Improving surgical decision-making by measuring and predicting long-term loss of independence after surgery

NIH Pandemic-Era Grants

Pandemic Era Grants

2024

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Principal Investigator: Keri Lyn Rodriguez
Organization: VETERANS HEALTH ADMINISTRATION
Fiscal Year: 2024
Funding agency: Veterans Affairs

Quality of life following surgery is critically important to Veterans, their families, and the VA Healthcare
System—especially for frail patients who are less likely to be discharged to home, more likely to be readmitted
within 30 days, and have substantially increased rates of postoperative mortality and complications. A
substantial survival benefit occurs for frail patients when surgeons preoperatively screen for frailty and adjust
treatment plans accordingly. Although survival is an important outcome for frail patients, many prioritize quality
of life based on preservation of independence. Yet data about long-term independence after surgery is lacking
because surgical registries focus on 30-day outcomes and typically do not assess functional status or other
more patient-centered quality measures. Discharge rates to skilled nursing facilities after major surgery range
from 30% to 40% for frail patients living at home preoperatively, but this is not unexpected as they are likely to
benefit from short-term rehabilitation. However, critical knowledge gaps exist regarding (a) whether these
patients regain their independence or remain institutionalized; and (b) how to effectively communicate those
perioperative risks to support shared decisions about surgical treatment aligned with patients' values.
 Postoperative Loss of Independence (LOI) is a critically important, but difficult to measure patient-centered
outcome, encompassing a broad range of activities important to patients. Here we narrowly define LOI as the
number of days living elsewhere than home after presenting from home for the index surgery. LOI may resolve
quickly (i.e., short-term LOI) or become protracted/permanent (i.e., long-term LOI). Risk factors for long-term
LOI are unknown, but likely include frailty, emergency surgery, and procedures that impose high physiological
stress. Prognosis regarding potential LOI is essential for surgeons and patients to make better-informed
decisions about surgical treatment that align with patients' goals and values. Specifically, we aim to:
Aim 1: Characterize common trajectories of postoperative LOI in the 365 days after surgery to describe
clinically meaningful heterogeneity in the patterns of healthcare utilization and their associations with frailty,
emergency surgery, and operative stress. In a large Veteran sample, we will quantify the setting and duration
of healthcare utilization in the year following surgery, modeling trajectories of LOI and associated risk factors.
We hypothesize that LOI will be more common among the frail and after both emergency and high-stress
surgery.
Aim 2: Adapt the Risk Analysis Index (RAI) to predict long-term LOI and explore alternative models for LOI
prediction. The RAI is a 14-item survey measure of surgical frailty that requires 30 seconds to administer at the
point-of-care and predicts postoperative mortality and complications. We will adapt the RAI to build, calibrate,
and validate models predicting long-term LOI and explore alternative models predicting LOI using variables in
the Electronic Health Record and existing risk measures. We hypothesize that item responses from the RAI
can accurately predict LOI at the point of care.
Aim 3: Explore key stakeholders' perspectives on how LOI risk prognosis might better align shared decisions
about surgical treatment with patients' values and goals. We will conduct focus groups with surgeons and
semi-structured interviews with patients and their caregivers to explore perspectives on perioperative risks and
strategies for aligning shared decisions with patients' values. Research will focus on the factors surgeons,
patients, and their informal caregivers consider when making surgical treatment decisions, the relative
importance of LOI prognosis in this context, and how the risk of LOI can be best communicated and
operationally implemented to inform and improve preference-sensitive surgical choices.

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