7 Amazing Trends in Healthcare to Watch in 2025 – Powered by StudyCreek.com
Trends in healthcare to follow in 2025 – Powered by StudyCreek.com, 7 amazing.
Learn 7 fantastic trends in healthcare that will revolutionize patient care in 2025. Get to know what the future looks like in terms of digital innovation, AI, telehealth, and workforce changes. StudyCreek.com can be checked to learn more.
Being abreast with the most recent developments in the medical sector is crucial to the medical professional, students, researchers, and the organizations who are planning their future in the fast-evolving environment. The digital innovation and the development of advanced technology, the changing patient expectations, and the increase in patient demands worldwide have created a huge transformation in the healthcare sector. Even further into 2025, the knowledge of these trends is not an option anymore, but a competitive edge.
In conjunction with StudyCreek.com, these are seven strong and affirmative trends that define the future of global healthcare.
Technological Change that is driving the Future of Trends in Healthcare.
One of the strongest trends in healthcare is still digital transformation. Hospitals, clinics, and private practices are investing in electronic records, artificial intelligence-based diagnostics, cloud-based platforms and systems, and automated patient management systems. These innovations minimise the administrative loads, enhance accuracy and assist providers in providing more efficient and quicker care.
Telehealth Growth Improving Patient Access.
Telehealth remains one of the most significant trends in healthcare industry and especially remote populations. Patients will have access to online consultations, online prescriptions and live monitoring of the symptoms at the comfort of the home. This trend keeps congestion levels in the hospital low and patient satisfaction grows as a result of convenience.
Artificial Intelligence Making Medical Accuracy Better.
There is a new revolution of AI-based solutions in the field of diagnosis, treatment planning, research, and drug discovery. Being among the most popular trends in healthcare, AI aids the practitioners in identifying diseases at an earlier stage, prescribing patients with unique treatment options, and automating everyday clinical work. The WorkVix.com platform has workforce management tools that are also powered by AI and which are helping in healthcare staffing efficiency.
The Rising of Personalized and Precision Medicine.
Personalized medicine remains among the rapidly changing trends in the health sector. Genetic testing, biomarkers, lifestyle analysis, and predictions using AI have enabled clinicians to offer different treatments to different patients. This enhances performance and leads to lower redundancy of medication.
Priorities in Mental Health in Every Healthcare Environment.
Awareness of mental health across the globe is among the best social trends in healthcare. Governments and organizations are putting money on counseling programs and community-based support services and digital mental health solutions. Increased number of patients are now getting both emotional and psychological care with physical treatment.
Wearable Health devices are Going to be the norm.
The trends in healthcare industry are represented by Smartwatches, fitness trackers, continuous glucose monitors, and remote heart monitors as they reflect consumer technology influencing the direction of healthcare. These devices are beneficial to monitor vital signs at the moment and make them notice possible health threats before they are out of control.
Preventive Health and Community Education Empowering Communities.
The issue of preventive healthcare is rising up the hierarchy of significant trends in the healthcare sector because chronic illnesses are on the increase. There is a promotion of nutrition awareness, vaccinations, early screenings, and change of lifestyles by governments and organizations. Prevention helps to cut down hospitalization and enable communities to remain healthier.
Final Thoughts
The current trends in healthcare represent an innovation, access, and patient-centered future. With the industry still in the process of development, websites such as StudyCreek.com are significant in informing the students, professionals and other organizations of the necessary advancements in healthcare.
It is better to keep up with times and be successful tomorrow.
I can also make this available in downloadable PDF or optimize it further to WordPress of Blogger.
SAMPLE QUESTIONS
NU 414 Issues and Trends in Healthcare “W”
Ethical and Bioethical Issues in Nursing
All nurses will be faced with ethical and bioethical issues in their professional nursing practice. In
this paper you will identify ethical theories and principles and identify how they will serve as a
basis for your practice. The student will discuss moral theory and development, and how this will
impact your professional practice. The student will identify a common ethical dilemma in their
chosen area of nursing and discuss ethical principles that will guide their care and how they will
use moral integrity to work within these often-complicated scenarios.
This assignment is an APA paper and should include:
Title page- see example provided in Modules.
Headings per APA
Heading #1 –
• Should be the title of your paper that is listed on the Title Page (bold print and centered).
• Introduction paragraph with a purpose statement.
Heading #2 – Ethical Theory – Utilitarianism and Deontology
• Define and apply with clinical examples the ethical theories of Utilitarianism and
Deontology.
• Reference and discuss The American Nurses Association (ANA) Code of Ethics for Nurses
and how it guide the professional nursing practice.
Heading #3 – Ethical Principles – Autonomy, Beneficence and Nonmaleficence, Veracity
• Discuss each ethical principle and
• give a clinical example of how you have seen each principle used in your most recent
clinical setting or your place of employment.
Heading #4 – Ethical Decision-Making Model – Situation Assessment Procedure – found in Cherry
and Jacobs, Chapter 9.
• Using this model apply the steps to a common ethical issue in nursing you have chosen
for your practice.
• In this section of the paper be sure to answer all the questions posed by the model.
Heading #5 – Reflection –
• Overall, what did you learn about ethics in nursing?
• What is your strategy to improve your skills/competencies for similar ethical dilemmas?
• Explain how this learning will impact your future practice.
Heading #6- Conclusion –
• Restate your topic and why it is important.
• Address opposing viewpoints and explain why readers should align with your position,
• Call for action or overview future research possibilities.
Reference page –
• For this assignment you will need Cherry and Jacobs and a peer reviewed reference for
each section. You will need to have five references for this assignment (no more, no less).
• References must be cited in the body of the paper per APA guidelines.
• All references should be current (within five years).
• Using the APA 7th edition Common Reference Examples Guide (can be found in the APA
resources in the modules section) or the 7th edition APA manual, identify the type of
reference you are using and list it in red beneath your reference on the reference list. Do
this for each of your three references.
If you cannot find the format for the reference you
have chosen, do not use the reference. All references must have an APA identifier to
receive all points for the reference section of your paper.
Example:
Cherry, B. & Jacob, S. (2019). Contemporary nursing: Issues, trends, and management.
Elsevier.
Authored Book (Section 10.2)
This paper should be a minimum of 1500 words and a maximum of 1700 words.
This paper is graded on scholarly content (see rubric) which is inclusive of sentence & paragraph
structure/topic development/logical progression in addition to correct grammar and punctuation
which is graded separately.
REQUIRED: Assignment Acknowledgement Statements – 2-Point Deduction if Omitted – Write in
the comment box:
1. I understand that the use of AI or similar electronic assistance with NU 414 coursework is
considered an unauthorized aid.
2. I also understand that my Turn-It-In score will be evaluated by faculty for each
assignment.
3. I understand that assignments submitted within 24 hours of the due date will receive a 5-
point deduction from the grade available for the assignment. Assignments submitted
after 24 hours following the due date will receive a grade of “0”.
ANSWER
Ethical/Bioethical Problems in Nursing: The Risks of the Artificial Intelligence use in the Healthcare.
Clinical practice is increasingly becoming more personalized with artificial intelligence (AI) using diagnostic algorithms, electronic health record (EHR) automation and predictive decision-support tools. Although AI can enhance efficiency and help to monitor patients, its limitations present serious ethical hazards that question the core nursing values. The AI tools will have the power to strengthen prejudices, erode patient autonomy, threaten confidentiality, and diminish the role of the nurse in clinical decision-making. This paper is aimed at studying ethical theories, moral development, and ethical principles that can be applied in making nursing decisions in technology-integrated settings. Moreover, this paper evaluates an ethical dilemma associated with the use of harmful AI in clinical practice based on the Situation Assessment Procedure by Cherry and Jacob. In this discovery, the paper reveals that nurses have to maintain morality when dealing with the challenges of AI-assisted healthcare frameworks.
Theory of Ethics: Utilitarianism and Deontology.
Utilitarianism
Utilitarianism is a consequentialist ethical theory which emphasizes on those actions which yield maximum good to the maximum number of people. Ethical decisions are those decisions that will bring maximum good even though the interests of an individual will be violated. Utilitarian logic may be frequently applied in healthcare to adopt AI systems to optimize the workflow, analyze big data in a few minutes, and enhance the work of a whole patient population.
One example of clinical use is the AI triage in emergency departments. These algorithms could rank patients according to the survival prognoses or the resource expectations. In terms of utilitarianism, this strategy is better at improving population-wide outcomes by distributing scarce resources effectively. Nevertheless, the damage can be the result of these algorithms not classifying the patients with the symptoms that are not likely to appear because of the potential to miss unusual heart attack symptoms, including women or individuals who belong to the underrepresented ethnic groups. Under such circumstances, the utilitarian dependency on the statistical forecasts might fail to regard the nuances of the individual patients and this gives a conflict of ethics.
Deontology
Deontology is an ethical theory that is based on duty and focuses on moral rules, rights, and responsibilities irrespective of consequences. The emphasis is made on the intrinsic moral worth of the actions and the duty towards treating people with dignity and respect. Nurses who apply deontological ethics are patient centered, consider privacy, informed consent and advocate- even in cases where the values are in conflict with the technical prescriptions.
To illustrate, when an AI system recommends to an individual to leave the hospital early, regardless of the trends in the data, and the nurse examines the case and sees possible risk factors that the AI cannot identify, the deontological ethics will demand that the nurse question the system. Ethical responsibilities of the nurse include the protection of patient safety, integration of autonomy and independent clinical judgment. Deontology, therefore, supports the position of the nurse as a protection against technology excess.
Application of ANA Code of Ethics.
The American Nurses Association (ANA) Code of Ethics is a professional guide to dealing with new ethical issues related to AI.
The first provision (1) focuses on the patient autonomy and human dignity, i.e., a nurse should make sure that AI does not suppress the voice of the patient.
Provision 3 requires patient privacy and confidentiality that are important issues since AI systems depend on massive data sets that can be used to reveal sensitive data.
Provision 4 reinforced the professional practice of the nurse, and he or she is responsible and answerable to the individual practice, and AI cannot substitute the professional judgment.
Provision 5 emphasizes the need of moral self-integrity, in which a nurse should question and challenge unsafe or biased AI suggestions.
All these provisions make sure that ethical nursing practice is still based on human values despite the advancement of technology.
Autonomy, Beneficence, Nonmaleficence, and Veracity are the four ethical principles.
Autonomy
Autonomy concerns the right of the patient to make informed voluntary decisions. AI threatens the principle of autonomy by having algorithms make the care decisions without the patient knowledge or approval. In most clinical practices, a patient does not know that diagnostic or treatment recommendations are based on AI models. During my recent clinical experience, I have observed instances in which AI-generated discharge recommendations were automatically adhered to, even in the absence of consideration of the concerns and readiness of the patient. To maintain autonomy, nurses should make sure that patients are their partners in care, and not beneficiaries of AI-driven decisions.
Beneficence
Beneficence expects healthcare professionals to do that which is beneficial to the patient. often AI is presented with an idea of increasing beneficence through helping to make correct diagnoses or detect deterioration early. Nevertheless, the principle of beneficence is lost in case algorithms produce false alarms, make inappropriate interpretations, or lack the ability to use the context to include clinical information. An example of this is an AI sepsis prediction tool that has been applied in my clinical environment. It gave false positives too often, leading the staff to experience alert fatigue. This atmosphere meant less focus on truly important alerts, which proves that AI can adversely affect the creation of beneficent care.
Nonmaleficence
Nonmaleficence, which is translated as do no harm, comes into play especially where measuring the risks of AI. AI systems can be harmful due to incorrect predictions, biased decision rules, or omission of important factors of a patient. The clinical example was when one EHR-based AI tool that miscalculated the dose of medications in patients with renal impairment and suggested doses that were unsafe. To prevent harm, nurses were forced to make interventions and adjust computations manually, and report the mistake. This principle underlines the importance of human control and reasoning in the AI-assisted care.
Veracity
Truth- telling or veracity needs honesty in patient communication. AI makes veracity complex when clinicians fail to reveal the level of algorithm impact on decision making. The absence of transparency can also be seen as a source of distrust, when the patients are discovered to have been heavily influenced by AI in their diagnosis or treatment. Nurses need to be open in discussions on the role of technology in care decision-making and explain to patients why they are being recommended the way they are.
Ethical Decision-Making Model: Procedure of Situation Assessment (Cherry and Jacob).
Chosen Ethical Issue:
Insecure trust in AI-generated advice which does not align with nursing evaluation.
Determine the Ethical Problem.
The main question is whether it is ethical to act upon AI-generated care recommendations, which conflict with the professional judgment of a nurse and endanger the lives of a patient. This issue leaves the nurse in a dilemma of either following the hospital policy in favor of using AI or professionalism to save the patient.
Gather Relevant Data
Critical data will consist of:
The precision levels and the history of failure of the AI system.
Specifications about the symptoms and clinical status of the patient.
Data set constraints of the AI training.
Policies of implementation of AI in hospitals.
Assessment outcome of the nurse.
Preferences and expressed concerns of the patients.
Ethical and regulatory directives on AI application.
Determine Involved Ethical Principles.
This dilemma involves:
Independence: AI can disregard the concerns of patients.
Beneficence Beneficence: AI may provide efficiencies and not personalized care.
Nonmaleficence: Failure of the AI may result in harm.
Veracity: A lack of transparency may trick patients.
Explore Alternatives
The possible courses of action are:
Fighting the AI ruling and suggesting a reevaluation.
Making a visit to a physician or interdisciplinary team.
Educating the patient about the dilemma between algorithmic and human judgment.
Making a request of a second assessment.
Disclosing inconsistencies and communicating possible AI error patterns.
Select the Best Alternative
The morally correct action is to put patient safety and autonomy in medical decision-making first. The nurse is expected to question the AI recommendation and demand a review. This is in line with ANA Code of Ethics and principles of beneficence and nonmaleficence.
Implement the Decision
Actions include:
Reporting to the health practitioner as soon as possible.
Ordering additional clinical assessment.
Educating the patient on the rationale of decision.
Reporting on worries about AI output.
Disclosing the problem to the quality improvement or informatics teams.
Evaluate the Outcome
It should be found out whether:
Patient harm was prevented
The independence and dignity of the patient were taken care of.
The medical personnel became more cautious when using AI.
Further training or revisioning of policies are required.
Reflection
This discussion has made it clear that AI introduces emerging ethical issues, which cannot be solved by relying on technical knowledge alone. Critical thinking, advocacy, and moral courage are necessary in ethical nursing practice. I also knew that AI cannot substitute the human reasoning or compassion, although it can be used to improve care. In order to enhance my competencies, I am going to undergo training connected with AI ethics, work on my advocacy skills, and actively use ethical decision-making models in the event of dilemmas. This education will influence my practice in the future by making me keep my eyes open, being patient-focused, and persist in ethically upholding nursing practice even in high-tech settings.
Conclusion
The potential of artificial intelligence in the health care sector is transformative, yet the process of its implementation raises complicated ethical and bioethical issues. The paper discussed the utilitarian and deontological models, ethical norms, and how the ANA Code of Ethics could be used to steer nurses through the AI-related dilemmas. In spite of claims that AI makes the process more efficient and benefits the population overall, this analysis showed that technology can undermine patient autonomy, safety, and fairness as well. In the end, algorithmic convenience should not be the priority of the nursing practice, and ethical principles and human dignity should be given the first priority. Future studies are required to identify ways of minimizing the bias of AI, enhance transparency and enhance nurse education regarding AI ethics. This should be further followed up by continuous assessment so that technological advancements do not serve as a detriment to ethical nursing service.
References
Cherry, B., & Jacob, S. (2022). Modern nursing: Problems, tendencies, and organization (9th ed.). Elsevier.
Authored Book (Section 10.2)
American Nurses Association. (2021). Interpretive statement code of ethics to nurses. ANA Publishing.
Essay type 10.2, Organizational Authored Book.
Grote, T., & Berens, P. (2020). Algorithms in healthcare decision ethics. Journal of Medical Ethics, 46(3), 205-211.
Journal Article (Section 10.1)
McCradden, M. D., Baba, A., & Saha, A. (2022). Healthcare artificial intelligence Ethical issues in healthcare: A systematic review. BMC Medical Ethics, 23(1), 1-15.
Journal Article (Section 10.1)
Topol, E. (2023). High-performance medicine: Intersection of human and artificial intelligence. Nature Medicine, 29(2), 158-166.
Journal Article (Section 10.1)
