This document summarizes the ASTER study, which tested a new automated system for generating and reporting adverse drug event reports directly from electronic health records. The study found that the new system:
- Required minimal physician time and interaction, typically less than 60 seconds per report.
- Generated over 200 reports over 3 months from physicians who had submitted no reports previously.
- Included more detailed patient information like lab results compared to traditional reporting methods.
- Was well received by participating physicians who saw its potential for improving post-marketing drug safety monitoring using digitized healthcare data sources.
2. Disclaimer Pfizer supports and funded ASTER and continues to invest in the concepts and goals involved in this work. During this talk, any opinions, suggestions or crazy statements are entirely my own.
3. 10:30:00 A Thursday in February, 2009 A doctor is working at an ambulatory clinic affiliated with Brigham and Womenâs Hospital They discontinue a patientâs drug due to an adverse eventâŚ
12. 10:40:00 A MedWatch report* derived directly from the source document (EHR), validated by the doctor, is delivered to FDA *The report is MedDRA coded and has an initial âserious/nonseriousâ assessment
13. ADE Spontaneous Triggered Electronic Reports David Westfall Bates, MD, M.Sc. Chief of the Division of General Internal Medicine at the Brigham and Women's Hospital; Professor of Medicine at Harvard Medical School and Professor of Health Policy and Management at the Harvard School of Public Health (Co-Director of the Program in Clinical Effectiveness) Jeffrey A. Linder, MD, MPH, FACP - PI of *ASTER Assistant Professor of Medicine, Harvard Medical School Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston MA
23. During the study, participants reported an average of approximately 5 reports in a 3 month time period
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26. RESULTS ...Physician interaction â âa blink (60 secs)â ...time for reviewing instructions - no instructions needed ...searching existing data sources - no searching required ...gathering and maintaining the data needed - transparent ...completing and reviewing the information - minimal interaction
27. Traditional ASTER Paper or separate site 36 minutes Several days or more 0 reports per physician 1 page of information At point of care 60 seconds 20 minutes (triaged) 5 reports per physician 7 pages of information
28. Why was it so easy to improve on how we were doing things ?
29. Specifically⌠Solved the reporterâs (providerâs) problems Solved the EHR ownerâs problems Made the final product palatable for the end-users (used appropriate standards for regulators, manufacturers) Used digitized data to simplify the workflow across groups and create economies of scale
30. "A design representation suitable to a world in which the scarce factor is information may be exactly the wrong one for a world in which the scarce factor is attention.â Herbert Simon The Sciences of the Artificial p.144
33. There are established and evolving standards for exchanging safety informationOnce transaction costs drop, new business models will be possible The Hypothesis
34. Hospitals Lab Data Rx Data Large Medical Practices Health Information Exchanges CurrentlyâŚstranded data Regulator Consumers Doctors Pharma replicating the same front-end process across companies Underutilized sources
35. Hospitals FDA Pharma Lab Data Rx Data Qualified Researchers Large Medical Practices Patient Organizations Health Information Exchanges Vision: A Public / Private PV Hub Regulatory Functions Technical Functions Secure Interface Secure Portal Safety Data Patient Safety Org* Doctors Consumers Consumers Patients *The Patient Safety Org. (PSO) is used here as an example of a public/private organization that can fulfill the requirements to serve as a pharmacovigilance hub Physicians
36. National Picture: Regionally-based Centers serve the country Collect reports from and provide services to their region Networked via NHIN / CONNECT Maintain data model, standards that allow querying of combined data
37. Global Picture: Common standards allow for data sharing and combined analyses Participating centers can share data Certain centers act as centers of excellence and provide guidance and analysis for other centers Queries can be run across select data at participating centers greatly increasing power and hypothesis testing capabilities
38. Value Simple, iterative Local rules Multiple actors Low threshold to join Existing complexity is distributed Data mapping Triggers Iterative Potential to transcend traditional limitations Denominators Potential to form evidenced-based loop Communications channel Baseline => Actions => Change ASTER scales in proportion to the amount of digitized healthcare data EHRs eRX Registries