AI’s Watchful Eye on Compliance Can Revolutionize The Healthcare Industry

In October 2023, the World Health Organization (WHO) unveiled new AI regulations in healthcare. Their goal is to elevate AI safety, effectiveness, and patient accessibility.

AI systems using health data carry the weight of safeguarding sensitive personal information. This impels organizations like the WHO to establish rigorous protocols, fortifying privacy and security measures. Contrary to misconceptions, these regulations do not signify a step backward. Instead, they catapult us into a new era. 

An even more tech-savvy approach to regulatory compliance is among us, redefining how we navigate protected health information. The question then arises: How precisely does AI drive regulatory compliance and ultimately advance patient care? Let’s explore the uses of AI in healthcare and how real-time monitoring and auditing tools are helping healthcare institutions stay compliant.

What is AI in Healthcare?

AI is a technique used to design and train software algorithms to learn from and act on data. Developers model AI-powered software — Software as a Medical Device (SaMD) — to diagnose, treat, or prevent illnesses.

Forbes lists the ten biggest AI trends in healthcare, some of which include:

1. Virtual assistants – Generative AI has the power to communicate with computers using human language. Look at Massive Bio’s AskFiona AI and DrArturo. These innovative, AI-driven solutions will redefine cancer care, patient and provider engagement, and global oncological research. Unlike traditional chatbots, GPT4’s deep-learning models can bring forth multitudes of data based on a simple prompt and reproduce it conversationally. This breaks down coding barriers and offers immense opportunities for 24/7 virtual patient assistants.

2. Personalized treatment plans – AI is being used to analyze patients’ DNA, help doctors diagnose and treat diseases, and create medicines that are personalized to specific people down to the molecular level. Ginkgo Biworks is one example. Its proprietary software platform, Owl, allows for AI-guided protein engineering.

3. Simulating critical health scenarios – AI in digital twins simulates virtual processes, systems, and scenarios. This will help hospitals understand how different conditions can impact their decisions, whether it’s the choice of scalpel for the surgery or identifying how patients’ neighborhoods could influence their health outcomes.

4. Preventative care – Wearable AI and predictive analytics will increasingly help monitor a patient’s symptoms — pinpointing anomalies in heart rates and blood pressure to predict and prevent illnesses from progressing. Huma’s SaMD uses data from the UK’s Biobank to predict long-term risk of cardiovascular disease, enable early identification of patient condition changes, and allow for more timely and appropriate interventions.

Fears For Healthcare Regulators

The biggest concern for using modern AI, such as generative AI, in healthcare is its ability to consume vast amounts of data and reproduce it on a simple command using human language. That means sensitive information could leak to malicious actors if the data isn’t properly anonymized or correctly documented. Put simply, complex algorithms and integrations with third-party access send data security and privacy issues through the roof. 

In addition, AI systems rely on interoperability. There must be a solution if access to the necessary data or server is unavailable. For this reason, it’s critical to manage technology integrations with scrutiny for both data privacy and system functionality. 

Ultimately, healthcare professionals must address the quality and safety of care, ensuring patient privacy is always protected, and all systems comply with regulatory requirements, such as the WHO’s latest considerations, the Health Insurance Portability and Accountability Act (HIPPA) in the US, and the General Data Protection Regulation (GDPR) in Europe.

How AI Can Help Hospitals Stay Compliant

AI data protection is two-fold: developers must build secure code, and users must protect the data they train the systems on. The WHO outlines a number of regulation areas for healthcare AI. Let’s take a look at each one and how AI can help the healthcare industry stay compliant:

Increased Data Transparency

Since AI-powered tools can continuously audit data sources, they ensure transparency in collecting, storing, and sharing healthcare data. 

Take Recovery Audit Contractors (RAC) audits, for example — an examination of healthcare claims. RACs can use AI to automatically identify errors in billing data, such as if the provider, service, and price align on the medical bill. The AI will track every account and provide a comprehensive audit trail, allowing healthcare professionals to trace the origins and transformations of data, increasing data transparency.

Alongside boosting transparency, this gives back time to RACs to focus on more sensitive scenarios where additional medical documentation is required to complete the audit.

Risk Management

CharmHealth is recognized for its advanced and user-friendly electronic health record (EHR) system, practice management, revenue cycle management, and telehealth. The leading provider in healthcare technology works with digital consulting experts such as Nisum to streamline their operations, improve patient outcomes, and enhance overall efficiency. AI algorithms can anonymize healthcare data while identifying unusual patterns or outliers, signaling potential risks or irregularities in data sharing. 

AI safeguards against third-party data leaks by employing advanced security measures such as dynamic encryption and contextual access controls. Since it encrypts sensitive data based on context and user roles, the intercepted data remains indecipherable even if unauthorized access occurs.

In addition, AI’s ability to continuously monitor behavioral analysis helps identify abnormal access patterns, triggering timely alerts. This proactive approach enables healthcare providers to address issues before they escalate, reducing the risk of non-compliance or adverse events.

Increasing Collaboration with Regulatory Bodies

With AI, healthcare professionals can implement real-time reports on compliance metrics, collaborate with regulatory bodies transparently, and provide them with the necessary information to assess and validate compliance efforts.

These automated healthcare compliance checks might include continuously monitoring critical areas such as EHR integrity — verifying data entry for errors and inconsistencies aligned with standards like HL7 and SNOMED CT.

This automation streamlines the compliance process and facilitates a collaborative approach with regulatory bodies.

AI is increasingly being applied to healthcare, helping out with AI-augmented clinical research, assistive AI for cancer screening, and autonomous AI for diabetic eye exams. And regulators are intensifying scrutiny on compliance to make sure everything’s done right.

When implemented with suitable controls and human oversight, technology can help regulators and healthcare professionals keep a watchful eye on data transactions and more to ensure patient safety and quality of care.