Healthcare GRC
The Hidden Savings of Micro-Segmentation: A Prescription for Lower Cyber Insurance Costs


Healthcare IT teams are discovering that network segmentation, essentially splitting and isolating system components or functions, can be as lifesaving for electronic Protected Health Information (ePHI) as quarantines are for patients.
By containing potential threats to a smaller blast radius, segmentation strengthens security and has the added benefit of cutting costs in an area executives care increasingly about: cyber insurance premiums. In an industry where breaches cost an average of $9.7 million per incident, insurers have begun rewarding organizations that can limit damage through smart, secure network design.
The HIPAA Mandate: Isolating the Clearinghouse
The best way to approach compliance and security is to isolate critical systems beyond what the Health Insurance Portability and Accountability Act (HIPAA) explicitly asks. It’s like how a hospital doesn’t only isolate one patient; it prevents cross-contamination everywhere.
Segmentation has been on the minds of regulators for a long time; the HIPAA Security Rule even includes an addressable safeguard for “isolating healthcare clearinghouse functions.” In plain language, if a healthcare clearinghouse (e.g., a billing system) shares an environment with other units, you must wall it off from other network functions, by employing sufficient subnetting or security groups to isolate each functional system, so the larger organization can’t freely access that sensitive data. It’s a basic security quarantine for one particularly sensitive function.
But why stop at clearinghouses? Of course you should separate your claims clearinghouse database from, say, your general hospital network; however, today’s threat landscape demands broader isolation. You can separate your facilities management (i.e., HVAC) and other non-clinical systems from your IT environments, and your clinical areas from your administrative areas. Security by design mandates process isolation: Every system that handles ePHI or critical operations (i.e., electronic health record servers, lab systems, Internet of Things (IoT) devices) deserves its own “containment room” in your network architecture. Visitor-accessible networks should be relegated to their own VPC, if possible, and be completely walled-off from any systems that process sensitive information.
In order to be effective, as well as compliant, virtual segmentations need to utilize the strongest available encryption, at least FIPS 140-2 (remember that the current FIPS standard will be superseded by FIPS 140-3 in September 2026, and early adoption of the higher standard, where possible, can help save time and money down the line).
Proactively designing an “assume breach” strategy helps contain security incidents, protect operational technology, and secures vulnerable medical devices. Investing in scalable solutions that work within your security and technology budget can help you maximize the value and impact of your security and AI portfolios. Consider defensive architecture elements such as Automated Moving Target Defense (AMTD), which can also help reduce “alert fatigue” by preventing attacks deterministically. AMTD is also highly effective against zero-day exploits, in addition to ransomware and fileless attacks that can bypass standard EDR tools.
Prioritizing on strong defenses that offer big benefits, like employing virtual segmentation to create separate, secure areas in a network to help automate security and compliance work, you can maximize the effectiveness of your security and technology spend while making compliance easier (through automation) and scalable, which will help you stay safe from new threats and grow steadily, giving you that competitive advantage you’ve been looking for.
Segmentation isn’t just a legal checkbox; it’s a design philosophy. The result of a well-designed, properly segmented network is that even internal users are cordoned off from data they don’t need, and any intruder hitting one segment hits a dead end at the segment boundary.
Going Beyond to Stop Lateral Movement
Flat networks are a liability for healthcare. Network micro-segmentation can prevent an intruder’s lateral movement from a compromised endpoint to mission-critical systems like Electronic Health Record (EHR) systems. In addition to microsegments, network policy enforcement must be dynamic and identity aware. By preventing this lateral movement, providers can help ensure that a compromise in one zone doesn’t spread to critical systems. Using software-defined networking (SDN) or other Operational Technology (OT)/IoT-specific segmentation solutions, healthcare organizations can logically isolate IoMT devices into tightly controlled segments.
Modern cyberattacks, especially ransomware, thrive on “lateral movement,” where once hackers break in, they roam your network like an open floor plan. Segmentation slams the doors in their face. A stark lesson came in a widely publicized 2024 ransomware attack on a healthcare payment processor: the breach spread rapidly through flat networks, disrupting many providers’ operations for up to three months. If stronger internal segmentation had been in place, the attack might have been contained in a smaller zone, sparing the rest of the organization.
In 2024 alone, researchers identified 5,461 successful ransomware attacks, based on claims by ransomware groups on their data leak sites. Of those identified, 1,204 of those attacks were confirmed by the attacked organizations. Across North America and Europe, those 1,204 confirmed attacks led to the compromise of 195.4 million records.
This is where micro-segmentation (granular segments down to the workload or device level) shines. A recent industry study of 1,200 security leaders found most organizations do some network segmentation, but few have software-defined/virtual micro-segmentation across all workloads. Those that do report significantly faster threat containment and fewer systems compromised during incidents. Essentially, if malware infiltrates an imaging device network, micro-segmentation ensures it can’t jump into the EHR database or Active Directory. Each segment is a self-contained unit, vastly limiting the “blast radius” of any single breach.
Crucially for healthcare, micro-segmentation aligns with the Principles of Least Privilege and Least Functionality mandated by HIPAA’s Technical Safeguards. By pairing identity-based access controls with segmented network zones, hospitals can ensure only the right personnel or devices talk to each other. This prevents unauthorized snooping around ePHI and is exactly what auditors (and now insurers) love to see: concrete barriers against widespread compromise.
The Insurance Payoff: Lower Premiums and Better Terms
Here’s the part that might get the executive leadership team on board: Insurers increasingly ask about network segmentation during underwriting. Cyber insurance applications now include detailed questions on how you separate and protect critical systems. The reason is simple risk math: segmentation reduces the likely severity of a claim. If you can show that a breach in System A won’t cascade into Systems B, C, and D, insurers know any incident will be cheaper to resolve. And cheaper for them could lead to cheaper premiums for you.
Akamai’s 2025 Segmentation Impact Study noted a clear trend: organizations with mature micro-segmentation report receiving premium credits or reductions on cyber insurance. In fact, some carriers have begun requiring a certain level of micro-segmentation maturity just to bind coverage. It’s becoming a litmus test: a network that’s wide-open internally is seen as a higher-risk (i.e., more expensive) client. Conversely, demonstrating hardened internal firebreaks can tilt underwriting in your favor. As one security executive summarized, companies that adopt micro-segmentation are “responding faster to cyberthreats and enjoying lower insurance premiums.”
Moreover, micro-segmentation can influence more than just the premium cost. Insurers may offer lower deductibles or higher coverage limits if you prove you can contain incidents. In the event of a claim, having kept an intrusion confined might also make the incident less costly, preventing the dreaded post-breach premium spike. Many healthcare organizations have learned that a major breach drives insurance renewals through the roof. In short, robust segmentation is turning into real cash savings, either upfront or over time.
Building a Culture of Secure Isolation
To tie it all together, think of software-defined/virtual micro-segmentation as preventative care for your digital infrastructure. Just as a hospital enforces hand hygiene and separate wards to prevent infections, your IT environment should enforce strict separations to prevent cyber contagion. The HIPAA clearinghouse isolation rule was an early step, but today’s best practices take the spirit of that rule and apply it everywhere: isolate by default.
The broader theme is resilience. A segmented network is inherently more resilient, a single compromised device or user account doesn’t spell total chaos. This resilience not only protects patient safety and privacy but also demonstrates to regulators and insurers that you’re serious about risk management. It’s a proactive stance: you’re not just complying with the minimum (like isolating one clearinghouse); you’re embracing micro-segmentation as a core strategy to protect your entire enterprise. This resilience also pays off by enabling InfoSec teams to craft security policies and rules that apply to specific segments of the network, rather than a “one-size-fits-all” approach.
This can help reduce the costs associated with meeting your GRC requirements through continuous control monitoring, reporting, risk management, and response actions, leading to a more resilient operation that is easier to audit, potentially saving millions in compliance costs while at the same time improving security, and as we all know, security equals compliance!
Conclusion
In healthcare, where stakes are literally life and death, this approach pays dividends. You reduce the chance that a cyber incident interrupts patient care. You increase confidence among partners and patients that their data is safe. And as a bonus, you might just save a substantial sum on cyber insurance, freeing up the budget that can go back into patient services or innovative tech due to lower operational costs and better security for your providers.
Bottom line: Software-defined micro-segmentation is security hygiene that boosts your cyber immune system. It contains breaches before they become multi-million-dollar disasters, which keeps regulators happy, and insurers more likely to cut you a deal. For healthcare executives, that’s a healthy outcome all around: compliance boxes checked, risks mitigated, and costs controlled. In an era of rising cyber threats and insurance premiums, micro-segmentation of systems isn’t just good architecture; it’s good business.
The horizons are boundless when you partner with Coalfire to architect, scope, plan, design, and re-envision the future state of your business with security, AI governance, GRC, and compliance posture. Coalfire can help you unlock trust-centric business outcomes that redefine success and lead to savings on cyber-insurance, so that you can concentrate on saving lives.
Connect with Coalfire’s Healthcare GRC Advisory team. We bring deep, hands-on experience helping healthcare organizations build strong, scalable GRC programs.
Sources:
Abrams, J., Gomez, K., Huffaker, C., & Shivangi, S. (2025, September). Segmentation impact study 2025. Akamai Corporate. https://www.akamai.com/resources/research-paper/segmentation-impact-study-2025
Akamai. (2025, October 8). Reducing risk: Microsegmentation means faster incident response, lower insurance premiums for organizations. Akamai Corporation. https://www.akamai.com/newsroom/press-release/microsegmentation-means-faster-incident-response-lower-insurance-premiums-for-organizations
Alder, S. (2025, January 14). 2024 was another bad year for healthcare ransomware attacks. The HIPAA Journal. https://www.hipaajournal.com/2024-was-another-bad-year-for-healthcare-ransomware-attacks/
American Hospital Association. (2025, January). Change Healthcare cyberattack underscores urgent need to strengthen cyber preparedness for individual health care organizations and as a field. American Hospital Association. https://www.aha.org/system/files/media/file/2025/02/Change-Healthcare-Cyberattack-Underscores-Urgent-Need-to-Strengthen-Cyber-Preparedness.pdf
Centers for Medicare & Medicaid Services. (2025, April 10). Acceptable risk controls for Affordable Care Act (ACA), Medicaid, and partner entities (ARC-AMPE): Volume 1. https://www.cms.gov/files/document/arc-ampe-vol-1-v102-508-5cr-04112025.pdf
Hinton, M. (2025, October 8). Microsegmentation cuts risk fast: Lower cyber insurance premiums, faster containment. Cyber Insurance News. https://cyberinsurancenews.org/microsegmentation-cyber-insurance-premiums-2025/
IBM. (2025). Cost of a data breach report 2025: The AI oversight gap. IBM. https://www.ibm.com/reports/data-breach
Kotha, N. R. (2020, January). Network segmentation as a defense mechanism for securing enterprise networks. Turkish Journal of Computer and Mathematics Education (TURCOMAT). https://www.researchgate.net/publication/386653750_Network_Segmentation_as_a_Defense_Mechanism_for_Securing_Enterprise_Networks
McKeon, J. (2025, July 16). Minimizing healthcare cyberattacks with network segmentation. TechTarget. https://www.techtarget.com/healthtechsecurity/feature/Minimizing-healthcare-cyberattacks-with-network-segmentation#:~:text=HHS%20underscored%20the%20importance%20of,help%20healthcare%20organizations%20reduce%20risk
U.S. Department of Health and Human Services. (2013, March 26). HIPAA administrative simplification. Health and Human Services U.S. Government. https://www.hhs.gov/sites/default/files/ocr/privacy/hipaa/administrative/combined/hipaa-simplification-201303.pdf
Morphisec. (n.d.). Achieving cyber resiliency with automated moving target defense. https://engage.morphisec.com/hubfs/Achieving-Adaptive-Cyber-Resiliency-WhitePaper.pdf