Diese Präsentation wurde erfolgreich gemeldet.
Wir verwenden Ihre LinkedIn Profilangaben und Informationen zu Ihren Aktivitäten, um Anzeigen zu personalisieren und Ihnen relevantere Inhalte anzuzeigen. Sie können Ihre Anzeigeneinstellungen jederzeit ändern.

Publication bias in service delivery research: a critique - John Ovretveit

Dr John Ovretveit's critique on Dr Yen-Fu Chen's presentation on publication bias in service delivery research for the CLAHRC WM Scientific Advisory Group, 10th June 2015, Birmingham, UK

  • Loggen Sie sich ein, um Kommentare anzuzeigen.

  • Gehören Sie zu den Ersten, denen das gefällt!

Publication bias in service delivery research: a critique - John Ovretveit

  1. 1. Publication Bias 1 John Øvretveit, Director of Research, Professor of Health Innovation and Evaluation, Karolinska Institutet, Stockholm, Sweden 6/12/2015
  2. 2. Key points QI interventions - many sites 5-10% average - uncertain attribution = no publish But high variation between sites 1) Bias to internal validity rather than external 2) Bias against adaptive implementation action evaluation & practitioner partnership research (audit) 3) Bias to intervention research rather than descriptive explanatory & multi-method26/12/2015
  3. 3. RCT of intervention to implement guidelines for management of urinary tract infection and sore throat  Trial found average little change, But variation 36/12/2015 Why did these change so much?
  4. 4. Process evaluation in parallel to RCT “A combination of organizational problems … and lack of time and engagement …is the most viable explanation for the lack of effect”  agreement with guidelines;  degree of participation in the project;  taking time to discuss the guidelines and their implementation;  use of the components of the interventions;  procedures for telephone consultations;  communication within each practice. 46/12/2015
  5. 5. Under-used “top- and bottom- 5” analysis  Prospective theory-informed  Which sites would you expect better performance and why  Retrospective investigation  Informant’s theories  Researchers analysis  Bias against explanatory and favors quantitative statistical association  All Biases = less relevant to practitioners 5
  6. 6. 6/12/2015 6 What do you think? Surprises? My examples / experience?