# Measuring, Mining and Understanding Communication Behaviors: Markers for Quality Healthcare

> **NIH VA I01** · EDITH NOURSE  ROGERS MEMORIAL VETERANS HOSPITAL · 2020 · —

## Abstract

Communication behaviors, including information seeking, information giving, and responding to emotions, can
be measured within in-person interpersonal health communication between Veterans and healthcare providers.
Investigators have developed reliable coding schemas to extract communication behaviors from audiotapes of
clinical encounters. Using these schemas, including the Roter Interaction Analysis System (RIAS), patterns of
communication behaviors have been positively associated with patient satisfaction, trust in providers, and
positive changes in Veteran self-management (e.g., medication adherence). Recently, RIAS has been adapted
for use with telehealth and asynchronous written communication (like email).
With the advent of Secure Messaging, VA has a new opportunity to directly measure communication behaviors
written into these messages. Over the past five years, our team has demonstrated that communication
behaviors are present in Secure Messages and can reliably be extracted using the same coding schemas
validated for in-person interpersonal exchanges.
In this project, we propose to advance knowledge and methods related to communication behaviors
measurable through asynchronous Secure Messages. We propose the following specific aims:
Specific Aim 1: Mine communication behaviors. Using a national corpus of Secure Messages, we will develop
a sentence classification system incorporating machine learning techniques to detect communication in Secure
Message responses from primary care doctors and clinical staff.
Specific Aim 2: Define communication behavior indicators (CBIs) that represent clinically meaningful measures
of Secure Message communication patterns between Veterans and Clinical Teams, then test the association of
CBIs with measures of Veteran Experience (2.a) and Patient-reported behavior (2.b), medication adherence.
We will identify and survey a sample of Veterans (CASES) with high CBI rates (top tertile) and a matched set
of (CONTROLS) with low rates (bottom tertile).
Aim 2.a Veteran experience with Secure Messaging and CBIs: We hypothesize (H1) that CASES (Veterans
with high rates of communication behaviors (CBIs)) will rate the experience with physician communication
through Secure Messaging more positively than CONTROL Veterans.
Aim 2.b. Veteran-reported medication adherence: In prior studies of in-person communication, patterns of
communication behaviors are strongly associated with measures of medication adherence. In our survey, we
will measure patient-reported medication adherence and assess the association of adherence reports with
secure messaging CBIs. We hypothesize (H2) that CASES will have better self-reported medication
adherence, compared with CONTROLS.
Specific Aim 3: Understand experiences of providers with high rates of CBIs in messages.
A high priority for the VA Under Secretary for Health is to collect and disseminate best practices in VA. In Aim
3, we will collect best practices from physicians (N = 30) with...

## Key facts

- **NIH application ID:** 9883635
- **Project number:** 5I01HX002289-03
- **Recipient organization:** EDITH NOURSE  ROGERS MEMORIAL VETERANS HOSPITAL
- **Principal Investigator:** Dezon Finch
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2018-01-01 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9883635

## Citation

> US National Institutes of Health, RePORTER application 9883635, Measuring, Mining and Understanding Communication Behaviors: Markers for Quality Healthcare (5I01HX002289-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9883635. Licensed CC0.

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