Ultimate Guide to Network Segmentation in Healthcare
Post Summary
Healthcare organizations face constant cyber threats, with the average cost of a data breach in the industry reaching $10.93 million per incident in 2024. Network segmentation - dividing networks into secure zones - reduces these risks by limiting lateral movement, isolating sensitive systems, and protecting critical medical devices. This approach aligns with regulatory requirements like HIPAA and supports Zero Trust principles.
Key Takeaways:
- What it is: Network segmentation creates separate zones in a network to control communication and reduce risks. Microsegmentation goes further by isolating individual devices.
- Why it matters: Prevents widespread damage during breaches, protects patient data, and ensures compliance with regulations like HIPAA.
- How it works: Uses tools like VLANs, firewalls, and NAC to enforce strict access controls and monitor traffic.
- Real-world example: The 2021 ransomware attack on Ireland's healthcare system showed how unsegmented networks allow attackers to spread easily.
- Steps to implement:
- Identify and prioritize devices (e.g., EHRs, infusion pumps, PACS).
- Design segmentation rules based on risk.
- Use tools like 802.1X, firewalls, and mTLS.
- Continuously monitor, test, and update policies.
With stricter HIPAA requirements expected by 2026, healthcare providers must act now to secure their networks. Segmentation minimizes breach impact, protects patient safety, and ensures compliance.
Healthcare Microsegmentation in 2025: RSAC Expert Discussion | Elisity
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Core Concepts and Regulatory Requirements
Let’s dive into the technical and regulatory foundations of network segmentation, a critical strategy for reducing risks and ensuring compliance.
Key Components of Network Segmentation
Network segmentation relies on tools like VLANs, VRFs, ACLs, and firewalls to create secure boundaries within a network. Here's how these components work:
- VLANs (Virtual Local Area Networks) and VRFs (Virtual Routing and Forwarding) group devices based on their function or sensitivity. For example, clinical systems are kept separate from administrative systems.
- ACLs (Access Control Lists) and firewalls enforce security by using default-deny policies, ensuring only approved traffic flows between segments. In a hospital, this might mean only DICOM traffic is allowed to access the PACS server.
Microsegmentation takes this a step further by isolating individual devices and workloads, significantly limiting lateral movement. This approach is particularly vital for protecting DAAS systems that handle sensitive data like ePHI.
Additionally, NAC (Network Access Control), often using protocols like 802.1X, profiles devices and isolates any that are unknown or non-compliant. Together, these technologies reduce the potential impact of breaches and help meet strict regulatory requirements for healthcare networks.
How Segmentation Maps to U.S. Regulatory Frameworks
Network segmentation plays a direct role in meeting key requirements of the HIPAA Security Rule. As Kevin Henry from AccountableHQ notes:
"Network segmentation is a primary way to meet [HIPAA] expectations by limiting who and what can reach ePHI systems, logging permitted flows, and preventing lateral movement." [3]
Here’s a breakdown of how segmentation aligns with specific HIPAA standards:
| HIPAA Security Rule Standard | Regulatory Citation | How Segmentation Supports Compliance |
|---|---|---|
| Risk Management | § 164.308(a)[3] | Reduces the attack surface and minimizes breach impact. |
| Workforce Security | § 164.308(a)[1] | Implements role-based access control by restricting data access based on job roles. |
| Access Control | § 164.312(a)[3] | Ensures only authorized personnel and processes can access ePHI. |
| Audit Controls | § 164.312(b) | Logs all traffic attempts between network segments, aiding in monitoring and incident response. |
| Transmission Security | § 164.312(e)[3] | Protects ePHI during electronic transmission from unauthorized access. |
Segmentation also aligns with the NIST Cybersecurity Framework, particularly its Identify, Protect, and Detect functions. With proposed updates to the HIPAA Security Rule expected by 2025, segmentation may soon shift from being "addressable" to a mandatory requirement for healthcare organizations [2]. Starting early on segmentation can help organizations stay ahead of these changes.
Flat vs. Segmented vs. Microsegmented Networks: A Comparison
The 2021 ransomware attack on Ireland's Health Service Executive (HSE) underscores the risks of unsegmented networks. A post-incident review revealed that the "primarily unsegmented" National Healthcare Network allowed attackers to move laterally across multiple organizations after the initial breach [1]. As the report stated:
"Network architecture, coupled with a complex and unmapped set of permissions for systems administrators... enabled the Attacker to access a multitude of systems across many organisations and create the large-scale impact that they did." [1]
The table below compares different network architectures:
| Network Type | Security Posture | Lateral Movement Risk | Regulatory Support | Implementation Complexity | Healthcare Use Case |
|---|---|---|---|---|---|
| Flat Network | Low; perimeter-only | High; unrestricted once breached | Poor; fails HIPAA risk management | Low | Suitable for small clinics without ePHI systems. |
| Segmented Network | Moderate; VLANs and firewalls | Medium; limited to broad zones | Meets basic HIPAA safeguards | Moderate | Ideal for separating guest Wi‑Fi from clinical VLANs. |
| Microsegmented | High; Zero Trust/identity‑based | Low; isolated to individual workloads | Supports upcoming HIPAA updates | High (requires automation) | Best for isolating critical devices like infusion pumps from EHR databases. |
For healthcare organizations, transitioning from flat to segmented and eventually microsegmented networks is essential to improve security and maintain compliance. A phased approach ensures manageable implementation while addressing both current and future regulatory needs.
Planning Network Segmentation for Healthcare
Flat vs. Segmented vs. Microsegmented Networks in Healthcare
Asset and Data Discovery
Before diving into segmentation, healthcare organizations must first identify every device connected to their network. This step isn't just a recommendation - it's a necessity. For instance, Main Line Health in Philadelphia manages over 60,000 devices, while Luminis Health in Maryland oversees a staggering 100,000 devices. At this scale, manually tracking assets is simply not feasible [4].
The next step is prioritizing assets for segmentation. This involves mapping data flows to understand which systems handle electronic Protected Health Information (ePHI). By documenting how ePHI is created, transmitted, or stored, organizations can pinpoint areas where microsegmentation is essential. Profiling communication patterns - such as identifying protocols like HL7, DICOM, and HTTPS - helps clarify whether connections are clinical or non-clinical, offering better visibility into network activity [3].
For sensitive medical devices like infusion pumps or patient monitors, passive discovery methods are the safer choice. Active scanning can disrupt these fragile devices, potentially causing instability [3].
Here’s an example of how assets can be prioritized after discovery:
| Asset Category | Examples | Segmentation Priority |
|---|---|---|
| Medical IoT/IoMT | Infusion pumps, patient monitors | High (life-safety) |
| Clinical Data Platforms | EHR, PACS, LIS, RIS, interface engines | High (ePHI sensitivity) |
| Infrastructure | Active Directory, DNS, backup systems | High (system integrity) |
| Operational Technology | HVAC, water pumps, building automation | Medium (business continuity) |
| General IT | Laptops, tablets, printers, VoIP phones | Low/Medium (standard risk) |
Maintaining a Software Bill of Materials (SBOM) for critical applications is another important step. Tracking vendor support and identifying known vulnerabilities ensures that organizations can design their segmentation strategies with risk in mind [3]. With a complete asset inventory and a clear priority list, healthcare providers are better equipped to implement segmentation strategies that focus on clinical risks.
Risk-Based Segmentation Design
Once all assets are accounted for, the next step is to design segmentation strategies based on risk. The idea here isn’t to isolate every device but to focus on reducing clinical and data-related risks effectively.
Segmentation controls should be tailored to each asset’s purpose. For example, imaging systems might only need DICOM protocols, while interface engines require HL7 [3]. This approach ensures that segmentation minimizes exposure to ePHI without disrupting essential operations.
The University of Michigan Health (Michigan Medicine) illustrates this strategy well. They use Cisco's Identity Services Engine (ISE) to automate device placement, ensuring that devices like infusion pumps are automatically assigned to the correct virtual network. This automation helps prevent unauthorized access and simplifies management [4].
Evaluating a device’s security posture before purchase can also save organizations from future headaches. Luminis Health learned this the hard way when a blood chemical analyzer arrived with Windows CE, an unsupported operating system. This forced them to implement defensive segmentation before allowing the device on their network [4].
Jason Taule, a Virtual CISO, summed up the challenge:
"Hospitals don't have billions of dollars to replace stuff that works. That means devices can stay in use for years, maybe even more than a decade." [4]
A phased rollout based on risk assessments is often the best way to avoid disruptions. Start with high-criticality zones, such as life-safety devices and ePHI platforms, and then move to operational technology and general IT systems [1].
Governance and Change Management
Even the best technical designs can fail without strong governance. Governance ensures that segmentation strategies remain effective as new devices are added, workflows evolve, and exceptions arise.
Achieving buy-in from clinical staff is one of the biggest hurdles. Aaron Weismann, CISO at Main Line Health, shared his experience during a 1.5-year microsegmentation rollout:
"Anytime you walk into a clinical space and say, 'I'm going to prevent some of your devices from talking to each other,' that gets very scary when it comes to potential disruptions to patient care. There's a long education process around what that actually means." [4]
Educating staff on the practical implications of segmentation is essential to maintain momentum.
On the policy side, segmentation rules should be treated like code - versioned, peer-reviewed, and tested before deployment [3]. New devices should not communicate on the network until they are classified and assigned to a segment, enforcing a "default-deny" approach [3]. Similarly, third-party vendor access must be tightly controlled. Business Associate Agreements (BAAs) should be tied to measurable network controls, with vendor access re-certified quarterly to eliminate unused accounts [3].
With the upcoming 2026 HIPAA Security Rule changes making network segmentation a mandatory requirement, documented governance is no longer just a good practice - it’s a baseline necessity [6].
Designing and Implementing Segmentation Architectures
Once planning and risk assessments are done, the next step is creating effective segmentation architectures.
Basic Segmentation Patterns
Let’s start with the building blocks of segmentation. At the core of any healthcare network segmentation project are VLANs (Virtual Local Area Networks) and ACLs (Access Control Lists). However, without Layer 3 inspection, traffic can still move laterally between VLANs. To address this, pairing VLANs with stateful firewalls is a must.
The first step is to define distinct zones. For example:
- Clinical IoT: Devices like infusion pumps and patient monitors
- Clinical Data: Systems such as EHR (Electronic Health Records) and PACS (Picture Archiving and Communication System)
- Operational Technology: Equipment like HVAC systems
- Guest Wi-Fi: Visitor and patient devices
Default-deny ACLs and client isolation should be applied where necessary. For instance, in guest Wi-Fi networks, client isolation blocks lateral movement, a common attack vector.
Another key practice is isolating the management plane. Keeping network management interfaces on a separate, out-of-band network ensures attackers can’t pivot to these critical systems, even if a production segment is compromised.
Building on these foundational patterns, microsegmentation adds a finer layer of control, targeting individual devices or workloads.
Microsegmentation and Zero Trust Implementation
Traditional VLANs group devices by type or department, but microsegmentation takes this further. It enforces policies at the individual device or workload level, ensuring that even devices within the same VLAN cannot communicate unless explicitly allowed.
This approach shifts access control to an identity-based model. Instead of granting access simply because a device is on a specific VLAN, access depends on verified identity, device health, and contextual factors. For instance, a policy might allow only an EHR application to communicate with its database on a specific port, while blocking all other traffic by default. This aligns with Zero Trust principles, which, as AccountableHQ explains:
"Zero trust treats every request as untrusted until identity, device posture, and context are verified." [3]
Implementing this often involves deploying 802.1X authentication, which requires devices to prove their identity before accessing the network. A practical example is Michigan Medicine’s use of Cisco Identity Services Engine (ISE). If a patient unplugs a medical device and connects a personal device (like a gaming console) to the same port, the system automatically disables the port.
For securing east–west traffic between clinical workloads, protocols like mutual TLS (mTLS) or IPsec provide encryption and authentication at both ends of the connection. To maintain clarity and prevent rule sprawl, treat segmentation rules as policy-as-code - versioned, peer-reviewed, and thoroughly tested.
Securing Medical IoT and Cloud Environments
Healthcare networks also need tailored strategies for securing medical IoT devices and cloud environments.
Medical IoT devices pose unique challenges. Many run outdated operating systems, lacking modern authentication and patching features. The solution? Place these devices in highly restricted segments that allow vendor updates but isolate them from other clinical networks.
Jason Taule, Virtual CISO at Luminis Health, highlights this issue:
"The U.S. Food and Drug Administration process is flawed, because you don't have to go through a new certification if you don't change your product, giving companies no incentive to update an old, unpatched, vulnerable thing." [4]
For cloud and hybrid environments, the same segmentation principles apply, but enforcement tools differ. Static IP-based rules don’t work well in dynamic cloud settings where workloads frequently change. Instead, use tags and labels tied to data classification. For instance, a container tagged for ePHI (electronic protected health information) processing can automatically inherit the necessary access restrictions, whether it’s running on-premises or in AWS.
Here’s a quick summary of control mechanisms by segment type:
| Segment Type | Target Assets | Primary Control Mechanism |
|---|---|---|
| Clinical IoT | Infusion pumps, monitors, ventilators | NAC (802.1X), sandboxing, default-deny ACLs |
| Medical Imaging | MRI, CT, Ultrasound, PACS | Protocol-specific filters (DICOM), restricted VLANs |
| Cloud Workloads | EHR apps, APIs, serverless functions | Identity-based tags, mTLS, Layer 7 policies |
| Operational Tech | HVAC, water pumps, elevators | Isolated OT segments, out-of-band management |
| Guest/Public Wi-Fi | Patient and visitor devices | Client isolation, complete network block |
To effectively manage third-party risk, never allow direct inbound connections to clinical VLANs. Instead, route vendor sessions through a hospital-controlled jump host within a dedicated vendor zone. Require multi-factor authentication and comprehensive session logging to maintain visibility and control.
These strategies lay the groundwork for the operational practices covered in the next section.
Operational Best Practices and Continuous Improvement
Keeping segmentation effective isn't a one-and-done task. As devices and workflows evolve, constant oversight is necessary to prevent even the best segmentation strategy from becoming outdated.
Monitoring and Measuring Segmentation Effectiveness
To make improvements, you need to measure performance. Key metrics to track include the number of blocked lateral movement attempts, unauthorized VLAN change attempts, and the percentage of policy coverage for critical assets [3].
Logging both east–west and north–south traffic is essential for spotting anomalies and maintaining HIPAA compliance. Tools like SIEM consolidate identity and network alerts, while NDR tools highlight internal traffic anomalies that perimeter defenses might overlook.
A useful way to test segmentation is through chaos engineering - controlled failure scenarios to see how segmentation holds up under stress. For example, in March 2026, Main Line Health tested this approach on 100,000 segmented devices. The results? No unplanned outages and the discovery of critical issues, like non-functional emergency communication lines, before attackers could exploit them [7].
"Chaos engineering is where you intentionally hinder your systems to test the resilience of the overall system. We wanted to intentionally force parts of our network down so we could test the resilience of our nurses, test the resilience of our patient care, test the resilience of our devices." - Aaron Weismann, CISO, Main Line Health [7]
Regular vulnerability scans are also crucial. They not only prevent policy drift but have helped 60% of organizations cut cyber insurance costs. Additionally, 75% of insurers now assess segmentation maturity as part of their underwriting process [7].
These monitoring efforts directly support solid change management and resilience planning.
Change Management and Resilience Planning
Every network change introduces potential segmentation risks. The best defense? Treat segmentation policies as policy-as-code - versioned, peer-reviewed, and tested before deployment. This approach minimizes manual errors and prevents unnecessary rules that could weaken security [3].
Connecting your asset inventory to change management workflows ensures no device joins the network without proper classification. Unclassified devices should automatically move to a quarantine VLAN using 802.1X, rather than being placed in production. After major updates, run out-of-cycle vulnerability scans to confirm no new vulnerabilities have been introduced [3].
Resilience planning isn't just about technology - it’s also about preparing clinical staff. Teach them how to revert to paper charting or analog processes if a segment becomes isolated. These aren't just IT drills; they're vital for patient safety. These steps ensure segmentation continues to protect ePHI and clinical operations.
| Change Management Phase | Best Practice | Objective |
|---|---|---|
| Pre-Deployment | Peer review and versioning of policies | Prevent misconfigurations |
| Implementation | Automated dependency mapping | Protect clinical workflows |
| Post-Deployment | Out-of-cycle vulnerability scanning | Validate that no new exploit paths exist |
| Maintenance | Fixed-cadence removal of unused rules | Reduce rule sprawl |
| Emergency | Auto-isolation to quarantine VLANs | Contain threats without full shutdown |
Integrating Segmentation with Risk Management Platforms
For long-term success, segmentation must align with centralized risk management. Tools like Censinet RiskOps™ provide healthcare organizations with a streamlined way to manage risk while enhancing cybersecurity.
Network segmentation is one of the 10 Enhanced Healthcare and Public Health Sector Cybersecurity Performance Goals (HPH CPGs) established by HHS on January 24, 2024 [8]. A centralized risk platform helps map technical controls to frameworks like HIPAA and the HPH CPGs, offering clear visibility from firewall rules to compliance status. This complements strategies for HIPAA compliance and Zero Trust implementation.
Censinet RiskOps™ enhances this with a Risk Register that tracks open segmentation gaps, automates corrective actions, and provides audit-ready reports for regulators and boards. For third-party vendors, the platform’s digital risk catalog identifies which vendors need segmented access and flags overdue re-certifications of vendor accounts [8].
"Network segmentation is a primary way to meet [HIPAA] expectations by limiting who and what can reach ePHI systems, logging permitted flows, and preventing lateral movement." - Kevin Henry, Accountable [3]
Conclusion and Key Takeaways
Network segmentation has become a non-negotiable pillar for healthcare organizations aiming to safeguard patient data and meet compliance standards. In 2024, a staggering 82% of the U.S. population's healthcare records were either exposed, stolen, or improperly disclosed [5]. Combine that with the $9.77 million average cost of a healthcare data breach [5], and the urgency for action becomes undeniable.
The key takeaway here is simple: unsegmented networks are a ticking time bomb. The 2021 HSE ransomware attack serves as a stark reminder - without segmentation, attackers can roam freely, causing widespread disruption across interconnected systems [1]. Segmentation acts as a critical barrier, slowing down attackers and minimizing the damage when breaches occur. This guide outlines how healthcare organizations can use segmentation as a roadmap to strengthen their network defenses.
Several principles stand out as essential. First, start with a comprehensive asset inventory - you can't secure what you don't know exists. This is especially critical when managing tens of thousands of devices. Next, isolate high-risk assets like EHRs, PACS, infusion pumps, and ventilators with default-deny policies. Treat segmentation as a continuous process - policies need regular testing, updates, and reviews to stay effective. Consistent monitoring and change management are equally vital to maintaining these defenses.
Aaron Weismann, CISO at Main Line Health, emphasizes the importance of this approach:
"Organizations have to implement network segmentation in some form, and they have to protect their devices in ways that simple patching won't be able to address." [4]
Looking ahead, the 2026 HIPAA Security Rule will enforce stricter technical controls, making segmentation a regulatory requirement rather than just a best practice [6]. To meet these evolving standards, healthcare organizations must integrate segmentation into their broader risk management strategies. By combining asset discovery, segmentation policies, and governance frameworks, they can build a resilient foundation for healthcare cybersecurity.
FAQs
What should we segment first in a hospital network?
To get started, identify and categorize all assets in your network - this includes devices, systems, and data flows. Pay particular attention to segmenting critical systems such as electronic health records (EHR), medical devices, and clinical applications. This segmentation helps strengthen security, enforce stricter access controls, and minimize potential threats.
Focus first on systems that handle sensitive data, like electronic protected health information (ePHI), and devices that may be more vulnerable to attacks. By doing so, you can reduce risks, prevent unauthorized access, and ensure compliance with regulations such as HIPAA.
How is microsegmentation different from VLAN-based segmentation?
Microsegmentation offers a level of precision and control that VLAN-based segmentation simply can't match. While VLANs group devices into large network segments, creating broader domains, they often leave room for lateral movement within those segments. Microsegmentation, on the other hand, enforces detailed, workload-specific policies. This approach restricts communication to only what’s necessary between specific devices, applications, or services, effectively limiting access and containing potential threats. This level of control is particularly crucial in healthcare, where protecting sensitive data like ePHI and securing medical devices is a top priority.
What tools are needed to enforce segmentation without disrupting patient care?
Healthcare organizations aiming to implement network segmentation without disrupting patient care rely on tools like VLANs and microsegmentation platforms. These technologies help isolate device groups and limit unnecessary communication across the network.
To ensure only approved devices access sensitive areas, Network Access Control (NAC) and device profiling come into play, along with real-time monitoring. Automated policy management and continuous testing also play a key role, supporting segmentation efforts while keeping clinical operations running smoothly.
