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POST-APPROVAL Summit 11-12 May 2010 ASTER Michael Ibara
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.
10:30:00 A Thursday in February, 2009 A doctor is working at an ambulatory clinic affiliated with Brigham and Women’s Hospital They discontinue a patient’s drug due to an adverse event…
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10:30:00 10:31:00 The doctor goes back to seeing the patient
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 ‘serious/nonserious’ assessment
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
Physician EHR Ambulatory Clinics  MAH ASTER at Brigham and Women’s Service Provider Patient * * Regulator Coding Bus Rules CDISC/IHE RFD *AE Report ,[object Object]
 Physician Assessment
 Coding & Bus Rule Results
 Electronic Wrapper*”Triggered” Adverse Event Reports
*ASTER started Nov 2008 30 Ambulatory care physicians Completing June 2009 > 200 Reports Sent to FDA
Information in Reports ,[object Object]
Matching regulatory serious outcome
Coded event matching an ‘always serious list’
 100% had height/weight, lab data,[object Object]
 During the study, participants reported an average of approximately 5 reports in a 3 month time period
 All participants reported at least 1 ADE,[object Object]
RESULTS  ...Physician interaction – ”a blink (60 secs)” ...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
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
Why was it so easy to improve on how we were doing things ?
Specifically… Solved the reporter’s (provider’s) problems Solved the EHR owner’s 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
"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.” Herbert Simon  The Sciences of the Artificial p.144
Gedankenexperiment When 60% of healthcare data is digitized, what will postmarketing safety look like?
Current post marketing safety reporting model in U.S. is built on vertical organizations having the resources to find, collect and process safety information Manufacturers have been the de facto owners of safety information and responsible for it (focus of regulations) because they were the only organizations able to afford the transaction costs Two developments  allow for a dramatic lowering of the ‘transaction cost’ of finding, collecting and reporting safety information ,[object Object]

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Post-approval Summit discussion covers ASTER study results for triggered adverse event reporting

  • 1. POST-APPROVAL Summit 11-12 May 2010 ASTER Michael Ibara
  • 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 Women’s Hospital They discontinue a patient’s drug due to an adverse event…
  • 5. Screen shots #2 Partners Native LMR
  • 10. Screen shots #7 Partners Native LMR
  • 11. 10:30:00 10:31:00 The doctor goes back to seeing the patient
  • 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 ‘serious/nonserious’ 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
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  • 16. Coding & Bus Rule Results
  • 17. Electronic Wrapper*”Triggered” Adverse Event Reports
  • 18. *ASTER started Nov 2008 30 Ambulatory care physicians Completing June 2009 > 200 Reports Sent to FDA
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  • 21. Coded event matching an ‘always serious list’
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  • 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 – ”a blink (60 secs)” ...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 reporter’s (provider’s) problems Solved the EHR owner’s 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.” Herbert Simon The Sciences of the Artificial p.144
  • 31. Gedankenexperiment When 60% of healthcare data is digitized, what will postmarketing safety look like?
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  • 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 Currently…stranded 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