Artificial Intelligence (AI) has been a catchphrase in the tech industry for many years but the health sector is gradually catching the ‘fever’. This is not surprising considering the new wave of challenges facing the sector—which requires new ideas to overcome. In this post, we will explore the future directions of AI in healthcare.
From analytics to diagnosis, healthcare management, and treatment, AI has proven to be an important tool that will create more efficient processes in healthcare systems. The benefits of AI integration in healthcare will be felt by the patients, medical personnel, and healthcare administrators.
In this article, we will talk about AI applications in healthcare, the benefits of doing so as well as the challenges and ethical considerations of doing so.
Table of Contents
- Application of AI in Healthcare
- Benefits of AI in Healthcare
- Challenges and Ethical Considerations
- Future Directions and Possibilities
- Conclusion
Application of AI in Healthcare
AI integration in healthcare has been able to streamline the role of healthcare administrators in several ways including automating healthcare records. It has also changed the way patients get medical assistance.
The integration of AI in patient care has the potential to improve healthcare outcomes. What is more fascinating is the potential for even more development that AI systems are bound to undergo in the coming years. Below are some of the ways AI can be integrated into healthcare systems.
1. Disease diagnosis and prediction
Healthcare professionals rely on efficient disease diagnosis to provide patients with the right healthcare interventions. Before the coming of AI, healthcare providers relied on human analysis and interpretations which often leads to delays in diagnosis—and higher human errors that increase with increasing workload.
Today, medical imaging techniques like MRIs, CT scans, and X-rays are now analyzed using AI-based systems to produce more accurate diseases diagnosis in shorter times. They’re also using AI-powered software to streamline the medical dictation process. This has helped to lower diagnostic errors, lessen the workload of physicians, and help physicians to correctly detect and predict various diseases and their progression.
2. Treatment and therapy
Deep Machine Learning can be exploited to speedily identify potential therapies that would be effective in the treatment of certain diseases. For example, AI-based systems can identify compounds (both existing and yet to be synthesized) that would be effective for the treatment of certain ailments.
AI systems can also fast-track the process of drug discovery by analyzing huge volumes of data within a short time—a feat that may be difficult for humans to achieve. AI models that identify data patterns will help researchers to predict the effectiveness of new drug candidates. in other words, the use of AI can lead to the production of more targeted drugs.
3. Patient care and monitoring
Oftentimes, patient care requires more than one hospital visit—like when a patient has had an operation and needs post-operative care. This can be a huge challenge for those in medical tourism. Physicians are now using wearable devices to remotely monitor patients, and overcome geographic constraints.
Data from these wearable devices are often analyzed by AI-powered systems in real-time and help patients to receive timely interventions when the need arises. In addition to predicting and preventing complications, it also saves patients the cost of always making multiple trips to the hospital.
4. Administrative and operational efficiency
Computer-Assisted Physician Documentation (CAPD) powered by AI can offer documentation suggestions to physicians that would make record-keeping in hospitals more thorough. These gentle nudges can save the physician the stress of remembering what data to collect at all times as well as enhance precise billing and reimbursement.
With thorough and more accurate record-keeping, clinics will easily tell when there is a spike in infection within a particular area. Such information will be crucial in stopping the next pandemic or making data-driven administrative decisions.
5. AI-powered customer service
The first point of contact when people want to make inquiries about a hospital on things like pricing, schedule, insurance, and so on, is the customer care line. These calls can be overwhelming sometimes, leading to overworking of staff—for hospitals without enough resources to hire more customer care representatives.
AI-powered customer services can help to lower that burden by answering frequently asked questions and only referring more serious inquiries to a human agent.
Benefits of AI in Healthcare
Arguably two of the most important benefits of AI in healthcare are the provision of personalized care and predictive analytics. With AI-powered data analytics tools, blunders in diagnosis due to human error and fatigue can be lowered significantly.
AI has the potential to revolutionize how healthcare is offered and consumed. In other words, the use of AI can have a tremendous positive impact on patients and everyone involved in healthcare delivery. The benefits of AI in healthcare include;
- AI-powered analytics tools can identify patients at risk of a particular disease or health condition by analyzing patient data like genetic information, lifestyle habits, medical history, and environmental factors
- Access to advanced imaging tools for the detection of diseases like cancer in earlier stages compared to traditional methods. This can help to improve the prognosis
- Faster analysis of large volumes of patient data with higher precision helps physicians to make more informed decisions
- Automation of processes like record-keeping has helped to reduce administrative healthcare workers’ burden
- AI-powered telemedicine has made disease diagnosis by qualified experts more available and accessible, bridging the gap in health access in low-income communities.
- Wearable devices that leverage AI are now used to remotely monitor patients to provide timely and quality post-operative care.
- Some AI-powered devices can serve as reminders that nudge patients to take their medicines
- In addition to checking a patient’s vitals, some smart devices can also help patients to make lifestyle changes that will help to advance their health outcomes.
- AI-powered surgical robots and assistants help to complete complex surgical procedures with higher precision.
Challenges and Ethical Considerations
There are growing concerns about the use of AI in healthcare systems, considering the sensitive nature of the sector—and because AI-powered systems are not immune to errors. Therefore, it is important to continuously monitor AI systems after they have been deployed to forestall adverse events.
There is a growing call for regulatory bodies and healthcare organizations to collaborate to gather and analyze the most vital datasets on AI safety and performance. Below are the challenges and ethical considerations regarding the use of AI in healthcare systems.
1. Retraining of healthcare personnel
Since AI is a relatively new field in healthcare, it would require the retraining of healthcare providers and administrative staff which could take time. The transition process can be long and hamper effective healthcare delivery. There is also the growing fear that health personnel that are unable to catch up with the transition will lose their jobs.
2. Data privacy and security
Patients’ files and medical records are supposed to be confidential. Before integrating AI-powered systems, healthcare organizations should take steps to ensure they have robust cybersecurity measures to prevent unauthorized access to patient’s data.
3. Challenge with training healthcare-based AI
AI depends on data for training. The higher the volume of data that AI algorithms are exposed to, the better the outcomes. However, obtaining medical data is usually difficult due to restricted access to some types of health data, inconsistent data format, and privacy concerns.
4. Possibility of bias
Bias, including gender and race, can be introduced into AI algorithms if they are not trained with adequate amounts of the right data. This is highly likely due to the paucity of data in some countries and races. This underscores the need for proper scrutiny of the production of AI-based tools as well as constantly monitoring the tools to ensure they remain unbiased.
5. Interoperability
Several software applications are used in healthcare organizations. AI-powered systems may face interoperability challenges with some of the software applications used in health settings.
Future Directions and Possibilities
Notwithstanding all these challenges, the future of AI in healthcare systems remains promising. Proper integration of AI technology can spearhead breakthroughs in disease discovery, improved personalized medicine that considers salient factors like lifestyle, age, race, gender, and so on, and overall enhancement of patient outcomes. Other future possibilities of AI include;
- The use of robots in operation and other delicate medical procedures
- Virtual health assistants powered by AI can offer probable diagnoses, answer basic queries, and offer medical advice to further reduce the workload of health professionals
- The use of AI tools to detect mental health conditions through facial recognition and speech tone analysis and offer support to patients
While all these innovations are ongoing, there will likely be more government scrutiny and the formulation of regulations to make the use of AI in healthcare systems safe as well as to protect the privacy of patients.
Conclusion
Artificial Intelligence has a place in healthcare systems. We highlighted the benefits of AI integration in healthcare systems including predictive analytics, personalized care, and better ability to detect terminal diseases at earlier stages when the chance of survival is higher.
For the full benefit of AI integration in healthcare systems to be achieved, the development of the tools needs to be properly scrutinized to make sure they are devoid of bias. Also, concerned regulatory bodies need to speedily come up with guidelines to ensure the safe deployment of these technologies since the AI revolution is inevitable.
