INCREASING MOBILITY IN THE HOSPITAL SETTING

Cynthia J. Brown, MD, MSPHGwen McWhorter, Ed.D., Endowed Chair in Geriatric Medicine

Director, Division of Gerontology, Geriatrics, and Palliative CareDirector, Comprehensive Center for Healthy Aging

Vice Chair, Faculty and Staff Development, Dept of Medicine

OBJECTIVES/ DISCLOSURES

After attendance at this lecture, participants will be able to:1. Describe prevalence and outcomes of hospital-associated

disability.2. Summarize interventions that have been successfully used in

the hospital setting to increase mobility.3. Define elements needed to create the necessary culture

change to promote hospital mobility

No disclosures to report

SCOPE OF THE PROBLEM

CONSEQUENCES OF LOW MOBILITY

• Many observed geriatric syndromes related to bed rest and low mobility during hospitalization:• Delirium• Pressure Ulcers• ADL Decline• Incontinence• Falls

CONSEQUENCES OF BED REST AND HOSPITALIZATION

Creditor MC Ann Intern Med 1995

STUDY OF MOBILITY: THE EARLY YEARS

Pre-2005, limited methods to measure mobility• Chart review of physician activity orders1

• Brief surveys of patient location2

• Periodic nursing reports3

• Direct observation of hallways4

In 2009, first paper published using accelerometers5

1 Lazarus BA, et al. Arch Intern Med, 1991; 2 Warshaw G, et al. JAMA 1982; 3 Brown CJ, et al. J Am Geriatr Soc, 2004;4 Callen BL, et al. Geriatr Nurs 2004; 5 Brown CJ, et al. J Am Geriatr Soc, 2009

DEFINITION AND FREQUENCY OF LOW MOBILITY

• Low mobility, defined as bed rest or bed to chair activity, common during hospitalization.

• 83% of hospital stay spent in bed• 43 min/day spent standing/walking; Results

duplicated

Brown CJ, et al. JAGS 2009

Patient-related factorsIllness severity

Comorbid conditionsAltered mental statusPatients symptoms

Institution-related factorsStaffing patterns

Environment encourages bed restLack of ambulatory devices

Treatment-related factorsHospital devices

Admitting diagnosisSide effects of medications

Attitudinal factorsAttitude toward mobility

Expectation of hospital stayConcern about falls

PATIENT

MODEL OF POTENTIAL BARRIERS

Brown CJ, et al. J Hosp Med, 2009

BARRIER: ENVIRONMENT

“I think it is just that patients, when they are in the hospital, they feel they are supposed to be in bed. And they are more comfortable there and a lot of times they can see the TV better.”

- a Doctor

BARRIERS TO HOSPITAL MOBILITY

PREVALENCE AND OUTCOMES

• 498 hospitalized medical patients, age ≥ 70 years• Mobility scale based on nurse report:

–degree of assistance needed –number of times transferred and ambulated

• Average of mobility observations for each patient, scores trichotomized–Low mobility: bed rest or bed to chair– Intermediate mobility–High mobility

Brown CJ, Friedkin RJ, Inouye SK. J Am Geriatr Soc. 2004.

RISK OF ADVERSE OUTCOMES BY MOBILITY LEVEL

Brown CJ, et al. JAGS 2004

IMPACT OF 10 DAYS OF BED REST IN HEALTHY OLDER ADULTS

Test Pre-Bed Rest

Post-Bed Rest

% Change P value

Knee ExtensionIsometric (N)

144.7 ± 15.1 117.6 ± 13.6 -11.2 ± 3.9 .017

Concentric (N·m/s) 69.9 ± 8.1 60.1 ± 7.0 -13.5 ± 4.4 .011Knee Flexion

Isometric (N)76.8 ±10.0 68.1 ± 10.5 -14.2 ± 3.6 .003

Concentric (N·m/s) 80.3 ± 8.8 71.6 ± 9.4 -11.8 ± 4.6 .03

DEXA Lean Mass, kg

Lower Extremity 15.01 (12.41 to

17.61)

14.06 (11.85 to 16.27)

-0.95 (-0.42 to -

1.48)

.003

% Change -6.3 (-3.1 to -9.5)

Kortebein P, et al. J Gerontol Med Sci , 2008; Kortebein P, et al. JAMA 2007

BEYOND FUNCTIONAL DECLINE

Study of Aging I:1000 Subjects, stratified, random sample of Medicare beneficiaries living in 5 counties in central Alabama

Study over-sampled males, African Americans, and rural residents

Autauga

Baldwin

Barbour

Bibb

Blount

Bullock

Butler

Calhoun

Chambers

Cherokee

Chilton

Choctaw

Clarke

Clay

Cleburne

Coffee

Colbert

Conecuh

Coosa

Covington

Crenshaw

Cullman

Dale

Dallas

De Kalb

Elmore

Escambia

Etowah

Fayette

Franklin

Geneva

GreeneHale

Henry

Houston

Jackson

Jefferson

Lamar

Lauderdale

Lawrence

Lee

Limestone

Lowndes

Macon

Madison

Marengo

Marion

Marshall

Mobile

Monroe

Montgomery

Morgan

Perry

Pickens

Pike

Randolph

Russell

Saint Clair

Shelby

Sumter

Talladega

Tallapoosa

Tuscaloosa

Walker

Washington

Wilcox

Winston

Urban CountiesRural Counties

ALABAMA

Life-Space asks in last 4 weeks: • how far travelled• frequency of travel• need for

assistance from equipment or another person

Scores range 0-120.

Well validated in person and by telephone

Bedroom

Home

Neighborhood

Town

Out of Town

Yard

MEASURING LIFE-SPACE

Sawyer P, et al. JAGS 2003

METHODS

• 211 hospitalizations among 687 participants over 4 years• Surgical admissions = 44; • Non-surgical admissions = 167

• Life-Space Assessment every 6 months• Using multilevel change model to determined

trajectory of Life-Space before and after hospitalization.

LIFE-SPACE TRAJECTORIES

= Surgical admissions = Non-surgical admissions

TESTED INTERVENTIONS

PREVIOUS OUT OF BED PROTOCOLS

• Transporters used to walk patients during quiet periods, especially nights, week-ends1

–Pilot study, demonstrated feasibility only• Nurse driven protocol of progressive

ambulation among patients with pneumonia2

–No functional outcomes assessed

1 Tucker D, et al. Geriatr Nurs. 2004 2 Mundy, et al. Chest, 2003

MOBILIZING OLDER ADULT PATIENTS VIANURSE-DRIVEN INTERVENTION (MOVIN)

Nurse-driven intervention with 5 components: Psychomotor skills training for nurses Increase self-efficacy in determining safety for ambulation

Communication tools White boards for information sharing

Ambulation pathways Pathways with visual markers to measure distance/ add

interest

Ambulation resources Both human and equipment to maximize ambulation

Ambulation culture Establish nurse ownership and sustainability of patient

ambulationKing B, et al, JAGS 2016

RESULTS

SAFETY AND EFFICACY OF A HOSPITAL MOBILITY PROGRAM

• 100 patients from Birmingham VAMC–Not delirious or demented, walking 2 weeks

PTA• Randomly assigned to Mobility Program (MP)

or Usual Care (UC)• Assessments by blinded assessors• One month telephone follow-up• Physicians blinded to assure no change in

usual care (e.g. activity orders, PT consults)

Brown CJ, et al. JAMA Intern Med, 2016

Mobility Program (MP)•Twice daily walks with assistance

•Provision of rolling walker, if needed & safe

•Provision of folder; document goals; track sitting, walking

•Daily motivational interviewing; focus on goals & barriers

Usual Care (UC)•Twice daily friendly visits

•Provision of folders; document friendly messages and track visitors

METHODS

BASELINE CHARACTERISTICS

N = 100 Usual CareWalking Program P value

Age 73.4 ± 7.0 74.4 ± 6.9 0.48Gender, male 49 (98%) 48 (96%) 0.56Race, black 8 (16%) 11 (22%) 0.44LOS, mean 3.6 ± 2.4 4.6 ± 4.0 0.13

median 3.0 3.0GDS 5.0 ± 3.0 4.7 ± 3.2 0.63Charleson Comorbidity 4.1 ± 2.6 4.4 ± 2.4 0.55APACHE 15.3 ± 11.8 14.3 ± 10.6 0.67PT Ordered 17 (34%) 24 (48%) 0.15

MOBILITY TECHS TO INCREASE MOBILITY

• Showed provision of mobility by techs feasible and safe.• 3 in-hospital falls, all in control group

• No change in ADLs; community mobility maintained in MP, and declined in UC.

Usual CareMobility Program P value

Baseline LSA 51.5 (21.1) 53.9 (29.4) 0.4

Post-Hospital LSA 41.6 (21.5) 52.5 (29.0) .0096

P-values for group differences between pre and post hospital outcomes adjusted for baseline, age, gender, race

MOVE TOWARD PRAGMATIC TRIALS

MOBILITY ASSESSMENTS

Attaching monitors not practical due to time and expense.Need method to measure mobility on all hospitalized patients.One available assessment relies on nurse observation of patient mobility. Johns Hopkins Highest Level of Mobility Scale

Hoyer E, J Hosp Med, 2016

VALIDATION OF THE ACUTE CARE MOBILITY ASSESSMENT (ACMA)

• Study Purpose: validate brief self-reported mobility assessment to measure frequency of out-of-bed activity during hospitalization.

• Recruitment:• Cognitively intact hospitalized adults age ≥ 65 years• Able to walk prior to admission

• 63 consented, 12 not used in analysis • lack of at least 22 hours of StepWatch data (n=10) • lack of patient data due to transfer to higher level of

care (n=2)• Accelerometer (StepWatch) worn for 24 hours • Assessments completed after accelerometer data

collected

ASSESSMENTS

Patients• Age• Self-identified gender &

race/ethnicity• Acute Care Mobility

Assessment

Medical Records• Charlson Comorbidity Index

Nurses• Katz index (prior to

admission; current)• Johns Hopkins Highest Level

of Mobility Scale

AnalysisUsed Spearman correlation coefficient comparing steps taken and time spent walking with ACMA and JH-HLM scale

ACUTE CARE MOBILITY ASSESSMENT (ACMA)

BASELINE CHARACTERISTICS

Characteristics (N=51) Mean (SD) or N (%)

Age, years, mean (SD) 74.3 (6.2)Self-identified Gender

FemaleMale

32 (63%)19 (37%)

Self-identified RaceAfrican-American WhiteAsian

29 (57%)20 (39%)2 (4%)

Katz ADL Score Prior to Admission, mean (SD), n=49 11.4 (2.0)Katz ADL Score at Study Entry, mean (SD), n=49 10.3 (2.9)Charlson Comorbidity Index, mean (SD) 1.98 (1.9)Steps Taken, mean (SD)

Range660 (662) 10 - 2831

Johns Hopkins-Highest Level of Mobility Score (n=43) 6.0 (1.3)

PROPORTION OF PATIENTS ACHIEVING EACH LEVEL

N (%) 1X 2X 3X ≥4XSat in chair or side of bed 51

(100%)4

(8%)4

(8%)5

(10%)38

(74%)

Walked in room 51 (100%)

2 (4%)

6 (12%)

4 (8%)

39 (76%)

Walked in hallway 25 (49%)

9 (18%)

4 (8%)

6 (12%)

6 (12%)

Walked off the unit 6 (12%)

2 (4%)

2 (4%)

2 (4%)

0

SPEARMAN CORRELATION

ACMA r p-value JH-HLM r p-valueTotal # of Steps 0.84 <.0001 0.64 <.0001

Total Time Walking 0.67 <.0001 0.54 0.0002

JH-HLM scale 0.59 <.0001

• Most highly correlated included only levels with walking;

• Did not include sitting or need for help.

POTENTIAL REVISION OF ACMA

STRENGTHS/ LIMITATIONS

Strengths:• Done in general medical population, not limited by

disease. • Representation of both genders and white/black (but

not other race/ethnicities). • Easy to complete, takes less than 3 minutes to get

information. Limitations:• Patients have to be cognitively intact enough to

complete scale• Not perfect correlation. • Not tied to outcomes (yet).

HOSPITAL CULTURE CHANGE

CULTURE CHANGE AROUND MOBILITY

Three key elements to culture change:• Team members must be able to articulate

what being proposed.• Team members need to understand the

“Why”.• Leaders define role of team members.

BARRIERS TO HOSPITAL MOBILITY CULTURE CHANGE

• Ownership of mobility unclear • Hospital culture encourages low mobility• Hospital environment encourages low mobility• Healthcare Policy encourages low mobility

OWNERSHIP OF HOSPITAL MOBILITY UNCLEAR

Physical Therapy: • Too few PTs to walk hospitalized patients; often not

skilled needNursing:

• Responsibilities increased significantly; more documentation, less patient care time.

• Many report not feeling comfortable walking patientsFamily:

• Need education and trainingVolunteers:

• Successful in programs like HELP; need robust training program

Transporters: • Successful in small pilot study; have other job

responsibilities

ENVIRONMENT ENCOURAGES LOW MOBILITY

• Not well studied

RE-ENVISIONING HOSPITAL ROOM DESIGN

2017 Environment for Aging (EFA) ConferenceBarbara Miszkiel OAA, MRAIC, LEED AP, EDAC and colleagues

GLOBAL POLICIES ENCOURAGE LOW MOBILITY

• Safety/ Fall Prevention• Falls with injury a “Never Event” per CMS in 20081

• Hospitals responded with robust Fall Prevention programs

• Key components of most fall prevention programs:• Patient to call for assistance prior to out of bed• Patient education regarding fall

prevention• Patient identification as fall risks• Bed and chair alarms

1Inouye, Brown, Tinetti. NEJM 2009

MOBILITY AS QUALITY INDICATOR

• Change focus from Fall Prevention to Safe Mobility• AGS published white paper recommending mobility

as QI measure• Centers for Medicare and Medicaid Innovation

project targets mobility in 300+ hospitals

• John A. Hartford Foundation’s Age-Friendly Health System includes Mobility as one of 4 M’s

UAB MOBILITY INITIATIVE

• Phase 1: Staff education via UAB Learning System• Phase 2: Train-the-Trainers; Focused on coaching• Phase 3: Unit coaching by trainers/championso Address gaps identified by nurse managero 1:1 or group coaching on addressing barrierso Mobility leaders spot check, provide feedback

• Phase 4: Sustainmento “Booster” education provided by mobility teamo Accountability monitoring by Directors, Managerso Mobility in Nursing/PCT orientationo Gait Belt training as part of annual comps

Slides courtesy of Helen Matthews, PT and Kellie Flood, MD

46 DAY MOBILITY TECH PILOT

PILOT: INTERVENTIONS PROVIDED

TAKE HOME POINTS

• Older adults spend significant proportion of hospital stay in bed.

• Many barriers to hospital mobility modifiable.

• Mobility programs have been shown to be feasible, safe and efficacious.

• Culture change is required to integrate hospital mobility as a best practice.

INCREASING MOBILITY IN THE HOSPITAL SETTING

Cynthia J. Brown, MD, MSPHGwen McWhorter, Ed.D., Endowed Chair in Geriatric Medicine

Director, Division of Gerontology, Geriatrics, and Palliative CareDirector, Comprehensive Center for Healthy Aging

Vice Chair, Faculty and Staff Development, Dept of Medicinecynthiabrown@uabmc.edu