Australian Health Review Australian Health Review Society
Journal of the Australian Healthcare & Hospitals Association
RESEARCH ARTICLE

Effective discharge planning – timely assignment of an estimated date of discharge

Lixin Ou A B , Jack Chen A , Lis Young A , Nancy Santiano A , La-Stacey Baramy A and Ken Hillman A
+ Author Affiliations
- Author Affiliations

A Simpson Centre for Health Services Research, The University of New South Wales, Locked Bag 7103, Liverpool BC, NSW 1871, Australia. Email: jackchen@unsw.edu.au; lis.young@sswahs.nsw.gov.au; nancy.santiano@sswahs.nsw.gov.au; la-stacey.baramy@sswahs.nsw.gov.au; ken.hillman@sswahs.nsw.gov.au

B Corresponding author. Email: lixin.ou@unsw.edu.au

Australian Health Review 35(3) 357-363 https://doi.org/10.1071/AH09843
Submitted: 13 October 2009  Accepted: 7 November 2010   Published: 25 August 2011

Abstract

Objective. To examine the implementation of estimated date of discharge (EDD) for planned admissions and admissions via the emergency department, to assess the variance between EDD and the actual date of discharge (ADD), and to explore the determinants of delayed discharge in a tertiary referral centre, Sydney, Australia.

Methods. Primary data from a convenience sample of 1958 admissions for allocation of EDDs were linked with administrative data. The window for assigning EDDs for planned admissions was 24 h, for admissions via the emergency department it was 48 h. Logistic regression models were used to examine the key factors associated with an EDD being assigned within 24 h or 48 h of an admission. An ordinal logistic regression model was used to explore the determinants of delayed discharge.

Results. Only 13.4% of planned admissions and 27.5% of admissions via the emergency department were allocated a timely EDD. Older patients, patients with significant burdens of chronic morbidity (OR = 0.903; P = 0.011); and patients from a non-English-speaking background (OR = 0.711; P = 0.059) were less likely to be assigned a timely EDD. The current Charlson Index score was a significant predictor of a positive variance between EDD and ADD.

Conclusions. The prevalence of the timely assignment of an EDD was low and was lowest for planned admissions. The current Charlson Index score is an effective tool for identifying patients who are more likely to experience delayed discharge.

What is known about the topic? Failure to assign an EDD is one of the major barriers to implementing effective discharge. Establishing an EDD for a patient within 24 h of an admission is thought to be a measure of efficient and high quality discharge planning.

What does this paper add? Older patients, patients with significant burdens of chronic morbidity, and patients from a non-English-speaking background were less likely to be assigned a timely EDD. The current Charlson Index score was a significant predictor of a positive variance between EDD and ADD.

What are the implications for practitioners? A significant gap existed between policy and the implementation of assigning EDD in a large sample of discharges. Effective discharge planning may be obstructed by failure to assign an EDD at the time of admission.

Additional keywords: admission, length of stay, elderly.


References

[1]  Ibrahim J, Buick M, Majoor J, McNeil J. Performance Indicators for Effective Discharge. Melbourne: Acute Health Division, Victorian Government Department of Human Services; 2000.

[2]  Rudd C, Smith J. Discharge planning. Nurs Stand 2002; 17 33–7.

[3]  Shared responsibility for patient care between hospitals and community-an effective discharge policy. Sydney: NSW Department of Health; 2001.

[4]  Waters K. Discharge planning: an explorative study of the process of discharge planning on geriatric wards. J Adv Nurs 1987; 12 71–83.
Discharge planning: an explorative study of the process of discharge planning on geriatric wards.CrossRef | 1:STN:280:DyaL2s7jvVOqtA%3D%3D&md5=d81908febde72f9725ec62330890d954CAS |

[5]  Managing Beds Better Balancing Supply and Demand. Canberra: Commonwealth Department of Health and Aged Care; 1999.

[6]  Achieving timely simple discharge from hospital: a toolkit for the multi-disciplinary team. London: Department of Health; 2004.

[7]  Supplementary Information for the Effective Discharge Strategy Performance Indicators Audit. Melbourne: Department of Human Services, Victoria Health; 2001.

[8]  Lees L, Delpino R. Facilitating an effective discharge from hospital. Nurs Times 2007; 103 30–1.

[9]  Discharge Planning: Responsive Standards (Revised May 2007). Sydney: NSW Department of Health; 2007.

[10]  Houghton A, Bowling A, Clarke KD, Hopkins AP, Jones I. Does a dedicated discharge coordinator improve the quality of hospital discharge? Qual Health Care 1996; 5 89–96.
Does a dedicated discharge coordinator improve the quality of hospital discharge?CrossRef | 1:STN:280:DyaK283pt1Srtw%3D%3D&md5=b3eb43aa6757845352d9dd92b2c4d946CAS |

[11]  Liverpool Health Service Corporate Policy Manual: Patient Flow Management. Sydney: Liverpool Health Service, Liverpool Hospital; 2004.

[12]  Health Information Exchange. Sydney: NSW Department of Health; 2005.

[13]  Statistical Clearing House. Sydney: NSW Department of Health; 2006.

[14]  Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies development and validation. J Chron Dis 1987; 40 373–83.
| 1:STN:280:DyaL2s7ms1GnsQ%3D%3D&md5=e096c71d0db0a32098ec1454d199e6b8CAS |

[15]  Romano PS, Roost LL, Jollis JG. Presentation adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol 1993; 46 1075–9.
Presentation adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives.CrossRef | 1:STN:280:DyaK2c%2FhsFWrsw%3D%3D&md5=4ab2a63b168f8b4e376c4fb6512bcd69CAS |

[16]  Bed management demand and discharge predictors: supporting the wait for a bed checklist & bed management toolkit. London: Department of Health; 2004.

[17]  Effective Discharge Strategy Performance Indicators Definitions and Reporting Guide. Melbourne: Department of Human Services, Victoria Health; 2002.

[18]  Lees L, Holmes C. Estimating date of discharge at ward level: a pilot study. Nurs Stand 2005; 19 40–3.

[19]  D’Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: the Charlson comorbidity index. Methods Inf Med 1993; 32 382–7.
| 1:STN:280:DyaK2c7isF2ltg%3D%3D&md5=1145f8568b08db6a5d38ba755452acbcCAS |

[20]  Sundararajan V, Henderson T, Perry C, Muggivan A, Quan H, Ghali WA. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol 2004; 57 1288–94.
New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality.CrossRef |

[21]  Anthony MK, Hudson-Barr DC. Successful patient discharge. A comprehensive model of facilitators and barriers. J Nurs Adm 1998; 28 48–55.
Successful patient discharge. A comprehensive model of facilitators and barriers.CrossRef | 1:STN:280:DyaK1c7osFagug%3D%3D&md5=03684fbceda4141002970eb8f05d5c55CAS |

[22]  Rothman KJ, Greenland S, Winters R. Modern Epidemiology. Philadelphia, PA: Lippincott-Raven; 1998.



Export Citation Cited By (4)

View Altmetrics