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Background: Spontaneous intracerebral hemorrhage (ICH) is associated with a disproportionately high mortality and disability when compared to ischemic stroke. Critically ill patients with ICH represent a specific challenge due to issues of intracranial pressure and hemodynamic instability in the early period post stroke. The aim of this study was to evaluate the effect of a progressive mobility algorithm, a structured tool used to guide mobilization of all patients in the neuroscience critical care unit (NCCU), on the time elapsed to earliest mobility activities in patients with primary ICH.Methods: We used a quasi-experimental design to examine current mobility practices for patients with ICH after rollout of the mobility algorithm in our NCCU. The Johns Hopkins Mobility algorithm was developed by an interdisciplinary mobility team and stratifies NCCU patients to progressive passive or active mobilization programs. Baseline data were collected retrospectively from electronic medical records for two 6 month periods, one before and one after program implementation. Time of first mobilization and frequency of mobilization were reported for baseline and post intervention comparison and adjusted based on patient characteristics.Results: Two groups of ICH patients (pre- rollout, n=28; post-rollout, n=29) were similar on baseline characteristics, with the exception of mean ICH severity scores which were greater in the post-rollout group (p=0.07). Patients in the post-intervention group were significantly more likely to be mobilized within the first 7 days after admission (55% versus 29% in the pre and post intervention groups respectively, p=0.04), No episodes of hypotension, falls or line dislodgements were reported in association with the early mobility intervention.Conclusions: Use of a progressive mobility algorithm in stroke patients with spontaneous ICH increases the percentage of patients who are mobilized in the early critical period without issues of safety. Additional work in larger prospective cohorts is needed to evaluate the reasons for delay of mobilization on day one of hospitalization and to enhance data support for best practice timing recommendations.