PEP Health's Peer-Reviewed Research Validates AI-Powered Patient Experience Platform as Early Indicator of Hospital Quality
MINNEAPOLIS, Aug. 6, 2025 /CNW/ - PEP Health, the AI-powered patient experience platform trusted by leading hospitals, payers, and health systems, announced the publication of its peer-reviewed research in The Journal of Patient Experience. The study validates PEP Health's proprietary technology, demonstrating that machine learning and natural language processing can accurately measure patient experience from unsolicited online reviews and serve as an early indicator of hospital quality performance.
The study, "Using Online Reviews to Drive Person-Centered Care: An HCAHPS-Validated Approach," analyzed 1.3 million online reviews across U.S. hospitals and found statistically significant alignment between PEP Health's automated analysis and HCAHPS Summary Star Ratings, establishing online patient feedback as a reliable proxy for gold-standard quality measures.
The full study is available here.
With healthcare organizations facing anticipated budget cuts following recent federal legislation, the ability to identify and address patient experience issues before they impact HCAHPS scores and reimbursement has become critical for financial sustainability.
"This peer-reviewed validation establishes that what patients say online provides an accurate, real-time measure of care quality," said Dr. Mark Lomax, CEO of PEP Health. "Healthcare leaders can now access validated patient experience insights months ahead of traditional surveys, enabling proactive interventions to improve outcomes and protect reimbursement before quality deterioration appears in official metrics."
Turning Unsolicited Feedback into Timely, Actionable Data
Collecting and analyzing unsolicited feedback at scale presents significant challenges. Online reviews are unstructured, feature slang, typos, and emojis, and are scattered across many diverse sources and platforms. PEP Health addresses this complexity through a proprietary approach that combines advanced machine learning with healthcare-specific natural language processing, trained on over 100,000 expertly annotated comments.
"We've demonstrated that hospitals performing well on HCAHPS show higher PEP Scores," said Dr. Joe Taylor, Head of Data Science at PEP Health and co-author of the study. "We can provide healthcare leaders with an early warning system that identifies quality trends as they emerge. This enables specific, actionable insights on where to focus improvement efforts for maximum impact, giving more time to generate the best possible results for both patients and reimbursement."
The research team achieved unprecedented accuracy levels:
99% accuracy in predicting overall patient experience scores
93-99% accuracy across seven domains of patient experience including Effective Treatment, Fast Access, and Emotional Support
Statistically significant agreement with HCAHPS across all 13 measure-domain pairings tested
Addressing Critical Gaps in Patient Experience Measurement
Traditional surveys like HCAHPS remain essential for performance evaluation and are directly tied to Medicare reimbursement. However, they are retrospective, slow, and often exclude key voices. Survey response rates continue to decline, dropping from 33% in 2008 to 24% in 2023.
Unsolicited online feedback offers a solution that's particularly valuable in today's environment. It's available daily, reflects a broader range of experiences, and captures perspectives from patients, family members, caregivers, and underrepresented populations without additional burden on patients or healthcare staff. Crucially, it provides health systems with specific priorities for improvement efforts, ensuring limited resources are directed where they can have the greatest impact on patient outcomes and financial performance.
According to the study:
"Patient experience is not 'just' part of quality; rather, a majority of patients cite quality, safety, and service as the key components of experience. Patient experience, whether positive or negative, is associated with profitability, patient loyalty and reduced risk of malpractice. Therefore, effective monitoring and interventions around patient experience not only lead to better health outcomes but also contribute to reduced readmission rates, higher patient retention, and lower operational costs."
Don't wait for HCAHPS scores to identify quality issues. Reach out directly to see how PEP Health can provide early warning indicators for your health system.
About PEP Health
PEP Health's advanced AI uses healthcare-specific natural language processing (NLP) and machine learning to analyze diverse, unsolicited patient feedback from online sources such as social media, review platforms, and forums, alongside hospital surveys and internal data. By providing a comprehensive, real-time view of patient and community experiences, PEP Health helps healthcare providers gain insights that traditional surveys often miss. This approach enables organizations to understand patient preferences more deeply, focus on what matters most, and align care more effectively with evolving expectations.
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