Overcoming Challenges in Healthcare Identity Verification: A Developer's Toolkit

Modern healthcare infrastructure depends on patient identity and the data associated with it. To maintain continuity of care, information is recorded across institutions and linked to a patient’s identity. This identity serves as the foundation for healthcare services and contains sensitive personal data that must be protected.

Regulations like the Health Insurance Portability and Accountability Act (HIPAA) promote health data safety, prevent unauthorized access, and reduce identity fraud. However, because these regulations are constantly updated, developers must continuously implement up-to-date industry verification and security measures while maintaining a seamless user experience. This requires a flexible, adaptable toolkit that integrates with your existing infrastructure.

This article will teach you how to navigate healthcare identity verification challenges. You’ll learn about integrating advanced biometric authentication, using blockchain technology, and more.

Understanding Healthcare Identity Verification

Patients’ identities are used for various administrative and clinical tasks and need to be verified on demand. This ensures they’re matched to the correct medical records and granted access to healthcare services like controlled prescription medications.

Encasing healthcare services under patient identity ensures better privacy and security for patients and healthcare providers. Healthcare organizations can restrict access to medical records and keep audit trails of record access. These trails help detect and trace fraudulent attempts and assist in compliance with regulations and industry laws.

Within the healthcare sector, you would commonly see several identity verification methods used, such as document-based verification, provider credentials, and issued tokens. In an ideal situation, using these methods would provide enough security. However, when subject to a large user base, malicious actors, and regulatory bodies, they are not enough.

Healthcare Identity Verification Challenges

While healthcare identity verification is beneficial, there are a number of concerns and challenges you’ll face when implementing it. Let’s talk about a few of them.

Data Privacy and Security Concerns

Protecting patients’ data should be a primary concern as it has financial and reputational consequences. The healthcare sector is one of the most popular targets for cyberattacks.

Businesses and individuals using your products or processes need to be confident that your data is secure. This requires strict authentication and encryption protocols to defend against unauthorized access and leaks.

Regulatory Compliance

You must comply with both healthcare-specific and general data regulations, like HIPAA, the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Information Blocking Rule. These regulations differ based on your operating regions and data storage localities.

You need to ensure your verification processes align with requirements for data handling, storage, and sharing.

Integration with Existing Systems

Interoperability is key for healthcare infrastructure. To achieve this, you need to work with various healthcare providers, many of which still rely on monolithic legacy systems with limited integration capabilities. Incorporating your identity verification requires you to accommodate varied system requirements while still maintaining stable operations across the infrastructure. This often results in the need for complex, customized solutions.

User Experience

Your systems and processes must meet increasingly demanding user needs. Prioritizing user experience requires a delicate balance between robust security and privacy and product usability. Unnecessarily complex verification procedures can frustrate users and drive churn, while insufficient security measures expose your infrastructure to unacceptable risk.

Scalability

The volume and variety of your user base are rarely set in stone. Your products and processes need to serve a large and fluctuating number of people and medical records. Ensuring your verification solution can scale efficiently is important because it helps reduce service disruptions.

Developer’s Toolkit: Solutions to Overcome Identity Verification Challenges

Creating secure, compliant, and user-friendly identity verification solutions requires tools and strategies that address compliance, integration, user experience, and scalability. The following are a few approaches and tools to help you achieve these goals effectively.

Multifactor Authentication (MFA)

There are three common factors of authentication: something you know (passwords and security questions), something you have (smart cards and tokens), and something you are (fingerprints and facial scans). MFA is a popular security method that utilizes two or more factors of authentication, adding extra layers to your access process to prevent malicious entries. Having two or more layers of verification and authentication ensures that a malicious actor cannot rely on one identity element to infiltrate your systems.

An example of MFA is logging into an account where, after entering your password, a one-time password (OTP) is sent to the account’s registered device for verification before granting access. Within your healthcare infrastructure, you can combine several forms of authentication—such as push notifications, one-time codes, hardware tokens, and biometric authentication—to enhance your identity verification process.

Consider using existing authentication systems within your infrastructure to reduce development overhead and improve compatibility. The experience of your users is also important. In addition, the healthcare environment can be time-sensitive, requiring hardware or biometric verification methods with reduced user friction and interruptions during patient care.

MFA is successful because it reduces reliance on a single point of failure and demands multiple forms of authentication. However, its success is dependent on your implementation. Overprioritizing your user experience can lead to MFA implementations that are easily bypassed with compromised devices.

Biometric Verification

Biometric verification can be a powerful tool to identify individuals and tighten security. It utilizes physical (fingerprint, facial, or iris scans) and behavioral (voice prints) characteristics of users to allow access to systems. Because these characteristics are difficult to replicate, when you implement them, there’s a higher degree of security. Facial and voice scans are contactless options, but they are susceptible to inaccuracy (especially with masks and other personal protective equipment) and background noise.

Within a healthcare environment, you should also consider the usability within the user workflows, their speed, effectiveness, and reliability. Conduct real-world testing with diverse data to optimize performance.

Fingerprint verification is a popular and cost-effective method, but it requires physical contact with hygiene concerns. Additionally, most biometric verification requires specialized scanners and storage for scanned data. You must keep this scanned data secure and integrated with your systems to ensure accessibility.

There are a number of biometric solutions that can be integrated into mobile and edge devices. It’s also convenient because it eliminates the need to remember complex passwords.

Biometric verification can be quick and user-friendly. However, if it’s the sole verification method, it can be bypassed. Passwords can be site-specific and can be reset, but biometrics cannot. Deepfakes or stolen biometric data can be used to authenticate all available systems if only biometric verification is used.

Additionally, environmental factors, such as changes in lighting, eyelashes, and humidity, can affect biometric data recognition.

Blockchain Technology

Blockchain technology essentially builds a digital ledger that is distributed and collectively maintained, making it difficult to hack or alter. All interactions with the ledger are logged, making it auditable and easily traced. This is particularly useful in the healthcare context.

Storing identity on the blockchain allows users to quickly create decentralized identifiers (DIDs), and it enables near-instant verification of credentials. This can be used for patient identity (insurance and vaccine records) and provider credentials (professional certifications and permissioned access). For example, FarmaTrust uses blockchain to create audit trails for pharmaceutical products and medical devices, and Avaneer Health focuses on improving healthcare administration through a decentralized network.

When you use the decentralized networks of blockchain technology, you can set up multi-signature authentication, ensuring more than one party is needed for sensitive actions. This reduces the risk of single points of failure and makes it harder for malicious actors to compromise the system.

Blockchain enables efficient security and tamper-proof identity management. It can be integrated as physical cards and QR codes into legacy systems to improve interoperability. However, regulation is stabilizing, and the permanence of data on the blockchain raises privacy concerns. Scalability is another factor as a large number of concurrent transactions can slow down the authentication process and increase costs.

Artificial Intelligence (AI) and Machine Learning (ML)

AI and ML are popular—they allow you to learn from a lot of data, automate repetitive tasks, and help make informed decisions based on data patterns. In a healthcare and identity verification context, you can use AI and ML to detect unusual login patterns or inconsistencies in your client data. You can automate verification processes and use AI agents to reduce your administrative burdens.

Popular AI and ML frameworks like TensorFlow already have healthcare use cases and offer compatible autoencoder technology that can be easily extended to anomaly detection within your identity infrastructure. With data privacy concerns in the healthcare environment, you can utilize data masking algorithms and anonymizing techniques for personally identifiable information (PII). Differential privacy in TensorFlow is an example of this, aimed at ensuring your models and AI agents can be made and used without exposing private and sensitive data.

The success of AI and ML is heavily dependent on the quality of your data and your AI and ML implementation. Data fragmented across different systems and formats has to be standardized and integrated into your AI solution. Missing or inconsistent data can reduce the accuracy of your predictive models. Extra care is needed to ensure anonymity and security when dealing with sensitive health data.

Depending on your industry regulations, your users need to consent to their data being processed by AI. The explainability of your models is also important as you need to ensure decisions are made ethically without inherent bias.

Interoperability

Interoperability is an important consideration when choosing and building tools within the healthcare space. You want to avoid siloed information and prevent bottlenecks when connecting your solution to the wider healthcare infrastructure.

You need your solution to be able to securely extend patient identities and information. This serves as the foundation for accurate patient matching across systems and locations, ensuring verified clients have access to the right services when needed. Tools such as a master patient index (MPI) can be used to pair patient identity to a single unique identifier that can be shared across systems, departments, and organizations.

There are standards like the Fast Healthcare Interoperability Resources (FHIR) aimed at easing the electronic exchange of healthcare information. FHIR specifies different ways electronic health records (EHR) can be presented, prioritizing flexibility for the wide range of use cases within the healthcare ecosystem. This standard comes with its own API guide that can ease integration into your infrastructure, with several popular cloud providers also having managed solutions integrating these APIs. Utilizing these FHIR-ready frameworks allows you to connect to supportive data schemas, security features, and tools, such as the MPI, without having to build anything from scratch.

User-Centric Design

User-centric design is an iterative process of evaluating and optimizing your solution with your users’ experiences, needs, and pain points in mind. This helps minimize user effort and ensures intuitive processes and accessibility for your diverse users, including those with disabilities.

From a healthcare identity verification standpoint, a user-centric design would explore your entire verification procedure and test it for obstacles in user flow, disruptive elements, and requirements that discriminate against users. For example, your identity sign-up and login processes might have to be accessed through digital assistants or voice-activated agents by your visually impaired users. What would that process look like? What options are available to minimize friction and ensure those users are satisfied?

These design considerations must be balanced against the requirements of your industry and compliance regulations. Make sure security measures are not bypassed in favor of user convenience.

Healthcare Identity Verification Best Practices

Creating modern healthcare infrastructure that is secure and user-friendly is a balancing act. The following are some best practices that can help.

Stay Informed of Regulatory Changes

The compliance and regulatory landscape is always changing, especially with technological advancements. Actively take note of the relevant healthcare regulations and other regional laws that can apply to your business. You can do this by subscribing to regulatory bodies and industry groups, utilizing regulation tracking tools, and employing or partnering with legal and compliance experts. Ignorance is not an excuse.

Continuously Test and Evaluate

Regularly test your solutions to identify new gaps and vulnerabilities, ensuring high security standards. Setup automated systems for continuous monitoring and set organizational appointments for quarterly penetration tests and annual comprehensive audits. Frequent evaluations can help you optimize your solution for business needs and user experience.

Collaborate with Healthcare Professionals

Healthcare professionals are subject matter experts with hands-on experience. They can offer insights into the workflow, challenges, and needs of both the users and healthcare service providers. Collaborating with the professionals who are working with your infrastructure can help ensure your solutions are both practical and user-friendly.

Invest in Training and Development

Your development teams need to be trained with your toolkit, understanding the security protocols and software deployment procedures. Make sure you implement ongoing education on emerging security and industry trends. This can help you stay ahead of threats and provide the best services for your users.

Conclusion

Patient identity is a central feature in modern-day healthcare. Your identity solution serves as the foundation for care continuity and management.

In this article, you explored some of the challenges you’ll face when ensuring seamless identity verification, including regulatory issues, scalability, and user experience. You also looked at a few strategies that can help you streamline identity verification and overcome the common challenges associated with it.

Prove is a leading provider of identity verification solutions and is known for its ability to provide an integrated infrastructure of secure, scalable, and user-friendly tools for your identity verification needs. They are specifically tailored to the healthcare sector and its regulatory landscape, with solutions such as Prove Pre-Fill® and Prove Identity Manager® that help optimize user experience and ensure data security and compliance.

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