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Understanding the Effect Of Patient Severity On Aphasia Rehabilitation Outcomes
e126 Main Outcome Measure(s): Whether (or not) lipid lowering medication was prescribed to patients prior to discharge from hospital. Results: Multi-level generalized linear modelling (2-level model, patients clustered in hospitals) identified patients were less likely to be taking lipid lowering medication when discharged from hospital if discharged on a weekend Odds Ratio (OR)Z0.46 (95%CIZ0.28, 0.76), had cognitive deficit ORZ0.57 (95%CIZ0.40, 0.87), female ORZ0.79 (95%CIZ0.58, 1.08), or had experienced a fever during their admission ORZ0.52 (95% CIZ0.26, 1.01). Patients were more likely to be discharged on lipid lowering medications if they received treatment on a specialized stroke unit ORZ1.37 (95%CIZ0.92, 2.01), and if prescribed lipid lowering medications prior to their current admission ORZ9.36, (95%CIZ5.92, 14.82). Approximately 18% (95%CIZ10%, 29%) of variation was attributable to differences between hospitals (rather than individual cases). Conclusion/Discussion: Correlates identified during this investigation may assist those seeking to improve rates of prescription of lipid lowering medications during hospital rehabilitation following ischemic stroke. Key Words: Stroke, Medication, Secondary Prevention, Quality Of Health Care, Implementation Disclosures: None. Research Poster 314870 Understanding the Effect Of Patient Severity On Aphasia Rehabilitation Outcomes Swathi Kiran (Boston University), Jason Godlove, Constant Advani Research Objectives: To understand the influence of patient severity and intensity of practice on aphasia rehabilitation outcomes. Design: Retrospective analysis (2013-2014) of anonymously aggregated data collected for over 4500 patients with post-stroke aphasia. Setting: Patients used a mobile therapy platform, Constant Therapy, downloaded on a tablet and agreed to their data being analyzed for scientific purposes. Participants: 4500 patients with post-stroke aphasia. Interventions: Constant Therapy includes over 60 evidence-based therapies for language and cognitive skills. This program was individualized for each patient with targeted tasks that dynamically adapted to each individual’s progress. Main Outcome Measure(s): Based on an initial baseline assessment, a given task was assigned as long as its performance was below 90% accuracy and average latency. For each patient fitting the cohort, accuracy and latency of the first and last 10 items were compared with t-tests to determine improvement and entered into further ANOVAs. Results: ANOVAs using average gain in accuracy and in latency as the dependent measures and initial performance and intensity of practice across domains of language and cognitive therapy showed a significant interaction effect (F (20, 1724) Z 11.3, p < .001), indicating that more severe patients improved with increased practice (100 - 1000 trials); and patients with initial accuracy less than 50% could achieve mastery (>80% accuracy with practice of 500 trials or more (F (24, 1724) Z 12.4, p < .0001)). Conclusion/Discussion: These results show that both patient severity and amount of therapy influence rehabilitation outcomes, but in positive ways. Patients with lower initial scores showed more improvements (30-50 points gains) than patients with higher initial scores, thus severe patients can achieve success on trained tasks, however, they need a lot of practice. Key Words: Severity, Aphasia Rehabilitation, Intensity Of Practice Disclosures: None. Research Poster 289017 Unplanned Hospital Readmission Rates Across Post-Acute Settings for Stroke Amol Karmarkar (University of Texas Medical Branch), Chih-ying Li, Amit Kumar, Kenneth Ottenbacher, Yong-fang Kuo Research Objectives: Compare hospital readmission rates across inpatient rehabilitation facility (IRF), skilled nursing facility (SNF), and home healthcare (HH) in stroke.
Research Posters Design: Secondary analysis of Medicare data (2012-2014). We linked the Medicare Provider Analysis and Review file with the individual-level assessment data, and the provider of services files. Setting: Acute hospitals and post-acute settings in the United States. Participants: Patients age 66 or older with ischemic/hemorrhagic stroke discharged to IRF, SNF, or HH (nZ75,814). Interventions: None. Main Outcome Measure(s): Using post-acute settings as an outcome, we computed propensity scores, adjusting for patient-level covariates (sociodemographic characteristics, acute length of stay, previous admission status, ischemic/hemorrhagic, Elixhauser comorbidity index, and Hierarchical Condition Category composite score), and hospital-level covariates (profit status, size, urban/rural, IRF as unit). Using propensity scores as the inverse probability of treatment weights (IPTW), we constructed hierarchical generalized linear mixed models for 30-day and 90-day unplanned hospital readmission. We adjusted for unbalanced covariates along with post-acute admission self-care and mobility status. Results: For 30-day readmission, there were no significant differences across the three post-acute settings. For functional status, the risk for 30-day readmission was significantly higher for patients in the ‘low’ category as compared to those in the ‘high’ category, self-care: 1.31 (95% CIZ1.211.41), and mobility: 1.31 (95% CIZ1.21-1.41). The risk for 90-day readmission was lower for HH as compared to IRF 0.91 (95% CIZ0.87-0.96), with no differences between IRF and SNF. Similarly, the risk for 90-day readmission was significantly higher for patients in the ‘low’ self-care and mobility category as compared to those in the ‘high’ category, self-care: 1.29 (95% CIZ1.21-1.36), and mobility: 1.20 (95% CIZ1.14-1.28). Conclusion/Discussion: The 90-day hospital readmission varies across institutional-based and non-institutional-based post-acute settings. The readmission risk is mediated by functional status. Key Words: Post-Acute Care, Functional Status, Unplanned Hospital Readmission Disclosures: None. Research Poster 295537 Unresponsive Wakefulness Syndrome Patient Communicating With Brain-Computer Interface Christoph Guger (g.tec medical engineering GmbH), Brendan Allison, Fan Cao, Alexander Heilinger, Rupert Ortner, Woosang Cho, Joanna Cakala, Krzysztof Malej Research Objectives: To assess an unresponsive wakefulness syndrome (UWS) patient to see if he is able to communicate via a brain-computer interface (BCI) system. Design: The system works with vibro-tactile with 3 tactors, odd-ball paradigms are presented to the patient for 2.5 minutes, and the patient has to actively count either deviant auditory stimuli or deviant vibrotactile stimuli. Setting: The patient has one tactor on the left hand, one tactor on the right hand and one on a neutral midline location. Participants: One unresponsive wakefulness syndrome (UWS) patient. Interventions: The person has to count either the stimuli on the left or right hand to produce a corresponding P300 response. Then, the evoked potentials are analysed statistically and a classification algorithm is applied on the data to provide an objective measure on classification accuracy. Main Outcome Measure(s): The patient will answer basic questions by counting the right-hand stimuli to say YES or counting left-hand stimuli to say NO. Results: In the current study the patient achieved 100 % accuracy in the testing stage. Based on this data, the system was calibrated and 20 questions were asked to the patient, 15 were answered correctly, 1 was wrong and 4 were undetermined. Conclusion/Discussion: The system can assess DOC patients and help us understand if they can do standard cognitive tasks. The classification accuracy is an objective marker to understand whether the patient can follow conversations and even communicate with the environment.
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Research Posters Design: Secondary analysis of Medicare data (2012-2014). We linked the Medicare Provider Analysis and Review file with the individual-level assessment data, and the provider of services files. Setting: Acute hospitals and post-acute settings in the United States. Participants: Patients age 66 or older with ischemic/hemorrhagic stroke discharged to IRF, SNF, or HH (nZ75,814). Interventions: None. Main Outcome Measure(s): Using post-acute settings as an outcome, we computed propensity scores, adjusting for patient-level covariates (sociodemographic characteristics, acute length of stay, previous admission status, ischemic/hemorrhagic, Elixhauser comorbidity index, and Hierarchical Condition Category composite score), and hospital-level covariates (profit status, size, urban/rural, IRF as unit). Using propensity scores as the inverse probability of treatment weights (IPTW), we constructed hierarchical generalized linear mixed models for 30-day and 90-day unplanned hospital readmission. We adjusted for unbalanced covariates along with post-acute admission self-care and mobility status. Results: For 30-day readmission, there were no significant differences across the three post-acute settings. For functional status, the risk for 30-day readmission was significantly higher for patients in the ‘low’ category as compared to those in the ‘high’ category, self-care: 1.31 (95% CIZ1.211.41), and mobility: 1.31 (95% CIZ1.21-1.41). The risk for 90-day readmission was lower for HH as compared to IRF 0.91 (95% CIZ0.87-0.96), with no differences between IRF and SNF. Similarly, the risk for 90-day readmission was significantly higher for patients in the ‘low’ self-care and mobility category as compared to those in the ‘high’ category, self-care: 1.29 (95% CIZ1.21-1.36), and mobility: 1.20 (95% CIZ1.14-1.28). Conclusion/Discussion: The 90-day hospital readmission varies across institutional-based and non-institutional-based post-acute settings. The readmission risk is mediated by functional status. Key Words: Post-Acute Care, Functional Status, Unplanned Hospital Readmission Disclosures: None. Research Poster 295537 Unresponsive Wakefulness Syndrome Patient Communicating With Brain-Computer Interface Christoph Guger (g.tec medical engineering GmbH), Brendan Allison, Fan Cao, Alexander Heilinger, Rupert Ortner, Woosang Cho, Joanna Cakala, Krzysztof Malej Research Objectives: To assess an unresponsive wakefulness syndrome (UWS) patient to see if he is able to communicate via a brain-computer interface (BCI) system. Design: The system works with vibro-tactile with 3 tactors, odd-ball paradigms are presented to the patient for 2.5 minutes, and the patient has to actively count either deviant auditory stimuli or deviant vibrotactile stimuli. Setting: The patient has one tactor on the left hand, one tactor on the right hand and one on a neutral midline location. Participants: One unresponsive wakefulness syndrome (UWS) patient. Interventions: The person has to count either the stimuli on the left or right hand to produce a corresponding P300 response. Then, the evoked potentials are analysed statistically and a classification algorithm is applied on the data to provide an objective measure on classification accuracy. Main Outcome Measure(s): The patient will answer basic questions by counting the right-hand stimuli to say YES or counting left-hand stimuli to say NO. Results: In the current study the patient achieved 100 % accuracy in the testing stage. Based on this data, the system was calibrated and 20 questions were asked to the patient, 15 were answered correctly, 1 was wrong and 4 were undetermined. Conclusion/Discussion: The system can assess DOC patients and help us understand if they can do standard cognitive tasks. The classification accuracy is an objective marker to understand whether the patient can follow conversations and even communicate with the environment.
www.archives-pmr.org