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

Callahan, Alison; Pernek, Igor; Štiglic, Gregor; Leskovec, Jure; Strasberg, Howard R.; Shah, Nigam H.

doi:10.2196/jmir.4427

Cited by 13 publications

(15 citation statements)

References 28 publications

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“…Earlier studies on health information-seeking behavior of Internet users have studied the relationship between search behavior and health concerns of search users. For instance, it has been shown that physician information-seeking behavior, as assessed by the mean page view duration for specific websites, is distinct from general online media activity [ 19 ]. Health anxiety in patients has also been shown to be associated with specific search patterns, such as intense search activity punctuated by periods of calm [ 20 ].…”

Section: Methodsmentioning

confidence: 99%

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis

Agarwal¹,

Zhang²,

Zhu³

et al. 2016

J Med Internet Res

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BackgroundBy recent estimates, the steady rise in health care costs has deprived more than 45 million Americans of health care services and has encouraged health care providers to better understand the key drivers of health care utilization from a population health management perspective. Prior studies suggest the feasibility of mining population-level patterns of health care resource utilization from observational analysis of Internet search logs; however, the utility of the endeavor to the various stakeholders in a health ecosystem remains unclear.ObjectiveThe aim was to carry out a closed-loop evaluation of the utility of health care use predictions using the conversion rates of advertisements that were displayed to the predicted future utilizers as a surrogate. The statistical models to predict the probability of user’s future visit to a medical facility were built using effective predictors of health care resource utilization, extracted from a deidentified dataset of geotagged mobile Internet search logs representing searches made by users of the Baidu search engine between March 2015 and May 2015.MethodsWe inferred presence within the geofence of a medical facility from location and duration information from users’ search logs and putatively assigned medical facility visit labels to qualifying search logs. We constructed a matrix of general, semantic, and location-based features from search logs of users that had 42 or more search days preceding a medical facility visit as well as from search logs of users that had no medical visits and trained statistical learners for predicting future medical visits. We then carried out a closed-loop evaluation of the utility of health care use predictions using the show conversion rates of advertisements displayed to the predicted future utilizers. In the context of behaviorally targeted advertising, wherein health care providers are interested in minimizing their cost per conversion, the association between show conversion rate and predicted utilization score, served as a surrogate measure of the model’s utility.ResultsWe obtained the highest area under the curve (0.796) in medical visit prediction with our random forests model and daywise features. Ablating feature categories one at a time showed that the model performance worsened the most when location features were dropped. An online evaluation in which advertisements were served to users who had a high predicted probability of a future medical visit showed a 3.96% increase in the show conversion rate.ConclusionsResults from our experiments done in a research setting suggest that it is possible to accurately predict future patient visits from geotagged mobile search logs. Results from the offline and online experiments on the utility of health utilization predictions suggest that such prediction can have utility for health care providers.

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Section: Methodsmentioning

confidence: 99%

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis

Agarwal¹,

Zhang²,

Zhu³

et al. 2016

J Med Internet Res

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“…On the other hand, more and more physicians use the convenience of the Internet to search drug information [8] and Web-based evidence sources such as UpToDate [9] for providing better medical care to patients.…”

Section: Introductionmentioning

confidence: 99%

The Association Between Internet Use and Ambulatory Care-Seeking Behaviors in Taiwan: A Cross-Sectional Study

Hsieh

Chen

et al. 2016

J Med Internet Res

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BackgroundCompared with the traditional ways of gaining health-related information from newspapers, magazines, radio, and television, the Internet is inexpensive, accessible, and conveys diverse opinions. Several studies on how increasing Internet use affected outpatient clinic visits were inconclusive.ObjectiveThe objective of this study was to examine the role of Internet use on ambulatory care-seeking behaviors as indicated by the number of outpatient clinic visits after adjusting for confounding variables.MethodsWe conducted this study using a sample randomly selected from the general population in Taiwan. To handle the missing data, we built a multivariate logistic regression model for propensity score matching using age and sex as the independent variables. The questionnaires with no missing data were then included in a multivariate linear regression model for examining the association between Internet use and outpatient clinic visits.ResultsWe included a sample of 293 participants who answered the questionnaire with no missing data in the multivariate linear regression model. We found that Internet use was significantly associated with more outpatient clinic visits (P=.04). The participants with chronic diseases tended to make more outpatient clinic visits (P<.01).ConclusionsThe inconsistent quality of health-related information obtained from the Internet may be associated with patients’ increasing need for interpreting and discussing the information with health care professionals, thus resulting in an increasing number of outpatient clinic visits. In addition, the media literacy of Web-based health-related information seekers may also affect their ambulatory care-seeking behaviors, such as outpatient clinic visits.

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“…However, in search engines providing access to a specific type of content or collection ("vertical search engines"), the search functionality is often different, hence, user behavior can be expected to differ. This has been shown, for example, for image archives (Han and Wolfram, 2015;Hollink et al, 2011), a medical knowledge portal (Callahan et al, 2015), a newspaper archive (Gooding, 2016), and in a study of a digital library (Niu and Hemminger, 2015).…”

Section: Introductionmentioning

confidence: 84%

Metadata categorization for identifying search patterns in a digital library

Bogaard

Hollink

Wielemaker

et al. 2019

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For digital libraries, it is useful to understand how users search in a collection. Investigating search patterns can help them to improve the user interface, collection management and search algorithms. However, search patterns may vary widely in different parts of a collection. This study demonstrates how to identify these search patterns within a well-curated historical newspaper collection using the existing metadata. Design/methodology/approach: The authors analyzed search logs combined with metadata records describing the content of the collection, using this metadata to create subsets in the logs corresponding to different parts of the collection. Findings: The study shows that faceted search is more prevalent than non-faceted search in terms of number of unique queries, time spent, clicks and downloads. Distinct search patterns are observed in different parts of the collection, corresponding to historical periods, geographical regions or subject matter. Originality/value: First, this study provides deeper insights into search behavior at a fine granularity in a historical newspaper collection, by the inclusion of the metadata in the analysis. Second, it demonstrates how to use metadata categorization as a way to analyze distinct search patterns in a collection.

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

Cited by 13 publications

References 28 publications

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis

The Association Between Internet Use and Ambulatory Care-Seeking Behaviors in Taiwan: A Cross-Sectional Study

Metadata categorization for identifying search patterns in a digital library

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