimotor, cognitive, and language deficits. Physical therapist and occupational therapist recommendations for poststroke rehabilitation services were somewhat different across the clusters, suggesting that standardized assessments, in part, are guiding poststroke acute care discharge recommendations for rehabilitation services.

Although recovery poststroke is heterogeneous, multiple studies suggest that general recovery of function can be reasonably predicted in the first few days after stroke.58–64 In the majority of these studies, standardized assessments were the foundation of these prediction rules. The K-means cluster analysis run in this study supports this concept. Table 2 is a clinical representation of the types of participants who were classified in each of the 4 clusters. In this figure, the scores from the mean cluster centers have been transformed into descriptors of a participant in each category. When the participants were characterized by impairments and activity limitations across the sensorimotor, cognitive, and language domains, 4 distinct groups were present. Thus, information from the standardized assessments can quantify participants' deficits into different levels of severity; we expected that discharge recommendations for additional rehabilitation services would largely match this pattern.

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Table 2.

Clinical Representation of Participants in Each of the 4 Clustersa

Discharge recommendations varied somewhat across clusters, but not as much as expected. There were individuals in cluster A who were recommended to go to an IRF and large, similar percentages in clusters B, C, and D, who also were recommended to go to an IRF, despite increasing severity and other factors predictive of poorer outcomes. Several reasons may exist as to why clusters from the standardized assessments do not more uniformly align with discharge recommendations. First, more therapy has been shown to produce better outcomes poststroke.65–67 Of the possible discharge recommendations, an IRF offers the most therapy per day (3 hours). It is possible that clinicians refer the bulk of patients with any amount of impairment or activity limitation to an IRF to foster the greatest opportunity for recovery.68 Second, an IRF may be more often recommended, anticipating that if a patient is discharged home, he or she may not ultimately receive necessary services at a later point in time. For example, when a patient is discharged home with orders for services, it may inherently be harder to obtain those services (eg, calling, scheduling, transportation, availability of an appointment) compared with if the patient was admitted to an IRF. Finally, although the standardized assessments are administered by clinicians, the score value of the assessment and its relationship to predictive models may not be completely understood or utilized by the clinician when making discharge recommendations. In addition, clinicians practicing in the acute care environment do not necessarily see the extent to which their patients improve by the end of their rehabilitation, making it more difficult to see the relationship between assessment at the acute hospital stay and final outcome. Thus, more education about the utility of these measures to the clinicians may be needed.

Study Limitations

Four limitations are important to consider when interpreting these results. The first is that the data came from a clinical database with missing data. The physical therapists and occupational therapists have been trained in the administration of the assessments, were monitored for consistency, and complete annual competencies on the assessments.10 Although the clinicians strive to complete 100% of assessments, it is not always possible to administer all of measures in a prescribed assessment battery in all circumstances in a clinical setting. Use of multiple imputation statistical methods to limit the loss of data and to decrease the introduction of selection bias is continuing to grow in the literature,69–71 although it is still underutilized in rehabilitation studies. Although we saw similar results when run on the nonimputed data, we cannot completely rule out the possibility that the imputation biased our data in some unknown, unpredictable way.

A second limitation is the exclusion of 1,196 participants from the study due to disagreement between physical therapist and occupational therapist discharge recommendations. For 385 participants, physical therapists and occupational therapists did not agree on the discharge location (home, IRF, SNF), and for 811 participants, physical therapists and occupational therapists did not agree on whether the participant should receive services at home. However, each discipline assesses somewhat different domains, so it is not surprising that differences in discharge recommendation exist. For example, a participant with a score of 45 on the Berg Balance Scale and minimal assist to walk may receive the recommendation from the physical therapist to discharge home with services. If this participant has significant cognitive dysfunction, the occupational therapist may recommend an IRF. As the recommendation for future services was the same for the majority of patients, the decision was made to exclude participants where physical therapists and occupational therapists did not agree. Exclusion was done to strengthen the analysis by eliminating some of the variability. In excluding participants, however, bias may have been introduced. This approach explains the higher percentage of overall IRF recommendations (largest group of participants) but does not explain why 74% to 80% of individuals were still recommended to go to IRF across clusters B, C, and D, which have varying levels of deficits.

The third limitation is the selection of 4 clusters as part of the analysis. We selected 4 clusters to match the number of discharge recommendations, although other numbers of clusters also were statistically feasible. It is possible that the true number of clusters could be different from 4. Other acute care hospitals may have different classifications of discharge recommendations (ie, more or less than 4). Our use of 4 clusters might limit the generalizability of these results to facilities using different recommendations.

The final limitation is that the discharge recommendation may have been influenced by factors not included in this analysis. The discharge recommendation is made at the time of the initial evaluation, when the clinician knows the results of his or her own assessment, but may have varying amounts of information about the patient's history and availability of family support. Additional factors such as clinical information from other disciplines, medication, medical needs, or insurance could and should have informed the discharge recommendation. It is unlikely, however, that across the 2,738 participants, these potential confounders would have outweighed the clinician's assessment of impairment or activity limitations so much as to modify or deny needed services.

Future Studies

Rehabilitation poststroke has the potential to save many people from disability,72,73 with the goal of returning people to home and community life with as much independence as possible.65 For patients to receive the maximum benefit from rehabilitation, the clinician must be able to determine additional rehabilitation services that are needed and the best setting for their delivery. As highlighted in a recent study,68 the prediction of discharge destination is a fundamental part of the clinician's role in acute care, and the predicted discharge recommendation is a central driver for all future rehabilitation care and the quality of that care that a patient poststroke receives. Therefore, our study is an important first step in examining how discharge recommendations are made and the types of information clinicians are utilizing to make these decisions. Future studies are needed to examine additional factors that may be contributing to the discharge recommendations made as well as to further probe the utility of the standardized assessments in clinical decision making.

It is also important to determine if the 4 resultant clusters in this analysis could be replicated at other institutions and if similar patterns exist in physical therapist and occupational therapist discharge recommendations. This information would further increase the generalizability of these results. In addition, this study analyzed only the recommendation for future discharge services, not where participants actually went or long-term outcomes. It would be important to compare the recommendation for services and the types of services that the patient actually received.

In conclusion, use of standardized assessment in clinical rehabilitation is continuing to grow and is becoming a mechanism for prediction of patient outcomes. These assessments are quick and efficient and can objectively classify deficits of impairment and activity limitations across the sensorimotor, cognitive, and language domains. These results suggest that standardized assessment scores partially guide poststroke acute care discharge recommendations for additional poststroke rehabilitation services.

Footnotes

  • Dr Bland, Ms Whitson, Dr Connor, Dr Fucetola, Dr Carter, Dr Corbetta, and Dr Lang provided concept/idea/research design. Dr Bland, Dr Connor, Dr Corbetta, and Dr Lang provided writing. Dr Bland, Dr Fucetola, and Dr Lang provided data collection. Dr Bland and Dr Lang provided data analysis. Dr Bland and Dr Connor provided project management. Dr Corbetta and Dr Lang provided fund procurement. Ms Whitson and Ms Harris provided participants. Ms Whitson, Ms Harris, Mr Edmiaston, and Dr Lang provided facilities/equipment. Ms Whitson, Ms Harris, and Dr Connor provided institutional liaisons. Ms Harris, Mr Edmiaston, Dr Connor, Dr Fucetola, and Dr Carter provided consultation (including review of manuscript before submission). The authors thank the staff, administrators, and data entry team at Barnes Jewish Hospital, The Rehabilitation Institute of St Louis, and Washington University for their enthusiasm, support, and efforts on this project.

  • Funding was provided by the Barnes Jewish Hospital Foundation and the Washington University McDonnell Center for Systems Neuroscience.

  • Received August 13, 2014.
  • Accepted November 26, 2014.
  • © 2015 American Physical Therapy Association

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Vol 95 Issue 5 Table of Contents
Physical Therapy: 95 (5)

Issue highlights

  • Does Perturbation-Based Balance Training Prevent Falls?
  • Descriptive Data Analysis Examining Standardized Assessments
  • Predicting 6-Minute Walking Distance in Recipients of Lung Transplantation
  • Intermanual Transfer Effect in Young Children After Training in a Complex Skill
  • Walking Dynamics in Preadolescents With and Without Down Syndrome
  • Construct Validity of the Canadian Occupational Performance Measure
  • Interrater Reliability of AM-PAC “6-Clicks” Short Forms
  • Questionnaire of Patients' Experiences in Postacute Outpatient Physical Therapy Settings
  • Stroke Impact Scale Version 2
  • Staged Approach for Rehabilitation of Shoulder Disorders
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Descriptive Data Analysis Examining How Standardized Assessments Are Used to Guide Post–Acute Discharge Recommendations for Rehabilitation Services After Stroke
Marghuretta D. Bland, Michelle Whitson, Hilary Harris, Jeff Edmiaston, Lisa Tabor Connor, Robert Fucetola, Alexandre Carter, Maurizio Corbetta, Catherine E. Lang
Physical Therapy May 2015, 95 (5) 710-719; DOI: 10.2522/ptj.20140347

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Descriptive Data Analysis Examining How Standardized Assessments Are Used to Guide Post–Acute Discharge Recommendations for Rehabilitation Services After Stroke
Marghuretta D. Bland, Michelle Whitson, Hilary Harris, Jeff Edmiaston, Lisa Tabor Connor, Robert Fucetola, Alexandre Carter, Maurizio Corbetta, Catherine E. Lang
Physical Therapy May 2015, 95 (5) 710-719; DOI: 10.2522/ptj.20140347
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