Without effective segmentation, attackers can pivot from the first compromised device into imaging systems, administrative tools, and other clinical assets. That expansion increases the likelihood of patient data exposure, operational disruption, and ransomware impact. In healthcare, the consequence is not just a larger incident, but a harder recovery and wider regulatory exposure.
Why Hospital Segmentation Breaks Matter at the Bedside
When a hospital network lacks effective segmentation around connected medical devices, a single foothold can become a path into systems that support care delivery, not just IT operations. That changes the incident from a contained device compromise into a broader clinical and governance problem, because imaging platforms, infusion-related workflows, and administrative tools often share trust relationships that attackers can abuse. Current guidance suggests that trust boundaries in healthcare should be treated as operational safety boundaries, not merely network design choices.
Hospitals also need to think about the identity and trust layer behind the devices. Many connected devices are difficult to patch, difficult to monitor, and dependent on service accounts or vendor access paths that are rarely managed like ordinary endpoints. Segmentation therefore protects more than traffic flow: it limits how far stolen access can move before defenders notice. The pattern is reflected in NHIMG research showing that 72% of organisations have experienced or suspect a breach of non-human identities, which is relevant here because medical devices often rely on machine credentials and embedded trust relationships.
In practice, many security teams discover the importance of segmentation only after an apparently narrow device issue has already disrupted clinical operations or exposed adjacent systems.
How Segmentation Works in Practice for Connected Medical Devices
Effective segmentation separates connected medical devices into tightly controlled zones with explicit rules for what they may reach, what may reach them, and which management paths are allowed. The goal is not to isolate every device completely. The goal is to stop lateral movement, reduce blast radius, and preserve essential clinical communications while blocking unnecessary east-west access.
In a hospital environment, that usually means distinguishing between device classes and business functions. A bedside monitor should not have the same reach as an imaging archive, and neither should have broad access to administrative systems. Where remote vendor support is required, the access path should be time-bound, logged, and restricted to the minimum destination set. Zero trust thinking is useful here because it treats each connection as something to verify, not something to inherit from a flat internal network. NIST SP 800-207 Zero Trust Architecture is a useful reference for this model.
Operationally, practitioners should expect three pressure points:
- Legacy devices may not support modern agents or inline controls, so network policy must do more of the work.
- Clinical uptime requirements can delay patching, which makes segmentation one of the few reliable containment controls.
- Shared service accounts and vendor tunnels can undermine otherwise good zoning if they are allowed to cross boundaries broadly.
NHIMG data is useful as a reality check here: the 2024 ESG report found that enterprises experiencing a compromised NHI averaged 2.7 separate incidents in the past 12 months. That matters in hospitals because repeated compromise is often what turns a device issue into a recurring operational problem rather than a one-time alert. For a deeper NHIMG discussion of breach patterns, see The 52 NHI breaches Report.
These controls tend to break down when device fleets are heterogeneous and business units have carved out ad hoc exceptions that bypass the intended zone model.
Common Variations and Edge Cases
Tighter segmentation often increases operational overhead, requiring hospitals to balance patient-care continuity against containment strength. That tradeoff is real, especially where device vendors assume broad internal reach or where clinical systems were never designed for strict network zoning.
Best practice is evolving around exceptions. For example, a life-critical device may need controlled connectivity to update servers, logging collectors, or support tools, but that does not justify unrestricted access to the rest of the hospital network. Similarly, an imaging platform may need to talk to a specific archive or orchestration service, yet still be barred from administrative workstations and general file shares. The design principle is to permit only the minimum necessary paths and to review them as a governance obligation, not a one-time infrastructure decision.
Hospitals should also be careful not to confuse segmentation with visibility alone. Passive monitoring helps detect unusual movement, but if the device can already reach too much, detection arrives after the exposure has expanded. For that reason, segmentation is strongest when paired with inventory discipline, credential scoping, and vendor access review. The practical question is not whether the network is “protected,” but whether a compromise of one device can realistically be kept from becoming a clinical-domain incident.
Practitioner Guidance: Prioritise the zones that connect clinical technology to administrative and identity-heavy systems first, because those crossings usually determine blast radius.
What to verify: Confirm that every allowed device-to-system path has a named business purpose, an owner, and a removal trigger. If a device relies on a shared account or vendor channel, treat that path as a segmentation exception requiring explicit review, not as normal connectivity.
What good looks like: A breach of one connected device should expose only a narrow set of services, with no direct route into clinical records, directory services, or broad administrative tooling.
Practitioner takeaway: In healthcare, segmentation is valuable because it preserves time, scope, and recoverability after the first compromise, not because it prevents every intrusion.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
CIS Controls v8, NIST CSF 2.0 and NIST Zero Trust (SP 800-207) set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| CIS Controls v8 | CIS Control 12 — Network Infrastructure Management | Segments hospital networks to limit lateral movement from compromised devices. |
| CIS Control 6 — Access Control Management | Restricts who and what can traverse device management and vendor access paths. | |
| Recommendation — Enforce zone boundaries and restrict east-west traffic between medical and administrative systems. Tighten permitted access paths for device admins, vendors, and shared accounts. | ||
| NIST CSF 2.0 | PR.AC — Identity Management, Authentication, and Access Control | Controls how trust and access are granted across clinical and device environments. |
| PR.PT — Protective Technology | Uses technical controls to confine device communications and reduce blast radius. | |
| RS.MI — Mitigation | Supports containment actions after device compromise to stop further spread. | |
| Recommendation — Apply least-privilege access rules to prevent one compromised device from reaching broader assets. Deploy technical containment controls that enforce segmentation and limit propagation. Contain compromised device paths quickly to reduce downstream clinical disruption. | ||
| NIST Zero Trust (SP 800-207) | SP 800-207 — Zero Trust Architecture | Treats internal device traffic as untrusted unless explicitly verified and bounded. |
| Recommendation — Verify each device connection explicitly and deny implicit trust across hospital zones. | ||
Related resources from NHI Mgmt Group
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on September 8, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
