# Improving Palliative Measurement Application with Computer-Assisted-Abstraction Study

> **NIH VA I01** · VETERANS ADMIN PALO ALTO HEALTH CARE SYS · 2022 · —

## Abstract

Background: VA needs to incorporate the Veteran and family voice in measuring performance, and it may
improve care to involve Veterans and families more deeply in improvement. This is especially true for
palliative and end of life care, given the 30% of lifetime Medicare costs in the last year of life, and the
divergent perspectives that Americans have expressed regarding end of life care. We have identified major
gaps in VA performance, but work is needed to prioritize indicators from the Veteran and family
perspective and to improve measure feasibility. The latter will foster better VA quality and experience of
care and facilitate monitoring the potential impact of paid, non-VA care on seriously ill Veterans.
Aims: The Improving Palliative Measurement Application with Computer-Assisted-Abstraction Study
(ImPACS), will prioritize measures and operationalize a subset of higher, intermediate, and lower feasibility
process and utilization measures for palliative and end of life cancer care. We aim to:
Aim 1: Solicit priorities from two Delphi panels - one of Veterans and families and a second of experts
regarding process and healthcare use quality measures for advanced cancer care, including which of the
42 Cancer Quality ASSIST measures to extract, and conduct interviews regarding how to integrate
Veterans and families in VA measurement and improvement for palliative and end of life cancer care, and
Aim 2: Extract high priority process and utilization measures using natural language processing of VA
charts and administrative data and in a sample drawn from Stanford and Dana Farber’s Healthcare's
Epic systems, focusing on the domains of pain and opioids, mental health, and goals of care
communication, and
Aim 3: Examine associations of the extracted measures with Veteran characteristics, focusing on
disparities in the care of rural and nonwhite Veterans and palliative care use.
Methods: For Aim 1, we will recruit two Delphi panels - one of Veterans, family members, and a second of
expert stakeholders. Veteran-family members will have experience with cancer. Experts will have expertise
in the methods and application of quality measures. Purposive sampling will focus on critical attributes
(e.g., race) that may affect priorities. Panelists will rate and rank measures within tiers of high,
intermediate, and low feasibility, informed by reviews of the evidence for intervention and impact of
performance gaps on patients and caregivers. We will also interview Veterans, family members and VA
leaders at high and low performing VA facilities based on the Bereaved Family Survey of end of life
experience, to see how deeper Veterans-family involvement might strengthen quality and experience of
end of life care. For Aim 2, we will operationalize a subset of prioritized process measures from Aim 1
including Cancer Quality ASSIST measures using natural language processing of text notes and machine
learning. In Aim 3, we will characterize variation in measures wit...

## Key facts

- **NIH application ID:** 10305693
- **Project number:** 5I01HX002513-04
- **Recipient organization:** VETERANS ADMIN PALO ALTO HEALTH CARE SYS
- **Principal Investigator:** Karl Lorenz
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2022
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2018-10-01 → 2024-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10305693

## Citation

> US National Institutes of Health, RePORTER application 10305693, Improving Palliative Measurement Application with Computer-Assisted-Abstraction Study (5I01HX002513-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10305693. Licensed CC0.

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