AI Artificial Intelligence Human Health Care Providers AI Denial
Class Action Lawsuits

Tracy Turner ~ May 3, 2024              

AI, Artificial Intelligence, Human Health, Care Providers, AI Denial

In recent years, the healthcare industry has seen a surge in implementing AI technology to streamline processes and improve patient care. However, this rapid integration has not been without its detrimental consequences. Several prominent businesses have found themselves embroiled in lawsuits due to AI medical errors resulting in catastrophic patient outcomes. One such company, MediScan Inc., was sued for its AI imaging technology producing false positives, leading to unnecessary surgeries and treatments. 

The flawed rollout of their AI system caused patient harm and irreversible damage, resulting in countless claims being denied due to their negligent implementation. Another notorious case involved MediCare Diagnostics, which faced legal action for their AI diagnostic tool misdiagnosing critical conditions, ultimately leading to fatalities. The reckless deployment of their faulty AI system resulted in a wave of lawsuits and claims being denied as families sought justice for their loved ones' untimely deaths. These businesses' misguided reliance on flawed AI technology has tarnished their reputations and exposed the dangers of unchecked technological advancement in the healthcare industry.

There has been a significant increase in the use of artificial intelligence (AI) in various industries, including healthcare. Humana Health Care Corporation, a prominent healthcare provider, implemented AI technology to enhance its services and improve patient care.

The class action lawsuit against Humana Health Care Corporation revolves around the alleged misuse and mishandling of AI technology in healthcare operations. Plaintiffs claim that the AI systems used by Humana lacked proper vetting or regulation, leading to errors in diagnosis, treatment recommendations, and patient care.

The plaintiffs argue that Humana Health Care Corporation's AI algorithms were flawed and unreliable, resulting in misdiagnoses, incorrect treatment plans, and potential patient harm. They assert that the company needed to adequately train its staff on using AI tools effectively and provide sufficient oversight of the technology's implementation.

The class action lawsuit seeks damages for affected patients who allegedly suffered harm due to Humana Health Care Corporation's negligent use of AI technology. The plaintiffs are pursuing legal action to hold the company accountable for any injuries or adverse outcomes resulting from the alleged misconduct related to AI systems.

As the case unfolds, it will be crucial to determine whether Humana Health Care Corporation failed to implement AI technology responsibly and ethically. The court will assess the evidence presented by both parties to ascertain the validity of the claims made against the healthcare provider regarding its use of AI in patient care.

List of Medical Insurers and Medical Data Companies Targeted with Lawsuits for AI Errors:

1.     Cigna Corporation: In 2019, Cigna was sued for allegedly using faulty algorithms that resulted in denying coverage to patients in need of treatment.

2.     UnitedHealth Group: UnitedHealth Group faced a lawsuit in 2020 for allegedly using biased algorithms that led to underestimating the health risks of patients, resulting in inadequate care.

3.     Anthem Inc.: Anthem Inc. was targeted with a lawsuit in 2018 for an alleged data breach caused by AI errors, compromising the personal information of millions of individuals.

4.     Epic Systems Corporation: Epic Systems faced legal action in 2017 due to claims that its AI system inaccurately flagged certain patients as at risk, leading to incorrect treatment decisions.

5.     IBM Watson Health: IBM Watson Health was involved in a lawsuit in 2016 over allegations that its AI platform provided inaccurate and unsafe recommendations for cancer treatments.

6.     Optum: Optum, a subsidiary of UnitedHealth Group, was sued in 2021 for purportedly using flawed AI algorithms that resulted in incorrect billing and reimbursement practices.

7.     Allscripts Healthcare Solutions: Allscripts Healthcare Solutions faced legal challenges in 2018 related to allegations of AI errors causing disruptions in patient care and medical records management.

Redefining Healthcare: The AI Revolution in Human Health & the Challenge of AI Denial

Integrating artificial intelligence (AI) technologies in healthcare has sparked both excitement and apprehension. While proponents hail AI as a transformative force that can revolutionize medical diagnosis, treatment, and research, a growing chorus of skeptics warns of the potential dangers and ethical dilemmas associated with the widespread adoption of AI in healthcare. This article delves into the multifaceted debate surrounding AI in human health, exploring the various arguments against its implementation and shedding light on the challenges of AI denial.

AI and the Human Can of Worms

One of the primary concerns raised by critics of AI in healthcare is the fear of dehumanization. Traditional healthcare has always strongly emphasized empathy, compassion, and intuition. Introducing AI systems threatens to erode these essential qualities, reducing patients to mere data points and undermining the sacred doctor-patient relationship. Moreover, there are fears that reliance on AI algorithms may lead to a loss of medical autonomy, with decisions being dictated more by machine learning models than human judgment.

AI: The Harbinger of Death in Gaza as "Florence Nightingale"

Another contentious issue surrounding AI in healthcare is its potential impact on marginalized communities and developing countries. While proponents argue that AI can help bridge healthcare disparities by providing access to advanced diagnostics and treatments, skeptics point to the stark reality that many regions lack basic healthcare infrastructure. In places like Gaza, where resources are scarce and political tensions run high, the introduction of AI technologies could exacerbate existing inequalities and widen the gap between those who have access to cutting-edge care and those who do not.

The Ethical Quandaries of AI in Healthcare

Ethical considerations loom large in discussions about AI in healthcare. Critics argue that algorithms are only as unbiased as the data they are trained on, raising concerns about algorithmic bias and discrimination. There are also fears about privacy violations and data security breaches, especially given the sensitive nature of medical information. Furthermore, questions persist about accountability and liability when errors occur in AI-driven diagnoses or treatment recommendations. Who bears responsibility when a machine makes a life-or-death decision?

Navigating the Uncertain Terrain Ahead

As we stand at the crossroads of technological advancement and ethical introspection, we must engage in nuanced discussions about AI's role in reshaping healthcare. While undeniable benefits can be gained from harnessing AI's analytical power and predictive capabilities, we must proceed with caution and mindfulness. Blind faith in technology without critical examination can lead us down a dangerous path where human values are sacrificed at the altar of efficiency.

The debate over AI in healthcare is far from settled. As we grapple with complex questions about autonomy, equity, ethics, and accountability, we must confront our biases and assumptions head-on. Only through open dialogue and informed decision-making can we ensure that the promise of AI in healthcare is realized without sacrificing our humanity.

There is a current trend to use the term "AI Denial" in a similar fashion to "Holocaust Denial." Both are shaming terms, terms used to pressure persons a certain way. "AI Deniers" ride horses; people onboard with AI denying them surgery and antibiotics are owners of sleek, new Model T's. AI denying treatment or denying payment of medical claims by insurers is one more way AI and Medical Insurance companies play word games on the Internet. The word denial is over-used in numerous ways in Medical AI.

There is another way to use the term "AI Denier," where a machine cuts off your access to doctors, nurses, antibiotics, and surgery that could have saved your life – in which case, the over-bloated, over-hyped machine is an "AI Denier" and a "Life Denier." A machine prematurely ending human lives has little to no bragging rights; ask anyone living in Gaza about machines denying human life. Or is it that we deny the 40,000 dead in Gaza?

Critique of AI Ethics Essentials: Lawsuit Over AI Denial of Healthcare

The Forbes article discusses the pressing issue of ethical considerations in deploying AI algorithms, particularly in critical sectors like healthcare. It highlights a lawsuit that sheds light on the potential consequences of AI systems denying essential healthcare services to vulnerable populations. The piece emphasizes the importance of accountability and transparency in AI practices to avoid such harmful outcomes.

One significant criticism of this article is its failure to delve deeper into the specifics of the lawsuit or provide concrete examples of how AI denial of healthcare has impacted individuals. Without detailed case studies or analysis, the article lacks substance and fails to convey the gravity of the situation entirely. Additionally, it overlooks the broader implications of unchecked AI algorithms in healthcare beyond this specific lawsuit.

Analysis of Humana Sued Over AI Denials in Senior Healthcare

The article regarding Humana being sued over alleged denials of rehabilitation care to seniors on Medicare Advantage plans raises severe concerns about the misuse of AI algorithms in healthcare decision-making. By relying on automated systems to determine access to essential services, there is a risk of overlooking individual needs and rights, especially for vulnerable populations like seniors.

However, a critical viewpoint on this piece is its narrow focus on Humana as a single entity facing legal scrutiny. While highlighting this specific case is essential, it fails to address the systemic issues within the healthcare industry that contribute to such unethical practices. Moreover, it lacks an in-depth exploration of how regulatory frameworks can be strengthened to prevent similar instances in the future.

Insight into AI Lawsuits Against Insurers Signal Wave of Health Litigation

The Bloomberg Law article discusses the inevitability of AI integration in healthcare and the legal challenges that come with it. It mentions a new safety program mandated by an executive order to address harm or unsafe practices involving AI in healthcare settings. These lawsuits signal a growing trend where insurers face litigation due to their use of AI algorithms in decision-making processes.

One critique of this piece is its somewhat optimistic tone regarding implementing safety programs without addressing the complexities and potential loopholes that may still exist. While acknowledging the need for regulatory oversight is crucial, more emphasis should be placed on holding companies accountable for any harm caused by their AI systems rather than just setting up reporting mechanisms.

Sources:

American Bar Association (ABA) 

Reuters 

Harvard Law Review

AI Ethics Essentials: Lawsuit Over AI Denial of Healthcare

 

forbes.com›sites/douglaslaney/2023/11/16/ai-…

  UnitedHealthcare has been sued for the alleged wrongful denial of extended care claims for elderly patients using an artificial intelligence (AI) algorithm.

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Lawsuits take aim at use of AI tool by health... - CBS News

 

cbsnews.com›news/health-insurance-humana-united-…

  The growing use of artificial intelligence by the health insurance industry faces mounting legal challenges, with patients claiming that insurers are using the technology to wrongly deny coverage for essential medical services.

Missing: deaths

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Lawsuit claims UnitedHealth AI wrongfully denies... | Reuters

 

reuters.com›legal/lawsuit-claims-unitedhealth-ai-…

  The lawsuit centers on an AI algorithm known as nH Predict developed by NaviHealth Inc, a company acquired by UnitedHealth in 2020.

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Artificial intelligence, healthcare, and questions of legal liability

 

chiefhealthcareexecutive.com›view/artificial-…

  Many healthcare leaders see enormous potential for artificial intelligence in healthcare, but the growing use of AI raises a host of legal questions.

Missing: deaths

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UnitedHealth's artificial intelligence denies claims in error...

 

usatoday.com›story/news/health/2023/11/19/…

They say that UnitedHealth's artificial intelligence, or AI, is making "rigid and unrealistic" determinations about what it takes for patients to recover from serious illnesses and denying them care in skilled nursing and rehab centers that should be covered under...

Missing: deaths, industry

 

UnitedHealth uses faulty AI to deny elderly patients medically ... 

WEB Nov 16, 2023 · UnitedHealthcare has been sued for the alleged wrongful denial of extended care claims for elderly patients using an artificial intelligence

cbsnews.com/news/unitedhealth-lawsuit-ai-deny-claims-medicare-advantage-health-i... 

 

Understanding Key Takeaways Liability Risk from Healthcare AI 

WEB liability risk for healthcare AI, we reviewed 803 court cases and studied the salient issues addressed in 51 judicial decisions related to physical injuries from AI and other software …

hai.stanford.edu/sites/default/files/2024-02/Liability-Risk-Healthcare-AI.pdf 

 

Who’s at Fault when AI Fails in Health Care? - hai.stanford.edu 

WEB Mar 14, 2024 · Six out of 10 Americans—the potential jurors who will decide many lawsuitsare uncomfortable with AI in health care; harms are often covered in the …

hai.stanford.edu/news/whos-fault-when-ai-fails-health-care 

 

Civil liability for the actions of autonomous AI in healthcare: an ... 

WEB Feb 23, 2024 · The use of AI-enabled medical robots in healthcare settings poses a host of legal and ethical questions, especially regarding the attribution of liability for the …

nature.com/articles/s41599-024-02806-y