The frequency of "do-not-resuscitate" order in aged in-patients: effect of patient- and non-patient-related factors

Neth J Med. 1994 Mar;44(3):78-83.

Abstract

Objective: The purpose of this study was to examine the effect of patient- and non-patient-related factors (co-morbidity, demographics, and method of surveillance) on the frequency of "do-not-resuscitate" (DNR) orders in aged inpatients.

Methods: On a geriatric ward, during three different periods within 1 year, we used two different methods of data collection (with or without a form) and two different time-frames (prevalence or incidence) in studying the frequency of DNR orders, demographic data and the Pre-Arrest Morbidity (PAM) Index.

Results: In a sample of 261 patients the DNR decision was related to patient-related factors, including the PAM score and age. Only 3 patients with a score above 4 had no DNR order and in the group of 142 patients > 83 years 85 (59.9%) had a DNR order, compared to 52 (43.7%) of the 119 patients of 83 years or less (p < 0.05). In contrast, gender and marital status were not related to the presence of a DNR order. The variables PAM score, age, form and time-frame classified 76.6% of the cardiopulmonary resuscitation (CPR) decisions correctly and 71.5% of the DNR decisions correctly. Without attention to the resuscitation decision, the written DNR order frequency decreased significantly from 64-59% to 23%. An explanation for this variance may be the passive process of data collection, a non-patient-related factor.

Conclusions: The DNR decision is related to the PAM index score and age. The variance in DNR decisions is partly related to the method of data collection, a non-patient-related factor in DNR decision-making. Without attention to the DNR/CPR decision, the DNR frequency decreased markedly.

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Bias
  • Comorbidity
  • Data Collection / methods*
  • Decision Making
  • Discriminant Analysis
  • Female
  • Geriatrics
  • Hospital Units
  • Humans
  • Inpatients / statistics & numerical data*
  • Logistic Models
  • Male
  • Middle Aged
  • Prospective Studies
  • Resuscitation Orders*
  • Severity of Illness Index*
  • Socioeconomic Factors