Analysing homogenous patient journeys to assess quality of care for patients admitted outside of their 'home-ward'

This study is the first to explore the quality of care based on the outlier or the inlier status of patients for a large heterogeneous General Medicine (GM) service at a busy public hospital. The study compared the quality of care between ward outliers and ward inliers based on a homogenous group of patients using Two-step clustering method. Contrary to common perception, ward outliers had overall shorter Length of Stay (LOS) than ward inliers. The study also was unable to support the perception of shorter LOS in the outlier group being associated with higher in-hospital mortality. The study confirmed that overall the outliers received inferior quality of care as discharge summaries for the outliers were delayed and more outliers were re-admitted within 7 days of discharge in comparison to the inliers.

[1]  Shaowen Qin,et al.  Gaining insight from patient journey data using a process-oriented analysis approach , 2012 .

[2]  George Braitberg,et al.  Emergency department overcrowding: dying to get in? , 2007, The Medical journal of Australia.

[3]  M. Beland,et al.  Charlson Comorbidity Index predicts patient outcome, in cases of inoperable non-small cell lung cancer treated with radiofrequency ablation. , 2012, European journal of radiology.

[4]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[5]  Douglas A Luke,et al.  Getting the Big Picture in Community Science: Methods That Capture Context , 2005, American journal of community psychology.

[6]  Brian Everitt,et al.  Cluster analysis , 1974 .

[7]  M. Sarstedt,et al.  A Concise Guide to Market Research , 2019, Springer Texts in Business and Economics.

[8]  D. Richardson,et al.  Increase in patient mortality at 10 days associated with emergency department overcrowding , 2006, The Medical journal of Australia.

[9]  T. Yong,et al.  Timeliness in discharge summary dissemination is associated with patients' clinical outcomes. , 2013, Journal of evaluation in clinical practice.

[10]  Naren Gunja,et al.  Senior Streaming Assessment Further Evaluation after Triage zone: A novel model of care encompassing various emergency department throughput measures , 2012, Emergency medicine Australasia : EMA.

[11]  Karen Grace-Martin,et al.  Data analysis with SPSS , 1998 .

[12]  Paul Stolee,et al.  K-means cluster analysis of rehabilitation service users in the Home Health Care System of Ontario: examining the heterogeneity of a complex geriatric population. , 2012, Archives of physical medicine and rehabilitation.

[13]  Wil M. P. van der Aalst,et al.  Process Mining Techniques: an Application to Stroke Care , 2008, MIE.

[14]  Peter Aitken,et al.  Demand for public hospital emergency department services in Australia: 2000–2001 to 2009–2010 , 2012, Emergency medicine Australasia : EMA.

[15]  W. Hammond,et al.  Computerized decision support based on a clinical practice guideline improves compliance with care standards. , 1997, The American journal of medicine.

[16]  Alexander Kolker,et al.  Process Modeling of Emergency Department Patient Flow: Effect of Patient Length of Stay on ED Diversion , 2008, Journal of Medical Systems.

[17]  Heather Wharrad,et al.  Going paperless at the emergency department: A socio-technical study of an information system for patient tracking , 2011, Int. J. Medical Informatics.

[18]  P. Sopp.  Cluster analysis. , 1996, Veterinary immunology and immunopathology.

[19]  Peter C. Austin,et al.  Effect of discharge summary availability during post-discharge visits on hospital readmission , 2002, Journal of General Internal Medicine.

[20]  Diogo R. Ferreira,et al.  Business process analysis in healthcare environments: A methodology based on process mining , 2012, Inf. Syst..

[21]  Boudewijn F. van Dongen,et al.  Business process mining: An industrial application , 2007, Inf. Syst..

[22]  J W Thomas,et al.  Is patient length of stay related to quality of care? , 1997, Hospital & health services administration.