Limits...
Developing a comprehensive database management system for organization and evaluation of mammography datasets.

Wu Y, Rubin DL, Woods RW, Elezaby M, Burnside ES - Cancer Inform (2014)

Bottom Line: A Health Insurance Portability and Accountability Act (HIPAA) compliant CMDB was created to store multi-relational datasets of demographic risk factors and mammogram results using the Breast Imaging Reporting and Data System (BI-RADS) lexicon.The CMDB collected both biopsy pathology outcomes, in a breast pathology lexicon compiled by extending BI-RADS, and our institutional breast cancer registry.Our procedure of developing the CMDB provides a framework to build a detailed data repository for breast imaging quality control and research, which has the potential to augment existing resources.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, University of Wisconsin, Madison, WI, USA.

ABSTRACT
We aimed to design and develop a comprehensive mammography database system (CMDB) to collect clinical datasets for outcome assessment and development of decision support tools. A Health Insurance Portability and Accountability Act (HIPAA) compliant CMDB was created to store multi-relational datasets of demographic risk factors and mammogram results using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. The CMDB collected both biopsy pathology outcomes, in a breast pathology lexicon compiled by extending BI-RADS, and our institutional breast cancer registry. The audit results derived from the CMDB were in accordance with Mammography Quality Standards Act (MQSA) audits and national benchmarks. The CMDB has managed the challenges of multi-level organization demanded by the complexity of mammography practice and lexicon development in pathology. We foresee that the CMDB will be useful for efficient quality assurance audits and development of decision support tools to improve breast cancer diagnosis. Our procedure of developing the CMDB provides a framework to build a detailed data repository for breast imaging quality control and research, which has the potential to augment existing resources.

No MeSH data available.


Related in: MedlinePlus

Sketched entity-relationship diagram for our comprehensive database management system. ∞ = associated multiple entries in a relationship.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC4214592&req=5

f1-cin-suppl.3-2014-053: Sketched entity-relationship diagram for our comprehensive database management system. ∞ = associated multiple entries in a relationship.

Mentions: After tables for demographics and mammogram results were created, we established one-to-many relationships between the patient table and the mammogram table, and between the mammogram table and the abnormality table since a patient may have multiple mammograms over time, and radiologists may detect several abnormalities on each mammogram. These relationships are shown in the schema depicted in Figure 1. Based on these relationships, we can easily find the patient ID and the mammogram ID for each abnormality in the abnormality table.


Developing a comprehensive database management system for organization and evaluation of mammography datasets.

Wu Y, Rubin DL, Woods RW, Elezaby M, Burnside ES - Cancer Inform (2014)

Sketched entity-relationship diagram for our comprehensive database management system. ∞ = associated multiple entries in a relationship.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4214592&req=5

f1-cin-suppl.3-2014-053: Sketched entity-relationship diagram for our comprehensive database management system. ∞ = associated multiple entries in a relationship.
Mentions: After tables for demographics and mammogram results were created, we established one-to-many relationships between the patient table and the mammogram table, and between the mammogram table and the abnormality table since a patient may have multiple mammograms over time, and radiologists may detect several abnormalities on each mammogram. These relationships are shown in the schema depicted in Figure 1. Based on these relationships, we can easily find the patient ID and the mammogram ID for each abnormality in the abnormality table.

Bottom Line: A Health Insurance Portability and Accountability Act (HIPAA) compliant CMDB was created to store multi-relational datasets of demographic risk factors and mammogram results using the Breast Imaging Reporting and Data System (BI-RADS) lexicon.The CMDB collected both biopsy pathology outcomes, in a breast pathology lexicon compiled by extending BI-RADS, and our institutional breast cancer registry.Our procedure of developing the CMDB provides a framework to build a detailed data repository for breast imaging quality control and research, which has the potential to augment existing resources.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, University of Wisconsin, Madison, WI, USA.

ABSTRACT
We aimed to design and develop a comprehensive mammography database system (CMDB) to collect clinical datasets for outcome assessment and development of decision support tools. A Health Insurance Portability and Accountability Act (HIPAA) compliant CMDB was created to store multi-relational datasets of demographic risk factors and mammogram results using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. The CMDB collected both biopsy pathology outcomes, in a breast pathology lexicon compiled by extending BI-RADS, and our institutional breast cancer registry. The audit results derived from the CMDB were in accordance with Mammography Quality Standards Act (MQSA) audits and national benchmarks. The CMDB has managed the challenges of multi-level organization demanded by the complexity of mammography practice and lexicon development in pathology. We foresee that the CMDB will be useful for efficient quality assurance audits and development of decision support tools to improve breast cancer diagnosis. Our procedure of developing the CMDB provides a framework to build a detailed data repository for breast imaging quality control and research, which has the potential to augment existing resources.

No MeSH data available.


Related in: MedlinePlus