TECHNICAL SUPPORT RELATED TO THE SEER-MEDICARE DATA
TECHNICAL SUPPORT RELATED TO THE SEER-MEDICARE DATA
批准号:
8571421
负责人:
金额:
$12.11万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-20 至 2013-09-19
关键词:
Cause of DeathCessation of lifeClinicalComplexContractsDataData FilesData SetData SourcesDatabasesDiagnosisDocumentationEligibility DeterminationEpidemiologyHealth ServicesHealth Services ResearchLinkMalignant NeoplasmsMedical SurveillanceMedicareMedicare claimPatterns of CarePersonsProceduresPublishingReadingResearchResearch PersonnelSEER ProgramServicesSourceTestingTimebeneficiarycancer diagnosiscancer therapycostfollow-upneoplasm registrypopulation based
中文摘要
点击翻译按钮获取中文摘要
英文摘要
The SEER-Medicare data reflect the linkage of two large population-based sources of data that provide detailed information about Medicare beneficiaries with cancer. The data come from the Surveillance, Epidemiology and End Results (SEER) program of cancer registries that collect clinical, demographic and cause of death information for persons with cancer and the Medicare claims for covered health care services from the time of a person's Medicare eligibility until death.
The linkage of these two data sources results in a unique population-based source of information that can be used for an array of epidemiological and health services research. For example, investigators using this combined dataset have conducted studies on patterns of care for persons with cancer before a cancer diagnosis, over the period of initial diagnosis and treatment, and during long-term follow-up. Investigators have also examined the use of cancer tests and procedures and the costs of cancer treatment.
The linked SEER-Medicare data files are large and complex. Before beginning an analysis, researchers are advised to read all documentation to determine whether the data will support their proposed research question. In addition, the SEER-Medicare data have a number of particular qualities and anomalies (see Analytic Support for Researchers). Researchers are strongly encouraged to understand the complexity of the data before undertaking any analyses or publishing findings.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文