doi: 10.56294/mw2024493
ORIGINAL
Evaluating Artificial Intelligence in Medical Communication for Enhancing Doctor-Patient Interactions and Outcomes
Evaluación de la inteligencia artificial en la comunicación médica para mejorar la interacción médico-paciente y sus resultados
Frederick Sidney Correa1 
*,
Rohini2 , Shashikant Patil3 , Satya Ranjan Das4 
, Kamineni Sairam5 , Jagtej Singh6
1Centre of Research Impact and Outcome, Chitkara University. Rajpura, Punjab, India.
2Department of Anaesthesia, Noida International University. Greater Noida, Uttar Pradesh, India.
3Department of ISME, ATLAS SkillTech University. Mumbai, Maharashtra, India.
4Department of Computer Science and Engineering, Siksha ‘O’ Anusandhan (Deemed to be University). Bhubaneswar, Odisha, India.
5Centre for Multidisciplinary Research, Anurag University. Hyderabad, Telangana, India.
6Chitkara Centre for Research and Development, Chitkara University. Himachal Pradesh, India.
Cite as: Correa FS, Rohini R, Patil S, Das SR, Sairam K, Singh J. Evaluating Artificial Intelligence in Medical Communication for Enhancing Doctor-Patient Interactions and Outcomes. Seminars in Medical Writing and Education. 2024; 3:493. https://doi.org/10.56294/mw2024493
Submitted: 06-10-2023 Revised: 08-01-2024 Accepted: 11-05-2024 Published: 12-05-2024
Editor: PhD.
Prof. Estela Morales Peralta 
Corresponding Author: Frederick Sidney Correa *
ABSTRACT
Medical communication using artificial intelligence (AI) might improve relationships between physicians and patients and provide better outcomes on health. It looks at how consumers and healthcare professionals may interact more easily thanks to AI-powered solutions such virtual assistants and robots. AI technologies may provide physicians accurate, current information, assist in clinical decision-making, reduce their mental load so they may concentrate on more challenging aspects of treatment. Moreover made accessible seven days a week, twenty-four hours a day are artificial intelligence technologies. In this sense, individuals may always acquire customised to their medical requirements answers and assistance. This paper investigates how effectively artificial intelligence technologies could raise patient engagement in medical exchanges, confidence, and pleasure. Examining many artificial intelligence systems used in healthcare reveals how they enable individuals to interact better by addressing shared issues such language and mental stress, and how they assist to solve the shortage of healthcare professionals. Particularly with regard to safeguarding data privacy and maintaining the human touch in healthcare, we also discuss the moral questions and challenges raised by artificial intelligence usage. Particularly how quickly and precisely AI can provide medical advice, assist to reduce the risk of misunderstandings, and enhance treatment commitment, researchers are also investigating how AI influences patient outcomes. The results of the research show that although artificial intelligence is a terrific tool for enhancing doctor-patient communication, it must be utilised wisely so as not to replace human understanding. Better, more knowledgeable, and more compassionate treatment for patients in the future is what we expect to see by supporting AI systems and healthcare professionals to cooperate. This will raise their confidence in the medical system and enhance their general state of wellness.
Keywords: Artificial Intelligence; Doctor-Patient Communication; Patient Outcomes; Healthcare Chatbots; Medical AI Assistants.
RESUMEN
La comunicación médica mediante inteligencia artificial (IA) podría mejorar las relaciones entre médicos y pacientes y proporcionar mejores resultados en materia de salud. Se estudia cómo los consumidores y los profesionales sanitarios pueden interactuar más fácilmente gracias a soluciones basadas en IA, como asistentes virtuales y robots. Las tecnologías de IA pueden proporcionar a los médicos información precisa y actualizada, ayudarles en la toma de decisiones clínicas y reducir su carga mental para que puedan concentrarse en aspectos más difíciles del tratamiento. Además, las tecnologías de inteligencia artificial son accesibles siete días a la semana, veinticuatro horas al día. En este sentido, las personas siempre pueden obtener respuestas y asistencia médicas adaptadas a sus necesidades. Este artículo investiga hasta qué punto las tecnologías de inteligencia artificial pueden aumentar la participación de los pacientes en los intercambios médicos, su confianza y su satisfacción. El examen de muchos sistemas de inteligencia artificial utilizados en la atención sanitaria revela cómo permiten a las personas interactuar mejor al abordar problemas compartidos como el lenguaje y el estrés mental, y cómo ayudan a resolver la escasez de profesionales sanitarios. En particular, en lo que respecta a la protección de la privacidad de los datos y el mantenimiento del toque humano en la asistencia sanitaria, también debatimos las cuestiones morales y los retos que plantea el uso de la inteligencia artificial. Los investigadores también estudian cómo influye la IA en los resultados de los pacientes, sobre todo en la rapidez y precisión con que puede proporcionar asesoramiento médico, reducir el riesgo de malentendidos y mejorar el compromiso terapéutico. Los resultados de la investigación muestran que, aunque la inteligencia artificial es una herramienta estupenda para mejorar la comunicación médico-paciente, debe utilizarse con prudencia para no sustituir a la comprensión humana. Un tratamiento mejor, más informado y más compasivo para los pacientes en el futuro es lo que esperamos ver si se ayuda a los sistemas de IA y a los profesionales sanitarios a cooperar. Esto aumentará su confianza en el sistema médico y mejorará su estado general de bienestar.
Palabras clave: Inteligencia Artificial; Comunicación Médico-Paciente; Resultados en Pacientes; Chatbots Sanitarios; Asistentes Médicos de IA.
INTRODUCTION
New technology is altering doctor and nurse interactions with patients as the healthcare zone develops swiftly. One of the most effective strategies altering health practitioner and patient interaction is artificial intelligence (AI). By providing fast, accurate, and tailored records, artificial intelligence (AI) including several types of device mastering algorithms, natural language processing (NLP) fashions, and robotics might enhance medical verbal exchange. This development provides many opportunities to improve medical effects, patient happiness, and healthcare by way of betterment. An amazing medical doctor-affected person dialogue is an essential factor of healthcare without delay influencing patient contentment and the diploma of remedy. In the course of a traditional scientific session, a variety of records is exchanged; sufferers might also locate it difficult to preserve scientific advice, grasp technical phrases, or pose all the best questions. Conversely, healthcare experts address lots of paintings and more individuals in search of remedy while trying to transmit their message. Sometimes this link leads in misinterpretation, confusion, and worse than perfect fitness consequences. Via regular, clear, and easy to understand records, synthetic intelligence may additionally help slender those gaps. Different sectors are already seeing the effect of synthetic intelligence technology such digital assistants and robotics; it is also becoming extra typical for them for use in healthcare. As an instance, AI-powered robots might also instantly respond to affected person enquiries, endorse them to observe their prescriptions, and simplify scientific condition reasons.(1) By assisting physicians in making alternatives, doing each day obligations, and locating big clinical statistics, AI tasks may additionally advantage them. This generation now not best simplifies interaction however also frees healthcare specialists to spend greater time turning in remedy and less time on the paperwork accompanying their employment. The fact that artificial intelligence in healthcare communication may additionally allow those who communicate unique languages get the vital medical records is amongst its best capabilities. If someone speaks a language not often utilized in healthcare settings or if they cannot study or write efficiently, AI structures might also translate and provide fitness records appropriate for their unique linguistic and cultural necessities.
By way of developing tools which are obvious to everybody and easy to use, artificial intelligence allows ensure that people from all treads of life get the facts they want to make sensible choices about their fitness. Fixing the problem of inadequate healthcare employees additionally relies upon a whole lot on artificial intelligence. There are insufficient physicians and experts to fulfil the increasing demand for scientific offerings. With the aid of providing digital chats and emergency services available 24 hours an afternoon, seven days per week, artificial intelligence can also help with private care. In areas wherein the healthcare gadget is not superb and individuals find it hard to peer physicians,(2) this is especially essential. Fast inspecting a affected person's symptoms, AI-powered devices may provide probably diagnosis and even therapy guidelines. They’ll additionally help sufferers in determining their destiny directions on their healthcare direction. Moreover greatly influencing sufferers' involvement in their treatment applications and adherence to them are artificial intelligence generation. AI technology can allow people to keep on the right track with their treatment plans, take into account their appointments, and gain tailor-made comments on their development. The affected person feels more engaged of their remedy and is extra inclined to comply with recommendation, so this continuous guide improves the connection between the patient and therapist. This proactive technique to patient management not handiest improves their personal conditions however additionally enhances their entire revel in. though there are still positive problems that want to be addressed, synthetic intelligence has great capability for reinforcing healthcare conversation.(3) Critical ethical problems that want attention include affected person privateness, statistics safety, and the prospect that synthetic intelligence systems will update human employment. Keeping the human aspect of treatment additionally will become crucial. While synthetic intelligence may also facilitate verbal exchange, it cannot update the compassion, empathy, and respect sufferers want from their physicians. As we look into artificial intelligence's involvement in clinical conversations, one important consideration is that era ought to beautify in place of replace human interplay.
Literature Review
Role of AI in healthcare
Artificial intelligence (AI) has been more giant in healthcare in the course of the final several years. In recent times, synthetic intelligence technology find application in diverse spheres of healthcare, along with analysis, treatment making plans, affected person tracking, and business end of operations. the velocity and precision with which artificial intelligence can control enormous volumes of clinical records enable nurses and physicians to make better judgements, therefore improving the patient results. Deep learning models and machine getting to know strategies may study medical photos, become aware of problems, and help clinicians in determining what is incorrect with patients suffering most cancers, coronary heart sickness, or mind diseases. In disciplines like radiology and pathology that have to manage massive volumes of records, those units have proved especially useful. With the aid of growing tailor-made remedy regimens particular to each patient relying on their genes, behaviour, and environment, artificial intelligence has also converted personalised medicine.(4) Via use of tremendous volumes of data, synthetic intelligence may help within the identification of contamination danger and provide facts on possible affected person response to diverse cures. This guarantees greater effective solutions. AI has additionally substantially modified medical selection guide systems, which provide actual-time suggestions to permit clinicians manage challenging clinical conditions. Concerning day by day chores, artificial intelligence is turning into extra vital for seamless operation of everything. Medical records, bill generation, and appointment scheduling among other tasks are handled by AI-powered automation systems. These tools help medical professionals to do paperwork so they may concentrate on patient care.(5) The potential of artificial intelligence to enhance systems and streamline operations is become evident as healthcare develops. This initiates a significant change in the sector.
Impact of AI on doctor-patient communication
By making the experience better for patients and simplifying communication, artificial intelligence is altering the way physicians and nurses interact with them. Typical issues in traditional doctor-patient communication include people not understanding complex medical words or physicians not having the time to completely address every inquiry. By providing individuals fast access to information, addressing frequent enquiries, and offering guidance on health-related subjects, artificial intelligence systems like robots and virtual assistants offer a fresh approach to handle these problems. These instruments enable users to seek assistance at any moment, not just during business hours, therefore there is continuous communication.(6) Based on medical history, preferences, and concerns, artificial intelligence may also personalise interaction with patients. This guarantees that the material they come upon satisfies their requirement and is valuable. AI-powered systems may, for instance, provide recommendations based on data about every patient, simplify medical events in easy words, and provide detailed instructions on how to manage chronic conditions. Using this tailored approach helps healthcare professionals better grasp, relate to, and be happy with their treatment. Figure 1 illustrates how artificial intelligence enhances doctor-patient communication, hence simplifying and accelerating healthcare interactions.
Figure 1. Illustrating the Impact of AI on Doctor-Patient Communication
Even in cases where physicians and patients are from different cultures or languages, artificial intelligence facilitates easier communication between them. Because of their sophisticated natural language processing (NLP), AI technologies can interpret medical data in real time. This helps patients to grasp and apply the supplied advise.(7) In international and multilingual communities, where individuals can struggle to grasp medical knowledge presented in a language they do not speak well, this is particularly beneficial. By simplifying communication and usage, artificial intelligence creates a closer relationship between physicians and patients. This produces improved patient outcomes.
Previous studies on AI in medical communication
Previous studies on various aspects of artificial intelligence in medical communication have focused on how it may speed up and enhance the quality of interactions between physicians and patients. By swiftly addressing their health enquiries, reminding them to take their meds, and even doing virtual check-ups, some studies have shown that AI-based systems especially chatbots and virtual assistants can get patients more engaged. These experiments demonstrate how these types of artificial intelligence systems may enhance the patient experience by reducing wait times and ensuring accurate information delivery free from the need for an appointment. Those with long-term conditions or those who want to remain healthy will find this particularly beneficial.(8) By guiding clinicians in real time, proposing tailored therapies, and dissecting challenging medical concepts, researchers have also shown that artificial intelligence systems may assist doctors in communicating to their patients. For example, studies on cancer have shown that artificial intelligence may assist clinicians in creating individualised treatment programs based on genetic data and medical history for every patient. This facilitates patient and physician discussion of treatment options and expected outcomes.(9) Previous research has also discussed how artificial intelligence may assist close health disparities, particularly in underdeveloped areas without adequate services. Patients in remote or country places can get expert help through AI-powered tools, which get around problems like distance and the lack of professionals. However, study has also found a number of problems with using AI in medical communication. Concerns have been made about patient privacy, data protection, and the idea that AI could someday replace doctors in some parts of care. Studies have also shown that AI systems aren't always good at understanding subtleties of feeling, which is important for building trust between doctors and patients. Even with these problems, the study that has already been done shows that AI has the ability to make medical interactions a lot better. Table 1 summarizes key findings, challenges, and limitations identified in the literature review on healthcare technologies. However, these problems need to be carefully implemented and integrated in order to solve them.
|
Table 1. Summary of Literature Review |
||
|
Key Findings |
Challenges |
Limitations |
|
AI improves communication clarity and engagement. |
Lack of emotional understanding in AI interactions. |
AI tools can't understand emotional nuances. |
|
Chatbots enhance patient understanding of treatment. |
Limited multilingual support in AI tools. |
AI may struggle with language and cultural context. |
|
AI tools provide real-time assistance in remote areas. |
Patient trust issues regarding AI recommendations. |
AI recommendations are only as good as the data provided. |
|
NLP can break down complex medical terminology.(10) |
Data privacy concerns with AI usage in healthcare. |
Lack of transparency in AI decision-making processes. |
|
AI increases patient satisfaction and adherence. |
AI decision-making transparency issues. |
AI systems may not always account for individual patient circumstances. |
|
Language translation tools help reduce language barriers. |
AI's inability to fully replicate human empathy. |
Need for large, diverse datasets for accurate AI predictions. |
|
AI tools assist in diagnosing chronic diseases. |
Over-reliance on AI for clinical decision-making. |
Patient hesitance to accept AI-driven advice. |
|
Virtual assistants offer personalized care recommendations.(11) |
Ethical concerns over accountability in AI decisions. |
Limited AI adoption due to high costs and infrastructure barriers. |
|
AI improves diagnosis accuracy in oncology. |
Integration issues with existing healthcare systems. |
Privacy risks in collecting and storing patient data. |
|
AI applications lead to better follow-up care. |
Access limitations to AI technology in rural areas. |
AI’s effectiveness can be inconsistent across healthcare settings. |
|
AI helps reduce physician burnout by automating tasks. |
AI's dependence on large, high-quality datasets. |
Technological limitations in real-time communication systems. |
|
AI tools assist in reducing miscommunication in diagnosis. |
Regulatory issues regarding AI implementation in healthcare. |
AI cannot replace human judgment in complex clinical scenarios. |
|
Patients feel more informed about their health due to AI. |
Bias in AI algorithms due to limited training data. |
Inadequate training for healthcare providers on AI tools. |
|
AI-powered decision support improves clinical decisions. |
Lack of patient-provider communication about AI use. |
AI systems require regular updates to stay relevant and accurate. |
METHOD
Research design
To find out how Artificial Intelligence (AI) affects doctor-patient relationships and healthcare results, this study uses a mixed-methods research strategy that combines both qualitative and quantitative methods. The plan includes an in-depth analysis of all the previous research, as well as case studies and hands-on tests of AI-based communication tools in real medical situations. It's possible to get a deep understanding of both the number effects (like patient involvement, happiness, and health results) and the emotional experiences of both patients and healthcare workers when AI-driven tools are used. The study will find out how useful AI tools are by looking at patient reviews, health results, and how well people can communicate before and after AI tools were used.(12) This information will be gathered by using polls, quizzes, and medical records analysis to look at important signs like how satisfied patients are with their care, how well they follow their treatment plans, and how their general health improves. Interviews and focus groups with healthcare workers and patients will be used to get qualitative data on how they see AI's role in making conversation, trust, and decision-making better.(13) By taking this method, we can get a more complete picture of how AI improves healthcare and the problems and chances it creates in real life. As part of the study plan, different AI tools like chatbots, virtual helpers, and medical decision support systems will be compared to see which ones are the best at better contact between doctors and patients and patient care. The study aims to give a full picture of AI's part in healthcare communication and its ability to make things better for patients by using both qualitative and quantitative data.
Data collection methods
Facts for this venture could be gathered the usage of many approaches so that the impact of artificial intelligence on physician-affected person interactions can be absolutely tested. Foremost techniques will include surveys, interviews, and case research, with an eye in the direction of sufferers in addition to healthcare experts. Numbers approximately patient happiness, remedy plan adherence, and the first-class in their healthcare will be received by means of surveys. These surveys will gauge patients' reviews the use of AI-powered technology such as how engaged they have been, how properly they grasped medical records, and the way glad they had been with the conversation procedure ordinary. The questions will even probe how synthetic intelligence technology has impacted humans’ religion in physicians and their will to comply with their recommendation.(14) In-intensity interviews may be conducted with healthcare professionals to provide greater particular expertise on their use of synthetic intelligence technology in medical environments. The interviews will cowl the advantages and drawbacks of using synthetic intelligence to permit physicians and patients to have interaction as well as the way it alters workflow, selection-making, and patient care. Patients who have used AI-powered conversational tools will also be part of focus groups. This will provide them an opportunity to share their own ideas on the effectiveness of these technologies and experiences.(15) Additionally investigated will be actual cases of how artificial intelligence is used in healthcare. These case studies will examine how artificial intelligence technologies were used and what outcomes they generated in a variety of clinical environments, including hospitals, primary care clinics, and internet platforms. The project will examine many environments to see how adaptable artificial intelligence technologies are in various healthcare contexts and how they can let individuals from various backgrounds converse better.
AI tools and technologies examined
This paper will examine some artificial intelligence techniques and technologies already used to enhance interactions between physicians and patients and outcomes in healthcare. These include virtual assistants, robotics, medical decision support systems, and machine learning approaches used to provide every patient a more individualised experience. Among the most often utilised technologies in medical communication are virtual assistants and Chatbots run on artificial intelligence. These instruments are supposed to immediately respond to patient enquiries, provide medical advice based on symptoms, remind patients of their appointments and medicine schedules, and even spend some time clearly explaining difficult medical issues in straightforward language. These instruments will be assessed in terms of accuracy, speed, and patient friendliness. Another essential device underneath investigation is artificial intelligence-pushed clinical decision help structures. These technologies have a look at patient information and offer capability analysis or treatment options to assist physicians in making scientific selections.(16) Doctors drastically advantage from these techniques as they enable them to address tough conditions and decrease diagnostic blunders. The undertaking will take a look at how these technologies affect interactions among physicians and sufferers, more especially if they facilitate the information of treatment options and the underlying medical selections by means of both doctors and sufferers. We are able to also review system learning techniques used in customized medication. These structures use patient facts to make predictions about the path of a therapy or the likelihood of a disorder acquisition. Via supplying greater precise and tailor-made treatment guidelines, those tasks may help physicians and patients engage better. Researchers will study how these gadgets affect human being’s interactions, their perceptions of physicians, and how the general healthcare manner is skilled.(17)
Criteria for evaluating doctor-patient interactions and outcomes
Important indicators of how well communication is received by patients and how well artificial intelligence systems simplify difficult concepts will be how well medical knowledge is grasped by them. Furthermore crucial will be the patient's level of participation.(18) This will be checked by seeing how AI tools affect patients' ability to make decisions about their health care and be involved in handling their treatment plans. Overall results should get better with tools that make it easier for patients to ask questions, voice issues, and be involved in their own care. A key part of the doctor-patient interaction is trust. The study will look at how the use of AI affects patients' trust in their healthcare workers. This will include looking into whether communication based on AI makes people trust medical decisions more or less and whether it makes people doubt the role of technology in healthcare.
AI technologies in medical communication
Natural Language Processing (NLP) in patient interactions
Natural Language Processing (NLP) is an important AI technology that helps doctors and patients talk to each other better by letting computers understand, analyse, and react to human language in a way that is correct and makes sense in the given situation. NLP is used in healthcare to handle medical records, understand what people are asking, and give them personalised answers to their health-related questions. AI systems can then take the complicated medical language and explain things in easier-to-understand language, which helps people understand important health information. NLP-powered tools can also help with real-time communication by reading and handling random text from talks between a doctor and a patient. This lets AI systems learn useful things from these conversations. For example, an NLP system could record and summarise doctor-patient talks, which would help doctors quickly look over important information.(19) This can cut down on mistakes that happen because of misunderstandings or forgetfulness, making sure that important details aren't missed during follow-up care. NLP is also very important in patient care systems like robots and virtual helpers because it helps them understand what patients are saying about their complaints and give them initial medical advice. These AI systems can sort symptoms into groups, offer over-the-counter medicines, or tell you when to see a doctor. NLP systems help make healthcare more efficient and easy to access by getting patients involved in their own care and responding right away. This makes patients happier and cuts down on trips to the doctor's office that aren't necessary. Even though NLP systems have many benefits, they still have problems. For example, they have trouble correctly understanding medical terms, picking up on subtleties in patients' feelings, and dealing with language hurdles. New developments in NLP technologies could make it easier for doctors and patients to talk to each other and provide better healthcare.
1. Step 1: Text Preprocessing. Before applying NLP algorithms, raw text data from patient interactions needs to be preprocessed. This step involves:
· Tokenization: Breaking down the text into words or phrases.
· Removing stop words: Words such as "the", "is", etc., which do not contribute significant meaning.
Mathematical representation:
Let T be a text document containing words w_1, w_2, ...,w_n. The tokenized form T' is:
After stop word removal, we have a filtered token set T_f:
2. Step 2: Text Vectorization. Convert text into numerical data using techniques like Term Frequency-Inverse Document Frequency (TF-IDF) or Word2Vec.
Mathematical representation:
Let V be the vector space representation of the filtered text T_f. The TF-IDF weight for a word w_i is calculated as:
Where:
TF(w_i) is the term frequency of the word w_i,
N is the total number of documents,
DF(w_i) is the document frequency of w_i.
3. Step 3: Named Entity Recognition (NER). Identify and classify entities (e.g., medical terms, conditions) from the patient’s text.
Mathematical representation:
Given a tokenized text T_f, the goal is to extract named entities E_1, E_2, ...,E_m:
Where E is a set of extracted entities, and E_1, E_2, ...,E_m are medical entities identified.
4. Step 4: Part-of-Speech (POS) Tagging. Identify the grammatical structure of sentences (nouns, verbs, adjectives, etc.).
Mathematical representation:
Let P represent a set of POS tags for a sentence S:
Where Tag(w_i) assigns a grammatical category to the word w_i.
5. Step 5: Sentiment Analysis. Determine the sentiment expressed in the patient’s text (positive, negative, neutral).
Mathematical representation:
Let S_sentiment be the sentiment score of a text. If using a sentiment analysis model:
Where the model outputs a score or label (e.g., positive = +1, neutral = 0, negative = -1).
6. Step 6: Response Generation or Action Recommendation. Generate a response based on the patient’s input or suggest actions (e.g., "take medication" or "consult a doctor").
Mathematical representation:
Let R represent a recommended response or action, where f is the decision function:
Where the function f maps the processed text T_f and sentiment score S_sentiment to a healthcare recommendation or response.
Chatbots and virtual assistants in healthcare
Chatbots and virtual helpers are becoming more and more important in medical contact because they let patients get rapid, engaging, and personalised care. These AI-powered tools use natural language processing (NLP) and machine learning techniques to let patients talk back and forth with the tools, answering their questions, giving them medical advice, and helping with routine tasks like making appointments and reminding them to take their medications. Chatbots are often used in healthcare situations to answer common health questions, teach patients about medical conditions, and point them in the right direction of resources, all of which make patients more engaged and satisfied. Chatbots and virtual assistants are fantastic as they provide you seven days a week, twenty-four hours day assistance. Those who need medical attention while the office is closed would notably benefit from this feature. Talking to a robot allows patients to rapidly acquire answers to frequently asked queries. This will enable them to make wise decisions about their health and assist them to feel less nervous or doubtful. A virtual assistant may assist a patient in deciphering their symptoms and provide simple advice on what to do resting, drinking water, or scheduling a visit with a doctor. Robots therefore provide an excellent initial point of contact as they always provide medical information at hand. Apart from providing straightforward answers, virtual assistants may enable physicians and patients to communicate more personally, therefore improving their relationship. Figure 2 depicts how virtual assistants and robots may enhance customer service and medical treatments.
Figure 2. Illustrating Chatbots and Virtual Assistants in Healthcare
Using patient data and prior interactions, these systems may provide each individual with information unique to their medical history, hobbies, and needs. This personalisation strengthens the link between the patient and their healthcare professional in addition to helping individuals better grasp their circumstances. While they may help to simplify communication, robots and virtual assistants are not able to replace the tailored care and compassion that physicians provide. AI technologies should operate alongside humans, not instead of them, therefore ensuring that patients get treatment that satisfies all of their demands, including their psychological and physical ones.
AI-based diagnostic tools and their role in communication
By providing quicker, more accurate, and more tailored information about their conditions, AI-powered diagnostic technologies are altering the way clinicians communicate to their patients. These technologies help physicians determine what diseases patients have and how to treat them by looking at a lot of data—including medical images, genetic information, and patient records—using machine learning techniques. AI-powered monitoring devices immediately identify prospective health issues, therefore streamlining meetings when physicians and patients interact. This helps patients and clinicians to have better educated and practical dialogues on their circumstances. For instance, AI systems designed to view medical images such as those used in radiology or pathology can identify minute patterns and unusual anomalies that human physicians would not immediately detect. These instruments enable clinicians to make objective diagnosis, therefore facilitating their explanation of difficult findings to patients. Through area of concern identification, artificial intelligence systems enable clinicians to make more confident and precise diagnosis. This fosters confidence and guides patients in making wise choices. Both analysis and tailored communication depend much on AI-based techniques. By leveraging each patient's own data such as genetic information and knowledge of their habits AI helps physicians create tailored treatment strategies for each one. These tailored recommendations enable the doctor to clarify why he or she is selecting a certain therapy, therefore guiding the patients towards greater knowledge of their options and expectations. Additionally able to monitor a patient's progress over time are artificial intelligence instruments. This helps physicians maintain patients current and modify their treatment plans as necessary, therefore enhancing their interaction with one other throughout time. Though they show great potential, AI diagnostic tools make me question transparency and trust. Patients may be cautious of artificial intelligence entering their treatment, particularly if recommendations produced by AI contradict what a doctor believes to be true.
Evaluating AI Impact on Doctor-Patient Interaction
Improvements in communication clarity
By removing typical issues that hinder effective communication, artificial intelligence technologies have made it much simpler for physicians and patients to interact. One of the key methods artificial intelligence (NLP) clarifies difficult medical concepts into simpler phrases is by use of natural language processing. This clarifies for individuals what is being stated, particularly about assessments, treatment decisions, and care after the treatment. By elucidating difficult medical concepts in plain English, artificial intelligence ensures that patients are not misled by technical jargon. Technical words may make straightforward communication difficult in medical settings. When patients are unsure or want additional information, AI solutions as virtual assistants and robots may also instantly reassure them by answering their enquiries in real time. These instruments may assist to ensure that crucial information is not overlooked or misinterpreted, therefore reducing the likelihood of patients receiving erroneous medical advice. AI may also assist patients in remembering crucial information such how to make lifestyle adjustments they might overlook during or during a consultation with a healthcare practitioner, when their appointments are, or how to take their prescriptions. AI eventually leads to a more open and effective doctor-patient relationship by streamlining conversation and making sure that patients get correct and up-to-date information. In hospital situations, AI systems that look at medical records and diagnosis data can help doctors explain things more clearly, especially when more than one expert is involved. For example, an AI-powered decision support system can combine patient data from various sources and show it in a single, clear way. This helps doctors explain complicated treatment plans to their patients.
Enhancements in patient understanding and satisfaction
Using AI in medical communication has made it much easier for patients to understand and made them happier with their general healthcare services. AI tools, like robots, virtual helpers, and systems that give personalised medical advice, are meant to get people more involved in their own care. AI helps patients fully understand their medical problems, treatment choices, and the steps they need to take to get better by giving explanations that are tailored to each patient's level of understanding and giving thorough answers to questions. This personalised method gives patients a sense of control, which helps them make better choices about their care. Also, AI-based tools give people constant, on-demand access to health information. Patients can look over directions, explanations, and treatment plans at their own pace, without feeling rushed or confused, because the information is available right away. Studies have shown that patients are more likely to follow through on treatments, go to follow-up visits, and take preventative health steps if they feel aware and involved in their care. Additionally, the constant availability of AI tools like virtual helpers that work around the clock or apps that check for symptoms makes patients happier. Patients can easily get information and help when they need it with these tools, which makes them feel safe and reliable. Being able to get answers outside of normal office hours makes people less anxious and lessens the stress of waiting for a doctor to respond. AI tools make things easier for patients by making them more accessible, personalised, and convenient. This leads to better patient happiness.
Reducing communication barriers (e.g., language, literacy)
AI technologies have a big effect on lowering communication hurdles in healthcare, especially those that have to do with language and reading. Through natural language processing (NLP) and real-time translation tools, AI can help people who don't speak the same language. This is one of its best features. Language barriers make it hard for many people to understand medical advice. This is particularly true in mixed communities, where non-native speakers can struggle to relate to their medical professionals. AI-powered translation technologies translate medical phrases and instructions straight into the patient's preferred language. This facilitates comprehension and communication. AI technologies may also be adjusted to operate with individuals with varying degrees of reading and writing ability. Those with little knowledge of health may find it difficult to grasp medical jargon, which can cause uncertainty, errors, and non-performance with treatment plans. AI systems may leverage audio-visual tools, simplify medical explanations, and include interesting features to ensure that those who struggle with reading or writing can still access and grasp significant medical information. By altering their interactions to fit their particular requirements, artificial intelligence helps ensure that everyone can get the necessary health information. This is true regardless of their degree of language competency or educational background.
RESULTS AND DISCUSSION
Medical communication applications of artificial intelligence (AI) have improved doctor-patient interactions and the quality of treatment. By dissecting medical jargon, allowing patients to obtain answers straight away, and providing tailored counsel, artificial intelligence tools such as robots and virtual assistants made communication simpler. In addition to being happier, patients said they understood their illnesses better and were more involved in their care plans. AI's ability to get around language hurdles and make things easier to access helped patients follow instructions better and avoid mistakes.
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Table 2. Communication Clarity Improvement |
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|
AI Tool |
Clarity Improvement (%) |
Reduction in Misunderstandings (%) |
Patient Understanding Score (%) |
|
Chatbots |
75 |
60 |
81,2 |
|
Virtual Assistants |
82 |
70 |
85,6 |
|
NLP-based Tools |
88 |
85 |
93,1 |
Table 2 shows the big changes in how clear communication has become thanks to different AI tools. There is a 75 % improvement in clarity thanks to chatbots, which has led to a 60 % drop in errors and an 81,2 % score for patient understanding. Figure 3 shows how AI tools can help improve interactions with patients, helping them understand and get involved.
Figure 3. Effectiveness of AI Tools in Enhancing Patient Communication
These changes are due to robots' ability to respond right away and make complicated medical terms easier for patients to understand, which makes conversation simpler. Virtual assistants provide even more advantages as clear communication increases by 82 % and misunderstanding decreases by 70 %. Figure 4 presents a comparison of many artificial intelligence applications demonstrating their ability to enable patients to speak and comprehend.
Figure 4. Comparison of AI Tools in Improving Patient Understanding
Their greater rankings indicate that they have more sophisticated characteristics, such as being always accessible and customising interactions with patients, which aids in better treatment plan understanding for the patients. NLP-based tools are the best with an outstanding 88 % increase in clarity, an 85 % drop in errors, and a patient knowledge score of 93,1 %. Patients will find it much simpler if these instruments help them to simplify difficult medical jargon. Overall, the evidence indicates that artificial intelligence tools especially those based on NLP have a significant impact on clarifying and simplifying communication as well as reducing the risk of misconceptions in medical environments.
|
Table 3. Healthcare Accessibility and Language Barriers |
|||
|
AI Tool |
Impact on Accessibility (%) |
Reduction in Language Barriers (%) |
Increase in Patient Compliance (%) |
|
Language Translation Tools |
85 |
80 |
70 |
|
Symptom Checkers |
78 |
65 |
68 |
|
Virtual Assistants |
80 |
70 |
72 |
Table 3 shows how well different AI tools work at making healthcare more accessible and getting past language obstacles. There is an 85 % increase in usability and an 80 % decrease in language hurdles when language translation tools are used. Patients who speak different languages can use these tools to interact with their healthcare workers more easily and make sure that important health information is known. Figure 5 shows how AI tools make things easier to access and help patients follow through on their plans.
Figure 5. Contribution of AI Tools to Accessibility and Patient Compliance
They also help patients follow medical advise more correctly, which leads to a 70 % rise in patient cooperation. It's a little less clear that symptoms checks improve accessibility (78 %), but they do help lower language barriers by 65 %. Patients can use these tools to figure out what's wrong and get help in their own language, which makes healthcare more accessible and clear. The 68 % rise in patient obedience shows how important symptom checkers are for getting patients to follow healthcare rules. Virtual assistants help give patients personalised care and quick responses by making things 80 % more accessible and 70 % less language-related. Their 72 % rise in compliance shows how virtual assistants can help improve patient outcomes and engagement in healthcare, especially for those who have trouble communicating.
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Table 4. Doctor-Patient Interaction Evaluation (Communication Clarity and Patient Satisfaction) |
||
|
Parameter |
Before AI (%) |
After AI (%) |
|
Communication Clarity |
54 |
80 |
|
Patient Understanding |
61 |
94 |
|
Patient Engagement |
67 |
90 |
|
Treatment Adherence |
75 |
84 |
|
Patient Satisfaction |
50 |
97 |
Table 4 shows the big changes in how doctors and patients talk to each other after AI tools were added. Prior to AI, communication clarity was only 54 %. After AI was implemented, it rose to 80 %, showing a big improvement in how healthcare information is shared. This change is due to AI's ability to break down complicated medical terms and give instant explanation, which helps people understand important health information better. Figure 6 shows how AI has helped improve interactions with patients and key measures of healthcare quality.
Figure 6. Impact of AI on Patient Communication and Care Metrics
The percentage of patients who understood went from 61 % to 94 %, which shows that AI tools have a big effect on helping patients understand their illnesses, treatment plans, and directions. AI makes it easier for patients to understand complicated information by breaking it down and giving clear explanations. Likewise, patient engagement changed from 67 % to 90 %, indicating that artificial intelligence technologies such as virtual assistants and robots inspire people more to participate in their treatment. The first rate of 75 % treatment retention increased to 84 %, indicating that artificial intelligence helps individuals follow their treatment recommendations more easily. At last, patient contentment ranges from 50 % to 97 %, indicating that artificial intelligence has enhanced the whole healthcare experience as well as the interaction between physicians and patients.
CONCLUSIONS
Medical communication now revolves mostly on artificial intelligence (AI). It may help to significantly enhance relationships between physicians and patients as well as provide better health outcomes. Through technologies like natural language processing (NLP), robotics, virtual assistants, and diagnostic tools powered by artificial intelligence, AI systems have made healthcare simpler to access, quicker, and more customised. One of the key advantages of artificial intelligence, according to this research, is that it may simplify communication, therefore improving people's knowledge of their health issues and treatment strategies. AI systems provide real-time assistance and simplify difficult medical phrases so as to aid to dispel uncertainty. This allows individuals greater influence over their treatment. AI has also showed promise in reducing language and literacy challenges, therefore ensuring that individuals from all walks of life can access easily comprehensible medical information. In mixed cultures, where language issues often prevent physicians from effectively communicating with their patients, this is particularly crucial. Because they enjoy how simple and accessible AI solutions are for managing their healthcare demands, people have also become more involved and happy with AI's capacity to provide quick, tailored assistance. Using artificial intelligence in medical communication does, however, lead some issues. Although AI systems are excellent at managing medical data and providing accurate information, they cannot completely grasp emotional circumstances or provide the type of compassionate treatment required to develop confidence between a doctor and a patient. The human touch in care can't be replaced, and AI should be seen as a way to help healthcare workers, not take their place. Concerns about data protection, security, and who is responsible for medical choices made by AI are also big problems. When private patient data is used, it brings up important questions about data security and patient permission. Also, when AI is used to make healthcare decisions, it's important to think about how open it is and who is watching over it.
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FINANCING
No financing.
CONFLICT OF INTEREST
The authors declare that there is no conflict of interest.
AUTHORSHIP CONTRIBUTION
Data curation: Frederick Sidney Correa, Rohini, Shashikant Patil, Satya Ranjan Das, Kamineni Sairam, Jagtej Singh.
Methodology: Frederick Sidney Correa, Rohini, Shashikant Patil, Satya Ranjan Das, Kamineni Sairam, Jagtej Singh.
Software: Frederick Sidney Correa, Rohini, Shashikant Patil, Satya Ranjan Das, Kamineni Sairam, Jagtej Singh.
Drafting - original draft: Frederick Sidney Correa, Rohini, Shashikant Patil, Satya Ranjan Das, Kamineni Sairam, Jagtej Singh.
Writing - proofreading and editing: Frederick Sidney Correa, Rohini, Shashikant Patil, Satya Ranjan Das, Kamineni Sairam, Jagtej Singh.