"Although we examined multiple predictor variables and stroke-related comorbid conditions that were previously thought to be predictive," explains Dr. Brown, "the strongest predictors of functional independence measure score and living setting at three months were those same factors at rehabilitation discharge."

Dr. Brown emphasizes that these findings also suggest that functional gains made during rehabilitation hospitalization that enable independent living are sustainable and may even improve with time.

"Our data show that the proportion of patients living at home increased over the follow-up period, from 82% at rehabilitation discharge to 92% at three months after discharge," says Dr. Brown. "This change indicates that functional recovery can continue after discharge, and that even patients with significant impairment are able to return home after receiving additional rehabilitation services."

The study also validated a number of what Dr. Brown calls intuitive findings indicating that data acquired at the point in time closest to the outcome of interest are better predictors of that outcome. "We confirmed that data collected at rehabilitation discharge are better predictors than those collected at admission, and that the patients who are most impaired and functionally limited at discharge are those most likely to need a skilled level of care at three months after discharge," explains Dr. Brown.

Overall, Dr. Brown and colleagues are hopeful that these data can inform clinicians, patients with stroke and their families about what to expect in the months after hospital discharge. They also acknowledge that their study has limitations. Although functional independence at rehabilitation discharge and discharge location were the strongest outcome predictors at three months when compared with other variables shown to be predictive in previous reports, the strength of this prediction was modest. This suggests that other factors may influence post-acute outcomes.

"Looking ahead, including educational status, socioeconomic factors and brain imaging may improve future efforts to refine predictive modeling," explains Dr. Brown.