Literature DB >> 16450628

Combining data mining tools with health care models for improved understanding of health processes and resource utilisation.

Paul Harper1.   

Abstract

Variability and uncertainty are inherent characteristics of most health care processes. Patient pathways and dwelling times even within the same process typically vary from patient to patient, such as the flow of patients through a particular health care provider or patient progression through the natural history of a given disease. The challenge for the OR modeller is to adequately handle and capture the stochastic features within developed models. This paper will discuss the benefits of combining patient classification tools (data mining techniques) with developed OR models, such as simulation tools, to more accurately capture patient outcomes, risks and resource needs. Illustrative applications will demonstrate the approach.

Entities:  

Mesh:

Year:  2005        PMID: 16450628

Source DB:  PubMed          Journal:  Clin Invest Med        ISSN: 0147-958X            Impact factor:   0.825


  2 in total

1.  Modeling the patient journey from injury to community reintegration for persons with acute traumatic spinal cord injury in a Canadian centre.

Authors:  Argelio Santos; James Gurling; Marcel F Dvorak; Vanessa K Noonan; Michael G Fehlings; Anthony S Burns; Rachel Lewis; Lesley Soril; Nader Fallah; John T Street; Lise Bélanger; Andrea Townson; Liping Liang; Derek Atkins
Journal:  PLoS One       Date:  2013-08-30       Impact factor: 3.240

2.  Multidisciplinary Collaboration in the Treatment of Patients With Type 2 Diabetes in Primary Care: Analysis Using Process Mining.

Authors:  Tania Conca; Cecilia Saint-Pierre; Valeria Herskovic; Marcos Sepúlveda; Daniel Capurro; Florencia Prieto; Carlos Fernandez-Llatas
Journal:  J Med Internet Res       Date:  2018-04-10       Impact factor: 5.428

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.