Mobility Outcomes At 2 Small Hospitals in the Mid North Coast of NSW Stephen Downs Jodie Marquez Pauline Chiarelli

Research Questions Change in balance Relationship between diagnosis and change in balance Accuracy of physiotherapist’s estimates of change Relationship between balance and discharge destination

Mid North Coast NSW

Exclusions: <16 years old Orthopedically unable to FWB on both legs Medically unfit to test balance testing Unable to understand balance testing instructions Unable to provide informed consent Expected to have a very short length of stay. Ethics: Approved by the North Coast Area Health Service and the University of Newcastle Human Research Ethics Committees

Baseline and Discharge Balance Score Physiotherapist’s Estimate of Change Clinically Significant conditions Discharge Destination Number of Physio interventions Recorded

Clinically Significant Conditions Condition affects mobility Or Condition was reason for admission Carer availability also noted

Berg Balance Scale (BBS) 14 parts each 0-4 (possible total 56 higher score is better) Reliable – Berg, et al 1989; Liaw et al (2008) Minimal detectable change (95%) – Donoghue et al (2009) Predicts Falls – Hall et al (2001)

173 Potential participants 131 Met Criteria 30 Declined 101 Enrolled 42 didn’t meet criteria 12 Lost 89 Completed Study

42 Patients did not meet the inclusion criteria : 2 were acutely unwell 2 were end stage palliative care 15 were not fully weight bearing 9 were too confused to follow instructions 14 were expected to be discharged after such a short time that the baseline and discharge measures could not be reasonably expected to change

173 Potential participants 131 Met Criteria 30 Declined 101 Enrolled 42 didn’t meet criteria 12 Lost 89 Completed Study

12 were lost from the study 1 became acutely unwell and was transferred to an acute care hospital 1 was too acutely unwell on the day of discharge to allow BBS testing 7 were lost to follow up 1 had too short a length of stay 3 withdrew

Age distribution of participants (mean = 80.95)

Conditions 40 Fall 33 Dementia 33 Cardiac/Resp/ Vascular 24 Infection 20Musculoskeletal 20 Delirium 19 Other Neurological 13 Depression 13 Stroke 9 Joint Replacement 9 # Proximal Femur 6 Palliative Care 1 # Pelvis None of these conditions predicted how much the BBS would change or accuracy of physiotherapist’s estimate

Pre Admission Status D/C to Community D/C to Hostel D/C to Nursing Home Community (81)64 (79%)4 (5%)13 (16%) Hostel (5)02(40%)3(60%) Nursing Home (3)003(100%)

Mean Change in BBS Baseline Mean (sd) Discharge Mean (sd) Mean change in BBS (sd) (5.86) (15.10) 8.47 (10.37) 95% CI The change was significant at p<0.001 but the 2 hospitals did not have significantly different changes in BBS (p=0.45)

Describing physiotherapy intervention (average intervention rate 3.65 per week)

Accuracy of initial physiotherapist prediction of discharge BBS (n=83 ) On average physio estimates were underestimates Average error 1.73 (sd 9.4) 95% CI (sd 6.49)

Probability of discharge to nursing home compared to Baseline BBS Observed —— Predicted ……. 95% confidence limit

Probability of discharge to nursing home compared to Final BBS Observed —— Predicted ……. 95% confidence limit

Days Under Care / Change in BBS

What Does This Study Add? Relationship between BBS and D/C destination Number of physio interventions How BBS changes Prevalence of various conditions Physios provide useful estimates of change

Limitations Generalisability No follow up Causality not shown Not enough power to predict changes from diagnosis

So What? We have an ageing population BBS-Nursing home connection Variable change – wait before placing Physio predictions of change useful