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. 2015 Aug 20;17(8):e204.
doi: 10.2196/jmir.4427.

Analyzing Information Seeking and Drug-Safety Alert Response by Health Care Professionals as New Methods for Surveillance

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Free PMC article

Analyzing Information Seeking and Drug-Safety Alert Response by Health Care Professionals as New Methods for Surveillance

Alison Callahan et al. J Med Internet Res. .
Free PMC article

Abstract

Background: Patterns in general consumer online search logs have been used to monitor health conditions and to predict health-related activities, but the multiple contexts within which consumers perform online searches make significant associations difficult to interpret. Physician information-seeking behavior has typically been analyzed through survey-based approaches and literature reviews. Activity logs from health care professionals using online medical information resources are thus a valuable yet relatively untapped resource for large-scale medical surveillance.

Objective: To analyze health care professionals' information-seeking behavior and assess the feasibility of measuring drug-safety alert response from the usage logs of an online medical information resource.

Methods: Using two years (2011-2012) of usage logs from UpToDate, we measured the volume of searches related to medical conditions with significant burden in the United States, as well as the seasonal distribution of those searches. We quantified the relationship between searches and resulting page views. Using a large collection of online mainstream media articles and Web log posts we also characterized the uptake of a Food and Drug Administration (FDA) alert via changes in UpToDate search activity compared with general online media activity related to the subject of the alert.

Results: Diseases and symptoms dominate UpToDate searches. Some searches result in page views of only short duration, while others consistently result in longer-than-average page views. The response to an FDA alert for Celexa, characterized by a change in UpToDate search activity, differed considerably from general online media activity. Changes in search activity appeared later and persisted longer in UpToDate logs. The volume of searches and page view durations related to Celexa before the alert also differed from those after the alert.

Conclusions: Understanding the information-seeking behavior associated with online evidence sources can offer insight into the information needs of health professionals and enable large-scale medical surveillance. Our Web log mining approach has the potential to monitor responses to FDA alerts at a national level. Our findings can also inform the design and content of evidence-based medical information resources such as UpToDate.

Keywords: Internet log analysis; data mining; drug safety surveillance; information-seeking behavior; physicians.

Conflict of interest statement

Conflicts of Interest: Howard Strasberg is an employee of Wolters Kluwer.

Figures

Figure 1
Figure 1
Example of term expansion for HCUP CCS codes; each code is represented as its set of ICD-9 codes. The ICD-9 code for essential hypertension is expanded using the UMLS Metathesaurus to identify the n terms mapped to that concept. Each of the n terms (eg, “essential hypertension nos,” red) is used as a seed query to our custom lexicon to identify additional concepts and their terms. Here, “essential hypertension nos” maps to the concept hypertensive disease, and its additional m-1 terms (green) are used in combination with the n seed terms to identify searches corresponding to the HCUP CCS codes for hypertension.
Figure 2
Figure 2
Overview of the method used to analyze sequences of queries and topic views in UpToDate. Using unique session identifiers, we grouped queries and topic views, and ordered them by time of occurrence (green table). Frequently occurring sequences of topic views (orange boxes) were identified, as well as the search terms that initiated them (blue boxes). The numbers in parentheses show the frequency of occurrence of the specific term.
Figure 3
Figure 3
Most frequently searched diseases (top) and drugs (bottom) in 2011-2012.
Figure 4
Figure 4
Distribution of searches across organ systems. Each organ system name is followed by the percentage of queries related to that system. Each pie chart shows the distribution of searches for that organ system grouped by their term category, followed by the 10 most frequent and 10 least frequent terms searched for related to that system. Searches about diseases and symptoms (dark blue) dominated most systems. Searches about the endocrine system included a significant number of drug searches, followed by the cardiovascular system.
Figure 5
Figure 5
Medical conditions with the highest mean aggregate cost, discharge volume, and/or UpToDate query volume over 2011 and 2012. Each point is a single medical condition and the size of the point represents the query volume. The shape of the point indicates if it was ranked in the top 10 by aggregate cost, discharge volume, and/or query volume. Cost and discharge data were taken from the HCUP National Inpatient Sample.
Figure 6
Figure 6
Distribution of long clicks in UpToDate topics (left) and search terms (right). The dotted lines in the left panel indicate the threshold for low and high long-click proportions determined using the Hampel identifier for outliers.
Figure 7
Figure 7
Scaled 7-day moving average of UpToDate query volume (red), 7-day moving average of media activity (blue), and raw media activity volume (grey) related to Celexa prior to and following the August 24, 2011 FDA warning (date indicated by the green dotted line).

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