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EHR Data Archiving for a Healthcare Organization: A Case Study

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Challenge

Preserving Historical EHR Data While Reducing Legacy System Dependency

 

CLIENT : A major health care organizationINDUSTRY:  HealthcareSOLUTION:  EHR Data Archiving & Legacy Data Management

The Challenge

A major U.S. healthcare provider with 1,000+ facilities, had accumulated approximately 30 years of legacy patient and clinical data. The growing environment was consuming storage, affecting database performance, and increasing the effort required for periodic maintenance. Backup and DR environments also carried redundant copies of the data.

30+

Years of legacy data

120

Physical servers

22,000

Tables

90%

Tables referenced by archival logic

 

Core challenge: The data was highly normalized and tightly connected. Separating live/current data from historical patient data required relationship-aware archival logic spanning about 90% of the tables.

The Requirement

  • Preserve historical EHR information while reducing dependency on the legacy environment.
  • Extract, transform, archive and validate eligible historical data without compromising data integrity.
  • Maintain critical relationships and context so archived information remains usable when required.
  • Automate archive and purge execution with logging, monitoring, error handling and reporting.
  • Apply retention and purge rules aligned with business, legal and regulatory requirements.

RalanTech’s Solution Design

RalanTech designed a structured Sybase ASE archive-and-purge framework using Python and BCP for controlled data movement into consolidated SQL Server archive databases, with SQL Server Agent providing scheduling, automation and operational monitoring.

 

SYBASE ASE
Source		Metadata +
Driver		Extract +
Transform		SQL Server
Archive		ValidatePurgeLog / Report

Implementation Approach

1. Assess & DefineAnalyze source databases, table relationships, retention rules and archival eligibility. Metadata captures table hierarchy, archival columns, and database type and retention policies.
2. OrchestrateA driver-based framework identifies eligible Sybase instances and controls the end-to-end workflow, including job initialization, retries and reruns.
3. Extract & TransformEligible data is extracted in controlled batches using Sybase BCP. Processing follows a deepest-child-first sequence to preserve referential integrity. Four metadata fields identify the source and job snapshot.
4. Load to ArchiveTransformed files are bulk-loaded into consolidated SQL Server archive databases using BCP. Idempotency checks and batch-level commits support restartable processing.
5. ValidateSource and target data are reconciled before deletion using row counts/control checks and exception reporting. No data is purged until archive validation succeeds.
6. Purge & RecoverValidated source rows are deleted in batches. Driver/archive flags support controlled deletion and reruns from the point of failure.

Technical Design Highlights

  • Consolidated SQL Server archive databases support Market, Billing, Reporting, Corporate and National environments.
  • Key metadata tables drive the process: archive_control_metadata, sybase_server_list, archive_worker, Archive_driver, Archive_log and Archive_exception.
  • Extraction and loading use 10,000-row batches; source deletion uses 1,000-row batches to control transaction and replication impact.
  • The framework uses multi-threading across Sybase instances while processing tables sequentially within each instance to limit source contention.
  • Replication impact is mitigated through controlled delete execution and separate execution handling for environments with or without replication.
  • SQL Server Agent schedules jobs and supports new runs and reruns; failures are logged for support analysis and recovery.

 

Compliance & Governance

The design includes retention-policy controls, auditable execution logs, timestamps, record counts, exceptions and execution status. Validation and reconciliation occur before purge, supporting traceability and controlled enforcement of business, legal and regulatory retention requirements.

Data Access & Operational Controls

  • Dedicated service-account access is recommended across Sybase and SQL Server environments.
  • Role-based access controls protect archive data, purge execution and reporting.
  • Version-controlled scripts, stored procedures and deployment artifacts support maintainability and controlled releases.
  • Monitoring and alerting cover job status, failures, performance metrics and abnormal conditions.

The Outcome

The archival program separated historical data from the operational dependency of the legacy database environment while preserving access to information required for future use.

60%+

Storage recovered

Recovered storage across database, backup and DR environments.

30%

Database size

Reduced the database footprint to approximately 30% of its prior size.

100%

Optimization

Database was defragmented and optimized to the fullest.

20%

Maintenance window

Reduced maintenance runtime to 20% of the previous overall runtime.

Business Impact

  • Reduced storage consumption and the overhead of redundant database copies across backup and DR environments.
  • Reduced database footprint and maintenance effort, improving the operational efficiency of the legacy environment.
  • Created a structured, auditable method for preserving historical healthcare information while progressing toward legacy-system modernization.
  • Established a repeatable archival framework that can be adapted to data volume, database architecture, retention requirements and access needs.

RalanTech EHR Data Archiving Framework

AssessExtractTransformArchiveValidateAccessRetire

 

Key Takeaway

EHR modernization does not have to mean losing access to historical information or maintaining expensive legacy environments indefinitely. A structured EHR data archiving strategy can preserve critical historical information, maintain controlled access and support legacy-system modernization.

Solution

Implementation Steps

Results

See How We Made It Happen

Challenge

Preserving Historical EHR Data While Reducing Legacy System Dependency

 

CLIENT : A major health care organizationINDUSTRY:  HealthcareSOLUTION:  EHR Data Archiving & Legacy Data Management

The Challenge

A major U.S. healthcare provider with 1,000+ facilities, had accumulated approximately 30 years of legacy patient and clinical data. The growing environment was consuming storage, affecting database performance, and increasing the effort required for periodic maintenance. Backup and DR environments also carried redundant copies of the data.

30+

Years of legacy data

120

Physical servers

22,000

Tables

90%

Tables referenced by archival logic

 

Core challenge: The data was highly normalized and tightly connected. Separating live/current data from historical patient data required relationship-aware archival logic spanning about 90% of the tables.

The Requirement

  • Preserve historical EHR information while reducing dependency on the legacy environment.
  • Extract, transform, archive and validate eligible historical data without compromising data integrity.
  • Maintain critical relationships and context so archived information remains usable when required.
  • Automate archive and purge execution with logging, monitoring, error handling and reporting.
  • Apply retention and purge rules aligned with business, legal and regulatory requirements.

RalanTech’s Solution Design

RalanTech designed a structured Sybase ASE archive-and-purge framework using Python and BCP for controlled data movement into consolidated SQL Server archive databases, with SQL Server Agent providing scheduling, automation and operational monitoring.

 

SYBASE ASE
Source		Metadata +
Driver		Extract +
Transform		SQL Server
Archive		ValidatePurgeLog / Report

Implementation Approach

1. Assess & DefineAnalyze source databases, table relationships, retention rules and archival eligibility. Metadata captures table hierarchy, archival columns, and database type and retention policies.
2. OrchestrateA driver-based framework identifies eligible Sybase instances and controls the end-to-end workflow, including job initialization, retries and reruns.
3. Extract & TransformEligible data is extracted in controlled batches using Sybase BCP. Processing follows a deepest-child-first sequence to preserve referential integrity. Four metadata fields identify the source and job snapshot.
4. Load to ArchiveTransformed files are bulk-loaded into consolidated SQL Server archive databases using BCP. Idempotency checks and batch-level commits support restartable processing.
5. ValidateSource and target data are reconciled before deletion using row counts/control checks and exception reporting. No data is purged until archive validation succeeds.
6. Purge & RecoverValidated source rows are deleted in batches. Driver/archive flags support controlled deletion and reruns from the point of failure.

Technical Design Highlights

  • Consolidated SQL Server archive databases support Market, Billing, Reporting, Corporate and National environments.
  • Key metadata tables drive the process: archive_control_metadata, sybase_server_list, archive_worker, Archive_driver, Archive_log and Archive_exception.
  • Extraction and loading use 10,000-row batches; source deletion uses 1,000-row batches to control transaction and replication impact.
  • The framework uses multi-threading across Sybase instances while processing tables sequentially within each instance to limit source contention.
  • Replication impact is mitigated through controlled delete execution and separate execution handling for environments with or without replication.
  • SQL Server Agent schedules jobs and supports new runs and reruns; failures are logged for support analysis and recovery.

 

Compliance & Governance

The design includes retention-policy controls, auditable execution logs, timestamps, record counts, exceptions and execution status. Validation and reconciliation occur before purge, supporting traceability and controlled enforcement of business, legal and regulatory retention requirements.

Data Access & Operational Controls

  • Dedicated service-account access is recommended across Sybase and SQL Server environments.
  • Role-based access controls protect archive data, purge execution and reporting.
  • Version-controlled scripts, stored procedures and deployment artifacts support maintainability and controlled releases.
  • Monitoring and alerting cover job status, failures, performance metrics and abnormal conditions.

The Outcome

The archival program separated historical data from the operational dependency of the legacy database environment while preserving access to information required for future use.

60%+

Storage recovered

Recovered storage across database, backup and DR environments.

30%

Database size

Reduced the database footprint to approximately 30% of its prior size.

100%

Optimization

Database was defragmented and optimized to the fullest.

20%

Maintenance window

Reduced maintenance runtime to 20% of the previous overall runtime.

Business Impact

  • Reduced storage consumption and the overhead of redundant database copies across backup and DR environments.
  • Reduced database footprint and maintenance effort, improving the operational efficiency of the legacy environment.
  • Created a structured, auditable method for preserving historical healthcare information while progressing toward legacy-system modernization.
  • Established a repeatable archival framework that can be adapted to data volume, database architecture, retention requirements and access needs.

RalanTech EHR Data Archiving Framework

AssessExtractTransformArchiveValidateAccessRetire

 

Key Takeaway

EHR modernization does not have to mean losing access to historical information or maintaining expensive legacy environments indefinitely. A structured EHR data archiving strategy can preserve critical historical information, maintain controlled access and support legacy-system modernization.

Solution

Implementation Steps

Results

Conclusion

About RalanTech

RalanTech is specialized in database managed services. We are passionate about leveraging cutting-edge solutions to drive innovation, efficiency, and growth for our clients.

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