# Provider and Patient-generated Remote Oro-Dental Health Electronic Data Capture for Algorithmic Longitudinal Evaluation and Risk-Assessment (PROHEALER)

> **NIH NIH K01** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2022 · $159,539

## Abstract

PROJECT SUMMARY/ABSTRACT
Research. Oral cavity and oropharyngeal (OC/OPC) cancers afflict more than 53,000 individuals in the United
States annually. Despite advancements in oncologic therapies, the majority of patients will experience significant
toxicity burden during and after therapy, including moderate-severe xerostomia, dysphagia, reduced mouth
opening (i.e. trismus), periodontal disease, and osteoradionecrosis. Remote electronic symptom monitoring
through standardized assessment tools for patient reported outcomes (ePROs) is an evidence-based best
practice, particularly in the COVID-19 era, yet few clinical practices have demonstrated sustainability of
implementation efforts. To date, acute and chronic orodental complications afflicting OC/OPC survivors are
largely managed on empirical knowledge with wide inter-provider management variability based on provider
experience and available clinical information which is often incomplete, incorrect, or nonexistent. Therefore,
standardization of electronic data capture of PROs and objective measures of provider-assessed orodental
toxicity severity remains an unmet public health need. Our central hypothesis is that synchronous optimization
of machine-readable patient- and provider-generated data collection can be achieved through prioritization of
effective implementation strategies for longitudinal oro-systemic ePRO data collection (Aim 1) and creation of
novel dental standards for accurate orodental toxicity reporting in both electronic health and dental records (Aim
2). As a subcomponent to Aim 2, we will also design and pilot a novel radiation odontogram to enhance treatment
communication between providers. Accurate risk predictions of high-morbidity high-prevalence post-therapy
orodental sequelae using high-quality electronic data from Aims 1 and 2 will be incorporated into a statistically
robust machine-learning based model (Aim 3). In summary, the PROHEALER proposal fosters innovative and
novel informatics approaches for data-driven risk assessment and algorithmic prevention and management of
treatment-related oral health diseases afflicting OC/OPC survivors.
Career Development & Training. Dr. Moreno's overarching goal is to become an internationally recognized
independent research investigator with domain expertise in advanced radiation therapy techniques, clinical
informatics and rigorous toxicity modeling methodologies as they pertain to improving patient quality of life and
promoting precision prevention and risk-based interventions for orodental complications. This proposal presents
Dr. Moreno's 5-year mentored career development plan which includes mentorship from prominent Established
NIH Investigators who have committed to overseeing the progress of the proposed projects and Dr. Moreno's
overall professional development. The outlined training activities build upon Dr. Moreno's clinical expertise as a
Head and Neck Cancer Radiation Oncologist and her prior work in EHR utility enhancem...

## Key facts

- **NIH application ID:** 10449579
- **Project number:** 1K01DE030524-01A1
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** Amy Catherine Moreno
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $159,539
- **Award type:** 1
- **Project period:** 2022-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10449579

## Citation

> US National Institutes of Health, RePORTER application 10449579, Provider and Patient-generated Remote Oro-Dental Health Electronic Data Capture for Algorithmic Longitudinal Evaluation and Risk-Assessment (PROHEALER) (1K01DE030524-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10449579. Licensed CC0.

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