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Original Investigation |

Comparison of Posthospitalization Function and Community Mobility in Hospital Mobility Program and Usual Care Patients A Randomized Clinical Trial

Cynthia J. Brown, MD, MSPH1,2; Kathleen T. Foley, PhD, OTR/L3; John D. Lowman Jr, PhD, PT4; Paul A. MacLennan, PhD5; Javad Razjouyan, PhD6,7; Bijan Najafi, PhD6,7; Julie Locher, PhD2; Richard M. Allman, MD8
[+] Author Affiliations
1Birmingham/Atlanta Veterans Affairs Geriatric Research, Education, and Clinical Care Center, Birmingham, Alabama
2Division of Gerontology, Geriatrics, and Palliative Care, University of Alabama at Birmingham, Birmingham
3School of Occupational Therapy, College of Health Sciences, Brenau University, Atlanta, Georgia
4School of Health Professions, University of Alabama at Birmingham, Birmingham
5Department of Surgery, University of Alabama at Birmingham, Birmingham
6College of Medicine, University of Arizona, Tucson
7currently with Baylor College of Medicine, Houston, Texas
8Geriatrics and Extended Care, Department of Veterans Affairs, Washington, DC
JAMA Intern Med. 2016;176(7):921-927. doi:10.1001/jamainternmed.2016.1870.
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Importance  Low mobility is common during hospitalization and associated with loss or declines in ability to perform activities of daily living (ADL) and limitations in community mobility.

Objective  To examine the effect of an in-hospital mobility program (MP) on posthospitalization function and community mobility.

Design, Setting, and Participants  This single-blind randomized clinical trial used masked assessors to compare a MP with usual care (UC). Patients admitted to the medical wards of the Birmingham Veterans Affairs Medical Center from January 12, 2010, through June 29, 2011, were followed up throughout hospitalization with 1-month posthospitalization telephone follow-up. One hundred hospitalized patients 65 years or older were randomly assigned to the MP or UC groups. Patients were cognitively intact and able to walk 2 weeks before hospitalization. Data analysis was performed from November 21, 2012, to March 14, 2016.

Interventions  Patients in the MP group were assisted with ambulation up to twice daily, and a behavioral strategy was used to encourage mobility. Patients in the UC group received twice-daily visits.

Main Outcomes and Measures  Changes in self-reported ADL and community mobility were assessed using the Katz ADL scale and the University of Alabama at Birmingham Study of Aging Life-Space Assessment (LSA), respectively. The LSA measures community mobility based on the distance through which a person reports moving during the preceding 4 weeks.

Results  Of 100 patients, 8 did not complete the study (6 in the MP group and 2 in the UC group). Patients (mean age, 73.9 years; 97 male [97.0%]; and 19 black [19.0%]) had a median length of stay of 3 days. No significant differences were found between groups at baseline. For all periods, groups were similar in ability to perform ADL; however, at 1-month after hospitalization, the LSA score was significantly higher in the MP (LSA score, 52.5) compared with the UC group (LSA score, 41.6) (P = .02). For the MP group, the 1-month posthospitalization LSA score was similar to the LSA score measured at admission. For the UC group, the LSA score decreased by approximately 10 points.

Conclusions and Relevance  A simple MP intervention had no effect on ADL function. However, the MP intervention enabled patients to maintain their prehospitalization community mobility, whereas those in the UC group experienced clinically significant declines. Lower life-space mobility is associated with increased risk of death, nursing home admission, and functional decline, suggesting that declines such as those observed in the UC group would be of great clinical importance.

Trial Registration  clinicaltrials.gov Identifier: NCT00715962

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Progress of the hospitalized patients through the phases of this clinical trial. ICU indicates intensive care unit.

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Submit a Comment
A mobility program too much? Comment on: comparison of posthospitalization function and community mobility in hospital mobility program and usual care patients: a randomized clinical trial.
Posted on July 28, 2016
Dr. Wing Tong, MD, PhD, MSc
Department of Hospital Medicine, Medical Center Haaglanden – Bronovo/Nebo (MCH-Bronovo/Nebo), The Hague, The Netherlands
Conflict of Interest: None Declared
With great interest the contribution of Brown and co-workers was read and they should be complimented for their impressive work. They reported that those in a mobility program (MP) were less likely to experience a decline in community mobility when compared with usual care and were able to maintain their prehospitalization community mobility status.[1] However, they conclude that a simple MP intervention had no effect on ADL function. Recently, Buurman and co-workers also studied the role of ADL in their RCT and reported that a systematic comprehensive geriatric assessment (CGA), followed by the transitional care bridge program, showed no effect on ADL functioning in acute hospitalized older patients.[2]
Both studies conclude that the vulnerable elderly are at risk within 30 days after discharge. So, implementing an easy-to-implement mobility program[1] and systematic CGA, followed by the transitional care bridge program[2] seem of value. However, what is a hospital mobility program the solution for? Therefore, some comments on the article of Brown and co-workers are made.
As mentioned in the invited commentary by dr S. Ryan Greysen[3], mainly male veterans were studied, therefore sex could be a potential confounder in their analysis. Also, the inclusion of hospitalized patients 65 years or older was not comparable with their calculated mean age (73.9 years) in the final group, suggesting that age is a confounder. Larger studies with a diverse range of participants are encouraged.
Second, some methodological issues are noted. These authors used mixed models to evaluate changes in ADL over time. Was this model based on an unstructured or auto-regressive covariance matrix? Given the small subgroups, were all characteristics and variables tested on its normality (as shown by the Shapiro-Wilk test). For example, the mean and standard deviation of the GDS and APACHE II scores, and Charlson comorbidity index were almost the same. These show skewed distributions. In addition, are the ADL scores not normally distributed. If so, why didn’t the authors log-transform these ADL scores? Therefore geometric means ± standard error of the mean could be presented in a Figure.
Of interest, Naylor and co-workers published that an advanced practice nurse-centered discharge planning and home care intervention for at-risk hospitalized elders decreased the costs of providing health care.[4] Is an easy-to-implement mobility program cost-effective?
In conclusion, geriatrics is aimed to improve quality of life, rather than to improve survival.
In accordance with dr S. Ryan Greysen[3], the next question should be studied: what if all aspects of hospital care for seniors were as patient centered as this?

References

1. Brown CJ, Foley KT, Lowman Jr JD, et al. Comparison of posthospitalization function and community mobility in hospital mobility program and usual care patients: a randomized clinical trial. JAMA Intern Med. 2016;176(7):921-927.
2. Buurman BM, Parlevliet JL, Allore HG, et al. Comprehensive geriatric assessment and transitional care in acutely hospitalized patients: the transitional care bridge randomized clinical trial. JAMA Intern Med. 2016;176(3):302-309.
3. Ryan Greysen S. Activating hospitalized older patients to confront the epidemic of low mobility. JAMA Intern Med. 2016;176(7):928-929.
4. Naylor MD, Brooten D, Campbell R, et al. Comprehensive discharge planning and home follow-up of hospitalized elders. JAMA. 1999;281(7):613-620.





Response to comment: A mobility program too much?
Posted on August 2, 2016
Cynthia J. Brown, Paul A. MacLennan, Julie Locher, Richard M. Allman
Birmingham/Atlanta Veterans Affairs Geriatric Research, Education, and Clinical Care Center; University of Alabama at Birmingham and Geriatrics and Extended Care, Department of Veterans Affairs, Washi
Conflict of Interest: Dr. Brown reports working as a consultant for Novartis. No other disclosures are reported.
We appreciate Dr. Tong’s comments regarding our randomized clinical trial of a mobility intervention—the first among a general medical population. The mobility intervention study was undertaken after a number of studies demonstrated that low mobility was common among older adults and associated with adverse events including activities of daily living (ADL) decline and nursing home placement even after controlling for illness severity and comorbidity. [1, 2, 3, 4]

We agree that maintaining or improving quality of life is an important focus of Geriatrics. We previously have shown that life-space mobility is a mediator of health related quality of life. [5] Therefore, the mobility program’s ability to prevent decline in life-space facilitates maintenance of social participation and mediates an improved health-related quality of life. As noted by Dr. Tong, ADL decline is common during hospitalization and we did not see a significant change in ability to perform ADLs after hospitalization. However as noted in our discussion, study patients did not have dementia or delirium, which may have affected our findings. In addition, the study was not powered to see significant ADL changes.

We disagree with the suggestion that gender and age confounded the study results. Gender and age were controlled for through two mechanisms: (1) patients were randomized into study groups and were similar by gender and age, and (2) inclusion of gender and age as covariates in multivariate models controlled for any residual confounding through statistical adjustment.

We agree that large and more diverse patient samples should be studied to enhance generalizability and to permit cost effectiveness analyses of the mobility program. Preliminary findings suggest that lower life-space scores are associated with increased health care utilization among older adults with heart failure. These preliminary findings suggest that the mobility program could prove cost-effective by reducing hospital readmissions in appropriately targeted groups. [6]

We used neither an unstructured nor an auto-regressive covariance matrix; rather, we chose the Variance Component matrix. We selected the best-fit model based on the Akaike information criteria (AIC). The VC had the lowest AIC, suggesting this model had the best fit.

We did consider log transforming the covariates Charlson comorbidity index, APACHE II scores, and GDS; however, statistical inference of the results did not differ by whether these covariates were or were not transformed. Consequently, we opted to use the non-transformed analysis due to ease of interpretability.

Though ADL data were right-skewed, we believe our use of a linear mixed model to be valid as, given the sample size of 100 subjects, we can assume normality through use of the Central Limit Theorem. That said, we looked into the use of mixed model for log-transformed ADL, and the statistical inference did not change.

Finally, we agree with Dr. Tong that the best care is patient-centered and individualized to meet each patient’s needs. We hope our study provides evidence that a mobility program is feasible and moves us toward the development of a mobility standard of care that can be adapted to the individual hospitalized patient.

[1] Brown CJ, Redden DT, Flood KL, Allman RM. The Under Recognized Epidemic of Low Mobility During Hospitalization of Older Adults. J Am Geriatr Soc, 57(9):1660-1665, 2009. PMID: 19682121
[2] Fisher SR, Goodwin JS, Protas EJ, Kuo YF, Graham JE, Ottenbacher KJ, Ostir GV. Ambulatory activity of older adults hospitalized with acute medical illness. J Am Geriatr Soc. 2011;59(1):91-95. PMID: 21158744
[3] Pedersen MM, Bodilsen AC, Petersen J, Beyer N, Andersen O, Lawson-Smith L, Kehlet H, Bandholm T. Twenty-four hour mobility during acute hospitalization in older medical patients. J Gerontol A Biol Sci Med Sci. 2013;68(3):331–337. PMID: 22972940
[4] Brown CJ, Friedkin RJ, Inouye SK. Prevalence and Outcomes of Low Mobility in Hospitalized Older Patients. J Am Geriatr Soc 52:1263-1270, 2004. PMID: 15271112.
[5] Bentley JP, Brown CJ, McGwin G Jr, Sawyer P, Allman RM, Roth DL. Function status, life-space mobility, and quality of life: A longitudinal mediation analysis. Qual Life Res. 22(7):1621-1632. Nov 2012. PMID:23161329 PMC361899
[6] Lo AX, Flood KL, Kennedy RE, Bittner V, Sawyer P, Allman RM, Brown CJ. The Association Between Life-Space and Health Care Utilization in Older Adults with Heart Failure. J Gerontol A Biol Sci Med Sci (2015) 70 (11): 1442-1447. PMID: 26219849
Comment on: A mobility program too much?
Posted on August 10, 2016
W.H. Tong, MD, PhD, MSc
Department of Hospital Medicine, Medical Center Haaglanden – Bronovo/Nebo (MCH-Bronovo/Nebo), The Hague, The Netherlands.
Conflict of Interest: None Declared
Brown and co-workers stress that their mobility program is to prevent decline in life-space facilitates maintenance of social participation and mediates an improved health-related quality of life.[1] Different studies demonstrated that low mobility was common among older adults and associated with adverse events including activities of daily living (ADL) decline and nursing home placement even after controlling for illness severity and comorbidity.[1-4]
The authors noted that gender is not confounding their study results. The two used mechanisms seem correct, however what was mentioned is that there is male predominance in their study. By including female in this study (e.g. approximately 50% male and 50% female), the results could be rather different. This study was conducted at Atlanta Veterans Affairs Geriatric Research, so this could clarify the use of mainly male veterans. Albeit, it is still encouraged to include mixed populations in a larger study to confirm their results.
Still some methodological questions exist. The Variance Component (VC) matrix suggest that measurements within the patient are independent and that seems impossible, despite of what the Akaike Information Criteria (AIC) will show? Also, the authors use the terminology: “Central Limit Theorem”. This is general and well-known, however the question arises whether the number of 100 subjects are enough in this study?
The authors opted to use the non-transformed analysis due to ease of interpretability. However, in the article of Tong and co-workers, they analyzed the data after log-transformation of measured values to get approximate normal distributions. And the mean values were estimated by backtransforming the mean log-values.[5] Hence, the interpretability was guaranteed.
To conclude, the work of Brown and co-workers is important, it provides some evidence that a mobility program is feasible. Although, it remains questionable if this program will move toward the development of a mobility standard of care that can be adapted to the individual hospitalized patient. It awaits final definite results of a much larger group (international and multi-center carried out, also outside the United States of America) to enhance generalizability, all over the world.


References

1. Brown CJ, Foley KT, Lowman Jr JD, et al. Comparison of posthospitalization function and community mobility in hospital mobility program and usual care patients: a randomized clinical trial. JAMA Intern Med. 2016;176(7):921-927.
2. Fisher SR, Goodwin JS, Protas EJ, et al. Ambulatory activity of older adults hospitalized with acute medical illness. J Am Geriatr Soc. 2011;59(1):91-95.
3. Pedersen MM, Boldilsen AC, Petersen J, et al. Twenty-four hour mobility during acute hospitalization in older medical patients. J Gerontol A Biol Sci Med Sci. 2013;68(3):331-337.
4. Brown CJ, Friedkin RJ, Inouye SK. Prevalence and outcomes of low mobility in hospitalized older patients. J Am Geriatr Soc. 2004;52(8):1263-1270.
5. Tong WH, Pieters R, de Groot-Kruseman HA, et al. The toxicity of very prolonged courses of PEGasparaginase or Erwinia asparaginase in relation to asparaginase activity, with a special focus on dyslipidemia. Haematologica. 2014;99(11):1716-1721.







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