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Improving Knowledge, Attitudes, and Skills of Medical Clinicians and Trainees in Clinical Medical Ethics.

Ruthe AliGina M Piscitello
Published in: The American journal of hospice & palliative care (2022)
Purpose: There is limited data in the medical literature evaluating knowledge, attitudes, and skill in clinical medical ethics for clinicians or medical trainees. Our study aimed to evaluate baseline clinician knowledge, attitudes, and skills regarding clinical medical ethics and to implement and evaluate a curriculum designed with the intent to improve these measures. Method: Internal medicine residents, palliative fellows, medical and pre-medical students, social workers, advanced practice providers, and chaplains were surveyed at a large urban academic center to determine their baseline knowledge, attitudes, and skills regarding clinical medical ethics (64% response rate, n = 93/145). A one-hour discussion-based curriculum on clinical medical ethics topics was implemented, followed by another survey; χ2 and McNemar tests were used to compare pre- and post-surveys to evaluate the curriculum. Results: Baseline knowledge of all respondents (n = 93) in the four principles of bioethics (54%-89%), determining an alternate decision-maker (5%-50%), decision-making capacity (14%-71%), and in-hospital cardiac arrest survival (19%-77%) significantly increased ( P < .0001) post-curriculum, as did baseline self-reported attitudes towards clinicians making medical recommendations to patients (27%-60%) and having had adequate education on code status discussions (42%-77%). Self-reported skills in determining an alternate decision-maker (40%-89%) and assessing decision-making capacity (40%-72%) also significantly increased post curriculum ( P < .01 and P < .05). Conclusion: Implementation of a curriculum in medical ethics improved baseline knowledge, attitudes and self-reported skills of medical providers and trainees in clinical medical ethics.
Keyphrases
  • healthcare
  • medical students
  • public health
  • decision making
  • big data
  • cardiac arrest
  • mental health
  • systematic review
  • blood pressure
  • machine learning
  • chronic kidney disease