Literature DB >> 29777381

Utility of Mayo Clinic's early screen for discharge planning tool for predicting patient length of stay, discharge destination, and readmission risk in an inpatient oncology cohort.

Caitlyn P Socwell1, Lucy Bucci2, Sharni Patchell2, Erika Kotowicz2, Lara Edbrooke2, Rodney Pope3,4.   

Abstract

PURPOSE: To examine the feasibility of using the Mayo Clinic's Early Screen for Discharge Planning (ESDP) tool in determining its predictive ability in an inpatient oncology hospital setting for variables including length of stay (LOS), discharge destination, and readmission risk.
METHODS: A prospective observational study was conducted at a metropolitan tertiary cancer centre in Melbourne, Australia. The ESDP score, along with patient outcomes and characteristics, were collected to examine the relationships between positive and negative ESDP scores and patient outcomes.
RESULTS: A total of 136 participants met inclusion criteria for this study. The proportion with positive ESDP scores was greater in those with unplanned hospital admissions compared with planned admissions (χ2(1, n = 136) = 3.94, p = 0.047). The ESDP status was not a significant predictor of oncology hospital LOS (rpb = 0.116, p = 0.178); however, the ESDP scores did predict discharge destination (χ2(2, n = 136) = 20.22, p < .001). Those re-admitted within 14 days were more likely to have negative ESDP scores than those not readmitted within this time period (χ2(1, n = 136) = 5.22, p = 0.022). Those with positive ESDP scores received a greater number of hospital services whilst admitted than those with negative scores (rpb = 0.388, p < .001) and were more likely to receive particular types of services.
CONCLUSION: The findings from this study suggest that the ESDP tool could be useful in an adult inpatient oncology population in a hospital with defined specialised hospital discharge planning services (SHDCPS). The ESDP may be beneficial for early identification of service types likely to be required in care and likely discharge destination, both of which can assist discharge planning (DP); however, the ESDP was not useful for predicting LOS or readmission risk in the adult inpatient oncology population without a SHDCPS model in place.

Entities:  

Keywords:  Discharge planning; ESDP; Inpatient; Oncology; Patient outcomes

Mesh:

Year:  2018        PMID: 29777381     DOI: 10.1007/s00520-018-4252-8

Source DB:  PubMed          Journal:  Support Care Cancer        ISSN: 0941-4355            Impact factor:   3.603


  13 in total

1.  Development and validation of a screen for specialized discharge planning services.

Authors:  Diane E Holland; Marcelline R Harris; Cynthia L Leibson; V Shane Pankratz; Kathleen E Krichbaum
Journal:  Nurs Res       Date:  2006 Jan-Feb       Impact factor: 2.381

2.  Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

Authors:  Paul A Harris; Robert Taylor; Robert Thielke; Jonathon Payne; Nathaniel Gonzalez; Jose G Conde
Journal:  J Biomed Inform       Date:  2008-09-30       Impact factor: 6.317

3.  Discharge planning reduces length of stay and re-admission rates for older people admitted with a medical condition.

Authors:  Stacey George; Anita Atwal
Journal:  Aust Occup Ther J       Date:  2013-10       Impact factor: 1.856

Review 4.  Use of comprehensive geriatric assessment in older cancer patients: recommendations from the task force on CGA of the International Society of Geriatric Oncology (SIOG).

Authors:  Martine Extermann; Matti Aapro; Roberto Bernabei; Harvey Jay Cohen; Jean-Pierre Droz; Stuart Lichtman; Vincent Mor; Silvio Monfardini; Lazzaro Repetto; Liv Sørbye; Eva Topinkova
Journal:  Crit Rev Oncol Hematol       Date:  2005-09       Impact factor: 6.312

5.  Poor discharge planning causes huge rise in adverse incidents.

Authors:  Petra Kendall-Raynor
Journal:  Nurs Stand       Date:  2016-05-18

6.  Comprehensive geriatric assessment: a meta-analysis of controlled trials.

Authors:  A E Stuck; A L Siu; G D Wieland; J Adams; L Z Rubenstein
Journal:  Lancet       Date:  1993-10-23       Impact factor: 79.321

7.  Preventability of emergent hospital readmission.

Authors:  S E Frankl; J L Breeling; L Goldman
Journal:  Am J Med       Date:  1991-06       Impact factor: 4.965

8.  Standardizing hospital discharge planning at the Mayo Clinic.

Authors:  Diane E Holland; Michele A Hemann
Journal:  Jt Comm J Qual Patient Saf       Date:  2011-01

Review 9.  Reducing hospital readmission rates: current strategies and future directions.

Authors:  Sunil Kripalani; Cecelia N Theobald; Beth Anctil; Eduard E Vasilevskis
Journal:  Annu Rev Med       Date:  2013-10-21       Impact factor: 13.739

Review 10.  Discharge planning from hospital to home.

Authors:  Sasha Shepperd; Natasha A Lannin; Lindy M Clemson; Annie McCluskey; Ian D Cameron; Sarah L Barras
Journal:  Cochrane Database Syst Rev       Date:  2013-01-31
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  2 in total

1.  Explainable Tree-Based Predictions for Unplanned 30-Day Readmission of Patients With Cancer Using Clinical Embeddings.

Authors:  Chi Wah Wong; Chen Chen; Lorenzo A Rossi; Monga Abila; Janet Munu; Ryotaro Nakamura; Zahra Eftekhari
Journal:  JCO Clin Cancer Inform       Date:  2021-02

2.  An Early Screening Tool for Discharge Planning Shortened Length of Hospital Stay for Elderly Patients with Community-Acquired Pneumonia.

Authors:  Hao Chen; Yu Hara; Nobuyuki Horita; Yusuke Saigusa; Takeshi Kaneko
Journal:  Clin Interv Aging       Date:  2021-03-10       Impact factor: 4.458

  2 in total

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