Marianne Kolbasuk McGee

Executive Editor, HealthcareInfoSecurity, ISMG

McGee is executive editor of Information Security Media Group's HealthcareInfoSecurity.com media site. She has about 30 years of IT journalism experience, with a focus on healthcare information technology issues for more than 15 years. Before joining ISMG in 2012, she was a reporter at InformationWeek magazine and news site and played a lead role in the launch of InformationWeek's healthcare IT media site.

Who Will Take the Lead in Setting Healthcare AI Regulations?

Marianne Kolbasuk McGee • September 20, 2024

It's yet to be determined whether a handful of states or the federal government will lead the charge in adopting comprehensive regulations involving the use of artificial intelligence in healthcare, said regulatory attorney Betsy Hodge, a partner in law firm Akerman.

AI in Healthcare: Ensuring Patients' Right to Know

Marianne Kolbasuk McGee • September 2, 2024

AI holds great promise for healthcare but ethical concerns abound. David Hoffman, assistant professor of bioethics at Columbia University, shares insights on balancing AI's benefits and risks, the need for informed consent by patients and ethical considerations in AI implementations.

Getting a Firmer Grip on AI Privacy Concerns in Healthcare

Marianne Kolbasuk McGee • June 17, 2024

Artificial intelligence technologies offer tremendous promise in healthcare, but it's crucial for organizations to carefully assess the complex data privacy concerns involved with different types of AI products and deployments, said Karen Habercoss, chief privacy officer at UChicago Medicine.

Properly Vetting AI Before It's Deployed in Healthcare

Marianne Kolbasuk McGee • March 14, 2024

The U.S. healthcare sector needs to closely watch government regulatory and legislative developments involving artificial intelligence, including the European Union AI Act, said Lee Kim, senior principal of cybersecurity and privacy at the Healthcare Information and Management Systems Society.

Critical Considerations for AI Developments in Healthcare

Marianne Kolbasuk McGee • March 11, 2024

AI has enormous potential for transforming and reimagining all aspects of healthcare but mitigating the risks requires a collaborative, comprehensive approach that prioritizes data security, regulatory compliance and ethical considerations, said Sunil Dadlani, CIO and CISO at Atlantic Health System.

US FTC Proposes Penalties for Deepfake Impersonators

Marianne Kolbasuk McGee , David Perera • February 16, 2024

The U.S. Federal Trade Commission said it's too easy for fraudsters to launch "child in trouble" and romance scams, so it has proposed rule-making that would give the agency new authority to sue in federal court any technology providers that facilitate impersonation fraud.

The Role of AI and ML in Clinical Testing of New Drugs

Marianne Kolbasuk McGee • February 1, 2024

AI tools can help to identify potential issues with drug candidates at an earlier stage, which enables researchers to address problems before starting costly and time-consuming clinical trials and reduces the overall risk of failure, said Jo Varshney, CEO and founder of VeriSIM Life.

Top Considerations for Complying With My Health My Data Act

Marianne Kolbasuk McGee • January 1, 2024

It's time for companies dealing with non-HIPAA-regulated health information to plan their compliance with Washington state's My Health My Data Act, which goes into effect in the new year and affects organizations that are based in other states, said attorney James Hennessy of law firm Reed Smith.

How Clinicians Are Using AI to Communicate With Patients

Marianne Kolbasuk McGee • December 28, 2023

The University of Texas Medical Branch just began piloting an AI assistant integrated into the organization's Epic MyChart patient portal platform, and already clinicians are seeing efficiencies in responding to patient messages, said UTMB's CIO George Gaddie and CMIO Carlos Clark.

The Critical Need for Human Oversight in Healthcare AI

Marianne Kolbasuk McGee • December 26, 2023

AI holds great promise for automating and improving many healthcare processes and tasks - including clinical decision support - but if some users become overly dependent on these systems, that could be potentially detrimental to patients, says attorney Lee Kim of HIMSS.

Fighting AI-Fueled Attacks With AI-Based Cyber Tools

Marianne Kolbasuk McGee • December 26, 2023

Healthcare CISOs must recognize the real and imminent threat of AI-fueled cyberattacks and take proactive steps, including the deployment of AI-based security tools, to protect patient data and critical healthcare services, said Troy Hawes, managing director at consulting firm Moss Adams.

Innovating Patient Care by Applying AI to EHR Data

Marianne Kolbasuk McGee • December 25, 2023

Truveta is a collaborative effort whose members include dozens of the largest healthcare systems in the U.S. It helps life sciences companies apply AI to a trove of electronic health records data to develop new treatments and study their effectiveness, said the organization's CEO, Terry Myerson.

FTC Bans Rite Aid From Using Facial Recognition Tech

Marianne Kolbasuk McGee • December 20, 2023

The Federal Trade Commission has banned Rite Aid from using AI-based facial recognition technology for security surveillance for five years after the retail drug store chain failed to implement safeguards such as mitigating risks for inaccurate outputs based on race and gender.

HHS 5-Year Health Data Strategy Prioritizes 'Responsible' AI

Marianne Kolbasuk McGee • December 15, 2023

The Biden administration is heavily counting on "responsibly" leveraging AI as part of a five-year strategy that aims to harness data to enhance the health and wellness of Americans. That includes ambitions to drastically improve cancer care and reduce cancer deaths, among other top goals.

Addressing Privacy and Data-Sharing Hurdles in Healthcare AI

Marianne Kolbasuk McGee • December 12, 2023

AI holds tremendous promise for both the administrative and clinical sides of healthcare, but obstacles still remain. One of the major hurdles is tied to patient privacy and the sharing of vast amounts of data needed to effectively tune AI models. What are some workarounds?