Most healthcare organizations have governance, risk, and compliance (GRC) programs. Most have some form of operational resiliency planning.
But have you connected the two in ways that explicitly account for legacy data? That gap is where impact radius grows unchecked.
GRC frameworks are designed to manage organizational governance, risk, and regulatory compliance. Resiliency programs focus on continuity of operations and technology recovery. When they function in silos, legacy data tends to fall through the cracks – acknowledged by neither program as its primary responsibility yet posing risk to both.
Integrating legacy data into your GRC and resiliency models requires asking some critical questions:
- Does your data governance framework explicitly include legacy systems and archived data?
- How often are legacy systems assessed for risk, and do active retirement plans exist?
- Is your HIM team equipped to efficiently access complete patient records when needed, including historical data from retired systems?
On the resiliency side, the imperative is to identify, classify, and manage data before a crisis forces the issue. Think of it in practical terms: some data gets used daily, some weekly, some quarterly, and some hasn’t been touched in years. Each category carries a different risk profile and warrants a different strategy for storage, backup, and recovery.
The organizations that handle incidents best are the ones who understand their data landscape before anything goes wrong. They know:
- which records are on which systems,
- have documented retention periods, and
- have moved inactive data off production environments.
A mature GRC and resiliency model operationalizes these practices through a continuous cycle: assess, design, implement, and operate.
Managing legacy data isn’t a one-time cleanup project. Rather, it’s an ongoing governance discipline. We’ll talk more about that – and the discipline of cyclic archiving – in our final post of the series.