Resolving Ethical Dilemmas, Paperback/Bernard Lo

Description What are the ethical issues raised by the increasing use of big data and artificial intelligence in health care? How should physicians respond when they have a conscientious objection to an intervention requested by a patient? How should health care organizations respond to physician requests? How can physicians best help patients make informed decisions about end-of-life and life-sustaining care? How should interns and residents respond to ethical dilemmas created by duty hours restrictions? Resolving Ethical Dilemmas: A Guide for Clinicians helps residents, students, and practitioners work through these and many more common and challenging ethical questions that affect patient care. The 6th Edition reflects important changes in medicine and healthcare policy and provides additional clarity to complex concepts. Offering practical, real-world advice, it helps you think through and resolve difficult cases, prompting thoughtful, well-reasoned answers to the question of "What do I do in this situation?" Begins with a concise discussion of clinical ethics that provides background information essential to understanding key ethical issues. Explores a wide range of real-world ethical dilemmas, each accompanied by expert guidance on salient issues and how to approach them. Provides new insights on cases related to oncology, palliative care, family medicine, clinical practice guidelines, genetic testing, the electronic health record, opioid prescriptions, evidence-based medicine, ambulatory care, quality improvement, and advance care planning. Helps you work thorough challenges such as how to handle changes arising from the Affordable Care Act, how to manage treatment when it no longer works for the patient, and much more. Uses a highly visual, two-color design to facilitate retention of material. Enhance Your eBook Reading Experience Read directly on your preferred device(s), such as computer, tablet, or smartphone. Easily convert to audiobook, powering your content with natural language text-to-speech.