Natural Language Processing to Assess Palliative Care Processes and Health Care Utilization in Seriously Ill Older Adults with Severe Trauma

Abstract

Background:

National guidelines recommend palliative care (PC) alongside life-sustaining treatment for older adults with severe trauma. However, outcomes associated with PC for these patients are not well-defined.

Objectives:

To determine frequency of inpatient PC process documentation in older adults with severe trauma and test associations with postdischarge health care utilization.

Design:

Retrospective cohort study using electronic health record data linked to Medicare claims.

Setting/Subjects:

We included adults ≥66 years old admitted to a large, regional U.S. health care system with severe trauma (2016–2018) using consensus criteria for serious illness in trauma.

Measurements:

Natural language processing was used to measure documentation of five inpatient PC processes: code status limitations, goals-of-care (GOC) conversations, hospice discussions, PC consultations, and health care proxy designations. Associations between PC processes and postdischarge health care utilization were tested using multivariable regression.

Results:

Among 1267 admissions, the median age was 82 years (interquartile range [IQR] 75–88), and median injury severity score (0–75, higher is worse) was 16 (IQR 9–21); ≥1 PC process was documented in 81%. Among those surviving hospitalization (87%), one-year mortality was 26%. Documentation of ≥1 PC process was not significantly associated with differences in mean hospital days (16 vs. 19), home days (306 vs. 307), emergency department visits (2.3 vs. 2.2), or intensive care unit days (0.6 vs. 0.9) at one year. PC processes were significantly associated with subsequent hospice enrollment (p < 0.01).

Conclusions:

PC was not associated with reduced health care utilization in older adults after trauma but was associated with one-year hospice enrollment. GOC conversations, specialty PC, and inpatient hospice discussions had low utilization, highlighting target areas for improvements in care delivery.