Linked Life Data

10386082

Source:http://linkedlifedata.com/resource/pubmed/id/10386082

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6 Suppl
pubmed:dateCreated
1999-7-2
pubmed:abstractText
Increasingly, physicians are attempting to incorporate best evidence into their clinical decision making. However, best evidence takes a variety of forms, including clinical trials, cohort studies, administrative data, and patient preference data. Incorporating multiple data sources in a way that informs complex clinical decisions is a substantial analytical challenge. One approach to this challenge is to develop a simulation/decision model that explicitly represents the natural history of disease and the impact of treatments on that natural history. The model should be requisite--that is, sufficient in form to address the decision problem--but not overly complex. Such a model can be of value because it (1) allows a variety of viewpoints to be considered, (2) incorporates the best scientific evidence, and (3) permits sensitivity analyses to evaluate the impact of alternative clinical scenarios and uncertainty in model inputs. The Stroke Prevention Policy Model (SPPM) illustrates this approach. The SPPM is a simulation model designed to predict the best among various treatment alternatives for preventing strokes. Similar models can be applied to treatment outcomes for liver disease.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0270-9139
pubmed:author
pubmed:issnType
Print
pubmed:volume
29
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
36S-39S
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Using outcomes data to identify best medical practice: the role of policy models.
pubmed:affiliation
Center for Clinical Health Policy Research, Duke University Medical Center, Durham, NC 27705, USA. match001@mc.duke.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.