Physician resource use and willingness to participate in assisted suicide

Arch Intern Med. 1998 May 11;158(9):974-8. doi: 10.1001/archinte.158.9.974.

Abstract

Objective: To explore the relationship between general internists' tendency to conserve medical resources and their willingness to participate in physician-assisted suicide (PAS).

Design and participants: Survey of a random sample of general internists in 6 urban areas of the United States.

Measurements: We assessed the physicians' use of medical resources by constructing a scale based on 6 hypothetical clinical scenarios in which respondents were given a choice between resource-intensive and resource-conserving options. We then presented a scenario of a competent terminally ill patient with breast cancer making stable and persistent requests for PAS.

Results: Sixty-seven (33%) of the 206 respondents indicated that they would participate in the suicide of the depicted patient. In a multivariate model, physicians who were more conservative with resources were 6.4 times more likely than their resource-intensive counterparts to prescribe the requested drugs (P = .02); minority physicians were less willing than whites to participate in PAS (odds ratio, 0.34; P = .03). Physicians' number of years in practice, location, sex, reported percentage of fee-for-service patients, and self-reported strength and direction of financial incentives in the respondents' practices were not associated with willingness to prescribe drugs for PAS.

Conclusions: Most general internists, especially minority physicians, are personally reluctant to participate in PAS. While the characteristics of their practices do not affect PAS, physicians who tend to practice resource-conserving medicine are significantly more likely than their resource-intensive counterparts to provide a lethal prescription at the request of a terminally ill patient.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Health Resources / statistics & numerical data*
  • Humans
  • Internal Medicine*
  • Logistic Models
  • Multivariate Analysis
  • Odds Ratio
  • Physicians / statistics & numerical data*
  • Practice Patterns, Physicians'*
  • Resource Allocation
  • Suicide, Assisted*
  • Surveys and Questionnaires
  • United States
  • Urban Population