# Leveraging large-scale administrative claims data to evaluate prescription opioid use, risks, and outcomes in older adults living with HIV

> **NIH NIH K01** · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · 2024 · $196,106

## Abstract

PROJECT SUMMARY
The purpose of this Mentored Research Scientist Development Award (K01) is to provide support for me to
become an independent investigator with a multidisciplinary research program in HIV at the intersection of
prescription drug use, comorbidities, and aging. In this project, I propose to leverage existing administrative
claims data from Medicare beneficiaries ≥65 years of age from 2007-2018 to determine how high-risk prescription
opioid use, e.g. high dose use (≥120 mg/day) or prolonged use (≥90 days), affects health outcomes and health
care utilization in older people living with HIV (PLWH). Building on my strong foundation in HIV epidemiology
and HIV comorbidities across the lifespan, the training from this K01 will allow me to (1) obtain proficiency in the
analysis of large-scale, longitudinal administrative claims data; (2) attain content expertise in prescription drug
utilization research and pharmacoepidemiology; and (3) develop expertise in the application of machine learning
methods. My career development plan includes specific coursework, seminars, conferences, directed readings,
and tailored mentoring from a multidisciplinary team comprised of experts in administrative claims data,
substance use epidemiology, pharmacoepidemiology, and machine learning methods. Rutgers University
provides an exceptional environment for completion of this training, with research support and infrastructure for
analyzing large, multiyear datasets (including Medicare claims) and conducting high-impact HIV research. The
proposed research is significant given that a substantial gap exists in understanding how prescription opioid use
affects a growing population of aging PLWH who commonly report chronic pain, and have multiple comorbidities,
increasing polypharmacy, and increased risk for untoward drug-drug interactions. This research is critical to
target appropriate prevention and treatment programs to optimize health outcomes for this population. To fill this
gap, specific aims are to: (1) Assess the associations between HIV infection and a) adverse health outcomes
(e.g. falls/fractures, dementia, mortality) and b) health care utilization (e.g. emergency department use, inpatient
hospitalizations, and outpatient visits) among older adults, and estimate the interaction between HIV infection
and high-risk prescription opioid use on adverse outcomes and utilization; (2) Among older PLWH, estimate
drug-drug interactions between high-risk prescription opioid use and specific antiretroviral drug classes or
sedatives (e.g. benzodiazepines) on risk of adverse health outcomes and health care utilization; and (3) Examine
the feasibility of applying existing machine learning approaches to predict adverse health outcomes and high
health care utilization among older PLWH based on patient profiles and opioid prescription patterns in a large
administrative claims database. Findings from this project will generate valuable new information and tools to
suppo...

## Key facts

- **NIH application ID:** 10834292
- **Project number:** 5K01DA053157-05
- **Recipient organization:** RUTGERS BIOMEDICAL AND HEALTH SCIENCES
- **Principal Investigator:** Stephanie Shiau
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $196,106
- **Award type:** 5
- **Project period:** 2021-06-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10834292

## Citation

> US National Institutes of Health, RePORTER application 10834292, Leveraging large-scale administrative claims data to evaluate prescription opioid use, risks, and outcomes in older adults living with HIV (5K01DA053157-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10834292. Licensed CC0.

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