I-MOVE: Inpatient Pre-Discharge Mobility Score As a Predictor of Post-Discharge Mortality

From the Mayo Clinic Center for Innovation (Dr. Romero-Brufau) Department of Medicine (Drs. Manning, Borrud, Keller, Kashiwagi, Huddleston, and Croghan) Department of Health Sciences Research (Mr. Cha), Mayo Clinic, Rochester, MN.

Abstract

• Objective: To determine whether a score of 8 or greater on the I-MOVE, a bedside instrument that evaluates the need for assistance in turning, sitting, standing, transferring from bed to a chair, and ambulating, predicts lower risk for 30-day readmission or mortality.
• Design: Retrospective cohort study of patients discharged from 2003 to 2011 from a referral hospital in Southeastern Minnesota. We used a convenience sample of 426 inpatients who had at least one documented calculation of the I-MOVE score performed as part of the clinical process during the study.
• Results: Overall 30-day mortality rate, readmission rate, and rate of the combined death/readmission outcome were 6.1% (26 patients), 15% (64 patients) and 19.7% (84 patients), respectively. After controlling for confounding variables, an I-MOVE score ≥ 8 was a significant predictive factor for 30-day mortality (OR = 0.136, P < 0.01) but not 30-day readmission (OR = 1.143, P = 0.62) or the combined outcome death/readmission (OR = 0.682, P = 0.13).
• Conclusion: The clinical information provided by a patient's I-MOVE score before discharge does not provide information about readmission risk but may offer incremental information about 30-day mortality risk.

Risk factors for hospital 30-day readmission have been studied by Hasan et al [1], van Walraven et al [2], Allaudeen et al [3], and more recently, Donze et al [4]. Risk factors found to be associated with readmission include race, length of stay, and number of hospitalizations in the last 12 months. Additionally, patients identified “feeling unprepared for discharge” and “difficulty performing activities of daily living” as top issues contributing to readmission. The Affordable Care Act established the Value-Based Purchasing (VBP) model for defined hospital illnesses such as acute myocardial infarction, heart failure, and community acquired pneumonia. This has focused more attention on post-discharge 30-day mortality and readmissions as publicly reported metrics that in part determine the Centers for Medicare and Medicaid Services care reimbursement rates [5].

In our hospital, over 400 inpatients have been evaluated since 2004 using the I-MOVE scoring system in the course of their usual care. I-MOVE was most commonly employed by geriatricians in the division of hospital internal medicine, who collectively endorsed the tool in their practice meetings, especially for elderly patients returning to home alone whose mobility independence was uncertain.

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.