A Robust ETL-Based Framework for Healthcare Data Integration and Patient Record Deduplication Using SQL Server and SSIS
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2026
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| _version_ | 1866901929933668352 |
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| author | Surendra Reddy Alavala |
| author_facet | Surendra Reddy Alavala |
| contents | The healthcare industry increasingly requires advanced concepts to capture accurate patient data. Although crucial, duplicate patient records remain a persistent challenge, leading to clinical errors, billing discrepancies, and reporting inconsistencies. Given the current challenges facing the healthcare industry, we propose a new state-of-the-art that utilizes Microsoft SQL Server to store data and SQL Server Integration Services (SSIS) to perform data extraction, transformation, and loading (ETL) from various sources to a centralized repository. This approach will not only store the data, but also implement a mandatory filtration process prior to loading to prevent data duplication. By combining these leading industry technologies that support data standardization, deterministic and probabilistic matching techniques, and governance rules, healthcare organizations can significantly improve data quality and patient identity integrity |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18848564 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A Robust ETL-Based Framework for Healthcare Data Integration and Patient Record Deduplication Using SQL Server and SSIS Surendra Reddy Alavala Data quality healthcare data patient identity deduplication Microsoft SQL Server ETL SQL Server Integration Services (SSIS). The healthcare industry increasingly requires advanced concepts to capture accurate patient data. Although crucial, duplicate patient records remain a persistent challenge, leading to clinical errors, billing discrepancies, and reporting inconsistencies. Given the current challenges facing the healthcare industry, we propose a new state-of-the-art that utilizes Microsoft SQL Server to store data and SQL Server Integration Services (SSIS) to perform data extraction, transformation, and loading (ETL) from various sources to a centralized repository. This approach will not only store the data, but also implement a mandatory filtration process prior to loading to prevent data duplication. By combining these leading industry technologies that support data standardization, deterministic and probabilistic matching techniques, and governance rules, healthcare organizations can significantly improve data quality and patient identity integrity |
| title | A Robust ETL-Based Framework for Healthcare Data Integration and Patient Record Deduplication Using SQL Server and SSIS |
| topic | Data quality healthcare data patient identity deduplication Microsoft SQL Server ETL SQL Server Integration Services (SSIS). |
| url | https://doi.org/10.5281/zenodo.18848564 |