title: The Stroke Prevention Patient Outcomes Research Team. Goals and methods.
abstract: OBJECTIVE
  The aim of the present study, based at Duke University and involving 14 other institutions, is to identify the most appropriate and cost-effective clinical strategies for prevention of ischemic (thrombotic or embolic) stroke in high-risk individuals and to design and test an intervention to disseminate this information to providers and the public.
  
  
  METHODS
  The study uses (1) secondary data from literature review, Medicare claims, and population-based data from three epidemiological studies and (2) primary data generated in national physician and patient surveys and in demonstration trials. Phases I through III involve data collection and analysis using a decision/cost-effectiveness model and consensus development methods. Phase IV includes intervention in physicians' practice patterns. Data is collected by literature survey and abstraction, review of medical records, claims analysis, and patient and physician surveys.
  
  
  CONCLUSIONS
  A structured decision model and a well-defined clinical focus provide a successful organization for a PORT on stroke prevention.
authors.affiliation: Center for Health Policy Research and Education, Duke University, Durham, NC.
authors.forename: D B
authors.initials: DB
authors.lastname: Matchar
authors.forename: P W
authors.initials: PW
authors.lastname: Duncan
authors.forename: G P
authors.initials: GP
authors.lastname: Samsa
authors.forename: J P
authors.initials: JP
authors.lastname: Whisnant
authors.forename: G H
authors.initials: GH
authors.lastname: DeFriese
authors.forename: D J
authors.initials: DJ
authors.lastname: Ballard
authors.forename: J E
authors.initials: JE
authors.lastname: Paul
authors.forename: D M
authors.initials: DM
authors.lastname: Witter
authors.forename: J P
authors.initials: JP
authors.lastname: Mitchell
mesh_terms: D002561:Cerebrovascular Disorders / Q000517:prevention & control*; D003362:Cost-Benefit Analysis; D003625:Data Collection; D003663:Decision Trees; D006801:Humans; D007256:Information Systems; D006278:Medicare; D017063:Outcome Assessment, Health Care; D012307:Risk Factors; D014481:United States