Responsibly Embracing Artificial Intelligence in Healthcare for Progressive Care

As we face modern healthcare dilemmas, we must explore modern solutions. Companies like IBM, Apple, Amazon, Microsoft, and other tech typhoons are heavily investing in language processing information (e.g. natural language processing, rule-based expert systems, machine learning, healthcare analytics, diagnostics and treatment applications, and administrative applications) and other artificial intelligence (AI) technologies to interpret human communication for healthcare sector applications. With the rapid emergence of AI in various economic sectors, healthcare must also harness its power. However, with such immense potential comes an ethical responsibility of equal magnitude. To achieve the Quadruple Aim effectively, comprehensive policy frameworks addressing a range of critical requirements are essential: patient privacy, data security, transparency, explainability, regulatory oversight, ethical consideration, clinical validation and efficacy, healthcare professional collaboration, continued monitoring and evaluation, education and training, interoperability, and public awareness and engagement. Responsible and ethical use of innovation is vital to balance its potential with the enhancement of patient outcomes and healthcare quality while minimizing costs and staff difficulties. This approach is crucial to thereby achieve unified health equity.

AI in healthcare has immense potential for efficiently detecting, diagnosing, and monitoring life-threatening diseases like cancer. Within AI, machine learning specializes in using trained data to predict cancer, often achieving higher accuracy rates than clinicians and improving diagnoses, prognoses, and overall life quality. For example, surgery centers have used AI to detect and diagnose brain tumors in real-time, analyze medical images, differentiate between malignant and normal tissue, analyze gene tissue and activity levels, and identify colorectal mismatch repair deficits. Notably, the American Cancer Society reports that AI has accelerated the review and translation of mammograms by 30 times with 99% accuracy. 

In addition to the significant clinical benefits, AI has improved clinical workflows, interpreted medical forms and histories, integrated electronic health records, reduced human resource costs, increased data efficiency, enhanced diagnostic accuracy, and elevated treatment outcomes. Many health systems have begun to embrace AI technologies; for instance, Cayuga Medical Center adopted a CDI Software Solution with Meditech integration, resulting in $130,000 in savings. However, while estimates project AI to contribute over $30 trillion to the global economy by 2030, effective regulation is still necessary to manage its growth responsibly within the healthcare industry.

One issue of utmost importance to monitor is algorithmic bias. Ensuring that data is from diverse backgrounds enables such algorithms to work for all demographics, regardless of gender, race, ethnicity, age, or any other factor. Also, while many software companies, like Google with their DeepMind, prioitize utilizing neural networks to mimic the human brain, it is crucial that any biases from developers do not poison their creations. Unfortunately, bias from developers has affected patient care in the past. For instance, developers assumed certain symptoms were less likely in Black women compared to non-Hispanic White women, causing practitioners to miss key diagnosis indicators and diminishing the quality of care. Further, in 2007, an algorithm falsely suggesting higher rates of cesarean deliveries to Black patients based on an incorrect assumption that they had less success with vaginal birth after cesarean delivery. While this error was discovered and corrected in 2017, it demonstrates the importance of learning from past mistakes. AI provides hope: Despite current struggles, according to the Pew Research Center, 51% of Americans believe that AI in diagnosis and treatment recommendations will help reduce bias and unfair treatment.

Following the necessary alignment with the American Medical Association’s 2018 framework, ensuring AI’s role solely benefits patients, physicians, and the health care system, careful safeguarding is vital. On October 30th, 2023, the Biden-Harris Administration signed an Executive Order to ensure AI is safely and responsibly utilized to improve health outcomes while upholding security and privacy standards. In response, in December of 2023, numerous AI companies, payers, and providers voluntarily joined forces with the Department of Health and Human Services to develop responsible models. With the focus on achieving Fair, Appropriate, Valid, Effective, and Safe (FAVES) outcomes, managing risks and fostering patient transparency are crucial to ensure accessible, equitable, and affordable care while mitigating medical burnout and improving care coordination and care experience. With the potential to save billions of lives and dollars, widespread support for AI in healthcare policies like these is vital.