Discrepancy between Health Care Rationing at the Bedside and Policy Level

Med Decis Making. 2018 Oct;38(7):881-887. doi: 10.1177/0272989X18793637. Epub 2018 Sep 10.

Abstract

Background: Whether doctors at the bedside level should be engaged in health care rationing is a controversial topic that has spurred much debate. From an empirical point of view, a key issue is whether there exists a behavioral difference between rationing at the bedside and policy level. Psychological theory suggests that we should indeed expect such a difference, but existing empirical evidence is inconclusive.

Objective: To explore whether rationing decisions taken at the bedside level are different from rationing decisions taken at the policy level.

Method: Behavioral experiment where participants ( n = 573) made rationing decisions in hypothetical scenarios. Participants (medical and nonmedical students) were randomly assigned to either a bedside or a policy condition. Each scenario involved 1 decision, concerning either a life-saving medical treatment or a quality-of-life improving treatment. All scenarios were identical across the bedside and policy condition except for the level of decision making.

Results: We found a discrepancy between health care rationing at policy and bedside level for scenarios involving life-saving decisions, where subjects rationed treatments to a greater extent at the policy level compared to bedside level (35.6% v. 29.3%, P = 0.001). Medical students were more likely to ration care compared to nonmedical students. Follow-up questions showed that bedside rationing was more emotionally burdensome than rationing at the policy level, indicating that psychological factors likely play a key role in explaining the observed behavioral differences. We found no difference in rationing between bedside and policy level for quality-of-life improving treatments (54.6% v. 55.7%, P = 0.507).

Conclusions: Our results indicate a robust "bedside effect" in the life-saving domain of health care rationing decisions, thereby adding new insights to the understanding of the malleability of preferences related to resource allocation.

Keywords: decision making; experiment; health care rationing; identifiability; individuals and groups.

Publication types

  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Clinical Decision-Making*
  • Female
  • Health Care Rationing*
  • Health Care Surveys
  • Humans
  • Male
  • Organizational Policy*
  • Point-of-Care Systems*
  • Students, Medical
  • Young Adult