Exploring the relationship between AM-PAC scores and mobility components in falls and pressure injury risk assessment tools: A pathway to improve nursing clinical efficiency.

BACKGROUND: Nurses routinely perform multiple risk assessments related to patient mobility in the hospital. Use of a single mobility assessment for multiple risk assessment tools could improve clinical documentation efficiency, accuracy and lay the groundwork for automated risk evaluation tools. PURPOSE: We tested how accurately Activity Measure for Post-Acute Care (AM-PAC) mobility scores predicted the mobility components of various fall and pressure injury risk assessment tools. METHOD: AM-PAC scores along with mobility and physical activity components on risk assessments (Braden Scale, Get Up and Go used within the Hendrich II Fall Risk Model®, Johns Hopkins Fall Risk Assessment Tool (JHFRAT) and Morse Fall Scale) were collected on a cohort of hospitalised patients. We predicted scores of risk assessments based on AM-PAC scores by fitting of ordinal logistic regressions between AM-PAC scores and risk assessments. STROBE checklist was used to report the present study. FINDINGS: AM-PAC scores predicted the observed mobility components of Braden, Get Up and Go and JHFRAT with high accuracy (≥85%), but with lower accuracy for the Morse Fall Scale (40%). DISCUSSION: These findings suggest that a single mobility assessment has the potential to be a good solution for the mobility components of several fall and pressure injury risk assessments.

Using Nursing Assessments of Mobility and Activity to Prioritize Patients Most Likely to Need Rehabilitation Services.

OBJECTIVE: To identify nursing assessments of mobility and activity associated with lower-value rehabilitation services. DESIGN: Retrospective cohort analysis of admissions from December 2016 to September 2019 SETTING: Medicine, neurology, and surgery units (n=47) at a tertiary hospital. PARTICIPANTS: We included patients with a length of stay ≥7 days on units that routinely assessed patient function (n=18,065 patients). INTERVENTIONS: Not applicable. MAIN OUTCOME: 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. MEASURES: 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). RESULTS: 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. CONCLUSIONS: 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.

A unit-based, multi-center evaluation of adopting mobility measures and daily mobility goals in the hospital setting.

BACKGROUND: Promoting patient mobility helps improve patient outcomes, but mobility status is not widely tracked nor do patients have specific individualized mobility goals. PURPOSE: 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. METHOD: 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. FINDINGS: 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. DISCUSSION: The JH-AMP program improved adoption of mobility status tracking and higher nursing inpatient mobility levels.

The Johns Hopkins Activity and Mobility Promotion Program: A Framework to Increase Activity and Mobility Among Hospitalized Patients.

BACKGROUND: Greater mobility and activity among hospitalized patients has been linked to key outcomes, including decreased length of stay, increased odds of home discharge, and fewer hospital-acquired morbidities. Systematic approaches to increasing patient mobility and activity are needed to improve patient outcomes during and following hospitalization. PROBLEM: While studies have found the Johns Hopkins Activity and Mobility Promotion (JH-AMP) program improves patient mobility and associated outcomes, program details and implementation methods are not published. APPROACH: JH-AMP is a systematic approach that includes 8 steps, described in this article: (1) organizational prioritization; (2) systematic measurement and daily mobility goal; (3) barrier mitigation; (4) local interdisciplinary roles; (5) sustainable education and training; (6) workflow integration; (7) data feedback; and (8) promotion and awareness. CONCLUSIONS: Hospitals and health care systems can use this information to guide implementation of JH-AMP at their institutions.

Identifying Cognitive Impairment in the Acute Care Hospital Setting: Finding an Appropriate Screening Tool.

IMPORTANCE: Identifying cognitive impairment in adults in acute care is essential so that providers can address functional deficits and plan for safe discharge. Occupational therapy practitioners play an essential role in screening for, evaluating, and treating cognitive impairment. OBJECTIVE: To test and compare the psychometrics and feasibility of three cognitive screens and select the ideal screen for use in acute care. DESIGN: Prospective mixed methods. SETTING: Acute care hospital. PARTICIPANTS: Fifty adults. OUTCOMES AND MEASURES: We examined the interrater reliability, administration time, and usability of the Brief Cognitive Assessment Tool Short Form (BCAT-SF), the Activity Measure for Post-Acute Care "6-Clicks" Applied Cognitive Inpatient Short Form (AM-PAC ACISF), and the Montreal Cognitive Assessment (MoCA). We compared the construct validity, sensitivity, and specificity of the BCAT-SF and AM-PAC ACISF with those of the MoCA. RESULTS: Interrater reliability was good to excellent; ICCs were .98 for the MoCA, .97 for the BCAT-SF, and .86 for the AM-PAC ACISF. The BCAT-SF and the AM-PAC ACISF both had 100% sensitivity, and specificity was 74% for the BCAT-SF and 98% for the AM-PAC ACISF. The optimal cutoff score for cognitive impairment on the AM-PAC ACISF was <22. Administration time of the AM-PAC ACISF (1.0 min) was significantly less than that of the BCAT-SF (5.0 min) and the MoCA (13.3 min; p < .001). CONCLUSIONS AND RELEVANCE: Each screen demonstrated acceptable reliability and construct validity. The AM-PAC ACISF had the optimum mix of performance and feasibility for the fast-paced acute care setting. What This Article Adds: Early identification of cognitive impairment using the AM-PAC ACISF can allow for timely occupational therapy intervention in acute care settings.

An interprofessional examination of the Johns Hopkins Mobility Goal Calculator among hospitalized postsurgical patients.

Individualized mobility goals created using a goal calculator have been shown to increase patient mobility on medical nursing units, but have not been studied among postoperative populations. This study aimed to examine the feasibility of an automated mobility goal calculator on a postoperative nursing unit. To examine this, we used the goal calculator to create goals for patients (N = 128) following surgery and mobilized each patient with either a nurse or physical therapist. Each patient's highest level of mobility was recorded and providers completed surveys on the appropriateness of calculated goals. Overall, 94% of patients achieved calculated goals. Patients with more pain achieved goals significantly less often than those with less pain. Those with higher mobility achieved their goals similarly with either provider. Providers reported 47% of goals were appropriate, with goals being set too low as the primary reason for goals being inappropriate. We conclude that the automated goal calculator can be used on postoperative nursing units to set realistic goals for patients after surgery.

Psychometric Testing of the Activity Measure for Post-Acute Care (AM-PAC) in the Pediatric Acute Care Setting.

PURPOSE: To determine interrater reliability and construct validity of the Activity Measure for Post-Acute Care (AM-PAC) Inpatient "6-clicks" Short Forms for children in acute care. METHODS: Eight physical therapists (PTs) scored the AM-PAC Basic Mobility, 30-second walk test (30SWT), and Timed Up and Go (TUG) for 54 patients (4-17 years); 6 occupational therapists (OTs) scored the AM-PAC Daily Activity and handgrip dynamometry for 50 patients (5-17 years). Correlations between the AM-PAC Basic Mobility, 30SWT, and TUG and between the Daily Activity AM-PAC and handgrip dynamometry were calculated for evidence of construct validity. RESULTS: Interrater reliability for the AM-PAC was excellent for PTs and OTs. Validity was strong to moderate for Basic Mobility when compared with the 30SWT and TUG. Daily Activity had weak correlation with mean left handgrip strength and no correlation with mean right handgrip strength. CONCLUSIONS: AM-PAC Short Forms have acceptable psychometrics for use among children in acute care.

Perceived Barriers to Mobility in a Medical ICU: The Patient Mobilization Attitudes & Beliefs Survey for the ICU.

PURPOSE: Early mobilization in the intensive care unit (ICU) can improve patient outcomes but has perceived barriers to implementation. As part of an ongoing structured quality improvement project to increase mobilization of medical ICU patients by nurses and clinical technicians, we adapted the existing, validated Patient Mobilization Attitudes & Beliefs Survey (PMABS) for the ICU setting and evaluated its performance characteristics and results. MATERIALS AND METHODS: The 26-item PMABS adapted for the ICU (PMABS-ICU) was administered as an online survey to 163 nurses, clinical technicians, respiratory therapists, attending and fellow physicians, nurse practitioners, and physician assistants in one medical ICU. We evaluated the overall and subscale (knowledge, attitude, and behavior) scores and compared these scores by respondent characteristics (clinical role and years of work experience). RESULTS: The survey response rate was 96% (155/163). The survey demonstrated acceptable discriminant validity and acceptable internal consistency for the overall scale (Cronbach α: 0.82, 95% confidence interval: 0.76-0.85), with weaker internal consistency for all subscales (Cronbach α: 0.62-0.69). Across all respondent groups, the overall barrier score (range: 1-100) was relatively low, with attending physicians perceiving the lowest barriers (median [interquartile range]: 30 [28-34]) and nurses perceiving the highest (37 [31-40]). Within the first 10 years of work experience, greater experience was associated with a lower overall barrier score (-0.8 for each additional year; P = 0.02). CONCLUSIONS: In our medical ICU, across 6 different clinical roles, there were relatively low perceived barriers to patient mobility, with greater work experience over the first 10 years being associated with lower perceived barriers. As part of a structured quality improvement project, the PMABS-ICU may be valuable in assisting to identify specific perceived barriers for consideration in designing mobility interventions for the ICU setting.

Managing the Rehabilitation Wave: Rehabilitation Services for COVID-19 Survivors.

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.

Association between ambulatory status and call bell use in hospitalized patients-A retrospective cohort study.

AIM: Characterize the relationship between patient ambulatory status and in-hospital call bell use. BACKGROUND: Although call bells are frequently used by patients to request help, the relationship between physical functioning and call bell use has not been evaluated. METHODS: Retrospective cohort study of 944 neuroscience patients hospitalized in a large academic urban medical centre between April 1, 2014 and August 1, 2014. We conducted multiple linear regression analyses with number of daily call bells from each patient as the primary outcome and patients' average ambulation status as the primary exposure variable. RESULTS: The mean number of daily call bell requests for all patients was 6.9 (6.1), for ambulatory patients 5.6 (4.8), and for non-ambulatory patients, it was 7.7 (6.6). Compared with non-ambulatory patients, ambulatory patients had a mean reduction in call bell use by 1.7 (95% CI 2.5 to -0.93, p < .001) calls per day. In a post hoc analysis, patients who could walk >250 feet had 5 fewer daily call bells than patients who were able to perform in-bed mobility. CONCLUSION: Ambulatory patients use their call bells less frequently than non-ambulatory patients. IMPLICATIONS FOR NURSING MANAGEMENT: Frequent use of call bells by non-ambulatory patients can place additional demands on nursing staff; patient mobility status should be considered in nurse workload/patient assignment.

Implementing an Opioid Risk Reduction Program in the Acute Comprehensive Inpatient Rehabilitation Setting.

OBJECTIVE: 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. DESIGN: Prospective cohort quality improvement project. SETTING: Eighteen-bed acute comprehensive inpatient rehabilitation (ACIR) unit at a large academic institution. PARTICIPANTS: Patients admitted to ACIR between December 2015-November 2016 (N=788). INTERVENTIONS: 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. MAIN OUTCOME MEASURES: (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. RESULTS: 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). CONCLUSIONS: 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.

Towards improving hospital workflows: An evaluation of resources to mobilize patients.

AIM: To characterize resources to safely mobilize different types of hospitalized patients. BACKGROUND: Current approaches to determine nurse-patient ratios do not always include information regarding the specific demands of patients who require extra resources to mobilize. Workflows must be designed with knowledge of resource requirements to integrate patient mobility into the daily nursing team care plan. METHODS: Nurse-led mobility sessions were evaluated on two adult hospital units, which consisted of nurse-patient encounters focused on patient mobility only. The resources assessed for each session were time-to-mobilize patient, time-to-document, need for additional staff support, and the need for assistive devices. Mobility sessions were also categorized by patient ambulation status, level of mobility limitations (low, medium and high) and diagnosis. RESULTS: In 212 total mobility sessions, the median time-to-mobilize and time-to-document were 7.75 and 1.27 min, respectively. Additional staff support was required for 87% and 92% of patients with medium and high mobility limitations, respectively. All patients with low mobility limitations ambulated, and only 14% required additional staff. Ambulating patients with high mobility limitations was the most time-intensive (median 12.55 min). Ambulating stroke patients required one additional staff and an assistive device in 92% and 69% of the sessions, respectively. CONCLUSION: This study describes the resources associated with mobilizing inpatients with different levels of mobility impairments and diagnoses. IMPLICATIONS FOR NURSING MANAGEMENT: These results could assist nursing management with facilitating appropriate daily nurse-patient ratios and justify the need for assistive devices and staff support to safely mobilize patients.

Improving Outcomes After Hospitalization: A Prospective Observational Multicenter Evaluation of Care Coordination Strategies for Reducing 30-Day Readmissions to Maryland Hospitals.

BACKGROUND: Patients frequently experience suboptimal transitions from the hospital to the community, which can increase the likelihood of readmission. It is not known which care coordination services can lead to improvements in readmission rates. OBJECTIVE: To evaluate the effects of two care coordination interventions on 30-day readmission rates. DESIGN: Prospective multicenter observational study of hospitalized patients eligible for two care coordination services between January 1, 2013, and October 31, 2015. Readmission rates were compared for patients who received each care coordination intervention versus those who did not using multivariable generalized estimating equation logistic regression models. PARTICIPANTS: A total of 25,628 patients hospitalized in medicine, neurosciences, or surgical sciences units. INTERVENTIONS: Patients discharged home and deemed to be at high risk for readmission were assigned a nurse Transition Guide (TG) for 30 days post-discharge. All other patients were assigned the Patient Access Line (PAL) intervention, which provided a post-discharge phone call from a registered nurse. SETTING: Two large academic hospitals in Baltimore, MD. MAIN MEASURES: Thirty-day all-cause readmission to any Maryland hospital. KEY RESULTS: Among all patients, 14.2% (2409/16,993) of those referred for the PAL intervention and 22.8% (1973/8635) of those referred for the TG intervention were readmitted. PAL-referred patients who did not receive the intervention had an adjusted odds ratio (aOR) for readmission of 1.27 (95% confidence interval [95% CI] 1.12-1.44, p < 0.001) compared with patients who did. TG-referred patients who did not receive the TG intervention had an aOR of 1.83 (95% CI 1.60-2.10, p < 0.001) compared with patients who received the intervention. Younger age, male sex, having more comorbidities, and being discharged from a medicine unit were associated with not receiving an assigned intervention. These characteristics were also associated with higher readmission rates. CONCLUSIONS: PAL and TG care coordination interventions were associated with lower rates of 30-day readmission. Our findings underscore the importance of determining the appropriate intervention for the hardest-to-reach patients, who are also at the highest risk of being readmitted.

Patterns of Hospital Performance on the Hospital-Wide 30-Day Readmission Metric: Is the Playing Field Level?

BACKGROUND: Hospital performance on the 30-day hospital-wide readmission (HWR) metric as calculated by the Centers for Medicare and Medicaid Services (CMS) is currently reported as a quality measure. Focusing on patient-level factors may provide an incomplete picture of readmission risk at the hospital level to explain variations in hospital readmission rates. OBJECTIVE: To evaluate and quantify hospital-level characteristics that track with hospital performance on the current HWR metric. DESIGN: Retrospective cohort study. SETTING/PATIENTS: A total of 4785 US hospitals. METRICS: We linked publically available data on individual hospitals published by CMS on patient-level adjusted 30-day HWR rates from July 1, 2011, through June 30, 2014, to the 2014 American Hospital Association annual survey. Primary outcome was performance in the worst CMS-calculated HWR quartile. Primary hospital-level exposure variables were defined as: size (total number of beds), safety net status (top quartile of disproportionate share), academic status [member of the Association of American Medical Colleges (AAMC)], National Cancer Institute Comprehensive Cancer Center (NCI-CCC) status, and hospital services offered (e.g., transplant, hospice, emergency department). Multilevel regression was used to evaluate the association between 30-day HWR and the hospital-level factors. RESULTS: Hospital-level characteristics significantly associated with performing in the worst CMS-calculated HWR quartile included: safety net status [adjusted odds ratio (aOR) 1.99, 95% confidence interval (95% CI) 1.61-2.45, p < 0.001], large size (> 400 beds, aOR 1.42, 95% CI 1.07-1.90, p = 0.016), AAMC alone status (aOR 1.95, 95% CI 1.35-2.83, p < 0.001), and AAMC plus NCI-CCC status (aOR 5.16, 95% CI 2.58-10.31, p < 0.001). Hospitals with more critical care beds (aOR 1.26, 95% CI 1.02-1.56, p = 0.033), those with transplant services (aOR 2.80, 95% CI 1.48-5.31,p = 0.001), and those with emergency room services (aOR 3.37, 95% CI 1.12-10.15, p = 0.031) demonstrated significantly worse HWR performance. Hospice service (aOR 0.64, 95% CI 0.50-0.82, p < 0.001) and having a higher proportion of total discharges being surgical cases (aOR 0.62, 95% CI 0.50-0.76, p < 0.001) were associated with better performance. LIMITATION: The study approach was not intended to be an alternate readmission metric to compete with the existing CMS metric, which would require a re-examination of patient-level data combined with hospital-level data. CONCLUSION: A number of hospital-level characteristics (such as academic tertiary care center status) were significantly associated with worse performance on the CMS-calculated HWR metric, which may have important health policy implications. Until the reasons for readmission variability can be addressed, reporting the current HWR metric as an indicator of hospital quality should be reevaluated.

Increasing patient mobility through an individualized goal-centered hospital mobility program: A quasi-experimental quality improvement project.

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.

Using a Real-Time Location System for Assessment of Patient Ambulation in a Hospital Setting.

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.

Dynamic Prediction of Post-Acute Care Needs for Hospitalized Medicine Patients.

OBJECTIVES: 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. DESIGN: Retrospective cohort analysis of electronic medical records. SETTING AND PARTICIPANTS: Patients admitted to the two participating Hospitals from November 2016 through December 2019 with ≥72 hours in a general medicine service. METHODS: 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. RESULTS: 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%. CONCLUSIONS AND IMPLICATIONS: 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.

Inaccuracy of Initial Clinical Mobility Assessment in Venous Thromboembolism Risk Stratification.

BACKGROUND: Venous thromboembolism risk increases in hospitals due to reduced patient mobility. However, initial mobility evaluations for thromboembolism risk are often subjective and lack standardization, potentially leading to inaccurate risk assessments and insufficient prevention. METHODS: A retrospective study at a quaternary academic hospital analyzed patients using the Padua risk tool, which includes a mobility question, and the Johns Hopkins-Highest Level of Mobility (JH-HLM) scores to objectively measure mobility. Reduced mobility was defined as JH-HLM scores ≤3 over ≥3 consecutive days. The study evaluated the association between reduced mobility and hospital-acquired venous thromboembolism using multivariable logistic regression, comparing admitting health care professional assessments with JH-HLM scores. Symptomatic, hospital-acquired thromboembolisms were diagnosed radiographically by treating providers. RESULTS: Of 1715 patients, 33 (1.9%) developed venous thromboembolism. Reduced mobility, as determined by the JH-HLM scores, showed a significant association with thromboembolic events (adjusted OR: 2.53, 95%CI:1.23-5.22, P = .012). In contrast, the initial Padua assessment of expected reduced mobility at admission did not. The JH-HLM identified 19.1% of patients as having reduced mobility versus 6.5% by admitting health care professionals, suggesting 37 high-risk patients were misclassified as low risk and were not prescribed thrombosis prophylaxis; 4 patients developed thromboembolic events. JH-HLM detected reduced mobility in 36% of thromboembolic cases, compared to 9% by admitting health care professionals. CONCLUSION: Initial mobility evaluations by admitting health care professionals during venous thromboembolism risk assessment may not reflect patient mobility over their hospital stay. This highlights the need for objective measures like JH-HLM in risk assessments to improve accuracy and potentially reduce thromboembolism incidents.

The effects of task demands on bimanual skill acquisition.

Bimanual coordination is essential for everyday activities. It is thought that different degrees of demands may affect learning of new bimanual patterns. One demand is at the level of performance and involves breaking the tendency to produce mirror-symmetric movements. A second is at a perceptual level and involves controlling each hand to separate (i.e., split) goals. A third demand involves switching between different task contexts (e.g., a different uni- or bimanual task), instead of continuously practicing one task repeatedly. Here, we studied the effect of these task demands on motor planning (reaction time) and execution (error) while subjects learned a novel bimanual isometric pinch force task. In Experiment 1, subjects continuously practiced in one of the two extremes of the following bimanual conditions: (1) symmetric force demands and a perceptually unified target for each hand or (2) asymmetric force demands and perceptually split targets. Subjects performing in the asymmetric condition showed some interference between hands, but all subjects, regardless of group, could learn the isometric pinch force task similarly. In Experiment 2, subjects practiced these and two other conditions, but in a paradigm where practice was briefly interrupted by the performance of either a unimanual or a different bimanual condition. Reaction times were longer and errors were larger well after the interruption when the main movement to be learned required asymmetric forces. There was no effect when the main movement required symmetric forces. These findings demonstrate two main points. First, people can learn bimanual tasks with very different demands on the same timescale if they are not interrupted. Second, interruption during learning can negatively impact both planning and execution and this depends on the demands of the bimanual task to be learned. This information will be important for training patient populations, who may be more susceptible to increased task demands.