OBJECTIVES: Drug safety surveillance using observational data requires valid adverse event, or health outcome of interest (HOI) measurement. The objectives of this study were to develop a method to review HOI definitions in claims databases using (1) web-based digital tools to present de-identified patient data, (2) a systematic expert panel review process, and (3) a data collection process enabling analysis of concepts-of-interest that influence panelists' determination of HOI. METHODS: De-identified patient data were presented via an interactive web-based dashboard to enable case review and determine if specific HOIs were present or absent. Criteria for determining HOIs and their severity were provided to each panelist. Using a modified Delphi method, six panelist pairs independently reviewed approximately 200 cases across each of three HOIs (acute liver injury, acute kidney injury, and acute myocardial infarction) such that panelist pairs independently reviewed the same cases. Panelists completed an assessment within the dashboard for each case that included their assessment of the presence or absence of the HOI, HOI severity (if present), and data contributing to their decision. Discrepancies within panelist pairs were resolved during a consensus process. RESULTS: Dashboard development was iterative, focusing on data presentation and recording panelists' assessments. Panelists reported quickly learning how to use the dashboard. The assessment module was used consistently. The dashboard was reliable, enabling an efficient review process for panelists. Modifications were made to the dashboard and review process when necessary to facilitate case review. Our methods should be applied to other health outcomes of interest to further refine the dashboard and case review process. CONCLUSION: The expert review process was effective and was supported by the web-based dashboard. Our methods for case review and classification can be applied to future methods for case identification in observational data sources.
OBJECTIVES: Drug safety surveillance using observational data requires valid adverse event, or health outcome of interest (HOI) measurement. The objectives of this study were to develop a method to review HOI definitions in claims databases using (1) web-based digital tools to present de-identified patient data, (2) a systematic expert panel review process, and (3) a data collection process enabling analysis of concepts-of-interest that influence panelists' determination of HOI. METHODS: De-identified patient data were presented via an interactive web-based dashboard to enable case review and determine if specific HOIs were present or absent. Criteria for determining HOIs and their severity were provided to each panelist. Using a modified Delphi method, six panelist pairs independently reviewed approximately 200 cases across each of three HOIs (acute liver injury, acute kidney injury, and acute myocardial infarction) such that panelist pairs independently reviewed the same cases. Panelists completed an assessment within the dashboard for each case that included their assessment of the presence or absence of the HOI, HOI severity (if present), and data contributing to their decision. Discrepancies within panelist pairs were resolved during a consensus process. RESULTS: Dashboard development was iterative, focusing on data presentation and recording panelists' assessments. Panelists reported quickly learning how to use the dashboard. The assessment module was used consistently. The dashboard was reliable, enabling an efficient review process for panelists. Modifications were made to the dashboard and review process when necessary to facilitate case review. Our methods should be applied to other health outcomes of interest to further refine the dashboard and case review process. CONCLUSION: The expert review process was effective and was supported by the web-based dashboard. Our methods for case review and classification can be applied to future methods for case identification in observational data sources.
Authors: Richard A Hansen; Michael D Gray; Brent I Fox; Joshua C Hollingsworth; Juan Gao; Peng Zeng Journal: Drug Saf Date: 2013-10 Impact factor: 5.606
Authors: Peggy L Peissig; Vitor Santos Costa; Michael D Caldwell; Carla Rottscheit; Richard L Berg; Eneida A Mendonca; David Page Journal: J Biomed Inform Date: 2014-07-15 Impact factor: 6.317
Authors: Bryony A Thompson; Amanda B Spurdle; John-Paul Plazzer; Marc S Greenblatt; Kiwamu Akagi; Fahd Al-Mulla; Bharati Bapat; Inge Bernstein; Gabriel Capellá; Johan T den Dunnen; Desiree du Sart; Aurelie Fabre; Michael P Farrell; Susan M Farrington; Ian M Frayling; Thierry Frebourg; David E Goldgar; Christopher D Heinen; Elke Holinski-Feder; Maija Kohonen-Corish; Kristina Lagerstedt Robinson; Suet Yi Leung; Alexandra Martins; Pal Moller; Monika Morak; Minna Nystrom; Paivi Peltomaki; Marta Pineda; Ming Qi; Rajkumar Ramesar; Lene Juel Rasmussen; Brigitte Royer-Pokora; Rodney J Scott; Rolf Sijmons; Sean V Tavtigian; Carli M Tops; Thomas Weber; Juul Wijnen; Michael O Woods; Finlay Macrae; Maurizio Genuardi Journal: Nat Genet Date: 2013-12-22 Impact factor: 38.330