Post-stroke inpatient rehabilitation .2. Predicting discharge disposition

被引:41
|
作者
Brosseau, L
Potvin, L
Philippe, P
Boulanger, YL
机构
[1] UNIV MONTREAL, FAC MED, DEPT SOCIAL & PREVENT MED, MONTREAL, PQ H3C 3J7, CANADA
[2] UNIV MONTREAL, FAC MED, DEPT MED, MONTREAL, PQ H3C 3J7, CANADA
关键词
activities of daily living; disability; destination; hemiplegia; outcome and process assessment; predictive validity; rehabilitation; self-care;
D O I
10.1097/00002060-199611000-00006
中图分类号
R49 [康复医学];
学科分类号
100215 ;
摘要
This study was undertaken to identify indicators that predict discharge disposition after an acute stroke rehabilitation program. A cohort of 152 incident cases suffering from stroke (76 women and 76 men) voluntarily participated in this study. They were recruited from a general hospital in which they were participating in a rehabilitation program. Post-stroke biologic, sociodemographic, and psychosocial characteristics were considered in our analyses. A polychotomous nominal logistic regression analysis was used to predict inpatient rehabilitation discharge disposition. The three discharge disposition categories were (1) private home, (2) rehabilitation center, and (3) long-term care facility. Significant predictors related to the discharge toward a rehabilitation center were functional status at admission, presence of social support, and gait status. Significant predictors for discharge to a long-term care facility were functional status at admission, presence of social support, gait status, and presence of medical complications. Functional status measured on rehabilitation admission should be considered, in conjunction with the patient's social support, gait status, and presence of medical complications, to be predictive of post-stroke rehabilitation discharge disposition.
引用
收藏
页码:431 / 436
页数:6
相关论文
共 50 条
  • [1] Patient and Facility Characteristics Associated with Discharge to Inpatient Rehabilitation Post-stroke
    Williams, Linda S.
    Arling, Greg
    Li, Xinli
    Chumbler, Neale
    Schmid, Arlene
    Ordin, Diana
    Bravata, Dawn
    STROKE, 2011, 42 (03) : E337 - E337
  • [2] Post-stroke inpatient rehabilitation .1. Predicting length of stay
    Brosseau, L
    Philippe, P
    Potvin, L
    Boulanger, YL
    AMERICAN JOURNAL OF PHYSICAL MEDICINE & REHABILITATION, 1996, 75 (06) : 422 - 430
  • [3] Post-stroke rehabilitation Factors predicting discharge to acute versus subacute rehabilitation facilities
    Rakesh, Neal
    Boiarsky, Daniel
    Athar, Ammar
    Hinds, Shaliesha
    Stein, Joel
    MEDICINE, 2019, 98 (22)
  • [4] Disposition Disparities: Differences in Discharge and Rehabilitation Post-Stroke Between Racial and Ethnic Groups
    Romano, Madison
    Dombroski, Allison
    de Segonzac, Beatriz Dunoyer
    Weiss, Kayla
    Sturn, Michael
    Coughlin, Emily
    Burgin, William S.
    STROKE, 2024, 55
  • [5] Predicting Post-stroke Hospital Discharge Disposition Using Interpretable Machine Learning Approaches
    Cho, Jin
    Alharin, Alnour
    Hu, Zhen
    Fell, Nancy
    Sartipi, Mina
    2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2019, : 4817 - 4822
  • [6] Post-Stroke Lateropulsion: Resolution and Function After Discharge From Inpatient Rehabilitation - A Cohort Study
    Nolan, Jessica
    Godecke, Erin
    Spilsbury, Katrina
    Singer, Barbara
    PHYSIOTHERAPY CANADA, 2023, 75 (03) : 264 - 268
  • [7] Post-stroke Discharge Disposition Prediction using Deep Learning
    Cho, Jin
    Hu, Zhen
    Sartipi, Mina
    SOUTHEASTCON 2017, 2017,
  • [8] Post-stroke depression: Improving the efficiency of screening on an inpatient stroke rehabilitation unit
    de Hartog, A.
    Mertens, V
    STROKE, 2012, 43 (11) : E136 - E136
  • [9] FIM score, FIM efficiency, and discharge disposition following inpatient stroke rehabilitation
    Bottemiller, KL
    Bieber, PL
    Basford, JR
    Harris, M
    REHABILITATION NURSING, 2006, 31 (01) : 22 - 25
  • [10] POST-STROKE REHABILITATION
    BULLOCK, EA
    ROYAL SOCIETY OF HEALTH JOURNAL, 1975, 95 (06): : 284 - 286