We have all read of the negative side of data mining (e.g. to manipulate elections, reviews, advertising, etc.). This is an interesting and, hopefully, somewhat more positive direction.
My personal experience of WebMD has not been that good, but the message boards/forums might have much the same issues as anywhere else.
(Be aware, if you are not in the USA, you might be diverted to a local WebMD - such as Boots in the UK.)
This sentence is concerning:
Furthermore, treatment satisfaction on levothyroxine depended on what primary medication concerns the patient had.
Isn't it likely that people post about primary medication concerns precisely because their treatment satisfaction isn't that good?
J Med Internet Res. 2018 Oct; 20(10): e11085.
Published online 2018 Oct 24. doi: 10.2196/11085
PMCID: PMC6231751
PMID: 30355555
Identification of Primary Medication Concerns Regarding Thyroid Hormone Replacement Therapy From Online Patient Medication Reviews: Text Mining of Social Network Data
Monitoring Editor: Gunther Eysenbach
Reviewed by Judith Taylor and Tinh-Hai Collet
So Hyun Park, PharmD#1,2 and Song Hee Hong, PhD
1 Research Institute of Pharmaceutical Science, College of Pharmacy, Seoul National University, Seoul, Republic Of Korea
2 Korea Institute of Drug Safety and Risk Management, Drug Safety Information Office of Adverse Drug Reaction Relief, Anyang, Republic Of Korea
Abstract
Background
Patients with hypothyroidism report poor health-related quality of life despite having undergone thyroid hormone replacement therapy (THRT). Understanding patient concerns regarding levothyroxine can help improve the treatment outcomes of THRT.
Objective
This study aimed to (1) identify the distinctive themes in patient concerns regarding THRT, (2) determine whether patients have unique primary medication concerns specific to their demographics, and (3) determine the predictability of primary medication concerns on patient treatment satisfaction.
Methods
We collected patient reviews from WebMD in the United States (1037 reviews about generic levothyroxine and 1075 reviews about the brand version) posted between September 1, 2007, and January 30, 2017. We used natural language processing to identify the themes of medication concerns. Multiple regression analyses were conducted in order to examine the predictability of the primary medication concerns on patient treatment satisfaction.
Results
Natural language processing of the patient reviews of levothyroxine posted on a social networking site produced 6 distinctive themes of patient medication concerns related to levothyroxine treatment: how to take the drug, treatment initiation, dose adjustment, symptoms of pain, generic substitutability, and appearance. Patients had different primary medication concerns unique to their gender, age, and treatment duration. Furthermore, treatment satisfaction on levothyroxine depended on what primary medication concerns the patient had.
Conclusions
Natural language processing of text content available on social media could identify different themes of patient medication concerns that can be validated in future studies to inform the design of tailored medication counseling for improved patient treatment satisfaction.
Keywords: medication counseling, social network data, primary medication concerns, satisfaction with levothyroxine treatment
Full paper freely available here: