# Adapting & Evaluating Measures of Decision Quality for Common Medical Decisions

> **NIH AHRQ R01** · MASSACHUSETTS GENERAL HOSPITAL · 2020 · $466,548

## Abstract

Project Summary/Abstract
In 2004, the investigators started working to develop measures of “decision quality” and
“decision making process” that focus on three elements—the extent to which the patient (1)
understands the options and their pros and cons, (2) is meaningfully involved the decision-
making process and (3) receives treatment that reflects their goals. Since then, the investigators
have produced fourteen decision-specific Decision Quality Instruments and a generic Shared
Decision Making (SDM) Process survey to assess these three elements. They recently received
endorsement by the National Quality Forum for two performance measures based on these
surveys for specific elective surgical decisions.
The investigators have amassed a large amount of data on the SDM Process survey in different
medical contexts, with different patients, using different modes of administration. However, there
has not yet been any systematic examination of existing data to determine the best ways to
word items and whether or how the items should vary based on aspects of the clinical decision.
Further, the survey has been predominantly used in adults 40 and older, with a major focus on
elective surgery decisions. As a result, there is still much work to be done to extend
generalizability of the SDM Process survey.
In this proposal, the investigators will make significant improvements to the SDM Process
survey and will extend its generalizability. We will conduct secondary analyses of existing data
from more than 13,000 respondents and compare performance across clinical topics (Aim 1),
we will conduct targeted online field tests with 2,000 respondents to evaluate alternative
approaches to wording items and to extend generalizability to younger adults and parents
making decisions for their children (Aim 2), and we will conduct field tests in clinical settings that
have decision support programs in order to establish validity and feasibility (Aim 3). The
adapted measure will be practical and feasible to implement, with strong psychometric
properties. The measure and associated user guides will provide researchers and clinicians a
clear means to evaluate shared decision making and compare different decision support
strategies designed to improve the quality of medical decisions.

## Key facts

- **NIH application ID:** 9965910
- **Project number:** 5R01HS025718-03
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** KAREN R SEPUCHA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2020
- **Award amount:** $466,548
- **Award type:** 5
- **Project period:** 2018-09-01 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9965910

## Citation

> US National Institutes of Health, RePORTER application 9965910, Adapting & Evaluating Measures of Decision Quality for Common Medical Decisions (5R01HS025718-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9965910. Licensed CC0.

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