Tash Brusco - Cabrini Health - Factors that Predict Discharge Destination for Patients in a Transition Care Program

Factors to predict discharge des/na/on in the

Transi/on Care Program Authors:

Natasha K Brusco 1,2, Nicholas F Taylor1,2, Natalie A de Morton1,3, Ilana

Hornumg4, Anna Smith5, Kate Lawler2, Lauri Wood6, Shanandoah Schaffers7

1, La Trobe University; 2, Eastern Health; 3, Northern Health; 4, Western Health; 5, Southern Health; 6, Echuca Health; 7, Peninsula Health

Acknowledgements

• The concept and iniIaIon of this project was via the Victorian Physiotherapy TransiIon Care Program Network. We acknowledge the 11 TransiIon Care Program managers and Physiotherapy site managers of the included sites for the support of their staff to parIcipate in the study.

• Eastern Health Allied Health Research Scholarship provided project lead hours over a 12 month period that greatly assisted in facilitaIng and co-‐ordinaIng the project (NB) and La Trobe University.

Presen/ng 2 separate published papers

• The de Morton Mobility Index (DEMMI) provides a valid method for measuring and monitoring the mobility of paIents making the transiIon from hospital to the community: an observaIonal study • Natalie A. De Morton, Natasha K. Brusco, Lauri Wood, Katherine Lawler, and Nicholas F. Taylor.

"The de Morton Mobility Index (DEMMI) provides a valid method for measuring and monitoring the mobility of paIents making the transiIon from hospital to the community: an observaIonal study." Journal of physiotherapy 57, no. 2 (2011): 109-‐116

• Factors that predict discharge desInaIon for paIents in transiIonal care: a prospecIve observaIonal cohort study • Natasha K. Brusco, Nicholas F. Taylor, Ilana Hornung, Shanandoah Schaffers, Anna Smith, and

Natalie A. de Morton. "Factors that predict discharge desInaIon for paIents in transiIonal care: a prospecIve observaIonal cohort study." Australian Health Review 36, no. 4 (2012): 430-‐436.

Background – Paper 1 The DEMMI

• NaIonal Program established 2004 / 2005 • Mandatory use of the MBI on admission and discharge to the program

• de Morton Mobility Index developed in 2008 • Research QuesIons:

• Does the DEMMI have the properIes required to measure and monitor the mobility of TCP paIents?

• Are DEMMI scores valid when applied by an allied health assistant to TCP paIents?

• How does the DEMMI compare to the MBI?

Methods – Paper 1 The DEMMI

• The 14 TCPs across Tasmania and Victoria invited to parIcipate

• Full Human Research Ethics approval required

• MulI-‐centre prospecIve cohort observaIonal study • Baseline and discharge data collected • 6 month data collecIon period from October 2009 unIl April 2010

• Inclusion and exclusion criteria applied

Methods – Paper 1 The DEMMI

• MBI • 10 items ordinal scale 0 – 100 • Higher scores indicate greater independence in the domains of mobility, personal care and conInence

• Well validated • DEMMI • Mobility outcome measure recently developed • 15 items interval level scale from 0 – 100 • 8.8 minutes to complete

Results – Paper 1 The DEMMI

• 11 of the 14 sites were included • 696 parIcipants • Mean age 81.9 (SD8.7), 40.5% male • TCP segng was 39.3% hospital based, 41.3% residenIal, 20.9% community based

• Mean LOS 42.3 (SD29.6) • Discharge desInaIon was 39.0% home, 14.7% LLRC, 46.3% HLRC

• Change score DEMMI 6.4 (13.9), MBI 4.0 (22.0)


• The DEMMI and MBI are both valid measures of acIvity limitaIon for TCP paIents

• The DEMMI has a broader scale width than the MBI, provides interval level measurement and is significantly more responsive to change than the MBI for measuring the mobility of TCP paIents

• DEMMI items performed consistently regardless of whether a physiotherapist or AHA administered the assessment

• This adds to the current literature by introducing a valid measure of mobility for physiotherapists in TCP that can also be delegated for administered by an AHA, as well as validaIng the current use of the MBI within TCP



• Minimal clinically important difference

• Analysed change in DEMMI / MBI score versus self reported change (self report scale with “much bejer” opIon)

• DEMMI change of 12 is a MCID • MBI change of 13 is a MCID

Background – Paper 2 Discharge Predic/on

• Guidelines require low intensity allied health therapy • Research QuesIons: • What are the factors that predict the discharge desInaIon for paIents in the TCP?

• What are the factors that predict the discharge mobility and funcIonal status for paIents in the TCP?

• What are the factors that predict the length of stay for paIents in the TCP?

Methods – Paper 2 Discharge Predic/on

• Discharge desInaIon • Home • Low Level ResidenIal Care • High Level ResidenIal Care • Other (acute, rehabilitaIon, death)


• Modified Barthel Index • DEMMI • Length of Stay • Baseline factors recorded: • Age, gender, diagnosis, Aged Care Assessment Service classificaIon, admigng facility (acute facility, sub-‐acute facility, community segng), TCP segng, co-‐morbidiIes as a measure of the Charlson Co-‐morbidiIes Index, gait aid on admission, Modified Barthel Index and DEMMI, number of physiotherapy sessions, raIo of physiotherapists to paIents in the program


• StaIsIcal analysis • Regression modeling techniques • Baseline variable were used as potenIal covariates

• The relaIonship between intensity physiotherapy staffing raIo and physiotherapy sessions received each week was explored with Pearson’s product moment correlaIon

Results – Paper 2 Discharge Predic/on

• As per previous paper for the paIent and program demographics

• Physiotherapy could be provided by a physiotherapist or an allied health assistant

• Average physiotherapy sessions per week 2.0 (SD1.8) • Average staffing raIo was 0.06 (SD 0.04) (~1 physio to 18 paIents), with a range of 0.02 (~1 physio to 50 paIents) to 0.18 (~1 physio to 6 paIents)


• Primary outcome

• PaIents discharged home – on admission LLRC assessment and a higher physiotherapy staffing raIo

• PaIents discharged to LLRC – on admission higher DEMMI score, older age and lower physiotherapy staffing raIo

• PaIents discharged to HLRC – on admission HLRC assessment and lower physiotherapy staffing raIo


• Secondary outcomes

• Higher discharge mobility status – on admission higher mobility status and higher physiotherapy staffing raIo

• Higher discharge funcIonal status – on admission higher funcIonal status and higher physiotherapy staffing raIo


• Secondary outcomes cont.

• Shorter length of stay – on admission TCP in the hospital segng and higher physiotherapy staffing raIo

• The physiotherapy staffing raIo had a Pearsons correlaIon of 0.8 with the intensity of physiotherapy received

Discussion

• Supports validity of the DEMMI for measuring and monitoring the mobility of paIents making the transiIon from hospital to the community

• The moderate correlaIon between the DEMMI and the MBI demonstrates that they serve different purposes • Uni-‐dimensional measure of mobility versus independence in acIviIes of daily living

• Allied Health Assistant versus Physiotherapist • Workforce implicaIons

Discussion

• Physiotherapy staffing raIo was a consistent factor that predicted discharge desInaIon to home, LLRC, HLRC.

• This raIo, highly correlated to the number of physiotherapy sessions received by the paIent

• Results of this study does not mean that the increased staff raIo caused the posiIve outcomes, although this is one possible explanaIon

• Results consistent with the 2008 NaIonal EvaluaIon of the TCP, higher Allied Health = bejer outcomes

Discussion

• Strengths • Large scale prospecIve observaIonal study including 11 of the 14 TCPs in Victoria and Tasmania

• This was 17% of the NaIonal TCPs at the Ime • Similar characterisIcs as those reported in the 2008 NaIonal EvaluaIon of the TCP

• Therefore careful generalisaIon is allowed • High quality, achieving 6 of the 7 relevant criteria for an observaIonal study

Discussion

• LimitaIons

• Care not to infer causaIon from observed relaIonships

• Not an intervenIon trial • Only included paIents with ongoing physiotherapy intervenIon, and those discharged within the 6 month period

• Did not report other factors that may influence outcomes, e.g. social support

Conclusion

• The DEMMI and MBI are both valid measures of acIvity limitaIon in the TCP

• This study has validated the DEMMI for measuring and monitoring the mobility of paIents in TCP

• Broad scale width that captures the diverse range of mobility levels

• DEMMI is more responsive to change than the MBI

Conclusion

• Factors on admission to the TCP that predict discharge home include an ACAS classificaIon of “home with support” as well as a higher physiotherapy staffing raIo

• The higher physiotherapy staffing raIo also predicted higher discharge mobility and funcIonal status

• A shorter LOS was predicted with a TCP segng in the hospital and a higher physiotherapy staffing raIo

Thankyou

Tash Brusco Manager of Physiotherapy Services

e: [email protected] m: 0408 251 124

Health & Medicine

Tash Brusco - Cabrini Health - Factors that Predict Discharge Destination for Patients in a Transition Care Program