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Journal ArticleDOI

Perspective: Physician advocacy: what is it and how do we do it?

01 Jan 2010-Academic Medicine (Acad Med)-Vol. 85, Iss: 1, pp 63-67
TL;DR: The authors propose a definition and, using the biographies of actual physician advocates, describe the spectrum of physician advocacy, as first steps toward building a model for competency-based physician advocacy training and delineating physician advocacy in common practice.
Abstract: Many medical authors and organizations have called for physician advocacy as a core component of medical professionalism. Despite widespread acceptance of advocacy as a professional obligation, the concept remains problematic within the profession of medicine because it remains undefined in concept, scope, and practice. If advocacy is to be a professional imperative, then medical schools and graduate education programs must deliberately train physicians as advocates. Accrediting bodies must clearly define advocacy competencies, and all physicians must meet them at some basic level. Sustaining and fostering physician advocacy will require modest changes to both undergraduate and graduate medical education. Developing advocacy training and practice opportunities for practicing physicians will also be necessary. In this article, as first steps toward building a model for competency-based physician advocacy training and delineating physician advocacy in common practice, the authors propose a definition and, using the biographies of actual physician advocates, describe the spectrum of physician advocacy.
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Journal ArticleDOI
TL;DR: A concept analysis is conducted, exploring the practical philosophical understanding of social responsibility and its implications for medical education and practice, to inform curricular development, professional practice, and further research on social responsibility.
Abstract: There is a growing demand for educating future physicians to be socially responsible. It is not clear, however, how social responsibility is understood and acted on in medical education and practice, particularly within the context of a growing desire to improve health care through an equitable and sustainable delivery system. The authors conduct a concept analysis, exploring the practical philosophical understanding of social responsibility and its implications for medical education and practice. The aim is to inform curricular development, professional practice, and further research on social responsibility. The particular ways in which social responsibility is interpreted can either enhance or establish limits on how it will appear across the continuum of medical education and practice. A physician's place in society is closely tied to a moral sense of responsibility related to the agreed-on professional characteristics of physicianhood in society, the capacity to carry out that role, and the circumstances under which such professionals are called to account for failing to act appropriately according to that role. The requirement for social responsibility is a moral commitment and duty developed over centuries within societies that advanced the notion of a "profession" and the attendant social contract with society. A curriculum focused on developing social responsibility in future physicians will require pedagogical approaches that are innovative, collaborative, participatory, and transformative.

152 citations

Journal ArticleDOI
TL;DR: Shen et al. as mentioned in this paper proposed a chatGPT model that optimizes language models for dialogue and showed that it is possible to train a few-shot language model with human preferences.
Abstract: HomeRadiologyVol. 307, No. 2 PreviousNext Reviews and CommentaryEditorialChatGPT and Other Large Language Models Are Double-edged SwordsYiqiu Shen , Laura Heacock, Jonathan Elias, Keith D. Hentel, Beatriu Reig, George Shih, Linda MoyYiqiu Shen , Laura Heacock, Jonathan Elias, Keith D. Hentel, Beatriu Reig, George Shih, Linda MoyAuthor AffiliationsFrom the Center for Data Science, New York University, 60 5th Ave, New York, NY 10011 (Y.S.); Department of Radiology, New York University School of Medicine, New York, NY (L.H., B.R., L.M.); and Departments of Primary Care (J.E.) and Radiology (K.D.H., G.S.), Weill Cornell Medicine, New York, NY.Address correspondence to Y.S. (email: [email protected]).Yiqiu Shen Laura HeacockJonathan EliasKeith D. HentelBeatriu ReigGeorge ShihLinda MoyPublished Online:Jan 26 2023https://doi.org/10.1148/radiol.230163See editorial bySom BiswasSee editorial byFelipe C. KitamuraMoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In References1. Min B, Ross H, Sulem E, et al. Recent advances in natural language processing via large pre-trained language models. arXiv 2111.01243 [preprint]. https://arxiv.org/abs/2111.01243. Posted November 1, 2021. Accessed January 19, 2023. Google Scholar2. Vaswani A, Shazeer N, Parmar N, et al. Attention is all you need. Advances in Neural Information Processing Systems 2017;30. https://papers.nips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html. Google Scholar3. ChatGPT: Optimizing Language Models for Dialogue. OpenAI. https://openai.com/blog/chatgpt/. Published November 30, 2022. Accessed January 19, 2023. Google Scholar4. Brown T, Mann B, Ryder N, et al. Language models are few-shot learners. Advances in Neural Information Processing Systems 2020;33:1877–1901.https://papers.nips.cc/paper/2020/hash/1457c0d6bfcb4967418bfb8ac142f64a-Abstract.html. Google Scholar5. OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic. TIME. https://time.com/6247678/openai-chatgpt-kenya-workers/. Published January 18,2023. Accessed January 21, 2023. Google Scholar6. Christiano PF, Leike J, Brown T, Martic M, Legg S, Amodei D. Deep reinforcement learning from human preferences. Advances in Neural Information Processing Systems 2017;30. https://papers.nips.cc/paper/2017/hash/d5e2c0adad503c91f91df240d0cd4e49-Abstract.html. Google Scholar7. Rohrbach A, Hendricks LA, Burns K, Darrell T, Saenko K. Object Hallucination in Image Captioning. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing 2018;4035–4045. Google Scholar8. Xiao Y, Wang WY. On Hallucination and Predictive Uncertainty in Conditional Language Generation. In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume 2021. Google Scholar9. Clinical Decision Support. American Medical Informatics Association. https://amia.org/community/working-groups/clinical-decision-support#:~:text=Clinical%20Decision%20Support%20(CDS)%20is,care%20services%20and%20patient%20outcomes. Accessed January 16, 2023. Google Scholar10. Appropriate use criteria for advanced diagnostic imaging services. Code of Federal Regulations. https://www.ecfr.gov/current/title-42/chapter-IV/subchapter-B/part-414/subpart-B/section-414.94/. Accessed January 18, 2023. Google Scholar11. @tiktokrheumdok. ChatGPT to save time with Insurance Denials. TikTok. https://www.tiktok.com/@tiktokrheumdok/video/7176660771806383403. Published December 13, 2022. Accessed January 4, 2023. Google Scholar12. @StuartBlitz. You: There’s no ChatGPT use case in healthcare. Docs: Watch this. Twitter. https://twitter.com/StuartBlitz/status/1602834224284897282. Published December 13, 2022. Accessed January 13, 2023. Google Scholar13. ChatGPT FAQ: Commonly asked questions about ChatGPT. OpenAI. https://help.openai.com/en/articles/6783457-chatgpt-faq#:~:text=It%20has%20limited%20knowledge%20of%20world%20and%20events%20after%202021/. Accessed January 22, 2023. Google Scholar14. Reyes M, Meier R, Pereira S, et al. On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities. Radiol Artif Intell 2020;2(3):e190043. Link, Google Scholar15. Shen Y, Wu N, Phang J, et al. An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization. Med Image Anal 2021;68:101908. Crossref, Medline, Google Scholar16. Shen Y, Shamout FE, Oliver JR, et al. Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams. Nat Commun 2021;12(1):5645. Crossref, Medline, Google Scholar17. Shamout FE, Shen Y, Wu N, et al. An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. NPJ Digit Med 2021;4(1):80. Crossref, Medline, Google Scholar18. Luft LM. The essential role of physician as advocate: how and why we pass it on. Can Med Educ J 2017;8(3):e109–e116. Crossref, Medline, Google Scholar19. Earnest MA, Wong SL, Federico SG. Perspective: Physician advocacy: what is it and how do we do it? Acad Med 2010;85(1):63–67. Crossref, Medline, Google Scholar20. Szakaly D. How ChatGPT Hijacks Democracy. New York Times. https://www.nytimes.com/2023/01/15/opinion/ai-chatgpt-lobbying-democracy.html. Published January 15, 2023. Accessed January 16, 2023. Google Scholar21. Report of the Select Committee on Intelligence, United States Senate, on Russian Active Measures Campaigns and Interference in the 2016 U.S. Election Volume 2: Russia’s Use of Social Media with Additional Views. https://www.intelligence.senate.gov/sites/default/files/documents/Report_Volume2.pdf. Accessed January 16, 2023. Google Scholar22. Huang K. Alarmed by A.I. Chatbots Universities Start Revamping How They Teach. New York Times. https://www.nytimes.com/2023/01/16/technology/chatgpt-artificial-intelligence-universities.html. Published January 16, 2023. Accessed January 19, 2023. Google Scholar23. Tian E. GPTZero https://gptzero.substack.com/. Published January 3, 2023. Accessed January 19, 2023. Google Scholar24. Gao CA, Howard FM, Markov NS, et al. Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers. bioRxiv 2022. https://doi.org/10.1101/2022.12.23.521610. Posted December 27, 2022. Accessed January 13, 2023. Google Scholar25. Bolton E, Hall D, Yasunaga M, Lee T, Manning C, Liang P. PubMedGPT 2.7B. Center for Research on Foundation Models, Stanford University. https://crfm.stanford.edu/2022/12/15/pubmedgpt.html. Accessed January 19, 2023. Google Scholar26. Clarification on Large Language Model Policy LLM. ICML 2023: Fortieth International Conference on Machine Learning. https://icml.cc/Conferences/2023/llm-policy. Accessed January 19, 2023. Google Scholar27. Bik EM, Casadevall A, Fang FC. The prevalence of inappropriate image duplication in biomedical research publications. MBio 2016;7(3):e00809–16. Crossref, Medline, Google Scholar28. Yue W, AbdAlmageed W, Natarajan P. ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019; 9543–9552. https://ieeexplore.ieee.org/document/8953774. Google Scholar29. Aditya R, Dhariwal P, Nichol A, Chu C, Chen M. Hierarchical Text-Conditional Image Generation with CLIP Latents. arXiv 2204.06125 [preprint]. https://arxiv.org/abs/2204.06125. Posted April 13, 2022. Accessed January 18, 2023. Google Scholar30. Rombach R, Blattmann A, Lorenz D, Esser P, Ommer B. High-resolution image synthesis with latent diffusion models. In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, June 2022. Google Scholar31. Chambon P, Bluethgen C, Langlotz CP, Chaudhari A. Adapting pretrained vision-language foundational models to medical imaging domains. arXiv 2210.04133 [preprint]. https://arxiv.org/abs/2210.04133. Posted October 9, 2022. Accessed January 18, 2023. Google Scholar32. Biswas S. ChatGPT and the Future of Medical Writing. Radiology 2023;307(2):e223312. Link, Google Scholar33. Kitamura FC. ChatGPT Is Shaping the Future of Medical Writing But Still Requires Human Judgment. Radiology 2023;307(2):e230171. Link, Google ScholarArticle HistoryReceived: Jan 23 2023Revision requested: Jan 23 2023Revision received: Jan 23 2023Accepted: Jan 23 2023Published online: Jan 26 2023 FiguresReferencesRelatedDetailsCited ByChatGPT Is Shaping the Future of Medical Writing But Still Requires Human JudgmentFelipe C. Kitamura, 2 February 2023 | Radiology, Vol. 307, No. 2The Role and Limitations of Large Language Models Such as ChatGPT in Clinical Settings and Medical JournalismFurkan Ufuk, 7 March 2023 | Radiology, Vol. 0, No. 0The potential impact of ChatGPT in clinical and translational medicineVivian WeiwenXue, PingguiLei, William C.Cho2023 | Clinical and Translational Medicine, Vol. 13, No. 3Large language models (LLM) and ChatGPT: what will the impact on nuclear medicine be?Ian L.Alberts, LorenzoMercolli, ThomasPyka, GeorgePrenosil, KuangyuShi, AxelRominger, AliAfshar-Oromieh2023 | European Journal of Nuclear Medicine and Molecular ImagingTransformers, codes and labels: large language modelling for natural language processing in clinical radiologyDenisRemedios, AlexRemedios2023 | European RadiologyChatGPT—a foe or an ally?Om PrakashYadava2023 | Indian Journal of Thoracic and Cardiovascular SurgeryChatGPTDiveshSardana, Timothy R.Fagan, John TimothyWright2023 | The Journal of the American Dental AssociationThe promise and peril of ChatGPT in geriatric nursing education: What We know and do not knowXiangQi, ZhengZhu, BeiWu2023 | Aging and Health Research, Vol. 3, No. 2Authors in the Age of Language-generation AI: To be or not to be, is that Really the Question?José DaríoMartínez-Ezquerro2023 | Archives of Medical ResearchBeyond chatting: The opportunities and challenges of ChatGPT in medicine and radiologyJuan M. LavistaFerres, William B.Weeks, Linda C.Chu, Steven P.Rowe, Elliot K.Fishman2023 | Diagnostic and Interventional ImagingAttention is not all you need: the complicated case of ethically using large language models in healthcare and medicineStefanHarrer2023 | eBioMedicine, Vol. 90Chatting or cheating? The impacts of ChatGPT and other artificial intelligence language models on nurse educationEdmond Pui HangChoi, Jung JaeLee, Mu-HsingHo, Jojo Yan YanKwok, Kris Yuet WanLok2023 | Nurse Education Today, Vol. 125Is ChatGPT a valid author?Jaime A.Teixeira da Silva2023 | Nurse Education in Practice, Vol. 68Do Large Language Models Understand Chemistry? A Conversation with ChatGPTCayque MonteiroCastro Nascimento, André SilvaPimentel2023 | Journal of Chemical Information and Modeling, Vol. 63, No. 6Readership Awareness Series – Paper 4: Chatbots and ChatGPT - Ethical Considerations in Scientific PublicationsMohammad JavedAli, AliDjalilian2023 | Seminars in OphthalmologyA SWOT analysis of ChatGPT: Implications for educational practice and researchMohammadrezaFarrokhnia, Seyyed KazemBanihashem, OmidNoroozi, ArjenWals2023 | Innovations in Education and Teaching InternationalChatGPT and other artificial intelligence applications speed up scientific writingTzeng-JiChen2023 | Journal of the Chinese Medical Association, Vol. 86, No. 4ChatGPT for tourism: applications, benefits and risksInêsCarvalho, StanislavIvanov2023 | Tourism ReviewImplications of large language models such as ChatGPT for dental medicineFlorinEggmann, RolandWeiger, Nicola U.Zitzmann, Markus B.Blatz2023 | Journal of Esthetic and Restorative DentistryAI and GPT for Management Scholars and Practitioners: Guidelines and ImplicationsSudhirRana2023 | FIIB Business Review, Vol. 12, No. 1Can ChatGPT improve communication in hospitals?DavidSantandreu-Calonge, PabloMedina-Aguerrebere, PatrikHultberg, Mariam-AmanShah2023 | El Profesional de la informaciónChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid ConcernsMalikSallam2023 | Healthcare, Vol. 11, No. 6Future Speech Interfaces with Sensors and Machine IntelligenceBruceDenby, Tamás GáborCsapó, MichaelWand2023 | Sensors, Vol. 23, No. 4Editorial: The Use of Artificial Intelligence (AI)-Assisted Technologies in Scientific DiscourseArvieVitente, RolandoLazaro, Catherine JoyEscuadra, JocelRegino, EsmeritaRotor2023 | Philippine Journal of Physical TherapyChatGPT and Big Data: Enhancing Text-to-Speech ConversionHatim AbdelhakDida, DSKChakravarthy, FazleRabbi2023 | Mesopotamian Journal of Big DataAn era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challengesAbidHaleem, MohdJavaid, Ravi PratapSingh2022 | BenchCouncil Transactions on Benchmarks, Standards and Evaluations, Vol. 2, No. 4Artificial intelligence and dental researchSMBalaji2022 | Indian Journal of Dental Research, Vol. 33, No. 4Accompanying This ArticleChatGPT and the Future of Medical WritingFeb 2 2023RadiologyChatGPT Is Shaping the Future of Medical Writing But Still Requires Human JudgmentFeb 2 2023RadiologyChatGPT- Special Radiology:AI Podcast CollaborationFeb 21 2023Default Digital Object SeriesEpisode 17: ChatGPT- Special Radiology Podcast CollaborationFeb 21 2023Default Digital Object SeriesRecommended Articles Deep Generative Adversarial Networks: Applications in Musculoskeletal ImagingRadiology: Artificial Intelligence2021Volume: 3Issue: 3Deep Learning: A Primer for RadiologistsRadioGraphics2017Volume: 37Issue: 7pp. 2113-2131Current Applications and Future Impact of Machine Learning in RadiologyRadiology2018Volume: 288Issue: 2pp. 318-328Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural NetworksRadiology2017Volume: 284Issue: 2pp. 574-582Convolutional Neural Networks for Radiologic Images: A Radiologist’s GuideRadiology2019Volume: 290Issue: 3pp. 590-606See More RSNA Education Exhibits Artificial Intelligence in Diagnostic Imaging: Current Applications and Future PerspectiveDigital Posters2019Artificial Intelligence in Breast Imaging: Past, Present, and FutureDigital Posters2020Generative Adversarial Networks (GANs): A Primer for RadiologistsDigital Posters2019 RSNA Case Collection Dynamic MRI findings of COVID-19 pneumoniaRSNA Case Collection2020Slow-growing cancerRSNA Case Collection2020Creutzfeldt-Jakob DiseaseRSNA Case Collection2021 Vol. 307, No. 2 PodcastPodcastMetrics Altmetric Score PDF download

151 citations

Journal ArticleDOI
TL;DR: The author argues that claims that political advocacy are a professional responsibility are mistaken, because civic virtues are outside the professional realm, and even if civic virtues were professionally obligatory, it is unclear that civic participation is necessary for such virtue.
Abstract: It is increasingly suggested that political advocacy is a core professional responsibility for physicians. The author argues that this is an error. Advocacy on behalf of societal goals, even those goals as unexceptionable as the betterment of human health, is inevitably political. Claims that political advocacy are a professional responsibility are mistaken, the author argues, because (1) civic virtues are outside the professional realm, (2) even if civic virtues were professionally obligatory, it is unclear that civic participation is necessary for such virtue, and (3) the profession of medicine ought not to require any particular political stance of its members. Claims that academic health centers should systematically foster advocacy are also deeply problematic. Although advocacy may coexist alongside the core university activities of research and education, insofar as it infects those activities, advocacy is likely to subvert them, as advocacy seeks change rather than knowledge. And official efforts on behalf of advocacy will undermine university aspirations to objectivity and neutrality.American society has conferred remarkable success and prosperity on its medical profession. Physicians are deserving of such success only insofar as they succeed in offering society excellence and dedication in professional work. Mandatory professional advocacy must displace such work but cannot substitute for it. The medical profession should steadfastly resist attempts to add advocacy to its essential professional commitments.

90 citations

Journal ArticleDOI
TL;DR: Medical residents endorsed the role of health advocate and reported proficiency in determining the medical and bio-psychosocial determinants of individuals and communities, due to multiple barriers.
Abstract: Background The CanMEDS Health Advocate role, one of seven roles mandated by the Royal College of Physicians and Surgeons Canada, pertains to a physician's responsibility to use their expertise and influence to advance the wellbeing of patients, communities, and populations. We conducted our study to examine resident attitudes and self-reported competencies related to health advocacy, due to limited information in the literature on this topic.

68 citations


Cites background from "Perspective: Physician advocacy: wh..."

  • ...Other hypotheses that have been suggested include a gradual erosion of altruism during residency resulting in poor engagement, and endorsement of advocacy because it is socially desirable, but not inherently believed [12]....

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Journal ArticleDOI
TL;DR: The authors argue that advocacy can help physicians fulfill their social contract and understand the challenges of the health care system and how to change it for the better so that physicians can experience increased professional satisfaction and effectiveness.
Abstract: As the modern medical system becomes increasingly complex, a debate has arisen over the place of advocacy efforts within the medical profession. The authors argue that advocacy can help physicians fulfill their social contract. For physicians to become competent in patient-centered, clinical, administrative, or legislative advocacy, they require professional training. Many professional organizations have called for curricular reform to meet society's health needs during the past 30 years, and the inclusion of advocacy training in undergraduate, graduate, and continuing medical education is supported on both pragmatic and ethical grounds. Undergraduate medical education, especially, is an ideal time for this training because a standard competency can be instilled across all specialties. Although the Accreditation Council for Graduate Medical Education includes advocacy training in curricula for residency programs, few medical schools or residency programs have advocacy electives. By understanding the challenges of the health care system and how to change it for the better, physicians can experience increased professional satisfaction and effectiveness in improving patient care, systems-based practice, and public health.

62 citations

References
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01 Jan 2002
TL;DR: The Charter on Medical Professionalism Project is the product of several years of work by leaders in the ABIM Foundation, the ACP‐ASIM Foundation, and the European Federation of Internal Medicine and consists of a brief introduction and rationale, three principles, and 10 commitments.
Abstract: Project of the ABIM Foundation, ACP–ASIM Foundation, and European Federation of Internal Medicine* To our readers: I write briefly to introduce the Medical Professionalism Project and its principal product, the Charter on Medical Professionalism. The charter appears in print for the first time in this issue of Annals and simultaneously in The Lancet .I hope that we will look back upon its publication as a watershed event in medicine. Everyone who is involved with health care should read the charter and ponder its meaning. The charter is the product of several years of work by leaders in the ABIM Foundation, the ACP‐ASIM Foundation, and the European Federation of Internal Medicine. The charter consists of a brief introduction and rationale, three principles, and 10 commitments. The introduction contains the following premise: Changes in the health care delivery systems in countries throughout the industrialized world threaten the values of professionalism. The document conveys this message with chilling brevity. The authors apparently feel no need to defend this premise, perhaps because they believe that it is a universally held truth. The authors go further, stating that the conditions of medical practice are tempting physicians to abandon their commitment to the primacy of patient welfare. These are very strong words. Whether they are strictly true for the profession as a whole is almost beside the point. Each physician must decide if the circumstances of practice are threatening his or her adherence to the values that the medical profession has held dear for many millennia. Three Fundamental Principles set the stage for the heart of the charter, a set of commitments. One of the three principles, the principle of primacy of patient welfare, dates from ancient times. Another, the principle of patient autonomy, has a more recent history. Only in the later part of the past century have people begun to view the physician as an advisor, often one of many, to an autonomous patient. According to this view, the center of patient care is not in the physician’s office or the hospital. It is where people live their lives, in the home and the workplace. There, patients make the daily choices that determine their health. The principle of social justice is the last of the three principles. It calls upon the profession to promote a fair distribution of health care resources. There is reason to expect that physicians from every point on the globe will read the charter. Does this document represent the traditions of medicine in cultures other than those in the West, where the authors of the charter have practiced medicine? We hope that readers everywhere will engage in dialogue about the charter, and we offer our pages as a place for that dialogue to take place. If the traditions of medical practice throughout the world are not congruent with one another, at least we may make progress toward understanding how physicians in different cultures understand their commitments to patients and the public. Many physicians will recognize in the principles and commitments of the charter the ethical underpinning of their professional relationships, individually with their patients and collectively with the public. For them, the challenge will be to live by these precepts and to resist efforts to impose a corporate mentality on a profession of service to others. Forces that are largely beyond our control have brought us to circumstances that require a restatement of professional responsibility. The responsibility for acting on these principles and commitments lies squarely on our shoulders.

1,014 citations

Journal ArticleDOI
03 Oct 2003-Science
TL;DR: The NIH Roadmap identifies the most compelling opportunities in three arenas: new pathways to discovery, research teams of the future, and reengineering the clinical research enterprise.
Abstract: The NIH Roadmap is a set of bold initiatives aimed at accelerating medical research. These initiatives will address challenges that no single NIH institute could tackle alone, but the agency as a whole must undertake. The Roadmap identifies the most compelling opportunities in three arenas: new pathways to discovery, research teams of the future, and reengineering the clinical research enterprise.

867 citations

Journal ArticleDOI
TL;DR: The problems with and success in trying to teach one of the core values of medicine, professionalism, are described and the authors say it becomes easier to teach.
Abstract: This article in the Medical Education series describes the problems with and success in trying to teach one of the core values of medicine, professionalism. As we better define professionalism, the authors say, it becomes easier to teach.

345 citations

Journal ArticleDOI
TL;DR: Incentives that depend on limiting referrals or on greater productivity apply selective pressure to physicians in ways that are believed to compromise care.
Abstract: Background Managed-care organizations' use of financial incentives to influence the practice of primary care physicians is controversial We studied the prevalence and effects of these incentives Methods We surveyed a probability sample of primary care physicians practicing in the largest urban counties in California in 1996 The physicians were asked about the types of incentives they encountered, the amount of income that was keyed to incentives, their experience of pressure in their practices, and the ways in which such pressure affected patient care Results Data were analyzed for 766 physicians involved in managed-care systems Thirty-eight percent of these physicians reported that their arrangements with the managed-care system included some type of incentive in the form of a bonus Fifty-seven percent of the physicians reported that they felt pressure from the managed-care organization to limit referrals (17 percent said they believed such pressure compromised patient care), and 75 percent felt pr

296 citations

Journal ArticleDOI
07 Jan 2004-JAMA
TL;DR: This work proposes a definition and a conceptual model of public roles that require evidence of disease causation and are guided by the feasibility and efficacy of physician involvement, and frames a public agenda for individual physicians and physician organizations that focuses on advocacy and community participation.
Abstract: Although leaders and other commentators have called for the medical profession's greater engagement in improving systems of care and population health, neither medical education nor the practice environment has fostered such engagement. Missing have been a clear definition of physicians' public roles, reasonable limits to what can be expected, and familiarity with tasks that are compatible with busy medical practices. We address these issues by proposing a definition and a conceptual model of public roles that require evidence of disease causation and are guided by the feasibility and efficacy of physician involvement. We then frame a public agenda for individual physicians and physician organizations that focuses on advocacy and community participation. By doing so, we aim to stimulate dialogue about the appropriateness of such roles and promote physician engagement with pressing health issues in the public arena.

290 citations