Routine Inpatient Mobility Assessment and Hospital Discharge Planning

Hoyer, Erik H.; Young, Daniel L.; Friedman, Lisa Aronson; Brotman, Daniel J.; Klein, Lisa M.; Friedman, Michael

doi:10.1001/jamainternmed.2018.5145

Cited by 49 publications

(51 citation statements)

References 8 publications

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“…These findings are consistent with other studies [8,39,40]. Moreover, our results suggest that initial evaluation of patients using these metrics could help to identify patients in need of mobilization during hospital stay [9].…”

Section: Physically Active Versus Inactive Patientssupporting

confidence: 92%

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Accelerometry assessed physical activity of older adults hospitalized with acute medical illness - an observational study

et al. 2020

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Background In a hospital setting and among older patients, inactivity and bedrest are associated with a wide range of negative outcomes such as functional decline, increased risk of falls, longer hospitalization and institutionalization. Our aim was to assess the distribution, determinants and predictors of physical activity (PA) levels using wrist-worn accelerometers in older patients hospitalized with acute medical illness. Methods Observational study conducted from February to November 2018 at an acute internal medicine unit in the University hospital of Lausanne, Switzerland. We enrolled 177 patients aged ≥65 years, able to walk prior to admission. PA during acute hospital stay was continuously recorded via a 3D wrist accelerometer. Clinical data was collected from medical records or by interview. Autonomy level prior to inclusion was assessed using Barthel Index score. PA levels were defined as < 30 mg for inactivity, 30–99 mg for light and ≥ 100 for moderate PA. Physically active patients were defined as 1) being in the highest quartile of time spent in light and moderate PA or 2) spending ≥20 min/day in moderate PA. Results Median [interquartile range - IQR] age was 83 [74–87] years and 60% of participants were male. The median [IQR] time spent inactive and in light PA was 613 [518–663] and 63 [30–97] minutes/day, respectively. PA peaked between 8 and 10 am, at 12 am and at 6 pm. Less than 10% of patients were considered physically active according to definition 2. For both definitions, active patients had a lower prevalence of walking aids and a lower dependency level according to Barthel Index score. For definition 1, use of medical equipment was associated with a 70% reduction in the likelihood of being active: odds ratio (OR) 0.30 [0.10–0.92] p = 0.034; for definition 2, use of walking aids was associated with a 75% reduction in the likelihood of being active: OR = 0.24 [0.06–0.89], p = 0.032. Conclusion Older hospitalized patients are physically active only 10% of daily time and concentrate their PA around eating periods. Whether a Barthel Index below 95 prior to admission may be used to identify patients at risk of inactivity during hospital stay remains to be proven.

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Section: Physically Active Versus Inactive Patientssupporting

confidence: 92%

“…Most PA levels are assessed based on observational data such as periodic nursing reports [ 2 , 7 , 8 ] or on nurse standardized functional assessment [ 6 , 9 ]. These qualitative assessments are less accurate compared to objective measures of PA such as accelerometry [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Accelerometry assessed physical activity of older adults hospitalized with acute medical illness - an observational study

et al. 2020

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“…Compared to physically active patients, pphysically inactive patients more frequently reported the use of walking aids 2 weeks before hospitalization, were more frequently admitted for a reason associated with functional decline, were at higher risk of bedsores at admission, and had a higher dependency level according to Barthel Index score. These findings are consistent with other studies (8, 39 , 40 ) and suggest that initial evaluation of patients using these metrics could help to identify patients in need of mobilization (9). Physically inactive patients also had physiotherapy prescribed more frequently.…”

Section: Physically Active Versus Inactive Patientssupporting

confidence: 90%

“…Most PA levels are assessed based on observational data such as periodic nursing reports (2,7,8) or on nurse standardized functional assessment (6,9). These qualitative assessments are less accurate compared to objective measures of PA such as accelerometry (10).…”

Section: Introductionmentioning

confidence: 99%

Accelerometry Assessed Physical Activity of Elderly Adults Hospitalized with Acute Medical Illness - an Observational Study

Tasheva

Kraege

Vollenweider

et al. 2019

Preprint

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Background: In a hospital setting and among elderly patients, inactivity and bedrest are associated with a wide range of negative outcomes such as functional decline, increased risk of falls, longer hospitalization and new institutionalization. Our aim was to assess the distribution and determinants of physical activity (PA) levels using wrist-worn accelerometers in elderly adults hospitalized with acute medical illness. Methods: Observational study conducted from February to November 2018 at an acute internal medicine unit in the University hospital of Lausanne, Switzerland. We enrolled 177 patients aged ≥65 years, able to walk independently prior to admission. PA during acute hospital stay was continuously recorded via a 3D wrist accelerometer. As previously suggested, PA was defined as an acceleration ≥12 mg. Clinical data was collected from medical records or by interview. Autonomy level prior to inclusion was assessed using Barthel Index score. Results: Median [interquartile range - IQR] age was 83 [74-87] years and 60% of participants were male. The median [IQR] time spent inactive and in PA was 485 [404-563] and 177 [114-255] minutes/day, respectively. PA was distributed into three peak periods during the day: between 8 and 10 am, at 12 am and at 6 pm. Approximately 50% of patients were considered physically active. Stepwise logistic regression identified Barthel index [odds ratio and (95% confidence interval) for increase in category [1.85 (1.09-3.14)], prescription of sedatives [0.31 (0.12-0.80)] and prescription of physiotherapy [2.16 (1.08-4.58)] as significantly and independently associated with inactivity. Conclusion: Elderly hospitalized patients are physically active only one quarter of the day and concentrate their PA around eating periods. A Barthel Index below 91 could be used to identify patients at risk of physical inactivity.

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“…3 Systematic measurement of patient mobility that extends beyond evaluations by physical therapists is not common practice but has the potential to facilitate early discharge planning. 7,8 At our hospital, mobility assessment is performed routinely using a reliable and valid interdisciplinary assessment of mobility throughout the patient's entire hospitalization. 9 We recently showed that nurse-recorded mobility status within the first 24 hours of hospitalization was associated with discharge disposition, 7 but a prediction tool to help aid clinicians in the discharge planning process would be more useful.…”

mentioning

confidence: 99%

Prediction of Disposition within 48-hours of Hospital Admission Using Patient Mobility Scores

et al. 2019

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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.

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Routine Inpatient Mobility Assessment and Hospital Discharge Planning

Abstract: 2. Jadoon KA, Ratcliffe SH, Barrett DA, et al. Efficacy and safety of cannabidiol and tetrahydrocannabivarin on glycemic and lipid parameters in patients with type 2 diabetes: a randomized, double-blind, placebo-controlled, parallel group pilot study.

Cited by 49 publications

References 8 publications

Accelerometry assessed physical activity of older adults hospitalized with acute medical illness - an observational study

Accelerometry assessed physical activity of older adults hospitalized with acute medical illness - an observational study

Accelerometry Assessed Physical Activity of Elderly Adults Hospitalized with Acute Medical Illness - an Observational Study

Prediction of Disposition within 48-hours of Hospital Admission Using Patient Mobility Scores

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