Published Sep 2007
Citation
Garrison LP Jr, Neumann PJ, Erickson P, et al. Using real-world data for coverage and payment decisions: the ISPOR Real-World Data Task Force Report. Value Health. 2007;10(5):326-335.
Abstract
Objectives: Health decision-makers involved with coverage
and payment policies are increasingly developing policies that
seek information on “real-world” (RW) outcomes. Motivated
by these initiatives, the International Society for Pharmacoeconomics
and Outcomes Research (ISPOR) created a
Task Force on Real-World Data to develop a framework to
assist health-care decision-makers in dealing with RW data,
especially related to coverage and payment decisions.
Methods: Task Force cochairs were selected by the ISPOR
Board of Directors. Cochairs selected chairs for four working
groups on: clinical outcomes, economic outcomes, patientreported
outcomes, and evidence hierarchies. Task Force
members included representatives from academia, the pharmaceutical
industry, and health insurers. The Task Force met
on several occasions, conducted frequent correspondence and
exchanges of drafts, and solicited comments on three drafts
from a core group of external reviewers and from the ISPOR
membership.
Results: We defined RW data as data used for decisionmaking
that are not collected in conventional randomized
controlled trials (RCTs). We considered several characterizations:
by type of outcome (clinical, economic, and patientreported),
by hierarchies of evidence (which rank evidence
according to the strength of research design), and by type of
data source (supplementary data collection alongside RCTs,
large simple trials, patient registries, administrative claims
database, surveys, and medical records). Our report discusses
eight key issues: 1) the importance of RW data; 2) limitations
of RW data; 3) the fact that the level of evidence required
depends on the circumstance; 4) the need for good research
practices for collecting and reporting RW data; 5) the need
for good process in using RW data in coverage and reimbursement
decisions; 6) the need to consider costs and benefits
of data collection; 7) the ongoing need for modeling; and
8) the need for continued stakeholder dialogue on these
topics.
Conclusions: Real-world data are essential for sound coverage
and reimbursement decisions. The types and applications
of such data are varied, and context matters greatly in determining
the value of a particular type in any circumstance. It
is critical that policymakers recognize the benefits, limitations,
and methodological challenges in using RW data, and
the need to consider carefully the costs and benefits of different
forms of data collection in different situations.
Keywords: methodology, outcomes research, real-world
data, research design.
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