BACKGROUND: Every health policy jurisdiction is endeavoring to enhance its ability to evaluate drug effectiveness, safety and cost in the real world (pharmacosurveillance). METHODS: A nominal group consensus conference of stakeholders finalized data items deemed necessary for pharmacosurveillance. Large administrative datasets (LADs), electronic health records (EHRs) and electronic patient registries (PRs), were investigated as sources of this information and for their vulnerability to methodologic bias. Health data privacy legislation and research guidelines were systematically reviewed for their constraint to linked data resource analyses. RESULTS: More than 129 data items were strongly recommended for routine pharmacosurveillance. LADs had very complete information, but restricted to a small number of required data items. EHRs, especially with e-pharmacy links, offer by far the most complete set of health information domains but data entry completeness is highly variable. Adjustment methods for channeling bias are inadequate to mimic randomized trials. Anonymized, linked data held within a secure academic research environment, poses the least privacy concerns. CONCLUSIONS: Notwithstanding major technical, methodologic and privacy challenges, individual-level linkage of health data resources poses the best option for pharmacosurveillance today. In future, drug regulators and reimbursement agencies should consider mandatory post-marketing randomized trials.
BACKGROUND: Every health policy jurisdiction is endeavoring to enhance its ability to evaluate drug effectiveness, safety and cost in the real world (pharmacosurveillance). METHODS: A nominal group consensus conference of stakeholders finalized data items deemed necessary for pharmacosurveillance. Large administrative datasets (LADs), electronic health records (EHRs) and electronic patient registries (PRs), were investigated as sources of this information and for their vulnerability to methodologic bias. Health data privacy legislation and research guidelines were systematically reviewed for their constraint to linked data resource analyses. RESULTS: More than 129 data items were strongly recommended for routine pharmacosurveillance. LADs had very complete information, but restricted to a small number of required data items. EHRs, especially with e-pharmacy links, offer by far the most complete set of health information domains but data entry completeness is highly variable. Adjustment methods for channeling bias are inadequate to mimic randomized trials. Anonymized, linked data held within a secure academic research environment, poses the least privacy concerns. CONCLUSIONS: Notwithstanding major technical, methodologic and privacy challenges, individual-level linkage of health data resources poses the best option for pharmacosurveillance today. In future, drug regulators and reimbursement agencies should consider mandatory post-marketing randomized trials.
Authors: Jack V Tu; Donald J Willison; Frank L Silver; Jiming Fang; Janice A Richards; Andreas Laupacis; Moira K Kapral Journal: N Engl J Med Date: 2004-04-01 Impact factor: 91.245
Authors: Jacques E Rossouw; Garnet L Anderson; Ross L Prentice; Andrea Z LaCroix; Charles Kooperberg; Marcia L Stefanick; Rebecca D Jackson; Shirley A A Beresford; Barbara V Howard; Karen C Johnson; Jane Morley Kotchen; Judith Ockene Journal: JAMA Date: 2002-07-17 Impact factor: 56.272
Authors: Richard T Scheife; Lisa E Hines; Richard D Boyce; Sophie P Chung; Jeremiah D Momper; Christine D Sommer; Darrell R Abernethy; John R Horn; Stephen J Sklar; Samantha K Wong; Gretchen Jones; Mary L Brown; Amy J Grizzle; Susan Comes; Tricia Lee Wilkins; Clarissa Borst; Michael A Wittie; Daniel C Malone Journal: Drug Saf Date: 2015-02 Impact factor: 5.606