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The purpose of this paper is to test the usefulness of sentiment analysis and time-to-next-complaint methods in quantifying text-based information located on the internet. As important, the authors demonstrate how managers can use time-to-next-complaint techniques to organize sentiment analysis derived data into useful information, which can be shared with doctors and other staff.

The authors used sentiment analysis to review patient feedback for a select group of gynecologists in Virginia. The authors utilized time-to-next-complaint methods along with other techniques to organize this data into meaningful information.

The authors demonstrated that sentiment analysis and time-to-next-complaint techniques might be useful tools for healthcare managers who are interested in transforming web-based text into meaningful, quantifiable information.

This study has several limitations. For one thing, neither the data set nor the techniques the authors used to analyze it will account for biases that resulted from selection issues related to gender, income, and culture, as well as from other socio-demographic concerns. Additionally, the authors lacked key data concerning patient volumes for the targeted physicians. Finally, it may be difficult to convince doctors to consider web-based comments as truthful, thereby preventing healthcare managers from using data located on the internet.

The report illustrates some of the ways in which healthcare administrators can utilize sentiment analysis, along with time-to-next-complaint techniques, to mine web-based, patient comments for meaningful information.

The paper is one of the first to illustrate ways in which administrators at clinics and physicians’ offices can utilize sentiment analysis and time-to-next-complaint methods to analyze web-based patient comments.