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Using Google Trends to Predict Pediatric Respiratory Syncytial Virus Encounters at a Major Health Care System

  • Systems-Level Quality Improvement
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Abstract

To assess whether Google search activity predicts lead-time for pediatric respiratory syncytial virus (RSV) encounters within a major health care system. Internet user search and health system encounter database analysis. Pediatric RSV encounter volumes across all clinics and hospitals in the Duke Health system were tabulated from 2005 to 2016. North Carolina Google user search activity for RSV were obtained over the same time period. Time series analysis was used to compare RSV encounters and search activity. Cross-correlation was used to determine the ‘lag’ time difference between Google user search interest for RSV and observed Pediatric RSV encounter volumes. Google search activity and Pediatric RSV encounter volumes demonstrated strong seasonality with predilection for winter months. Granger Causality testing revealed that North Carolina RSV Google search activity can predict pediatric RSV encounters at our health system (F = 5.72, p < 0.0001). Using cross-correlation, increases in Google search activity provided lead time of 0.21 weeks (1.47 days) prior to observed increases in Pediatric RSV encounter volumes at our health system. RSV is a common cause of upper airway obstruction in pediatric patients for which pediatric otolaryngologists are consulted. We demonstrate that Google search activity can predict RSV patient interactions with a major health system with a measurable lead-time. The ability to predict when illnesses in a population result in increased health care utilization would be an asset to health system providers, planners and administrators. Prediction of RSV would allow specific care pathways to be developed and resource needs to be anticipated before actual presentation.

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Acknowledgements

The authors would like to thank Google for providing open-access to their search term database.

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Authors and Affiliations

  1. Department of Otolaryngology-Head & Neck Surgery, Sunnybrook Health Sciences Centre, Toronto, Ontario, M4N 3N5, Canada

    Matthew G. Crowson & Antoine Eskander

  2. Division of Otolaryngology-Head & Neck Surgery, Duke University Medical Center, Durham, NC, USA

    David Witsell

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  1. Matthew G. Crowson
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  2. David Witsell
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Correspondence to Matthew G. Crowson.

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Crowson, M.G., Witsell, D. & Eskander, A. Using Google Trends to Predict Pediatric Respiratory Syncytial Virus Encounters at a Major Health Care System. J Med Syst 44, 57 (2020). https://doi.org/10.1007/s10916-020-1526-8

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