# Identifying Networks of Transmission by Examining Routines of Action, Contact, and Thinking (INTERACT)

> **NIH VA I01** · VA SALT LAKE CITY HEALTHCARE SYSTEM · 2020 · —

## Abstract

Controlling the spread of healthcare associated infections is a priority to reduce morbidity, mortality, and cost.
Interventions and control strategies abound but have had inconsistent impacts. Intervention decisions are often
based on model or simulation outputs that depend on input data and generally focus on one facility. Poor hand
hygiene adherence contributes to the spread of disease and attempts to improve hand hygiene adherence
have limited documented effect. The adherence measurements are based on observation and therefore error-
prone, so actual adherence rates before and after interventions are uncertain in most studies. Transmission of
disease occurs during contact between providers and between providers and patients. A recent study linking
transmission to an observed contact network has clearly revealed the need for more data on contact. Limited
small scale studies have used the electronic health record to create contact networks and wireless sensors to
measure hand hygiene adherence and capture contact networks. Healthcare provider behaviors (contact and
hand hygiene) vary among individuals, wards, and facilities so larger scale studies are needed in order to
understand behavior across different facilities. Models to evaluate interventions must also consider multiple
facilities and take these differences into account.
We propose to extend the use of electronic health record and wireless sensor methods to multiple facilities in
the Veterans Affairs Medical Centers (VAMC's) and expand model simulations to estimate and incorporate
differences among facilities to evaluate control strategies for healthcare associated infections.
Using the electronic health record we will link patients to providers who write notes in their record, thus creating
a contact network. We will do this for 3 years of data from 78 VAMC's representing complexity and regions. We
will use wireless sensors in three of these VAMC's to collect contact network and hand hygiene data. Wireless
sensors detect proximity between people, occupancy of a room, and use of alcohol-based hand sanitizer and
soap dispensers and sinks. There will be two two-week deployments at each site. An existing one-facility agent
based model simulation will be expanded to input contact network and hand hygiene adherence data and be
calibrated to multiple facilities.
The data will be used to estimate differences in contact network characteristics among wards and facilities.
Explanations for differences in contact networks may be due to different staff mixes, use of consults, types of
wards, or even regional social norms. Hand hygiene rates will be assessed for differences among wards,
health care provider roles, self-reported beliefs, and care situations. We hypothesize that differences will shed
light on when, where, and by who hand hygiene adherence breaks down and therefore can lead to
improvements. The expanded agent based model simulations will be used to evaluate interventions at multiple
fa...

## Key facts

- **NIH application ID:** 10038294
- **Project number:** 5I01HX002060-02
- **Recipient organization:** VA SALT LAKE CITY HEALTHCARE SYSTEM
- **Principal Investigator:** Molly Leecaster
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2016-10-01 → 2020-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10038294

## Citation

> US National Institutes of Health, RePORTER application 10038294, Identifying Networks of Transmission by Examining Routines of Action, Contact, and Thinking (INTERACT) (5I01HX002060-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10038294. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*