Although it was initially designed to help clinicians understand the mobility independence of a patient before discharge, it may provide incremental value discerning risk of 30-day readmission and/or death. We therefore hypothesized that an I-MOVE score of less than 8 (not being able to transfer from a bed to a chair without assistance) would be a significant predictor of 30-day readmission and/or death.
Methods
Study Design
We performed a retrospective cohort study using a convenience sample including the patients in which the I-MOVE score had been calculated as part of the clinical process of care.
Setting and Participants
Participants were any inpatients discharged from the general medicine unit at Mayo Clinic Rochester from January 2003 to May 2011 who had at least one documented calculation of the I-MOVE score performed as part of the clinical process. Patients in the general medicine unit are adults not requiring subspecialty cardiovascular or neurology, coronary care unit, surgical, psychiatry, or rehabilitation. Patients were excluded if there was missing key outcome information or if they died during the hospitalization. For patients with more than one I-MOVE assessment, only the one closest to discharge was used. Data were abstracted from the electronic medical records between July and August 2011.
Variables
Outcome variables were 30-day readmission, 30-day mortality, and the combined outcome of mortality or readmission. We used the last I-MOVE score as a dichotomous variable with a cut-off of 8, which corresponds to the ability to transfer from bed to a chair unaided, for predicting the 2 outcomes. Only readmissions to the study hospital were captured. Deaths were identified from the electronic medical record. Mayo Clinic patient records are updated monthly with external reports of confirmed, actuarial records of deaths reported from public databases.
To control for possible confounding variables, we included the following covariates: age, gender, race/ethnicity, dates of admission and discharge, insurance (Medicare, Medicaid, self-pay, or private), marital status (currently married/not currently married), length of hospital stay, emergent admission, number of hospital admissions in the last 12 months, number of visits to the emergency department in the last 6 months and Charlson Index. All variables were abstracted from the electronic medical record.
Sample
A search was performed in the electronic medical record to find clinical documents (admission notes, progress notes, and hospital summaries) that mentioned the term “I-MOVE.” Manual review of the records was performed to confirm inclusion criteria.
Statistical Analysis
Separate analyses were performed for the 2 outcomes considered. First, a univariate analysis was performed with all covariates for variable selection. Variables that were significantly predictive with P < 0.1 were included in the multivariate model. Variables included in the first run of the multivariate model were excluded from the final multivariate model if they were not independently significant with P < 0.05. The I-MOVE variable was then added to that model to check its predictive power beyond that of the included covariates.
Results
Patient Characteristics
