# Informatics approaches to assessing patient frailty in surgical care

> **NIH NIH R01** · KAISER FOUNDATION RESEARCH INSTITUTE · 2020 · $629,037

## Abstract

ABSTRACT
Surgical complications are common, costly, and deadly. Older patients are at high risk of adverse surgical
outcomes, especially when they exhibit frailty. Frailty is a state of decreased physiologic reserve and loss of
capacity to adapt to stressors. Over the past decade, while frailty has been increasingly recognized as an
important risk factor for poor surgical outcomes, integration of a standardized frailty metric into clinical care has
not been achieved. A key barrier is that existing frailty assessments are not standardized, objective, or widely
available, limiting their routine application in surgical decision-making. With the long-term goal of improving
surgical care for older adults, we will evaluate two “e-frailty” metrics that can be automatically derived from
electronic or digital data that are already collected as part of routine clinical care. These e-frailty metrics
include, first, granular patient profiles of electronic health record (EHR) data (risk scores based on claims data
or on physiologic and laboratory values), and second, muscle loss assessed from pre-surgical computed
tomography (CT) scans (low skeletal muscle mass, known as sarcopenia, and fatty infiltration into muscle
indicative of reduced physical function, known as myosteatosis). In Aim 1, we will calculate these two e-frailty
metrics among a diverse population of over 41,000 abdominal surgical patients; characterize the overlap
between patients designated as frail by the two e-frailty metrics; and evaluate their associations with 30-day
readmission and other adverse surgical outcomes (30-day and 1-year mortality, complications, non-home
discharge, and length of stay >7 days). In Aim 2, we will compare the performance of e-frailty metrics for
predicting 30-day readmission and other adverse surgical outcomes to that of standard risk stratification tools
(acute and chronic illness severity metrics) already embedded in EHRs today using cross-validation and an
independent validation dataset of over 14,000 more recent abdominal surgeries. In Aim 3, we will examine
whether e-frailty metrics modify the benefits that patients derive from achieving postoperative targets -including
early and sustained mobilization- in one of the largest Enhanced Recovery After Surgery (ERAS) programs in
the nation. We will examine e-frailty metrics as salient indicators of biologic age for predicting morbidity and
mortality. In sum, e-frailty metrics show great promise for identifying high-risk patients in the surgical domain,
but they need to be integrated within clinical workflows to be scalable and sustainable. This proposal will
compute standardized e-frailty metrics automatically derived from EHR data and provide new information
regarding the potential value of these e-frailty metrics for improving surgical care for older adults. This study
will also lay the groundwork for future prospective interventions integrating e-frailty metrics into clinical care to
improve risk stratifica...

## Key facts

- **NIH application ID:** 10051346
- **Project number:** 1R01AG065334-01A1
- **Recipient organization:** KAISER FOUNDATION RESEARCH INSTITUTE
- **Principal Investigator:** Elizabeth Marjorie Cespedes Feliciano
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $629,037
- **Award type:** 1
- **Project period:** 2020-09-01 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10051346

## Citation

> US National Institutes of Health, RePORTER application 10051346, Informatics approaches to assessing patient frailty in surgical care (1R01AG065334-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10051346. Licensed CC0.

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