{
  "abstract": "Objective\n\nPatients increasingly describe care in their own words on public review platforms, but this evidence has been too large and unstructured to use. We aimed to develop and validate a reproducible artificial intelligence (AI)-based method to make this source usable and apply it to cardiac surgery.Methods\n\nPatient comments on online platforms (2020-2026) were collected. Cardiac surgery comments were identified by registered specialty or, where absent, by key word filtering and AI classification (Claude API [Anthropic], validated by physician, 95% sensitivity, and 85% specificity). Sentiment and praise and complaint themes were classified by the same approach and validated by a psychologist (91% accuracy). Cardiac surgery was compared against 4 noncardiac surgery groups, and 6 cardiac surgery subgroups were compared using Wilcoxon rank-sum tests for comment ratings and χ² tests for theme comparisons.Results\n\nOf 28.8 million comments, 14,678 cardiac surgery comments were identified. Sentiment was positive in 82%. Cardiac surgery rated higher than every noncardiac comparator, including clinically comparable specialties (4.31 vs 4.13; P < .001). The most common complaints were interpersonal (unprofessionalism, coldness, dismissiveness, and poor communication), whereas surgical complications ranked sixth. Among subgroups, aortic surgery alone rated significantly higher; transplant patients showed uniquely lower praise across themes, whereas congenital surgery combined elevated gratitude with the only elevated complaint theme.Conclusions\n\nPatients describe cardiac surgical care with overwhelming gratitude and rate it above every comparator group examined. Where they voice dissatisfaction, it centers on how patients are treated as people rather than on the surgical outcomes, identifying communication as the principal target for improvement.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Cardiovascular Sciences, East Carolina University, Greenville, NC.",
    "Department of Psychology, East Carolina University, Greenville, NC.",
    "PEP Health Inc, Kansas City, Mo.",
    "ECU Health, Greenville, NC.",
    "Division of Cardiac Surgery, Department of Surgery, Johns Hopkins University, Baltimore, Md."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "M Melih Dogan"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Samuel F Sears"
    },
    {
      "affs": [
        2
      ],
      "name": "Verena Sarrazin"
    },
    {
      "affs": [
        1
      ],
      "name": "Dina Dejanovic"
    },
    {
      "affs": [
        1
      ],
      "name": "Maeve M Sargeant"
    },
    {
      "affs": [
        3
      ],
      "name": "Julie Oehlert"
    },
    {
      "affs": [
        2
      ],
      "name": "Joseph G Taylor"
    },
    {
      "affs": [
        4
      ],
      "name": "Ahmet Kilic"
    },
    {
      "affs": [
        0
      ],
      "name": "Shahab A Akhter"
    },
    {
      "affs": [
        0
      ],
      "name": "Michael J Bates"
    },
    {
      "affs": [
        0
      ],
      "name": "Walter Douglas Boyd"
    },
    {
      "affs": [
        0
      ],
      "name": "Wiley L Nifong"
    },
    {
      "affs": [
        0
      ],
      "name": "Benjamin C Degner"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2ndq2vwfwjanp.bib",
  "cited_by": 0,
  "doi": "10.1016/j.xjon.2026.102075",
  "fulltext_url": "https://europepmc.org/articles/PMC13711192",
  "id": "2ndq2vwfwjanp",
  "issns": [
    "2666-2736"
  ],
  "landing_url": "https://europepmc.org/article/MED/42948423",
  "language": "eng",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Adult: Education: Evolving Technology"
    ],
    [
      "openalex",
      "3600|Patient Satisfaction in Healthcare"
    ]
  ],
  "openalex": "W7203945172",
  "pdf_url": "https://europepmc.org/articles/PMC13711192?pdf=render",
  "pmcid": "PMC13711192",
  "pmid": "42948423",
  "published": "2026-08-21",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/2ndq2vwfwjanp.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T00:20:35Z",
      "native_id": "MED:42948423",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42948423"
    },
    {
      "first_seen": "2026-10-31T12:22:00Z",
      "native_id": "PMC13711192",
      "source": "pmc",
      "url": "https://doi.org/10.1016/j.xjon.2026.102075"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "journal-openalex:F27",
      "subfield": "general"
    }
  ],
  "title": "Compliments to the surgeon: An artificial intelligence-based analysis of online patient reviews on cardiac surgical care in the United States.",
  "title_text": "Compliments to the surgeon: An artificial intelligence-based analysis of online patient reviews on cardiac surgical care in the United States.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-31T12:22:00Z",
  "url": "https://research.draconitic.com/paper/2ndq2vwfwjanp",
  "venue": "JTCVS open",
  "versions": []
}