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To identify nursing assessments of mobility and activity associated with lower-value rehabilitation services. Retrospective cohort analysis of admissions from December 2016 to September 2019 Medicine, neurology, and surgery units (n=47) at a tertiary hospital. We included patients with a length of stay ≥7 days on units that routinely assessed patient function (n=18,065 patients). Not applicable. We examined the utility of nursing assessments of function to identify patients who received lower-value rehabilitation consults, defined as those who received ≤1 therapy visit. Patient function was assessed using 2 Activity Measure for Post-Acute Care (AM-PAC or "6 clicks") inpatient short forms: (1) basic mobility (eg, bed mobility, walking) and (2) daily activity (eg, grooming, toileting). Using an AM-PAC cutoff value of ≥23 correctly identified 92.5% and 98.7% of lower-value physical therapy and occupational therapy visits, respectively. In our cohort, using a cutoff value of ≥23 on the AM-PAC would have eliminated 3482 (36%) of lower-value physical therapy consults and 4076 (34%) of lower-value occupational therapy consults. Nursing assessment, using AM-PAC scores, can be used to help identify lower-value rehabilitation consults, which can then be reallocated to patients with greater rehabilitation needs. Based on our results, an AM-PAC cutoff value of ≥23 can be used as a guide to help prioritize patients with greater rehabilitation needs. [ABSTRACT FROM AUTHOR]

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The coronavirus disease 2019 (COVID-19) pandemic is having a profound effect on the provision of medical care. As the curve progresses and patients are discharged, the rehabilitation wave brings a high number of postacute COVID-19 patients suffering from physical, mental, and cognitive impairments threatening their return to normal life. The complexity and severity of disease in patients recovering from severe COVID-19 infection require an approach that is implemented as early in the recovery phase as possible, in a concerted and systematic way. To address the rehabilitation wave, we describe a spectrum of interventions that start in the intensive care unit and continue through all the appropriate levels of care. This approach requires organized rehabilitation teams including physical therapists, occupational therapists, speech-language pathologists, rehabilitation psychologists or neuropsychologists, and physiatrists collaborating with acute medical teams. Here, we also discuss administrative factors that influence the provision of care during the COVID-19 pandemic. The services that can be provided are described in detail to allow the reader to understand what services may be appropriate locally. We have been learning and adapting real time during this crisis and hope that sharing our experience facilitates the work of others as the pandemic evolves. It is our goal to help reduce the potentially long-lasting challenges faced by COVID-19 survivors. • Rehabilitation care of coronavirus disease 2019 (COVID-19) recovering patient can be safely provided starting in the intensive care unit. • Redeployment of outpatient therapy workforce was useful to provide rehabilitation to patients recovering from COVID-19 in the acute medical care. • Objective functional assessments allowed for a tailored rehabilitation approach based on the individual patient's needs. • Changes in Medicare regulation allowed for the provision of acute inpatient rehabilitation services outside the rehabilitation unit. COVID-19 patients were able to receive acute comprehensive inpatient rehabilitation level of care while still recovering from the acute infection. [ABSTRACT FROM AUTHOR]

To describe the implementation and evaluation of an interdisciplinary quality improvement (QI) project to increase prescription of take-home naloxone (THN) to reduce risks associated with opioids for patients admitted to an acute inpatient rehabilitation unit. Prospective cohort quality improvement project. Eighteen-bed acute comprehensive inpatient rehabilitation (ACIR) unit at a large academic institution. Patients admitted to ACIR between December 2015-November 2016 (N=788). An interdisciplinary QI model comprised of planning, education, implementation, and maintenance was used to implement a THN and opioid risk-reduction program involving provider and patient education. Analyses consisted of comparisons between baseline, early, and late phases of the project. (1) The proportion of eligible patients who received a prescription for naloxone upon discharge from ACIR; (2) the proportion of patients originally admitted to ACIR on opioids that were weaned off upon discharge. The adjusted odds of eligible patients being discharged from ACIR with a naloxone prescription during the late QI period were 7 (95% confidence interval [CI]: 3-21) times higher than during the early QI period (late QI period: 43%, 95% CI: 25%-63%; early QI period: 10%, 95% CI: 3%-28%; P <.001). For patients admitted on opioids, the adjusted odds of being weaned off opioids during the late QI period were 10 (95% CI: 4-25) times higher than during baseline (late QI period: 29%, 95% CI: 17%-45%; baseline: 4%, 95% CI: 1%-10%; P <.001). Implementation of a THN and opioid risk reduction QI project in an inpatient rehabilitation setting led to significantly more eligible patients receiving naloxone and more patients weaned off schedule II opioids. [ABSTRACT FROM AUTHOR]

• Unnecessary delays in hospital discharge are a problem for patients and hospitals. • Early identification of need for post-acute care might reduce discharge delays. • Mobility is the most important predictor of post-acute care need. • Accuracy of post-acute care prediction is similar across medical conditions. One-fifth of patient discharges from the acute hospital are delayed due to non-medical reasons. Prior research on small specific samples shows that patient mobility is important for predicting post-acute care (PAC) need. Our purpose was to create a disposition prediction model for PAC need in a large, clinically diverse. A random forest (RF) was constructed to analyze patient admissions at 2 hospitals. The primary outcome was discharge disposition (home or PAC). Predictors included the lowest AM-PAC '6-clicks' mobility score within 48-hours of admission (primary predictor) and demographic and clinical characteristics. A global summary tree was constructed to summarize the RF. Among 34,432 patient admissions, the most important variables for predicting PAC placement were AM-PAC, BMI, and age. The AUC was 0.80 (95% confidence interval: 0.79, 0.81). Using a predicted probability for PAC of 0.25 or higher, the sensitivity, specificity and overall accuracy was 76%, 70% and 72%, respectively. Patients 66 years or older with AM-PAC of <31 had the highest probability (0.76) for discharge to PAC. Patients with AM-PAC of >43 had the highest probability for discharge to home. Systematic assessment of inpatients admission mobility should be implemented and used for discharge planning. Electronic medical record systems should be designed to collect and facilitate availability of mobility data on all patients to providers who play key roles in discharge planning. Patient's mobility status during hospitalization has been used to predict their next level of care at discharge, but this work has been done with more limited methods and focused on select patient groups. Using a machine learning technique on thousands of patients with very different medical problems, this study shows that mobility status very early in hospitalization predicts post-acute care (PAC) needs. Based on this study we recommend that early assessment of patient mobility in the hospital should occur for all patients as it can facilitate more effective discharge planning. [ABSTRACT FROM AUTHOR]

Background Hospital-acquired functional decline due to decreased mobility has negative impacts on patient outcomes. Current nurse-directed mobility programs lack a standardized approach to set achievable mobility goals. Purpose We aimed to describe implementation and outcomes from a nurse-directed patient mobility program. Method The quality improvement mobility program on the project unit was compared to a similar control unit providing usual care. The Johns Hopkins Mobility Goal Calculator was created to guide a daily patient mobility goal based on the level of mobility impairment. Findings On the project unit, patient mobility increased from 5.2 to 5.8 on the Johns Hopkins Highest Level of Mobility score, mobility goal attainment went from 54.2% to 64.2%, and patients exceeding the goal went from 23.3% to 33.5%. All results were significantly higher than the control unit. Discussion An individualized, nurse-directed, patient mobility program using daily mobility goals is a successful strategy to improve daily patient mobility in the hospital. [ABSTRACT FROM AUTHOR]

Promoting patient mobility helps improve patient outcomes, but mobility status is not widely tracked nor do patients have specific individualized mobility goals. We evaluated nursing adoption of mobility measures and daily mobility goal achievement using the Johns Hopkins Mobility Goal Calculator (JH-MGC), a tool to guide an individualized patient mobility goal based on the level of mobility capacity. Built on a translating research into practice framework, the Johns Hopkins Activity and Mobility Promotion (JH-AMP) program was the vehicle to promote use of the mobility measures and the JH-MGC. We evaluated a large-scale implementation effort of this program on 23 units across two medical centers. Units significantly improved documentation compliance to mobility measures and achieving daily mobility goals. Units with the highest documentation compliance rates had higher rates of daily mobility goal achievement, especially for longer distance ambulation goals. The JH-AMP program improved adoption of mobility status tracking and higher nursing inpatient mobility levels. • Multi-center implementation of a quality improvement program to promote inpatient mobility • Improvement science framework helps patients achieve individualized daily mobility goals by nurses. • Insights into strategies to infuse mobility promotion into the culture of hospital units [ABSTRACT FROM AUTHOR]

Abstract: Objective: To determine whether functional status on admission to a Comprehensive Integrated Inpatient Rehabilitation Program (CIIRP) is associated with unplanned readmission to acute care. Design: Retrospective cohort study. Setting: Academic hospital-based CIIRP. Participants: Consecutive patients (N=1515) admitted to a CIIRP between January 2009 and June 2012. Interventions: Patients' functional status, the primary exposure variable, was assessed using tertiles of the total FIM score at CIIRP admission, with secondary analyses using the FIM motor and cognitive domains. A propensity score, consisting of 25 relevant clinical and demographic variables, was used to adjust for confounding in the analysis. Main Outcome Measures: Readmission to acute care was categorized as (1) readmission before planned discharge from the CIIRP, (2) readmission within 30 days of discharge from the CIIRP, and (3) total readmissions from both groups, with total readmissions being the a priori primary outcome. Results: Among the 1515 patients, there were 347 total readmissions. Total readmissions were significantly associated with FIM scores, with adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for the lowest and middle FIM tertiles versus the highest tertile (AOR=2.6; 95% CI, 1.9–3.7; P<.001 and AOR=1.7; 95% CI, 1.2–2.4; P=.002, respectively). There were similar findings for secondary analyses of readmission before planned discharge from the CIIRP (AOR=3.5; 95% CI, 2.2–5.8; P<.001 and AOR=2.1; 95% CI, 1.3–3.5l P=.002, respectively), and a weaker association for readmissions after discharge from the CIIRP (AOR=1.6; 95% CI, 1.0–2.4; P=.047 and AOR=1.3; 95% CI, 0.8–1.9; P=.28, respectively). The FIM motor domain score was more strongly associated with readmissions than the FIM cognitive score. Conclusions: Functional status on admission to the CIIRP is strongly associated with readmission to acute care, particularly for motor aspects of functional status and readmission before planned discharge from the CIIRP. Efforts to reduce hospital readmissions should consider patient functional status as an important and potentially modifiable risk factor. [Copyright &y& Elsevier]

Objective To assess the feasibility of using an infrared-based Real-Time Location System (RTLS) for measuring patient ambulation in a 2-minute walk test (2MWT) by comparing the distance walked and the Johns Hopkins Highest Level of Mobility (JH-HLM) score to clinician observation as a criterion standard. Design Criterion standard validation study. Setting Inpatient, university hospital. Participants Patients (N=25) in an adult neuroscience/brain rescue unit. Interventions Not applicable. Main Outcome Measures RTLS and clinician-reported ambulation distance in feet, and JH-HLM score on an 8-point ordinal scale. Results The RTLS ambulation distance for the 25 patients in the 2MWT was between 68 and 516ft. The mean difference between clinician-reported and RTLS ambulation distance was 8.4±11.7ft (2.7%±4.6%). The correlation between clinician-reported and RTLS ambulation distance was 97.9% ( P <.01). The clinician-reported ambulation distance for 2 patients was +100ft and −99ft compared with the RTLS distance, implying clinician error in counting the number of laps (98ft). The correlation between the RTLS distance and clinician-reported distance excluding these 2 patients is 99.8% ( P <.01). The accuracy of the RTLS for assessment of JH-HLM score for all 25 patients was 96%. The average patient speed obtained from RTLS data varied between 0.4 and 3.0mph. Conclusions The RTLS is able to accurately measure patient ambulation and calculate JH-HLM for a 2MWT when compared with clinician observation as the criterion standard. [ABSTRACT FROM AUTHOR]

Use patient demographic and clinical characteristics at admission and time-varying in-hospital measures of patient mobility to predict patient post-acute care (PAC) discharge. Retrospective cohort analysis of electronic medical records. Patients admitted to the two participating Hospitals from November 2016 through December 2019 with ≥72 hours in a general medicine service. Discharge location (PAC vs home) was the primary outcome, and 2 time-varying measures of patient mobility, Activity Measure for Post-Acute Care (AM-PAC) Mobility "6-clicks" and Johns Hopkins Highest Level of Mobility, were the primary predictors. Other predictors included demographic and clinical characteristics. For each day of hospitalization, we predicted discharge to PAC using the demographic and clinical characteristics and most recent mobility data within a random forest (RF) for survival, longitudinal, and multivariate (RF-SLAM) data. A regression tree for the daily predicted probabilities of discharge to PAC was constructed to represent a global summary of the RF. There were 23,090 total patients and compared to PAC, those discharged home were younger (64 vs 71), had shorter length of stay (5 vs 8 days), higher AM-PAC at admission (43 vs 32), and average AM-PAC throughout hospitalization (45 vs 35). AM-PAC was the most important predictor, followed by age, and whether the patient lives alone. The area under the hospital day–specific receiver operating characteristic curve ranged from 0.76 to 0.79 during the first 5 days. The global summary tree explained 75% of the variation in predicted probabilities for PAC from the RF. Sensitivity (75%), specificity (70%), and accuracy (72%) were maximized at a PAC probability threshold of 40%. Daily assessment of patient mobility should be part of routine practice to help inform care planning by hospital teams. Our prediction model could be used as a valuable tool by multidisciplinary teams in the discharge planning process. [ABSTRACT FROM AUTHOR]