# Measuring Chronic Pain Impact

> **NIH NIH R01** · RAND CORPORATION · 2022 · $168,515

## Abstract

Summary/Abstract
Collection of individual patient-reported outcome (PRO) data in clinical contexts is increasing and has been
shown to enhance clinician-patient communication. It can be used to identify patient priorities and preferences,
set treatment expectations, and support shared decision-making. At an aggregate level, PROs can be used to
examine the clinical- and cost-effectiveness of treatments, measure and monitor quality, and optimize planning
and delivery of healthcare services. The Patient-Reported Outcome Measurement Information System
(PROMIS®) measures are attractive for use in clinical settings because of their psychometric soundness,
straightforward interpretation, and standardized metrics normed to the general population. However, the
existing PROMIS Profile measures are burdensome for routine clinical use, leading many to opt for shorter
more limited measures within or outside the PROMIS library. Our overarching goal is to plan and conduct
complex statistical analyses, including item response theory analyses to fill this gap by identifying a
brief and psychometrically sound measure that future researcher can use to examine impacts of their
interventions on whole person health outcomes that matter most to patients. Specifically, we propose to
develop a Short PROMIS Profile measure (SPP) that can: 1) efficiently produce scores for eight health
domains (i.e., physical function, pain interference, fatigue, sleep disturbance, depression, anxiety, social role
participation, cognitive function); 2) generate physical and mental health summary scores; and 3) calculate the
PROMIS preference (PROPr) score. Our approach includes ongoing input from invested stakeholders who will
work closely with the study to ensure broad buy-in for the resulting SPP. Through our work on the parent grant,
our study team has identified 50 unique PROMIS items for possible inclusion in the SPP and has access to a
data source that includes responses to all candidate items. We will conduct analyses using the existing data
and arrive at an optimal SPP through completion of the following specific aims: 1. Construct several candidate
SPPs by identifying and combining optimally performing two-item sets for each of the 8 PROMIS domains
being considered for inclusion in the SPP; 2. Reduce and refine the number of candidate measures based on:
a) performance of general physical and mental health summary scores derived from factor analysis; and b)
evaluation of candidate profile measures’ estimated PROPr scores; and 3. Select the final SPP specification in
collaboration with the stakeholder group based on results from Aim 2. At the completion of these three aims we
will have a robust SPP that can be included in the PROMIS library and made available for general use. The
availability of this measure has the potential to significantly impact the frequency and usefulness of routine
PRO data collection in clinical care and will also enable behavioral health researchers and cli...

## Key facts

- **NIH application ID:** 10609108
- **Project number:** 3R01AT010402-03S1
- **Recipient organization:** RAND CORPORATION
- **Principal Investigator:** RONALD Dale HAYS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $168,515
- **Award type:** 3
- **Project period:** 2020-02-15 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10609108

## Citation

> US National Institutes of Health, RePORTER application 10609108, Measuring Chronic Pain Impact (3R01AT010402-03S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10609108. Licensed CC0.

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