Prioritizing Primary Care Patients for a Communication Intervention Using the "Surprise Question": a Prospective Cohort Study

J Gen Intern Med. 2019 Aug;34(8):1467-1474. doi: 10.1007/s11606-019-05094-4. Epub 2019 Jun 12.

Abstract

Background: Communication about priorities and goals improves the value of care for patients with serious illnesses. Resource constraints necessitate targeting interventions to patients who need them most.

Objective: To evaluate the effectiveness of a clinician screening tool to identify patients for a communication intervention.

Design: Prospective cohort study.

Setting: Primary care clinics in Boston, MA.

Participants: Primary care physicians (PCPs) and nurse care coordinators (RNCCs) identified patients at high risk of dying by answering the Surprise Question (SQ): "Would you be surprised if this patient died in the next 2 years?"

Measurements: Performance of the SQ for predicting mortality, measured by the area under receiver operating curve (AUC), sensitivity, specificity, and likelihood ratios.

Results: Sensitivity of PCP response to the SQ at 2 years was 79.4% and specificity 68.6%; for RNCCs, sensitivity was 52.6% and specificity 80.6%. In univariate regression, the odds of 2-year mortality for patients identified as high risk by PCPs were 8.4 times higher than those predicted to be at low risk (95% CI 5.7-12.4, AUC 0.74) and 4.6 for RNCCs (3.4-6.2, AUC 0.67). In multivariate analysis, both PCP and RNCC prediction of high risk of death remained associated with the odds of 2-year mortality.

Limitations: This study was conducted in the context of a high-risk care management program, including an initial screening process and training, both of which affect the generalizability of the results.

Conclusion: When used in combination with a high-risk algorithm, the 2-year version of the SQ captured the majority of patients who died, demonstrating better than expected performance as a screening tool for a serious illness communication intervention in a heterogeneous primary care population.

Keywords: advance care planning; end-of-life care; palliative care; patient identification.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Chronic Disease / mortality
  • Chronic Disease / therapy
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Male
  • Middle Aged
  • Palliative Care / organization & administration*
  • Primary Health Care / organization & administration*
  • Primary Health Care / statistics & numerical data
  • Prospective Studies
  • Risk Assessment / methods
  • Surveys and Questionnaires / standards*