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Background Post-hospitalization transition interventions remain a priority in preventing rehospitalization. However, not all patients referred for readmission prevention interventions receive them. We sought to 1) define patient characteristics associated with non-receipt of readmission prevention interventions (among those eligible for them), and 2) determine whether these same patient characteristics are associated with hospital readmission at the state level. Methods We used state-wide data from the Maryland Health Services Cost Review Commission to determine patient-level factors associated with state-wide readmissions. Concurrently, we conducted a retrospective analysis of discharged patients referred to receive 1 of 3 post-discharge interventions between January 2013 and July 2019—a nurse transition guide, post-discharge phone call, or follow-up appointment in our post-discharge clinic—to determine patient-level factors associated with not receiving the intervention. Multivariable generalized estimating equation logistic regression models were used to calculate the odds of not accepting or not receiving the interventions. Results Older age, male gender, black race, higher expected readmission rate, and lower socioeconomic status were significantly associated with 30-day readmission in hospitalized Maryland patients. Most of these variables (age, sex, race, payer type [Medicaid or non-Medicaid], and socioeconomic status) were also associated with non-receipt of intervention. Conclusions We found that many of the same patient-level characteristics associated with the highest readmission risk are also associated with non-receipt of readmission reduction interventions. This highlights the paradox that patients at high risk of readmission are least likely to accept or receive interventions for preventing readmission. Identifying strategies to engage hard-to-reach high-risk patients continues to be an unmet challenge in readmission prevention.

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.

BackgroundPatient flow directly affects quality of care, access and financial performance for hospitals. Multidisciplinary discharge-focused rounds have proven to minimise avoidable delays experienced by patients near discharge. The study objective was to support discharge-focused rounds by implementing a machine-learning-based discharge prediction model using real-time electronic health record (EHR) data. We aimed to evaluate model predictive performance and impact on hospital length-of-stay.MethodsDischarge prediction models were developed from hospitalised patients on four inpatient units between April 2016 and September 2018. Unit-specific models were implemented to make individual patient predictions viewable with the EHR patient track board. Predictive performance was measured prospectively for 12 470 patients (120 780 patient-predictions) across all units. A pre/poststudy design applying interrupted time series methods was used to assess the impact of the discharge prediction model on hospital length-of-stay.ResultsProspective discharge prediction performance ranged in area under the receiver operating characteristic curve from 0.70 to 0.80 for same-day and next-day predictions; sensitivity was between 0.63 and 0.83 and specificity between 0.48 and 0.80. Elapsed length-of-stay, counts of labs and medications, mobility assessments and measures of acute kidney injury were model features providing the most predictive value. Implementing the discharge predictions resulted in a reduction in hospital length-of-stay of over 12 hours on a medicine unit (pConclusionsIncorporating automated patient discharge predictions into multidisciplinary rounds can support decreases in hospital length-of-stay. Variation in execution and impact across inpatient units existed.

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 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.

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.

Key Points Question Are patient ambulation profiles predictive of hospital readmission, discharge location, and length of stay? Findings In this prognostic cohort study of 100 adults in a cardiac surgery progressive care unit, patient ambulation profiles were predictive of 30-day readmission (C statistic, 0.925), discharge location (C statistic, 0.930), and length of stay (correlation coefficient, 0.927). Meaning Patient ambulation profiles from a real-time location system enable prediction of clinically relevant outcomes., This prognostic cohort study evaluates novel ambulation metrics in predicting 30-day readmission rates, discharge location, and length of stay using a real-time location system to continuously monitor the voluntary ambulations of postoperative cardiac surgery patients., Importance Promoting patient mobility during hospitalization is associated with improved outcomes and reduced risk of hospitalization-associated functional decline. Therefore, accurate measurement of mobility with high–information content data may be key to improved risk prediction models, identification of at-risk patients, and the development of interventions to improve outcomes. Remote monitoring enables measurement of multiple ambulation metrics incorporating both distance and speed. Objective To evaluate novel ambulation metrics in predicting 30-day readmission rates, discharge location, and length of stay using a real-time location system to continuously monitor the voluntary ambulations of postoperative cardiac surgery patients. Design, Setting, and Participants This prognostic cohort study of the mobility of 100 patients after cardiac surgery in a progressive care unit at Johns Hopkins Hospital was performed using a real-time location system. Enrollment occurred between August 29, 2016, and April 4, 2018. Data analysis was performed from June 2018 to December 2019. Main Outcomes and Measures Outcome measures included 30-day readmission, discharge location, and length of stay. Digital records of all voluntary ambulations were created where each ambulation consisted of multiple segments defined by distance and speed. Ambulation profiles consisted of 19 parameters derived from the digital ambulation records. Results A total of 100 patients (81 men [81%]; mean [SD] age, 63.1 [11.6] years) were evaluated. Distance and speed were recorded for more than 14 000 segments in 840 voluntary ambulations, corresponding to a total of 127.8 km (79.4 miles) using a real-time location system. Patient ambulation profiles were predictive of 30-day readmission (sensitivity, 86.7%; specificity, 88.2%; C statistic, 0.925 [95% CI, 0.836-1.000]), discharge to acute rehabilitation (sensitivity, 84.6%; specificity, 86.4%; C statistic, 0.930 [95% CI, 0.855-1.000]), and length of stay (correlation coefficient, 0.927). Conclusions and Relevance Remote monitoring provides a high–information content description of mobility, incorporating elements of step count (ambulation distance and related parameters), gait speed (ambulation speed and related parameters), frequency of ambulation, and changes in parameters on successive ambulations. Ambulation profiles incorporating multiple aspects of mobility enables accurate prediction of clinically relevant outcomes.

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. To evaluate the effects of two care coordination interventions on 30-day readmission rates. 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. A total of 25,628 patients hospitalized in medicine, neurosciences, or surgical sciences units. 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. Two large academic hospitals in Baltimore, MD. Thirty-day all-cause readmission to any Maryland hospital. 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

Background The Johns Hopkins Highest Level of Mobility (JH-HLM) scale is used to document the observed mobility of hospitalized patients, including those patients in the intensive care unit (ICU) setting. Objective To evaluate the inter-rater reliability of the JH-HLM, completed by physical therapists, across medical, surgical, and neurological adult ICUs at a single large academic hospital. Methods The JH-HLM is an ordinal scale for documenting a patient’s highest observed level of activity, ranging from lying in bed (score = 1) to ambulating > 250 feet (score = 8). Eighty-one rehabilitation sessions were conducted by eight physical therapists, with 1 of 2 reference physical therapist rater simultaneously observing the session and independently scoring the JH-HLM. The intraclass correlation coefficient was used to determine the inter-rater reliability. Results A total of 77 (95%) of 81 assessments had perfect agreement. The overall intraclass correlation coefficient for inter-rater reliability was 0.98 (95% confidence interval: 0.96, 0.99), with similar scores in the medical, surgical, and neurological ICUs. A Bland–Altman plot revealed a mean difference in JH-HLM scoring of 0 (limits of agreement: −0.54 to 0.61). Conclusion The JH-HLM has excellent inter-rater reliability as part of routine physical therapy practice, across different types of adult ICUs.

Objective To expand an existing validated measure of basic mobility (Activity Measure for Post-Acute Care [AM-PAC]) for patients at the lowest levels of function. Design Item replenishment for existing item response theory (IRT) derived measure via (1) idea generation and creation of potential new items, (2) item calibration and field testing, and (3) longitudinal pilot test. Setting Two tertiary acute care hospitals. Participants Consecutive inpatients (N=502) ≥18 years old, with an AM-PAC Inpatient Mobility Short Form (IMSF) raw score ≤15. For the longitudinal pilot test, 8 inpatients were evaluated. Results Fifteen new AM-PAC items were developed, 2 of which improved mobility measurement at the lower levels of functioning. Specifically, with the 2 new items, the floor effect of the AM-PAC IMSF was reduced by 19%, statistical power and measurement breadth were greater, and there was greater measurement sensitivity in longitudinal pilot testing. Conclusion Adding 2 new items to the AM-PAC IMSF lowered the floor and increased statistical power, measurement breadth, and sensitivity.

Delayed hospital discharges for patients needing rehabilitation in a postacute setting can exacerbate hospital-acquired mobility loss, prolong functional recovery, and increase costs. Systematic measurement of patient mobility by nurses early during hospitalization has the potential to help identify which patients are likely to be discharged to a postacute care facility versus home. To test the predictive ability of this approach, a machine learning classification tree method was applied retrospectively to a diverse sample of hospitalized patients (N = 805) using training and validation sets. Compared with patients discharged to home, patients discharged to a postacute facility were older (median, 64 vs 56 years old) and had lower mobility scores at hospital admission (median, 32 vs 41). The final decision tree accurately classified the discharge location for 73% (95%CI:67%-78%) of patients. This study emphasizes the value of systematically measuring mobility in the hospital and provides a simple decision tree to facilitate early discharge planning.

This cohort study examines whether use of a mobility assessment tool in hospitalized patients with impaired mobility is associated with discharge to a postacute facility.

BACKGROUND Hospital-level studies have found an inverse relationship between patient experience and readmissions. However, based on typical survey response time, it is unclear if patients are able to respond to surveys before they get readmitted and whether being readmitted might be a driver of poor experience scores (reverse causation). OBJECTIVE Using patient-level Hospital Consumer Assessment of Healthcare Providers and Systems (HCHAPS) and Press Ganey data to examine the relationship between readmissions and experience scores and to distinguish between patients who responded before or after a subsequent readmission. DESIGN Retrospective analysis of 10-year HCAHPS data. SETTING Single tertiary care academic hospital. PARTICIPANTS Patients readmitted within 30 days of an index hospitalization who received an HCAHPS survey linked to index admission comprised the exposure group. This group was divided into those who responded prior to readmission and those who responded after readmission. Nonreadmitted patients comprised the control group. ANALYSIS Multivariable-logistic regression to analyze the association between HCHAPS and Press Ganey scores and 30-readmission status, adjusted for patient factors. RESULTS Only 15.8% of the readmitted patients responded to the survey prior to readmission, and their scores were not significantly different from the nonreadmitted patients. The patients who responded after readmission were significantly more dissatisfied with physicians (doctors listened 73.0% vs 79.2%, aOR 0.75, P < .0001), staff responsiveness, (call button 50.0% vs 59.1%, aOR 0.71, P < .0001) pain control, discharge plan, noise, and cleanliness of the hospital. CONCLUSIONS Our findings suggest that poor patient experience may be due to being readmitted, rather than being predictive of readmission.

Background: Although many hospitalized neuroscience patients have physical and occupational therapy (rehabilitation) needs, patients with none or minimal physical impairments frequently receive rehabilitation consultation, diverting from patients with greatest need. Methods: A multidisciplinary team on the general and cerebrovascular neurology acute inpatient services mapped the rehabilitation consultation process, resulting in multiple implemented interventions including physician education on appropriate acute rehabilitation consultations, modification of multidisciplinary rounds, and discussion of patient rehabilitation needs throughout hospitalization. Nurses used the same functional impairment measurement tool used by physical and occupational therapists, the Activity Measure for Post-Acute Care Inpatient Short Forms (Basic Mobility and Activity domains). Results: The rate for initial rehabilitation consults for patients with no limitations in mobility or activity during the 6-month baseline period was 12%, which was decreased to 7% and 10% during the 6-month intervention and sustain periods, respectively ( P < .001). The baseline rate for patients with no limitations receiving both physical therapy and occupational therapy consultations was 62% and was decreased to 21% and 39% in the intervention and sustain periods, respectively ( P < .001). Rehabilitation sessions per hospital day increased for patients with high functional impairments, from 0.52 at baseline to 0.64 in the intervention and 0.66 in the sustain periods ( P = .02), which equated to 1 more rehabilitation visit per patient hospitalization. Conclusions: A multifaceted intervention led to improved utilization of acute inpatient rehabilitation consultation while increasing the frequency of rehabilitation treatment for patients with highest functional impairment.

Current hospital readmission measures are part of the Centers for Medicare & Medicaid Services Five-Star Quality Rating System but are inadequate for reporting hospital quality. We review potential biases in the readmission measures and offer policy recommendations to address these biases. Hospital readmission rates are influenced by multiple sources of variation (eg, mix of patients served, bias in the performance measure); true differences in quality of care are often a much smaller source of this variation. Thus, variation from caring for large proportions of socioeconomically disadvantaged or tertiary-care patients will bias a hospital's ratings. Ratings aside, readmission measures may indirectly harm patients because low readmission rates do not correlate with reduced mortality, yet the Five-Star Quality Rating System weighs readmission equally with mortality. We propose that hospital quality rankings not use readmission measures as currently constructed.

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.

Background The lack of common language among interprofessional inpatient clinical teams is an important barrier to achieving inpatient mobilization. In The Johns Hopkins Hospital, the Activity Measure for Post-Acute Care (AM-PAC) Inpatient Mobility Short Form (IMSF), also called “6-Clicks,” and the Johns Hopkins Highest Level of Mobility (JH-HLM) are part of routine clinical practice. The measurement characteristics of these tools when used by both nurses and physical therapists for interprofessional communication or assessment are unknown. Objective The purposes of this study were to evaluate the reliability and minimal detectable change of AM-PAC IMSF and JH-HLM when completed by nurses and physical therapists and to evaluate the construct validity of both measures when used by nurses. Design A prospective evaluation of a convenience sample was used. Methods The test-retest reliability and the interrater reliability of AM-PAC IMSF and JH-HLM for inpatients in the neuroscience department (n = 118) of an academic medical center were evaluated. Each participant was independently scored twice by a team of 2 nurses and 1 physical therapist; a total of 4 physical therapists and 8 nurses participated in reliability testing. In a separate inpatient study protocol (n = 69), construct validity was evaluated via an assessment of convergent validity with other measures of function (grip strength, Katz Activities of Daily Living Scale, 2-minute walk test, 5-times sit-to-stand test) used by 5 nurses. Results The test-retest reliability values (intraclass correlation coefficients) for physical therapists and nurses were 0.91 and 0.97, respectively, for AM-PAC IMSF and 0.94 and 0.95, respectively, for JH-HLM. The interrater reliability values (intraclass correlation coefficients) between physical therapists and nurses were 0.96 for AM-PAC IMSF and 0.99 for JH-HLM. Construct validity (Spearman correlations) ranged from 0.25 between JH-HLM and right-hand grip strength to 0.80 between AM-PAC IMSF and the Katz Activities of Daily Living Scale. Limitations The results were obtained from inpatients in the neuroscience department of a single hospital. Conclusions The AM-PAC IMSF and JH-HLM had excellent interrater reliability and test-retest reliability for both physical therapists and nurses. The evaluation of convergent validity suggested that AM-PAC IMSF and JH-HLM measured constructs of patient mobility and physical functioning.

Federally mandated pay-for-performance initiatives promote minimizing 30-day hospital readmissions to improve healthcare quality and reduce costs. Although the reasons for readmissions are multifactorial, many patients are readmitted for a condition other than their initial hospital admitting diagnosis.1 Impairments in functional status experienced during acute care hospitalization contribute to patients being discharged in a debilitated state and being vulnerable to postdischarge complications and potentially hospital read-mission.2 As such, decreased functional status may be an important and potentially modifiable risk factor for acute care hospital readmission.3 Previous studies have suggested that impaired functional status may be an important predictor of rehospitalization.4–7 However, inferences from existing studies are limited because they did not consider functional status as their primary focus, they only considered specific patient populations (eg, stroke) or readmissions occurring well beyond the 30-day period defined by federal pay-for-performance standards.4–6,8–10 Our objective was to evaluate the association between functional status near the time of discharge from acute care hospital and 30-day readmission for patients admitted to an acute inpatient rehabilitation facility. As a secondary objective, we sought to investigate the relationship between functional status and readmission by diagnostic category (medical, neurologic, or orthopedic).

This chapter provides a sample case of developing a quality improvement project to encourage mobility in hospitalized patients. This chapter is unique in that it provides a perspective from both a resident and an attending in order to help delineate differences in commitment between these two roles. This chapter also explains the basic structure utilized in the book for other sample projects. SBAR template (see below) will be used to provide the motivation for the project and DMAIC template (see below) will be used to communicate the project implementation. SBAR will provide the context for the quality improvement opportunity, which often can be identified as a gap between current scientific evidence and present-day clinical practice. Each of the subsections below will be subdivided into What and How sections. What section describes goals and conclusions. How section illustrates how these were reached/accomplished.

OBJECTIVE Hospital discharge summaries can provide valuable information to future providers and may help to prevent hospital readmissions. We sought to examine whether the number of days to complete hospital discharge summaries is associated with 30-day readmission rate. PATIENTS AND METHODS This was a retrospective cohort study conducted on 87,994 consecutive discharges between January 1, 2013 and December 31, 2014, in a large urban academic hospital. We used multivariable logistic regression models to examine the association between days to complete the discharge summary and hospital readmissions while controlling for age, gender, race, payer, hospital service (gynecology–obstetrics, medicine, neurosciences, oncology, pediatrics, and surgical sciences), discharge location, length of stay, expected readmission rate in Maryland based on diagnosis and illness severity, and the Agency for Healthcare Research and Quality Comorbidity Index. Days to complete the hospital discharge summary—the primary exposure variable—was assessed using the 20th percentile (>3 vs ≤3 days) and as a continuous variable (odds ratio expressed per 3-day increase). The main outcome was all-cause readmission to any acute care hospital in Maryland within 30 days. RESULTS Among the 87,994 patients, there were 14,248 (16.2%) total readmissions. Discharge summary completion >3 days was significantly associated with readmission, with adjusted odds ratio (OR) (95% confidence interval [CI]) of 1.09 (1.04 to 1.13, P = 0.001). We also found that every additional 3 days to complete the discharge summary was associated with an increased adjusted odds of readmission by 1% (OR: 1.01, 95% CI: 1.00 to 1.01, P < 0.001). CONCLUSION Longer days to complete discharge summaries were associated with higher rates of all-cause hospital readmissions. Timely discharge summary completion time may be a quality indicator to evaluate current practice and as a potential strategy to improve patient outcomes. Journal of Hospital Medicine 2016;11:393–400. 2016 Society of Hospital Medicine

To determine whether a multidisciplinary mobility promotion quality-improvement (QI) project would increase patient mobility and reduce hospital length of stay (LOS).Implemented using a structured QI model, the project took place between March 1, 2013 and March 1, 2014 on 2 general medicine units in a large academic medical center. There were 3352 patients admitted during the QI project period. The Johns Hopkins Highest Level of Mobility (JH-HLM) scale, an 8-point ordinal scale ranging from bed rest (score = 1) to ambulating ≥250 feet (score = 8), was used to quantify mobility. Changes in JH-HLM scores were compared for the first 4 months of the project (ramp-up phase) versus 4 months after project completion (post-QI phase) using generalized estimating equations. We compared the relative change in median LOS for the project months versus 12 months prior among the QI units, using multivariable linear regression analysis adjusting for 7 demographic and clinically relevant variables.Comparing the ramp-up versus post-QI phases, patients reaching JH-HLM's ambulation status increased from 43% to 70% (P0.001), and patients with improved JH-HLM mobility scores between admission and discharge increased from 32% to 45% (P0.001). For all patients, the QI project was associated with an adjusted median LOS reduction of 0.40 (95% confidence interval [CI]: -0.57 to -0.21, P 0.001) days compared to 12 months prior. A subgroup of patients expected to have a longer LOS (expected LOS7 days), were associated with a significantly greater adjusted median reduction in LOS of 1.11 (95% CI: -1.53 to -0.65, P0.001) days. Increased mobility was not associated with an increase in injurious falls compared to 12 months prior on the QI units (P = 0.73).Active prevention of a decline in physical function that commonly occurs during hospitalization may be achieved with a structured QI approach. In an adult medicine population, our QI project was associated with improved mobility, and this may have contributed to a reduction in LOS, particularly for more complex patients with longer expected hospital stay. Journal of Hospital Medicine 2016. © 2016 Society of Hospital Medicine.

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.Criterion standard validation study.Inpatient, university hospital.Patients (N=25) in an adult neuroscience/brain rescue unit.Not applicable.RTLS and clinician-reported ambulation distance in feet, and JH-HLM score on an 8-point ordinal scale.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.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.

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.A cross-sectional, self-administered survey in two different hospital settings was completed by 120 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.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 (P0.001).The survey identified specific barriers common to both nurses and rehabilitation therapists and other barriers that were discipline specific.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.

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 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 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.