Joshua R Lakin1,2,3,4, Margaret G Robinson5, Ziad Obermeyer6,7,8, Brian W Powers9, Susan D Block10,11,6,9,12, Rebecca Cunningham9, Joseph M Tumblin13, Christine Vogeli13,14,15, Rachelle E Bernacki10,11,6,9. 1. Department of Psychosocial Oncology and Palliative Care, Dana-Farber Cancer Institute, Brookline Ave, Boston, MA, USA. jlakin@partners.org. 2. Division of Palliative Medicine, Brigham and Women's Hospital, Boston, MA, USA. jlakin@partners.org. 3. Ariadne Labs, Brigham and Women's Hospital & Harvard School of Public Health, Boston, MA, USA. jlakin@partners.org. 4. Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. jlakin@partners.org. 5. Stanford University School of Medicine, Stanford, CA, USA. 6. Ariadne Labs, Brigham and Women's Hospital & Harvard School of Public Health, Boston, MA, USA. 7. Department of Emergency Medicine, Brigham and Women's Hospital, Boston, MA, USA. 8. Departments of Emergency Medicine and Health Care Policy, Harvard Medical School, Boston, MA, USA. 9. Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. 10. Department of Psychosocial Oncology and Palliative Care, Dana-Farber Cancer Institute, Brookline Ave, Boston, MA, USA. 11. Division of Palliative Medicine, Brigham and Women's Hospital, Boston, MA, USA. 12. Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA. 13. Partners HealthCare, Boston, MA, USA. 14. Harvard Medical School, Boston, MA, USA. 15. Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
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.
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.
Entities:
Keywords:
advance care planning; end-of-life care; palliative care; patient identification
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