# Analyzing Online Reviews to Evaluate Quality of Care at Substance Use Disorder Treatment Facilities

> **NIH NIH R21** · UNIVERSITY OF PENNSYLVANIA · 2020 · $243,000

## Abstract

In the United States (US), an estimated 20 million adults have been diagnosed with substance use
disorder (SUD). A major challenge for patients is to identify the most appropriate treatment with the best
outcomes. Patients receive care in outpatient and inpatient facilities yet quality metrics at the level of these
individual facilities are not publicly available.
 In the era of digital data, the Internet and peer-to-peer resources are often the first place where
individuals look to find information about healthcare resources. Online reviews on sites like Google and Yelp
provide narratives about healthcare facilities and assign easily interpretable star ratings ranging from one to
five stars. These reviews of healthcare facilities provide information about patient experience, structure (e.g.
physical
education)
facility, organizational characteristics, payment methods), process (e.g. diagnosis, treatment, patient
and outcomes (e.g. knowledge, health-related quality of life morbidity, mortality).
 Prior work has demonstrated that online ratings of hospitals correlate with ratings from the national
Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. Little work however
has evaluated the utility of unvalidated, spontaneously generated, but widely accessible online reviews of SUD
treatment facilities. These reviews could fill a niche with providing patients and their family members with
useful information about the questions and experiences that are most important to them. Or these reviews
could be limited and provide misinformation or only biased perspectives. To date, less is known about the
potential value or usefulness of this emerging data source.
 For this proposal we aim to study online reviews of SUD treatment facilities in the US to identify the
areas of care that are reported as most important to patients and family members. For Aim 1, we will first
extract approximately 50,000 online reviews of SUD treatment facilities and code them for themes using
qualitative methodologies that involve manual coding and big data analytics using machine learning and
natural language processing. We hypothesize that these online narratives will include qualitative data about
patient experience and the type and quality of care (e.g. evidence-based treatments) provided at SUD
treatment facilities. For Aim 2, we will then assess how star ratings differentiate facilities relative to structure
and process measures reported in the National Survey of Substance Abuse Treatment Services.
 Overall, emerging online data resources have the potential to provide new information about a critically
vulnerable population affected by the opioid and more broadly the SUD crisis. Our project seeks to rigorously
study these new patient-centric data sources viewed by millions of individuals for the purposes of better
understanding the needs of patients and family members. These efforts can lay the groundwork for future work
in developing measures of ...

## Key facts

- **NIH application ID:** 9956035
- **Project number:** 1R21DA050761-01
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Raina Merchant
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $243,000
- **Award type:** 1
- **Project period:** 2020-03-01 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9956035

## Citation

> US National Institutes of Health, RePORTER application 9956035, Analyzing Online Reviews to Evaluate Quality of Care at Substance Use Disorder Treatment Facilities (1R21DA050761-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9956035. Licensed CC0.

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