How to develop a backup and recovery plan

Healthcare organizations and practices rely on a backup and recovery plan to keep their data safe and available. This strategic framework involves creating regular backups of critical data and storing them securely on-site, off-site, or in the cloud. The primary objective is to enable fast and effective data restoration in the event of data loss caused by system failures, human errors, cyberattacks, or natural disasters.

How to assess your data backup needs?

To ensure proper backup of critical data, it is important to evaluate your digital assets by analyzing your business operations. Once you have identified the essential data, you should categorize it based on its role in business continuity, legal compliance, and decision-making value.

After identifying the critical data, you need to consider the rate of data changes, compliance regulations, and the potential consequences of data loss to determine the frequency of backups required. For instance, data that changes frequently, such as transaction records, requires more frequent backups to minimize data loss during recovery. On the other hand, static data, such as historical records, may require less frequent backups.

See also: What is a HIPAA disaster recovery plan?

How to set recovery objectives?

Recovery Time Objective (RTO) and Recovery Point Objective (RPO) are metrics that guide the development of effective backup and recovery strategies. RTO defines the maximum acceptable duration to restore normal operations following a disruption, essentially setting a target time for recovery. This influences the complexity and speed of the recovery solutions you implement; a shorter RTO demands faster, more sophisticated recovery systems. 

RPO, on the other hand, establishes the maximum age of files that must be recovered from backup storage for normal operations to resume after a failure. This metric dictates the frequency of backups; a shorter RPO requires more frequent backups to ensure minimal data loss. Together, RTO and RPO shape the approach to data backup, determining how often data is backed up and the kind of technology required to meet the recovery timelines.

See also: What is a HIPAA data backup plan?

How to handle backup and recovery for different types of data?

Databases

Backing up databases ensures data consistency and integrity. This often involves using database-specific backup tools that can handle open transactions and lock the database to maintain a consistent state during the backup process. Incremental backups are common to reduce the volume of data being transferred and stored. For relational databases, it's also necessary to include transaction logs in backups for point-in-time recovery.

Emails

Backing up emails especially in the case of HIPAA compliant emails typically involves capturing not just the emails themselves, but also attachments and folder structures. Email backups might also need to integrate with specific email servers (like Microsoft Exchange or Google Workspace) in enterprise environments. Email backups must also consider legal and compliance issues, particularly for businesses in regulated industries.

Specialized data types

This can include multimedia files, proprietary formats, or data from specialized software. Here, the focus is on ensuring that the backup solution supports the specific data format and that metadata (like file attributes and permissions) is preserved.

Large-scale data/big data applications

Backing up large-scale data sets requires a strategy that can handle high volumes of data efficiently. This often involves:

• Incremental and differential backups: To manage the sheer volume of data, these methods are preferable as they only back up data that has changed.
• Scalable storage solutions: Cloud-based solutions are often used for their scalability and flexibility.
• Parallel processing and high-performance networks: To speed up the backup process, leveraging parallel processing and high-bandwidth networks can be effective.
• Data deduplication: This technique reduces the storage requirement by eliminating redundant data.