Literature DB >> 9357610

Inducing practice guidelines from a hospital database.

K C Abston1, T A Pryor, P J Haug, J L Anderson.   

Abstract

Improving health care quality requires the elimination of unnecessary variation in the care process. Decision support applications already exist that can foster adherence to standards. The challenge resides in developing standards consistent with good medical practice. In this paper we present our efforts in determining where sufficient clinical data are captured electronically to automatically define a care process, and what analyses can be done to identify additional data that would allow a care process to be defined. Data routinely collected by a hospital information system have been examined. The analysis tools utilized include logistic regression, a neural network, a Bayesian network, and a rule induction program.

Mesh:

Year:  1997        PMID: 9357610      PMCID: PMC2233591     

Source DB:  PubMed          Journal:  Proc AMIA Annu Fall Symp        ISSN: 1091-8280


  14 in total

1.  The analysis of humongous databases: problems and promises.

Authors:  C J McDonald; S L Hui
Journal:  Stat Med       Date:  1991-04       Impact factor: 2.373

Review 2.  Practice databases and their uses in clinical research.

Authors:  W M Tierney; C J McDonald
Journal:  Stat Med       Date:  1991-04       Impact factor: 2.373

Review 3.  Practice guidelines, a new reality in medicine. II. Methods of developing guidelines.

Authors:  S H Woolf
Journal:  Arch Intern Med       Date:  1992-05

4.  Using routinely collected data for clinical research.

Authors:  C Safran
Journal:  Stat Med       Date:  1991-04       Impact factor: 2.373

5.  Practice policies: where do they come from?

Authors:  D M Eddy
Journal:  JAMA       Date:  1990-03-02       Impact factor: 56.272

6.  Concept formation vs. logistic regression: predicting death in trauma patients.

Authors:  M Hadzikadic; A Hakenewerth; B Bohren; J Norton; B Mehta; C Andrews
Journal:  Artif Intell Med       Date:  1996-10       Impact factor: 5.326

7.  Continuous improvement as an ideal in health care.

Authors:  D M Berwick
Journal:  N Engl J Med       Date:  1989-01-05       Impact factor: 91.245

8.  Practice guidelines and practicing medicine. Are they compatible?

Authors:  R H Brook
Journal:  JAMA       Date:  1989-12-01       Impact factor: 56.272

9.  Guidelines you can follow and can trust. An ideal and an example.

Authors:  C J McDonald; J M Overhage
Journal:  JAMA       Date:  1994-03-16       Impact factor: 56.272

10.  Use of a neural network as a predictive instrument for length of stay in the intensive care unit following cardiac surgery.

Authors:  J V Tu; M R Guerriere
Journal:  Comput Biomed Res       Date:  1993-06
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  3 in total

1.  Medical decision support using machine learning for early detection of late-onset neonatal sepsis.

Authors:  Subramani Mani; Asli Ozdas; Constantin Aliferis; Huseyin Atakan Varol; Qingxia Chen; Randy Carnevale; Yukun Chen; Joann Romano-Keeler; Hui Nian; Jörn-Hendrik Weitkamp
Journal:  J Am Med Inform Assoc       Date:  2013-09-16       Impact factor: 4.497

2.  Type 2 diabetes risk forecasting from EMR data using machine learning.

Authors:  Subramani Mani; Yukun Chen; Tom Elasy; Warren Clayton; Joshua Denny
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

3.  Using data mining techniques to explore physicians' therapeutic decisions when clinical guidelines do not provide recommendations: methods and example for type 2 diabetes.

Authors:  Massoud Toussi; Jean-Baptiste Lamy; Philippe Le Toumelin; Alain Venot
Journal:  BMC Med Inform Decis Mak       Date:  2009-06-10       Impact factor: 2.796

  3 in total

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