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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. This study tested and compared the psychometrics and feasibility of three cognitive screens and concludes that each tool demonstrated acceptable reliability and construct validity in acute care hospitals, with the Activity Measure for Post-Acute Care "6-Clicks" Applied Cognitive Inpatient Short Form (AM-PAC ACISF) overall having the optimum mix of performance and feasibility. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective. Physical function is associated with important outcomes, yet there is often a lack of continuity in routine assessment. The purpose of this study was to determine data elements and instruments for longitudinal measurement of physical function in routine care among patients transitioning from acute care hospital setting to home with home health care. Methods. A 4-round modified Delphi process was conducted with 13 participants with expertise in physical therapy, health care administration, health services research, physiatry/medicine, and health informatics. Three anonymous rounds identified important and feasible data elements. A fourth in-person round finalized the recommended list of individual data elements. Next, 2 focus groups independently provided additional perspectives from other stakeholders. Results. Response rates were 100% for online rounds 1, 3, and 4 and 92% for round 2. In round 1, 9 domains were identified: physical function, participation, adverse events, behavioral/emotional health, social support, cognition, complexity of illness/disease burden, health care utilization, and demographics. Following the fourth round, 27 individual data elements were recommended. Of these, 20 (74%) are "administrative" and available from most hospital electronic medical records. Additional focus groups confirmed these selections and provided input on standardizing collection methods. A website has been developed to share these results and invite other health care systems to participate in future data sharing of these identified data elements. Conclusion. A modified Delphi consensus process was used to identify critical data elements to track changes in patient physical function in routine care as they transition from acute hospital to home with home health. Impact. Expert consensus on comprehensive and feasible measurement of physical function in routine care provides health care professionals and institutions with guidance in establishing discrete medical records data that can improve patient care, discharge decisions, and future research. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Hoyer EH, Brotman DJ, Chan KS, Needham DM: Barriers to early mobility of hospitalized general medicine patients: survey development and results. Am J Phys Med Rehabil 201 5 ;94 :3 0 4 -3 1 2. Objective: Functional status decline commonly accompanies hospitalization making patients vulnerable to complications. Such decline can be mitigated through hospital-based early mobility programs. Success in implementing patient mobility quality improvement processes requires evaluating providers' knowledge, attitudes, and behaviors. Design: A cross-sectional, self-administered survey in two different hospital settings was completed by 1 20 nurses and physical and occupational therapists (rehabilitation therapists, 38; nurses, 82) from six general medicine units. The survey was developed using published guidelines, literature review, and provider meetings and refined through pilot testing. Psychometric properties were assessed, and regression analyses were conducted to examine barriers to early mobility by hospital site, provider discipline, and years of experience. Results: Internal consistency reliability, item consistency, and discriminant validity psychometric characteristics were acceptable. In multivariable regression analysis, overall perceived barriers were similar between the two hospitals (P = 0.25) and significantly higher for staff with less experience (P = 0.02) and for nurses vs. rehabilitation therapists (P < 0.001 ).The survey identified specific barriers common to both nurses and rehabilitation therapists and other barriers that were discipline specific. Conclusions: This novel survey identified important barriers to mobilizing medical inpatients that were similar across two hospital settings. These results can assist with the implementation of quality improvement projects for increasing early hospital-based patient mobility. [ABSTRACT FROM AUTHOR]

Objectives: A decline in functional status is common during acute care hospitalization and may make patients vulnerable to further complications. This decline can be mitigated through hospital-based early activity and mobility programs. An important component of successful activity and mobility programs is systematic documentation of patient function, which can be an important barrier to program implementation in the acute care setting. Herein, we present a new nursing-based documentation system created as part of an early activity and mobility quality improvement (QI) project. Design: This project was undertaken, using a structured QI process, on two 24-bed general medicine units in an academic hospital. Our performance measure was based on a mobility scale currently-used in the ICU setting, known as "highest level of mobility" (HLM). HLM served as a daily "vital sign" and is an ordinal scale ranging from 1 to 8 (example scores: 1 = bed rest, 6 = ambulating >10 steps, 8 = ambulating >250 feet). We present prospective data on 440 consecutive patients with a length of stay (LOS) >2 days, admitted between 3/1/2013 and 6/7/2013. We analyzed the association between the average HLM during the first 2 days of admission for each patient and our two primary outcomes, hospital LOS and discharge to home. After logarithmic transformation, LOS was analyzed using linear regression. Discharge to home was analyzed using logistic regression. These models were adjusted for 7 relevant variables (age, gender, race, marital status, payer, expected LOS, and the AHRQ comorbidity index). Results: Mean (T standard deviation) LOS was 6.9 (±5.1), with 385 (88%) patients discharged home. Compared to non-ambulatory patients (HLM <6), patients who were able to ambulate >10 steps or more (HLM ≥6) during their first two days on admission had significantly shorter mean hospital LOS (6.4 (±5.3) versus 7.4 (±4.9) days, p=0.03), and higher rates of discharge home (98% versus 77%, p<0.001). In our adjusted analysis, a 1 point increase in HML was associated with a significantly shorter LOS by 0.6 (95% CI 0.3-0.8, p<0.001) days and an increased odds of discharge to home (OR 1.8, 95% CI 1.5-2.2, p<0.001). Conclusions: When implemented within a structured QI project, nursing-based documentation of patients' physical function shortly after acute care hospital admission may be helpful in identifying general medicine patients requiring a longer length of stay and institutionalization at discharge. [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]