Abstract-Monitoring of posture change in sagittal plane and walking speed is important for evaluate the effectiveness of rehabilitation program or brace. We have developed a wearable device for monitoring human activity. However, in the previous system, there still remain several drawbacks for practical use such as accuracy in angle measurement, cumbersome cable arrangements, and so on. In order to improve these practical drawbacks, a new sensor system was designed, and its availability was evaluated. The results demonstrated that the accuracy of this system showed superior to that of the previous, and this system appears to be a significant means for quantitative assessment of the patient's motion.

Background and purposeThe effects of therapy and patient characteristics on rehabilitation outcomes in patients with acute stroke are unclear. We investigated the effects of intensive occupational therapy (OT) on patients with acute stroke.MethodsWe performed a retrospective cohort study using the 2005–2016 Japan Rehabilitation Database, from which we identified patients with stroke (n = 10,270) who were admitted to acute care hospitals (n = 37). We defined active OT (AOT) and non-AOT as OT intervention times (total intervention time/length of hospital stay) longer or shorter than the daily physical therapy intervention time, respectively. The outcomes assessed were the Functional Independence Measure (FIM) and National Institutes of Health Stroke Scale (NIHSS) scores, duration of hospitalization, and rate of discharge. Propensity scores and inverse probability of treatment weighting analyses adjusted for patient characteristics were performed to investigate the effects of AOT on patient outcomes.ResultsWe enrolled 3,501 patients (1,938 and 1,563 patients in the AOT and non-AOT groups, respectively) in the study. After inverse probability of treatment weighting, the AOT group had a shorter length of hospitalization (95% confidence interval: −3.7, −1.3, p < 0.001), and the FIM (95% confidence interval: 2.0, 5.7, p < 0.001) and NIHSS (95% confidence interval; 0.3, 1.1, p < 0.001) scores improved significantly. Subgroup analysis showed that lower NHISS scores for aphasia, gaze, and neglect and lower overall NIHSS and FIM scores on admission led to a greater increase in FIM scores in the AOT group.ConclusionsAOT improved the limitations in performing activities of daily living (ADL) and physical function in patients with acute stroke and reduced the length of hospitalization. Additionally, subgroup analysis suggested that the increase in FIM score was greater in patients with severe limitations in performing ADLs and worse cognitive impairment, such as neglect, on admission.

Objectives: This study examined the association between intensive rehabilitation for subacute stroke patients and medical costs and readmission ratio during the year after discharge. Design: This was a natural experiment study. Setting and Participants: We identified individuals with a diagnosis of cerebrovascular disorder (ICD-10: I60-I69 cerebrovascular disease) in an insurance claims database in Japan from January 2005 to December 2017. From the database, 980 patients who were admitted to a convalescent rehabilitation unit with stroke were identified. After excluding 575 patients, 405 were eligible for the study. Methods: In Japan, from April 2011, a new policy was established that allows special costs to be added as rehabilitation time increases. This policy provides an additional medical fee for inpatients in a convalescent rehabilitation unit who receive more than 120 minutes of rehabilitation therapy. We defined high-intensity rehabilitation as transfer from hospitalization to a convalescent rehabilitation unit after April 2011. Outcomes were total direct medical costs and readmission ratio during the year after discharge from the convalescent rehabilitation unit. Results: Daily rehabilitation time, total rehabilitation time, and total medical costs of the high-intensity rehabilitation group were significantly higher than those of the low-intensity rehabilitation group (P < .001, P < .001, P ¼ .011, respectively). However, there was no significant difference in the medical costs during the year after discharge (P ¼ .653) or in the readmission ratio (hazard ratio: 1.09, 95% confidence interval: 0.55-2.18, P ¼ .804). Conclusions and Implications: Intensive rehabilitation did not reduce medical costs or the readmission ratio during the first year after discharge. Future studies should consider the necessary rehabilitation intensity given the severity of the patient's condition, using large sample sizes.

Background/Objective The purpose of this study is to develop and validate an instrument to assess interprofessional collaboration by occupational therapists, physical therapists, and speech-language therapists. Methods Item development consisted of a review of interprofessional collaboration and group interviews with occupational therapists, physical therapists, and speech-language therapists. The developed items were surveyed on a 4-point Likert scale among occupational therapists, physical therapists, and speech-language therapists. Ceiling effects, floor effects, and item-total correlation analysis for each item, as well as constructs, internal consistency, and cross-cultural validity of the scales were evaluated. Results A total of 47 items were extracted for evaluation and 28 items with five factors (“team-oriented behavior,” “exchange of opinions,” “flexible response,” “sharing the whole picture of the patient,” and “coordination of support methods”) were retained after the evaluation. The correlation coefficients of the five factors ranged from 0.48 to 0.72. The total score of each factor and the total score of all 28 items were compared for occupational therapists, physical therapists, and speech-language therapists, and the result showed that was no statistically significant difference between the total scores of all factors and the job titles. The Cronbach’s alpha coefficients for the five factors are 0.842, 0.840, 0.805, 0.732, and 0.734 for the first, second, third, fourth, and fifth factors, respectively. Conclusions The developed scale includes items aimed at facilitating patients' activities of daily living through interprofessional collaboration, and its content reflects the expertise of occupational therapists, physical therapists, and speech-language therapists.

Background: Previous prediction models have predicted a single outcome (e.g. gait) from several patient characteristics at one point (e.g. on admission). However, in clinical practice, it is important to predict an overall patient characteristic by incorporating multiple outcomes. This study aimed to develop a prediction model of overall patient characteristics in acute stroke patients using latent class analysis. Methods: This retrospective observational study analyzed stroke patients admitted to acute care hospitals (37 hospitals, N=10,270) between January 2005 and March 2016 from the Japan Association of Rehabilitation Database. Overall, 6,881 patients were classified into latent classes based on their outcomes. The prediction model was developed based on patient characteristics and functional ability at admission. We selected the following outcome variables at discharge for classification using latent class analysis: Functional Independence Measure (functional abilities and cognitive functions), subscales of the National Institutes of Health Stroke Scale (upper extremity function), length of hospital stay, and discharge destination. The predictor variables were age, Functional Independence Measure (functional abilities and comprehension), subscales of the National Institutes of Health Stroke Scale (upper extremity function), stroke type, and amount of rehabilitation (physical, occupational, and speech therapies) per day during hospitalization. Results: Patients (N=6,881) were classified into nine classes based on latent class analysis regarding patient characteristics at discharge (class size: 429%). Class 1 was the mildest (shorter stay and highest possibilities of home discharge), and Class 2 was the most severe (longer stay and the highest possibility of transfers inckuding deaths). Different gradations characterized Classes 39; these patient characteristics were clinically acceptable. Predictor variables at admission that predicted class membership were significant (odds ratio: 0.0107.9, P<.001). Conclusions: Based on these findings, the model developed in this study could predict an overall patient characteristic combining multiple outcomes, including the appropriate rehabilitation intensity. In actual clinical practice, internal and external validation is required.