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Current concepts on hematopoietic stem cell transplantation outcome registries; Emphases on resource requirements for new registries
Author(s) -
Fazal Hussain,
Naeem Chaudhri,
Feras Alfraih,
Mahmoud Aljurf
Publication year - 2017
Publication title -
hematology/oncology and stem cell therapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.666
H-Index - 22
eISSN - 1658-3876
pISSN - 2589-0646
DOI - 10.1016/j.hemonc.2017.05.011
Subject(s) - interoperability , credibility , observational study , medicine , transplantation , scope (computer science) , outcome (game theory) , accreditation , computer science , medical education , political science , mathematics , mathematical economics , law , programming language , operating system
There is tremendous variability in size, scope, and resource requirements for registries depending on the number of patients and participating sites. The outcome registries are organized systems to collect uniform data using an observational study methodology. Patient registries are used to determine specified outcomes for a population for predetermined scientific, clinical, or policy purposes. Historically, outcome registries established in the development of hematopoietic stem cell transplantation (HSCT) have now evolved into myriads of locoregional and international transplant activity and outcome resources. Over time, these registries have contributed immensely in determining trends, patterns, and treatment outcomes in HSCT. There is wider variation in the goals, mission, objectives, and outcomes of the ongoing registries depending on the organizational structure. There is a growing trend toward overarching relationship of these registries to serve as complementary and interoperable resources for high potential collaborative research. In addition to capacity building, standardized, accredited, and optimally operational registries can provide unmatched and unparalleled research data that cannot be obtained otherwise. Moving forward, HSCT data collection, collation, and interpretation should be an integral part of the treatment rather than an option. Quality assurance and continuous quality improvement of the data are pivotal for credibility, measurable/quantifiable outcomes, clinically significant impact, and setting new benchmarks.

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