The Future of Healthcare: AI Doctors, Robotic Surgeries & Personalized Medicine
Artificial Intelligence (AI) is increasingly becoming a game-changer in the healthcare industry. Its transformative potential is driving rapid advancements in medical technology, improving the quality of care, and enhancing patient outcomes in ways that were once unimaginable. From AI-powered diagnostics to robotic-assisted surgeries, AI is enabling healthcare professionals to make faster, more accurate decisions while improving efficiency and access to care for patients worldwide.
AI holds the promise to revolutionize medicine in three key areas: AI doctors that assist with diagnostics and treatment plans, robotic surgeries that offer precision and minimize human error, and personalized medicine that tailors healthcare treatments to individual patients based on their unique genetic makeup. Together, these innovations are poised to reshape how healthcare is delivered, making it more precise, accessible, and patient-centric.
In this article, we will explore the current applications of AI in healthcare, including AI doctors and robotic surgeries, and delve into how personalized medicine is helping to tailor treatments for individual patients. We will also examine the ethical and practical challenges that come with these innovations, such as the need for regulation, data privacy concerns, and the potential impact on healthcare professionals. Finally, we’ll look toward the future of AI in healthcare and the exciting possibilities it holds in transforming not only how we treat diseases but also how we approach overall healthcare.
AI Doctors: The Rise of Intelligent Healthcare Providers
The concept of an AI doctor represents a groundbreaking shift in how healthcare is delivered. Unlike traditional physicians, AI doctors rely on vast datasets, machine learning algorithms, and deep learning techniques to analyze patient data, medical records, and genetic information. These AI-driven systems are designed to assist in diagnostics, treatment planning, and offering health advice, often with the ability to process information much faster than a human doctor could.
AI in Diagnostics:
AI has proven to be a valuable asset in diagnostics, particularly in early disease detection and identifying complex conditions. Machine learning models can analyze medical images, genetic data, and patient histories to detect signs of diseases like cancer, heart disease, and neurological conditions, often before symptoms appear. In some cases, AI can even outperform human doctors in detecting certain diseases, as seen with AI-powered systems in radiology, where algorithms have been developed to read and interpret X-rays and MRIs with remarkable accuracy. For example, AI systems can analyze thousands of medical records to spot patterns or early warning signs that might be overlooked by human clinicians, giving patients a better chance of early intervention.
Virtual Health Assistants:
AI-driven virtual assistants, like chatbots and telemedicine platforms, are increasingly playing an essential role in delivering healthcare remotely. These AI systems are capable of providing 24/7 health monitoring, tracking vital signs, and offering real-time consultations. Virtual health assistants use natural language processing (NLP) to communicate with patients, answering questions about symptoms, advising on treatment options, and even helping patients manage chronic conditions. Many healthcare organizations are integrating telemedicine platforms powered by AI to provide remote consultations, allowing patients to receive timely medical advice without leaving their homes.
The Benefits and Limitations:
The benefits of AI doctors are immense. They provide efficiency, scalability, and accuracy in diagnosing and treating patients. AI can process large amounts of data in real time, enabling faster diagnoses and reducing wait times. Additionally, AI systems can operate 24/7, providing continuous support and guidance to patients. AI doctors also have the potential to democratize healthcare by making it more accessible to people in remote or underserved areas.
However, there are limitations to AI in healthcare. One major challenge is the lack of human empathy. While AI can analyze and diagnose with precision, it cannot replicate the emotional understanding and compassionate care that a human doctor provides. Furthermore, there is a risk of over-reliance on AI systems, particularly in complex or nuanced cases where human judgment and experience are crucial. AI systems are only as good as the data they are trained on, and there’s always a risk of biases in the data leading to misdiagnoses.
Real-Life Example:
One prominent example of AI’s impact on healthcare is IBM Watson Health. Watson Health uses AI to analyze vast amounts of clinical data, medical literature, and patient records to help doctors make more informed decisions. IBM has partnered with healthcare providers like the Memorial Sloan Kettering Cancer Center to develop AI-driven diagnostic and treatment recommendations. These partnerships have demonstrated the potential of AI to support healthcare professionals in making faster, more accurate decisions in the fight against complex diseases like cancer.
AI doctors are undeniably reshaping the healthcare landscape, offering significant improvements in efficiency and diagnostics. However, while they offer a valuable complement to human healthcare providers, they cannot replace the nuanced understanding and empathy that human doctors bring to the table. As AI continues to evolve, finding a balance between human expertise and AI-driven support will be key to creating an optimal healthcare system for the future.
Robotic Surgeries: Precision and Efficiency
The integration of AI into surgical practices is transforming the field of healthcare by enhancing the precision, efficiency, and overall safety of surgeries. Robotic surgery, often guided by AI-powered systems, offers significant advantages over traditional manual procedures, particularly in complex or delicate operations. These advancements promise to improve patient outcomes, reduce human error, and bring about quicker recovery times.
The Role of Robotics in Surgery:
AI-powered robotic systems are designed to assist surgeons by offering enhanced precision during operations. These robotic systems are equipped with highly sensitive instruments that can operate with millimeter precision, enabling surgeons to perform delicate procedures with unparalleled accuracy. AI plays a crucial role in interpreting patient data, suggesting optimal surgical approaches, and providing real-time insights during the surgery. The robotic systems can also be programmed to adjust their movements based on the surgeon’s commands, providing a level of fine-tuned control that is difficult to achieve manually.
These systems significantly reduce human error by offering more steady, consistent movements, which are especially beneficial during lengthy surgeries or those requiring intricate maneuvers. Additionally, AI can monitor the patient’s vitals and adjust the surgical approach accordingly, ensuring optimal conditions throughout the operation.
Advancements in Robotic Surgery:
The field of robotic surgery is advancing rapidly, with key innovations enhancing the capabilities of AI-driven systems. One of the most notable advancements is minimally invasive surgery, where small incisions are made, and robotic arms or tools are used to perform procedures that once required large cuts. This leads to reduced scarring, less trauma to surrounding tissues, and faster recovery for patients.
Tele-surgery is another breakthrough, where a surgeon, potentially thousands of miles away, can perform surgeries remotely using robotic arms controlled by AI. This allows for access to expert surgical care even in remote areas or where there is a shortage of skilled surgeons. Additionally, AI-driven robots are evolving to perform tasks autonomously, such as stitching or monitoring vital signs, without direct human intervention. This opens the door to increasing the availability of surgeries and reducing the burden on human surgeons.
Benefits of Robotic Surgery:
The benefits of robotic surgery are clear and multifaceted:
Faster Recovery Times: Minimally invasive surgeries typically result in smaller incisions, leading to less pain, quicker recovery times, and reduced hospital stays.
Fewer Complications: AI-powered robots can precisely target areas, reducing the risk of complications such as infections, blood loss, and damage to surrounding tissues.
Enhanced Precision: With AI’s real-time guidance and precise control, surgeons can execute complex procedures with greater accuracy, leading to improved surgical outcomes.
Improved Patient Safety: AI systems can continuously monitor patient vitals during surgery, making automatic adjustments if necessary and alerting the surgical team to potential risks.
These advantages demonstrate how AI-driven robotics are helping to elevate the field of surgery, making procedures safer, more effective, and more efficient for patients.
Ethical Concerns and Challenges:
Despite the tremendous potential of robotic surgery, several ethical concerns need to be addressed as AI becomes more involved in operating rooms:
Liability: If an AI-powered surgical system malfunctions, who is responsible for the outcome—the manufacturer, the surgeon, or the hospital? Legal frameworks will need to evolve to ensure clear accountability in cases where AI systems make errors.
Human Oversight: While AI systems offer incredible precision, there is a concern about removing the human element entirely. Surgery often requires quick thinking and adaptation to unforeseen complications. Should there be limits on the autonomy of AI systems in the operating room to preserve human judgment in critical situations?
Loss of the Human Touch: Surgery is not just a technical process; it also involves human empathy and decision-making that AI cannot replicate. The risk of dehumanizing the surgical experience is a real concern, particularly when patients may feel disconnected from their healthcare providers.
Real-Life Example:
The da Vinci Surgical System is one of the most widely used robotic surgical systems, providing a platform for minimally invasive surgeries across various specialties, including urology, gynecology, and general surgery. The system offers 3D visualization, precision controls, and enhanced dexterity, allowing surgeons to perform complex procedures with greater accuracy. Companies like Intuitive Surgical continue to innovate in the field, improving robotic systems with AI capabilities to further enhance performance and expand the reach of robotic surgery.
The introduction of AI-powered robotic surgery has the potential to revolutionize how we approach healthcare. While these systems offer unparalleled precision and efficiency, it is crucial to address the ethical challenges and ensure that AI remains a supportive tool rather than a replacement for human involvement in critical medical decisions. The continued development and regulation of AI in surgery will shape the future of healthcare, balancing technological advancement with human care.
Personalized Medicine: Tailoring Treatments to the Individual
Personalized medicine, often referred to as precision medicine, is revolutionizing the healthcare industry by enabling more individualized approaches to treatment and care. By utilizing AI, genomics, and patient-specific data, personalized medicine aims to customize healthcare plans based on a person’s genetic makeup, lifestyle, and environment. The goal is to move away from the traditional one-size-fits-all approach and provide more effective, targeted therapies that improve patient outcomes.
What is Personalized Medicine?
Personalized medicine is an innovative approach to healthcare that uses detailed patient data to create tailored treatments. This involves analyzing an individual’s genetic profile, lifestyle factors (such as diet and exercise), and environmental influences (such as exposure to toxins) to provide more precise treatments. With AI and genomics at its core, personalized medicine is moving healthcare toward predictive, preventive, and more effective care models, where patients receive treatments that are specifically suited to them.
In the past, many treatments were generalized based on the average response of a population. But with personalized medicine, treatments are designed to match each person’s unique biological makeup, potentially leading to better outcomes with fewer side effects. AI and data analytics are at the forefront of this transition, allowing healthcare providers to offer more precise care.
How AI Supports Personalized Medicine:
AI plays a pivotal role in personalized medicine by enabling the analysis and interpretation of complex patient data. AI algorithms are trained to identify patterns in genomic data, medical history, and lifestyle factors that can predict how a patient will respond to certain treatments. By analyzing vast amounts of data that would be impossible for a human to process, AI can uncover hidden insights and provide actionable recommendations to healthcare providers.
For example, AI can predict the most effective drug for a patient based on their genetic makeup, ensuring that the treatment will work as expected while minimizing adverse reactions. Additionally, AI-driven systems are capable of analyzing patient data in real-time, allowing healthcare providers to adjust treatment plans on the fly and ensure optimal results.
The Role of Genomics and AI:
One of the most promising applications of AI in personalized medicine is in the field of genomics. Genomic data, which includes information about an individual's DNA and how it influences their health, is a key component of personalized medicine. AI models are trained to interpret vast amounts of genomic data to identify genetic mutations, inherited diseases, and markers for various health conditions.
By combining AI with genomics, researchers can better understand the genetic basis of diseases, such as cancer, and develop more effective treatments. For instance, AI can help identify the genetic mutations that drive a specific type of cancer, enabling doctors to target those mutations with precision therapies. This approach allows for more personalized, targeted treatments, increasing the likelihood of successful outcomes and reducing the trial-and-error process common with traditional treatments.
The Benefits and Limitations:
The potential benefits of personalized medicine powered by AI are immense:
Improved Outcomes: Treatments tailored to the individual are more likely to be effective, reducing the chances of adverse side effects and improving overall health outcomes.
Early Detection: AI models can analyze genetic data to predict the likelihood of developing diseases, allowing for earlier interventions and preventative measures.
Targeted Treatments: By using AI to analyze genetic markers, doctors can prescribe medications that are specifically suited to a patient's genetic makeup, minimizing ineffective treatments and harmful side effects.
However, personalized medicine also faces challenges that need to be addressed:
Data Privacy: The use of genomic data raises serious concerns about data privacy and security. Sensitive personal health information must be protected to prevent misuse or unauthorized access.
Access to Testing: While AI and genomics hold great potential, not everyone has access to genetic testing or personalized treatments, creating potential inequities in healthcare access.
Ethical Concerns: There are concerns about the potential misuse of genetic data, such as discrimination based on genetic predispositions in employment or insurance.
Real-Life Example:
Companies like Tempus and Foundation Medicine are leading the charge in integrating AI with genomics to provide personalized cancer treatments. Tempus uses AI to analyze clinical and molecular data, helping doctors identify the most effective treatments for cancer patients. Foundation Medicine offers genomic profiling services that identify genetic mutations driving cancer, enabling oncologists to customize treatments based on a patient’s unique genetic profile. Both companies are using AI to tailor healthcare treatments to the individual, improving the precision and effectiveness of cancer therapies.
Through these innovations, AI and genomics are transforming how we approach cancer treatment, providing patients with the most accurate and personalized care possible. As AI continues to evolve, its ability to further personalize healthcare and treatment will likely expand, leading to even more advancements in precision medicine.
In summary, personalized medicine powered by AI has the potential to transform healthcare, making treatments more effective and tailored to each individual. While there are challenges to overcome, particularly regarding privacy, accessibility, and equity, the future of personalized medicine looks incredibly promising.
Ethical, Legal, and Privacy Concerns
As AI technology continues to transform healthcare, it brings with it a host of ethical, legal, and privacy concerns that need to be carefully addressed. While AI’s potential to improve patient outcomes and revolutionize medical practices is vast, it also presents significant challenges in the areas of data privacy, fairness, accountability, and the need for robust regulations.
Data Privacy:
One of the primary concerns with AI in healthcare is the protection of patient data. AI-driven healthcare solutions rely heavily on vast amounts of personal data, including medical records, genetic information, and real-time health data. This raises serious questions about how patient information is stored, shared, and protected.
While AI systems can potentially improve healthcare outcomes by providing more accurate diagnoses and personalized treatments, they also create the risk of sensitive data being exposed or accessed without consent. Data breaches or unauthorized access to this information can result in significant harm to patients, including identity theft, discrimination, and loss of trust in the healthcare system.
The growing reliance on electronic health records and AI systems amplifies the need for stringent cybersecurity measures. There’s an ongoing debate about who owns the patient’s data and how consent is managed in the context of AI-driven health solutions. If AI systems are allowed to access patient data without proper safeguards, patients may unknowingly risk their privacy and autonomy.
Bias in AI Models:
Bias in AI models is another major concern in healthcare, as AI systems learn from existing datasets, which may contain inherent biases. If these datasets are not diverse or representative of the population as a whole, AI-driven healthcare solutions could perpetuate or even exacerbate existing health disparities.
For example, if an AI model is trained on data that predominantly represents one demographic—such as white, middle-class patients—it may not perform as effectively for patients from other racial, ethnic, or socioeconomic backgrounds. This could lead to misdiagnoses or improper treatment recommendations for marginalized groups, exacerbating inequalities in the healthcare system.
In healthcare, such biases can have serious consequences. If AI systems are used to determine treatment plans, monitor chronic conditions, or predict health risks, biased outcomes could lead to worse healthcare experiences for vulnerable populations. Addressing these biases requires not only more inclusive datasets but also the development of AI models that are explicitly designed to identify and mitigate these biases.
Accountability and Liability:
As AI takes on more responsibilities in healthcare, the question of accountability becomes crucial. If an AI-driven system makes an error—whether in diagnosing a condition, recommending a treatment, or even performing a surgery—who is held accountable?
In traditional healthcare settings, human doctors and medical professionals are held liable for mistakes made during diagnosis or treatment. However, when AI systems are responsible for making decisions, the lines of accountability become murky. Should the AI developer be held responsible if the system fails? Should the healthcare provider be accountable for relying on AI, or does the responsibility fall on the patient for consenting to the AI-driven solution?
This dilemma is especially pressing when life-threatening medical decisions are involved. For example, if an AI system misdiagnoses a patient with cancer or recommends an inappropriate treatment, and this leads to harm, who is legally responsible? These questions need to be addressed by lawmakers, healthcare providers, and AI developers as AI continues to be integrated into the medical field.
Regulations and Oversight:
Given the potential risks and ethical dilemmas, it’s critical that AI systems in healthcare are tightly regulated and monitored. Developing clear, consistent standards for AI implementation in healthcare can help ensure that these technologies are used safely and ethically. Proper oversight is necessary to protect patients, healthcare workers, and institutions from harm while fostering innovation.
Regulations should cover various aspects, including data security, transparency, bias mitigation, and accountability for AI-driven decision-making processes. Some countries, such as the European Union, have already started taking steps toward regulating AI, with frameworks like the General Data Protection Regulation (GDPR) setting standards for data privacy. However, as AI in healthcare evolves, more specific regulations are needed to address issues unique to this sector.
AI models in healthcare need to be explainable, so patients and healthcare providers can understand how decisions are made. Transparency is key in gaining public trust and ensuring that AI is used responsibly. Legal frameworks will need to evolve alongside AI technology to protect both individuals and society at large from the potential harms of AI.
Real-Life Example:
One real-life example of these concerns involves the use of predictive analytics in healthcare. AI models are being used to predict patient outcomes, such as the likelihood of rehospitalization or readmission after surgery. However, these systems have faced criticism for embedding biases into the decision-making process. For instance, research found that certain predictive algorithms used by hospitals were less accurate for Black patients compared to white patients, resulting in inequitable treatment recommendations.
Such biases, if left unchecked, could contribute to unequal healthcare delivery and reinforce existing health disparities. In some cases, AI systems may even prioritize certain individuals for healthcare resources or interventions based on skewed predictions, leading to unfair outcomes. This raises the question of how AI systems can be held accountable when they lead to unintended or harmful consequences, particularly when it comes to vulnerable populations.
These examples highlight the urgency of creating ethical guidelines, frameworks, and regulatory oversight to ensure AI in healthcare benefits everyone, not just a privileged few. Ensuring fairness, transparency, and accountability in AI applications will be crucial in making AI a reliable and trustworthy tool in the future of healthcare.
The Future of AI in Healthcare: What's Next?
The future of AI in healthcare holds immense potential, promising advancements in drug discovery, personalized care, operational efficiency, and expanding access to medical services. As AI technologies continue to evolve, their integration into healthcare will help address long-standing challenges and create a more efficient, equitable, and accessible system for patients and healthcare providers alike.
AI in Drug Discovery and Development
AI is already playing a pivotal role in transforming the drug discovery and development process. By analyzing massive datasets and using machine learning algorithms, AI can identify potential drug candidates more quickly and accurately than traditional methods. This accelerates the timeline for developing new medications, vaccines, and treatments, helping to address pressing health challenges more efficiently.
For example, AI has already contributed to breakthroughs in the development of vaccines, particularly in response to the COVID-19 pandemic. By analyzing genetic sequences, protein structures, and other medical data, AI systems helped identify promising vaccine candidates and predict how they might interact with the human immune system. AI tools can also optimize clinical trial designs by identifying the right participants and predicting patient responses to treatments, which can drastically reduce the time and cost of developing life-saving drugs.
The potential for AI in drug development extends beyond infectious diseases, with AI playing an increasingly important role in personalized medicine, oncology, and neurodegenerative diseases, among others. As AI models improve, the future holds the promise of faster, more targeted therapies, leading to improved patient outcomes and more precise treatments.
AI in Healthcare Administration
One of the less discussed but highly impactful applications of AI is in healthcare administration. AI is being used to streamline administrative tasks, such as managing patient records, billing, scheduling, and even supply chain management within healthcare facilities. By automating these time-consuming and often error-prone processes, AI helps reduce costs and increase the overall efficiency of healthcare systems.
AI-powered tools can process and analyze electronic health records (EHRs), allowing doctors to access patient histories, lab results, and other critical data more efficiently, leading to faster diagnosis and treatment. Additionally, AI-driven administrative systems can reduce human error in managing medical records, ensuring that data is accurate and accessible, which is essential for providing high-quality patient care.
AI can also assist in optimizing hospital operations by predicting patient admission rates, resource utilization, and staff schedules, ensuring that healthcare providers have the resources they need at the right time. This can improve the quality of care, reduce wait times, and help healthcare providers manage their resources more effectively.
AI and the Aging Population
As the global population ages, there is an increasing need for personalized healthcare solutions that can support elderly patients. AI has the potential to address this need by providing tools for remote monitoring, personalized care plans, and even companionship for seniors.
AI-powered devices, such as wearables and health monitors, can track vital signs like heart rate, blood pressure, and blood sugar levels in real-time, alerting healthcare providers and caregivers to potential health issues before they become critical. AI systems can also help elderly patients manage chronic conditions by offering personalized recommendations for diet, exercise, and medication management based on their specific needs.
Beyond physical health, AI can help provide social and emotional support for aging populations. AI-powered virtual companions and telemedicine platforms can reduce feelings of loneliness by offering conversation, reminders, and mental stimulation. These technologies are particularly valuable for seniors in underserved areas where access to healthcare professionals may be limited.
Telemedicine and Remote Care
Telemedicine has been one of the most transformative shifts in healthcare, especially in the wake of the COVID-19 pandemic. AI has played a key role in expanding the reach and effectiveness of telemedicine by enabling remote consultations, diagnostics, and care management. AI-powered virtual assistants and chatbots can provide instant answers to patients' questions, guide them through basic health assessments, and even provide personalized health advice.
For patients in rural or underserved areas, AI-driven telemedicine platforms offer a lifeline by connecting them to healthcare providers without the need for long-distance travel. AI can also help reduce healthcare disparities by offering continuous care and support to populations that may otherwise struggle to access healthcare services due to geographical, financial, or logistical barriers.
As telemedicine platforms become more advanced, AI will help enhance the quality of remote care by enabling real-time diagnostics, patient monitoring, and personalized treatment plans based on a patient's medical history and ongoing health data. With AI, remote care will become increasingly effective, reducing hospital visits and making healthcare more accessible.
Real-Life Example:
During the COVID-19 pandemic, AI played a crucial role in vaccine development, speeding up the process of identifying promising vaccine candidates. Companies like Moderna and BioNTech leveraged AI-driven tools to analyze the virus’s genetic code and identify how the spike protein on the virus interacts with the human immune system. AI models helped simulate how various potential vaccines might respond to the virus, guiding the selection of the most promising candidates for clinical trials. This accelerated the vaccine development process, saving crucial time and saving countless lives in the process.
AI’s role in vaccine development demonstrates its vast potential in healthcare. As AI continues to evolve, its applications in drug discovery, telemedicine, personalized healthcare, and administrative efficiency will reshape the healthcare industry in profound ways.
Conclusion:
The future of healthcare powered by AI is incredibly promising, with the potential to revolutionize everything from diagnosis and treatment to healthcare access and efficiency. However, as AI technologies evolve, it will be critical to navigate the associated ethical, privacy, and regulatory challenges to ensure that these advancements benefit everyone equally. The continued development of AI in healthcare holds the key to improving patient outcomes, reducing costs, and making healthcare more accessible to people worldwide.
Embracing AI’s Potential in Healthcare
The Promise of AI in Medicine: As we look toward the future, AI promises to revolutionize healthcare, enhancing everything from diagnostics and treatment to surgical procedures and personalized care. AI’s ability to analyze vast amounts of data and identify patterns that human clinicians might miss is already improving the accuracy and efficiency of healthcare delivery. From AI doctors providing accurate diagnostics and personalized treatment plans to robotic surgeries offering enhanced precision, AI is fundamentally reshaping the medical landscape. With AI’s potential to assist in drug discovery, accelerate vaccine development, and monitor patients remotely, the promise of better, faster, and more accessible healthcare is within reach.
Challenges to Overcome: However, this transformation does not come without significant challenges. As AI becomes more integrated into healthcare systems, issues such as data privacy, algorithmic bias, accountability, and human oversight need to be carefully managed. AI models can only be as good as the data they are trained on, and biased data could result in inequalities in care. Moreover, ensuring the safety of AI systems and establishing clear legal frameworks around their use will be crucial. It’s imperative that AI technologies are not just powerful and efficient, but that they are also ethical, transparent, and respectful of patient rights. The development and implementation of AI in healthcare must be done with a view toward fairness, equity, and the safeguarding of personal information.
Call to Action: To achieve the full potential of AI in healthcare, it is vital that policymakers, healthcare professionals, and technologists collaborate to create regulatory frameworks that prioritize patient safety, privacy, and ethical standards. It will require a multidisciplinary approach to ensure that AI systems are developed and deployed responsibly, with human oversight and accountability at every step. We must also ensure that AI-driven healthcare solutions are accessible to all, preventing further healthcare disparities between wealthy and underserved communities.
Final Thought: AI has the transformative power to change the face of healthcare as we know it—enabling better diagnostics, more effective treatments, and greater access to care. But as we embrace these advancements, we must always ensure that human oversight, empathy, and ethical principles guide AI development. By combining the power of AI with human compassion and expertise, we can create a healthcare system that not only saves lives but does so in a way that is equitable, responsible, and aligned with the values of patient-centered care. The future of healthcare is bright, and AI has the potential to make it even brighter—but only if we move forward with caution, responsibility, and a commitment to doing what’s best for patients.
