Do patients read emails from their physician containing tips on improving lifestyle habits? A pilot study.

INTRODUCTION: Healthcare providers and organizations occasionally use electronic messages to provide information to patients. There is insufficient data on whether patients actually read the emails they receive. In this study, we aimed to assess the cooperation of patients in reading multiple information pages sent over 6 months from their diabetologist via email. METHODS: Adults with non-optimally controlled type 2 diabetes received via email, once every 2 weeks for 6 months, a message containing information and tips on how to improve diabetes control through lifestyle choices. The information was provided in a format that required the recipient to actively click on a "read more" tab in order to reveal the entire text. Each email contained a short questionnaire requesting a response. Analysis compared the effect of patient variables on co-operation with reading the emails and answering the questionnaires. MAIN FINDINGS: 45 patients completed the study, 53.3% of them read 66-100% of the emails, 17.8% read 34-65% of the emails and only 26.7% read less than 33% of the emails. Women answered more questionnaires than men did. Answering a questionnaire on nutrition or medications correlated with reading the following email sent. CONCLUSIONS: This study is the first to demonstrate that most patients do indeed read a significant portion of emails sent by their physician. Email could be an effective means of sharing information and improving patient engagement with treatment.

Validation of New Signal Detection Methods for Web Query Log Data Compared to Signal Detection Algorithms Used With FAERS.

INTRODUCTION: Post-marketing drug surveillance is largely based on signals found in spontaneous reports from patients and healthcare providers. Rare adverse drug reactions and adverse events (AEs) that may develop after long-term exposure to a drug or from drug interactions may be missed. The US FDA and others have proposed that web-based data could be mined as a resource to detect latent signals associated with adverse drug reactions. METHODS: Recently, a web-based search query method called a query log reaction score (QLRS) was developed to detect whether AEs associated with certain drugs could be found from search engine query data. In this study, we compare the performance of two other algorithms, the proportional query ratio (PQR) and the proportional query rate ratio (Q-PRR) against that of two reference signal-detection algorithms (SDAs) commonly used with the FDA AE Reporting System (FAERS) database. RESULTS: In summary, the web query methods have moderate sensitivity (80%) in detecting signals in web query data compared with reference SDAs in FAERS when the web query data are filtered, but the query metrics generate many false-positives and have low specificity compared with reference SDAs in FAERS. CONCLUSION: Future research is needed to find better refinements of query data and/or the metrics to improve the specificity of these web query log algorithms.