Improving online physician evaluations for surgeons using sentiment analysis and alternative perspectives
Year: 2024
Type: article
Abstract: Dear Editor, The methods for analyzing Internet reviews of healthcare practitioners, especially surgeons with fellowship training, need to be critically examined and improved as the healthcare landscape changes.[1] Researchers can better comprehend patient attitudes and perceptions in online reviews by taking a multifaceted strategy that combines qualitative and quantitative methodologies. This will ultimately improve the caliber and applicability of future studies in this area. Patients frequently use physician review websites to locate, evaluate, and rate surgeons. Sentiment analysis, a type of natural language processing, offers a thorough method for comprehending the subtleties of patient perception.[1] Sentiment analysis, which examines the language used in patient reviews, can assist in identifying recurring themes, issues, and favorable features that patients bring up. Both patients looking for a surgeon and doctors themselves may find this information useful because it can give them insight into their strengths and places for development. Moreover, sentiment analysis can be used to evaluate patient satisfaction trends over time, giving surgeons the ability to monitor their performance and modify their practices as necessary. In the end, this may result in better patient outcomes and general satisfaction with the medical attention they receive. Moreover, sentiment analysis can assist in locating possible red flags or areas of worry that patients may bring up, enabling timely involvement and problem solving. Surgeons can develop trust with their patients and improve their reputation by responding promptly to patient feedback. We would want to offer different viewpoints on the analysis of Internet reviews of surgeons training in fellowships using sentiment analysis techniques like ChatGPT. The application of ChatGPT must be done carefully since it might not fully reflect the emotional complexity contained in the judgments.[2] The trustworthiness of the results is further compromised by the lack of transparency surrounding the patient rating criteria. Although sentiment analysis might yield insightful information on patient experiences and happiness, it might not necessarily offer a complete picture of a surgeon’s skill set. The reliability of sentiment analysis results can be affected by a number of factors, including sample size, bias, and the absence of clinical context in online evaluations. The possibility of prejudice or manipulation in Internet reviews is another angle to take into account. For instance, a surgeon’s reputation may be harmed by rivals or unhappy parties posting poor ratings, while friends or relatives may post excessively positive ones. It is important to recognize the possibility of bias and manipulation when analyzing sentiment analysis data. Future research directions could involve expanding the sample size by including a bigger and more diverse group of foot and ankle surgeons in order to improve the applicability of the findings. Furthermore, examining the effects of Internet reviews on patient choices and results, as well as the variables affecting how patients evaluate surgeons in light of these reviews, may yield insightful information. Integrating sophisticated sentiment analysis tools with qualitative techniques like focus groups and interviews could provide a deeper understanding of the opinions expressed in Internet reviews. This is to ensure a more thorough review of online physician assessments in the context of surgery.
Source: Formosan Journal of Surgery
Authors: Pathum Sookaromdee, Viroj Wiwanitkit
Institution: Chandigarh University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4402285582