Data for cancer comparative effectiveness research
Abstract
Comparative
effectiveness research (CER) can efficiently and rapidly generate new
scientific evidence and address knowledge gaps, reduce clinical
uncertainty, and guide health care choices. Much of the potential in CER
is driven by the application of novel methods to analyze existing data.
Despite its potential, several challenges must be identified and
overcome so that CER may be improved, accelerated, and expeditiously
implemented into the broad spectrum of cancer care and clinical
practice. To identify and characterize the challenges to cancer CER, the
authors reviewed the literature and conducted semistructured interviews
with 41 cancer CER researchers at the Agency for Healthcare Research
and Quality's Developing Evidence to Inform Decisions about
Effectiveness (DEcIDE) Cancer CER Consortium. Several data sets for
cancer CER were identified and differentiated into an ontology of 8
categories and were characterized in terms of strengths, weaknesses, and
utility. Several themes emerged during the development of this ontology
and discussions with CER researchers. Dominant among them was
accelerating cancer CER and promoting the acceptance of findings, which
will necessitate transcending disciplinary silos to incorporate diverse
perspectives and expertise. Multidisciplinary collaboration is required,
including those with expertise in nonexperimental data, statistics,
outcomes research, clinical trials, epidemiology, generalist and
specialty medicine, survivorship, informatics, data, and methods, among
others.
Recommendations highlight the systematic, collaborative
identification of critical measures; application of more rigorous study
design and sampling methods; policy-level resolution of issues in data
ownership, governance, access, and cost; and development and application
of consistent standards for data security, privacy, and
confidentiality.