How to safeguard patient data and prevent medical identity theft

by Experian Health 4 min read July 23, 2019

Medical identity theft is a growing problem for the healthcare industry: nearly 15.1 million patient records were compromised in 2018, an increase of nearly 270% on the previous year.

While providers are busy rolling out patient portals and electronic medical records to better serve consumers, criminals are sneaking through the cracks to steal patient data and profit from vulnerable health systems.

The rapid rise in medical identity theft is partly explained by the fact that it goes undetected for much longer than other types of identity theft, giving criminals more time to use stolen personal information for financial gain. It’s also a lot more lucrative. Medical identities can be used to access treatment and drugs, make fraudulent benefits claims and even create fake IDs to buy and sell medical equipment.

This can be devastating for victims, both emotionally and financially. Unlike credit card theft, where victims aren’t considered financially liable, 65% of people who fall prey to medical identity fraudsters are left with hospital bills running into the tens of thousands. The compromised medical record is tough to reconcile, jeopardizing future medical treatment.

For providers, a data breach can mean significant reputational damage and loss of trust, and huge financial consequences – each breach costs an average of $2.2 million.

But what’s most alarming for providers is that more than half of data breaches originate within the organization. Unfortunately, many providers lack sufficient security protocols and detection tools to safeguard the data they’re holding.

The good news is that the tools exist to help you protect your patient data.

What can healthcare providers learn from other industries about identity protection?

Banking and financial services have pioneered identity protection over the last twenty years, and healthcare can learn a lot by looking at what’s worked in those industries.

For consumers, using digital technology to pay your bills, book flights and buy pretty much anything is the norm, all with reassuringly quick fraud detection and resolution.

Healthcare has been a little slower to embrace digitization in this way. Despite the opportunities, fears around security, privacy and inconveniencing patients have stalled efforts to transform outmoded processes.

Drawing on two decades of innovations in other fields, fast-paced technological developments mean many of the early challenges around implementing safe and secure patient portals have been overcome.

6 strategies to keep patient data safe

Here are six smart ways to ensure your organization has done everything possible to safeguard patient data.

  1.     Tell your patients how you’re keeping their data safe

Patient trust is at the heart of a successful patient-provider relationship. Share the steps your organization is taking to secure patient information, so patients feel reassured and confident in using their portal. Data security should be a key strand in your patient engagement messaging.

  1.     Verify patient identities to protect access to medical records

To avoid HIPAA violations, it’s critical to ensure you’re giving access to the right patient. Secure log-in monitoring and device intelligence can help you confirm that the person trying to log in is who they say they are. When something doesn’t add up, identity proofing questions can be triggered to provide an extra check.

In an exciting new development, the healthcare industry is also starting to see the use of biometrics to supplement existing identity-proofing solutions. Just as you might use facial recognition to unlock your smartphone, there are now ways to authenticate your healthcare consumers’ identity using the same technology.

  1.     Automate patient portal enrollment

You want your portal to be as secure as possible, but not at the expense of your patients’ time and effort. An automated enrollment process can eliminate the hassle of long, complicated set-ups and reduce errors at the same time.  

  1.     Arm your organization with a multi-layered security strategy

There is no silver bullet for protecting patient information—it will require various tools. A robust data security strategy will be multi-layered, including device recognition, identity proofing and fraud management.

  1.     Educate staff on security threats and warning signs

Data breaches aren’t all malicious – human error is a massive component, from mailing personal data to the wrong patients, to accidentally publishing data on public websites or leaving a laptop behind after getting off the subway. Training staff on the potential pitfalls will help them help you in protecting confidential patient information.

  1.     Develop a robust device strategy

‘Bring Your Own Device’ arrangements (BYOD) are convenient for staff and patients, but personal devices need to be secured when accessing patient information across the network. Make sure your teams, patients and visitors are aware of how to log-on securely to WiFi and follow best practice to keep data safe.

In a climate of ‘doing more with less’, healthcare leaders are turning to other industries to find ways to boost quality of care and streamline operational efficiency. Automation, digitization and consumer-centric approaches make good business sense across the board, but they’re sensible investments for your data security strategy too. Investing in secure patient identities is a way to prevent painful and unnecessary losses down the line – and it’s what patients have come to expect.

⁠—

Find out what more you could do to shore up your data security and prevent medical identity theft.

Related Posts

Andy’s New WP Workflow Test Article Using Quick Edit

Key takeaways: Revenue cycle teams can use automation to reduce repetitive work and apply AI where data-driven prediction, matching or prioritization can improve a workflow. Experian Health’s 2025 State of Claims survey found that 41% of providers now face denial rates of 10% or higher, while 68% say submitting clean claims is more challenging than a year ago. Patient Access Curator™ (PAC) uses AI to support front-end data validation and insurance discovery, while AI Advantage™ helps teams predict denial risk and prioritize denial follow-up. Artificial intelligence (AI) and automation can support administrative work in healthcare. In the revenue cycle, teams depend on accurate information, timely decisions and efficient follow-up to keep claims moving. In revenue cycle management, AI and automation can help organizations reduce manual checks, find data gaps, predict denial risk and prioritize work queues. These tools are most useful when they support staff judgment, payer expertise and compliance oversight. They can handle repetitive, data-heavy tasks so staff can focus on exceptions and decisions that need human review. In 2023, McKinsey & Company reported that research suggests effectively deploying automation and analytics could eliminate $200 billion to $360 billion of spending in U.S. healthcare. For revenue cycle leaders, the practical question is where to apply those capabilities first. The case for applying AI and automation in healthcare Revenue cycle teams juggle many daily tasks. Staff collect and verify patient information, confirm eligibility, identify the right payer, submit clean claims, monitor status, work denials and manage collections. Small data gaps at the beginning of the process can create downstream rework and delays. Rework also consumes staff time, adding to these operational pressures. As costs rise and revenue cycles tighten, there is increasing pressure to do more with less. Experian Health’s 2025 State of Claims survey found that 54% of providers say claim errors are increasing and 90% of claim denials are reworked with at least some human review before resubmission. Providers are also managing broader financial and administrative pressures. The American Hospital Association has reported that prior authorization requirements, claim audits, denials and other payer policies add administrative burden and cost for hospitals and health systems. These requirements also consume staff time to appeal denials and manage payer processes. AI and automation are different but complementary. Automation follows defined rules to complete repeatable work. AI models can identify patterns in data, predict risk and help teams decide where to focus attention. When used together, they can support more consistent revenue cycle workflows. How AI and automation can support revenue cycle workflows Revenue cycle management automation and AI are most useful when tied to a specific workflow and a measurable operational problem. The goal is to help teams act earlier, reduce avoidable rework and focus staff time where judgment is needed most. For example, automation can complete rule-based eligibility checks. AI can help identify claims with a higher likelihood of denial. In insurance discovery workflows, AI can also help identify coverage that wasn’t captured at registration. When these tools fit into existing workflows, they can support more consistent decisions and reduce manual work. Three practical applications include: 1. Improving front-end data quality with Patient Access Curator Patient and coverage information collected early in the revenue cycle can affect downstream claim outcomes. Incomplete or outdated demographic details, eligibility responses, coordination of benefits or Medicare Beneficiary Identifier information can create problems that lead to claim delays or denials later in the cycle. Experian Health’s Patient Access Curator helps prevent claim denials by validating demographics, eligibility, insurance discovery, coordination of benefits and Medicare Beneficiary Identifier data in seconds. PAC’s AI and machine learning capabilities help improve match accuracy, coverage sequencing and data confidence by writing the validated data back into the host system and sequencing payers before the claim is created. This automates work that would otherwise require manual coverage checks. 2. Using insurance discovery to find coverage not captured at registration When active coverage isn’t identified during registration, claims may be delayed or submitted with incomplete insurance information. Insurance discovery looks for coverage that may not have been captured during registration. Patient Access Curator includes insurance discovery as part of its front-end validation workflow. It can help identify and correct missing or incorrect insurance information so claims can be submitted with more complete coverage data. 3. Using AI to prevent and prioritize denials Even with strong front-end processes, some claims still require additional attention. AI can help claims teams decide which claims to review before submission and which denials to work first after payer response. Experian Health’s AI Advantage supports two denial management use cases:1. AI Advantage – Predictive Denials uses a client’s historical claims data and Experian’s knowledge of payer rules to identify claims with a high likelihood of denial before submission so teams can take corrective action.2. AI Advantage – Denial Triage uses AI to segment denials and identify those with the highest potential for reimbursement. This approach can help teams prioritize with more confidence. Rather than treating every claim or denial the same way, teams can use predictive models to focus on the work that needs the most attention. Potential benefits of AI and automation in the revenue cycle A high-performing revenue cycle depends on timely, accurate and consistent work. AI and automation can help providers modernize that work without losing the expertise of the people who manage complex payer and patient situations every day. When applied to the right workflows, these tools can help organizations: Reduce manual data searches that take staff away from higher-value work Improve front-end data quality before claims are created Identify missing or incorrect coverage information earlier Spot claims that may be at higher risk of denial Prioritize denied claims by potential reimbursement Reduce rework caused by inaccurate or incomplete information Give staff more consistent information for follow-up decisions A focused AI strategy starts with the workflow problem, uses data that is relevant to that problem and keeps staff in control of judgment-based decisions. A more proactive approach to revenue cycle management Revenue cycle teams can move from reactive work toward a more proactive approach: catch errors earlier, validate coverage before claims are created and prioritize the claims and denials that need the most attention. Experian Health offers revenue cycle solutions that use AI and automation in targeted ways to support front-end data quality, reduce rework and manage denials. Patient Access Curator supports registration and coverage validation, while AI Advantage supports denial prediction and triage. Learn more about Experian Health’s Patient Access Curator and AI Advantage.

October 2, 2026 by Andy.Monte@experian.com
Experian Health ranked #1 in Best in KLAS for 2025

Experian Health is very pleased to announce that we've ranked #1 in the 2025 Best in KLAS: Software & Services report, for our Contract Manager and Contract Analysis product, for the third consecutive year. Contract Manager, when paired with Contract Analysis, empowers healthcare providers by ensuring payers comply with contract terms, identifying and recovering underpayments, and arming them with real claims data to negotiate contracts. This enables providers to negotiate more favorable terms and maintain financial stability.  Clarissa Riggins, Chief Product Officer at Experian Health, says, “In the ever-evolving healthcare landscape, our Contract Manager solution has once again been recognized as the #1 Revenue Cycle Management tool by KLAS for the third consecutive year. This prestigious ranking underscores the significant value our solution delivers to our clients by identifying underpayments and facilitating revenue recovery. We are honored to continue supporting our clients with innovative solutions that drive financial success and operational efficiency.”  Learn more about how Contract Manager and Contract Analysis can help your healthcare organization validate reimbursement accuracy, recover underpayments and boost revenue.   Learn more Contact us

February 5, 2025 by kelly.nguyen
How to increase patient engagement

Learn how providers can increase patient engagement, why it matters and key strategies that deliver improved end-to-end patient experiences.

January 30, 2025 by Experian Health

Spotlight test

Spotlight Description

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Sticky Subscribe Title

Sticky Subscribe Description
Sticky Subscribe

Testing Spotlight Paragraph block

Testing the spotlight block header

Archive Testing

Categories