Health informatics. Deployment of a clinical data warehouse

2015 ◽  
Keyword(s):  
Data Warehouse ◽  
Clinical Data ◽  
Health Informatics ◽  
Clinical Data Warehouse

scholarly journals Evaluation of the Observed Cisplatin Nephrotoxicity in Adult Cancer Inpatients: A Historical Cohort Study by Using Clinical Data Warehouse

2006 ◽  
Vol 52 (2) ◽  
pp. 192-197
Author(s):  
Qiyan Zhang ◽  
Yasushi Matsumura ◽  
Tadamasa Teratani ◽  
Sachiko Yoshimoto ◽  
Takahiro Mineno ◽  
...  
Keyword(s):  
Cohort Study ◽  
Data Warehouse ◽  
Clinical Data ◽  
Historical Cohort ◽  
Cisplatin Nephrotoxicity ◽  
Clinical Data Warehouse ◽  
Historical Cohort Study

scholarly journals A clinical data warehouse-based process for refining medication orders alerts

2012 ◽  
Vol 19 (5) ◽  
pp. 782-785 ◽  
Author(s):  
Abdelali Boussadi ◽  
Thibaut Caruba ◽  
Eric Zapletal ◽  
Brigitte Sabatier ◽  
Pierre Durieux ◽  
...  
Keyword(s):  
Data Warehouse ◽  
Clinical Data ◽  
Clinical Data Warehouse

Enabling Precision Medicine in Cancer Care Through a Molecular Data Warehouse: The Moffitt Experience

2021 ◽  
pp. 561-569
Author(s):  
Steven A. Eschrich ◽  
Jamie K. Teer ◽  
Phillip Reisman ◽  
Erin Siegel ◽  
Chandan Challa ◽  
...  
Keyword(s):  
Cancer Research ◽  
Precision Medicine ◽  
Data Warehouse ◽  
Clinical Data ◽  
Molecular Data ◽  
Project Planning ◽  
Cancer Genome ◽  
Open Communication ◽  
Clinical Data Warehouse ◽  
Research Studies

PURPOSE The use of genomics within cancer research and clinical oncology practice has become commonplace. Efforts such as The Cancer Genome Atlas have characterized the cancer genome and suggested a wealth of targets for implementing precision medicine strategies for patients with cancer. The data produced from research studies and clinical care have many potential secondary uses beyond their originally intended purpose. Effective storage, query, retrieval, and visualization of these data are essential to create an infrastructure to enable new discoveries in cancer research. METHODS Moffitt Cancer Center implemented a molecular data warehouse to complement the extensive enterprise clinical data warehouse (Health and Research Informatics). Seven different sequencing experiment types were included in the warehouse, with data from institutional research studies and clinical sequencing. RESULTS The implementation of the molecular warehouse involved the close collaboration of many teams with different expertise and a use case–focused approach. Cornerstones of project success included project planning, open communication, institutional buy-in, piloting the implementation, implementing custom solutions to address specific problems, data quality improvement, and data governance, unique aspects of which are featured here. We describe our experience in selecting, configuring, and loading molecular data into the molecular data warehouse. Specifically, we developed solutions for heterogeneous genomic sequencing cohorts (many different platforms) and integration with our existing clinical data warehouse. CONCLUSION The implementation was ultimately successful despite challenges encountered, many of which can be generalized to other research cancer centers.

Construction of a bone marrow report registry using a clinical data warehouse

2021 ◽  
Author(s):  
Kwang Seob Lee ◽  
Dong‐Gyo Shin ◽  
Jin‐Hee Hwang ◽  
Ranhee Kim ◽  
Chang Hoon Han ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Data Warehouse ◽  
Clinical Data ◽  
Clinical Data Warehouse
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