In healthcare, third-party vendors often provide AI tools that automate tasks like appointment scheduling, claims processing, or answering front office calls. This lets medical offices focus more on patient care. Vendors supply special technologies and know-how that many practices don’t have inside their own teams. For example, companies like Simbo AI offer AI phone systems that answer patient calls, set up appointments, and give basic information all day and night. This helps office staff and makes it easier for patients to get services.
These AI tools also study large amounts of clinical data to help with diagnosis and treatment choices. Third-party vendors build systems that manage data analysis, language processing, and automated workflows. Working together with healthcare providers, these vendors speed up the use of AI in medicine. The AI healthcare market is expected to grow from $11 billion in 2021 to $187 billion by 2030.
Third-party vendors are important for healthcare AI, but they also make data privacy and security harder to manage. Healthcare organizations must share sensitive patient information with outside companies. This sharing can lead to risks like unauthorized access, data breaches, or misuse of information.
A big worry is that cyberattacks on third-party vendors can disrupt healthcare services and harm patient care. In 2024, a ransomware attack on Change Healthcare, a third-party provider for UnitedHealth Group, affected almost every hospital in the U.S. It caused delays in medical care and showed how closely vendors are tied to healthcare systems and how they can be weak points. John Riggi from the American Hospital Association said cyber risk is an issue that affects all parts of healthcare, not just IT departments.
Data shows a big rise in healthcare data breaches linked to third-party vendors. In 2023, about 58% of 77.3 million people affected by data breaches lost data because of breaches involving third parties. This was a 287% increase from 2022. The healthcare sector faced more breaches than any other. Cybercriminals often use a “hub and spoke” tactic, where breaking into one vendor (the hub) lets them access many healthcare organizations (the spokes). This spreads the damage widely.
For healthcare administrators and IT managers, managing risks from third-party vendors is very important. They must make sure vendors follow strict security rules and legal requirements like HIPAA to protect patient data and keep healthcare running smoothly.
In the U.S., HIPAA sets the minimum standards for protecting patient health information. It requires all groups handling patient data to follow privacy and security rules. When a medical practice uses third-party AI vendors, these vendors are usually considered business associates under HIPAA. That means they must keep patient data just as safe as the healthcare provider does.
Besides HIPAA, new rules have been made to handle risks from AI technologies. In October 2022, the White House released the Blueprint for an AI Bill of Rights. This document aims to protect people from AI risks like privacy invasion and unfair treatment. The National Institute of Standards and Technology (NIST) created the AI Risk Management Framework (AI RMF 1.0) with guidelines to help build and use AI safely and fairly.
The HITRUST AI Assurance Program adds AI risk management into healthcare’s common security rules. It promotes openness, responsibility, and ethical AI use. This helps healthcare groups and their vendors manage AI risks carefully.
Healthcare providers must make sure their vendors follow these rules about patient privacy, data security, clear AI decisions, and risk control.
AI depends on large sets of patient data to work well. This raises privacy concerns. AI systems often need access to many patient records, including Electronic Health Records (EHRs) and other clinical data. This creates risks in how data is collected, stored, used, and sometimes shared with outside groups.
One hard problem is called the “black box.” This means AI decision-making can be unclear, even to the people who built it. This lack of transparency makes it hard to trust AI results or be sure patients gave informed consent.
Another big worry is reidentification. Even if data is anonymized, AI algorithms can sometimes figure out who individuals are. Some studies show this can happen up to 85.6% of the time. This breaks usual privacy protections.
Private companies often control patient data through commercial AI solutions. For example, the UK’s National Health Service (NHS) worked with DeepMind (owned by Alphabet/Google) and faced criticism. Patient consent was not always clear, and data moved across countries, making it harder to follow local privacy laws.
These issues show the need for ongoing informed consent, clear rules on data ownership, strong anonymization, and allowing patients to withdraw their data and know how it’s used. U.S. healthcare groups must follow these rules to keep trust and stay legal.
Cybersecurity is a major concern when using third-party vendors for AI healthcare tools. Threats like ransomware, data poisoning, and attacks that trick AI systems are serious. Vendors without strong cybersecurity can let attackers in, risking sensitive data and disrupting care.
The American Hospital Association recommends healthcare groups create third-party risk management programs that include:
The Cybersecurity and Infrastructure Security Agency (CISA) promotes “Secure by Design,” which means AI vendors should build security into their products from the start. This helps reduce risk for healthcare providers who use these services.
Healthcare leaders and IT managers should stay alert by enforcing solid contracts, sharing minimal data with vendors, limiting access rights, and using encryption and anonymization whenever possible.
One useful way AI helps healthcare is by automating workflows and office tasks. AI automation can cut manual work, lower costs, and let clinical staff spend more time with patients.
For example, AI phone systems like Simbo AI’s can answer calls 24/7. They handle routine questions, schedule appointments, send reminders, and check insurance automatically. This reduces patient wait times, lowers missed calls, and improves how patients experience the office.
AI also helps with claims processing, patient registration, and data entry by pulling information from forms and documents. This speeds work and reduces errors.
But adding AI tools means paying close attention to data security. Automated systems move and store sensitive patient data. Following HIPAA and security best practices is important to avoid breaches.
Healthcare groups should work with vendors to make sure AI systems have:
By matching AI automation with strong security, practices can run more smoothly while keeping patient privacy and following the law.
Medical practice leaders and IT managers in the U.S. face the challenge of using AI while managing risks from third-party vendors.
They should use governance plans that include:
New privacy laws in states like California, Colorado, and Virginia require transparency, consent, and checks for AI bias. For example, the Colorado AI Act demands impact assessments for high-risk AI tools, which covers many healthcare AI uses.
Third-party vendors are key to offering AI healthcare tools that change how clinical and administrative tasks work. But their role creates tough data privacy and security challenges. Healthcare organizations must use strong risk management and follow compliance rules.
U.S. healthcare providers should build solid third-party risk programs, use AI to improve workflows safely, and follow rules like HIPAA, the AI Bill of Rights, and NIST’s AI Risk Management Framework.
By balancing new AI technology with careful data protection and security, medical practices can use AI well while keeping patient information safe and maintaining trust.
HIPAA, or the Health Insurance Portability and Accountability Act, is a U.S. law that mandates the protection of patient health information. It establishes privacy and security standards for healthcare data, ensuring that patient information is handled appropriately to prevent breaches and unauthorized access.
AI systems require large datasets, which raises concerns about how patient information is collected, stored, and used. Safeguarding this information is crucial, as unauthorized access can lead to privacy violations and substantial legal consequences.
Key ethical challenges include patient privacy, liability for AI errors, informed consent, data ownership, bias in AI algorithms, and the need for transparency and accountability in AI decision-making processes.
Third-party vendors offer specialized technologies and services to enhance healthcare delivery through AI. They support AI development, data collection, and ensure compliance with security regulations like HIPAA.
Risks include unauthorized access to sensitive data, possible negligence leading to data breaches, and complexities regarding data ownership and privacy when third parties handle patient information.
Organizations can enhance privacy through rigorous vendor due diligence, strong security contracts, data minimization, encryption protocols, restricted access controls, and regular auditing of data access.
The White House introduced the Blueprint for an AI Bill of Rights and NIST released the AI Risk Management Framework. These aim to establish guidelines to address AI-related risks and enhance security.
The HITRUST AI Assurance Program is designed to manage AI-related risks in healthcare. It promotes secure and ethical AI use by integrating AI risk management into their Common Security Framework.
AI technologies analyze patient datasets for medical research, enabling advancements in treatments and healthcare practices. This data is crucial for conducting clinical studies to improve patient outcomes.
Organizations should develop an incident response plan outlining procedures to address data breaches swiftly. This includes defining roles, establishing communication strategies, and regular training for staff on data security.
Simbo is using AI agents to automate all phone related workflows. Connect now to know more.
Schedule AI Agents Demo Now© Since 2019, Simbo AI.
