0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Investigation |

Surveillance Tools Emerging From Search Engines and Social Media Data for Determining Eye Disease Patterns

Michael S. Deiner, PhD1; Thomas M. Lietman, MD1,2,3,4; Stephen D. McLeod, MD1,2; James Chodosh, MD, MPH5; Travis C. Porco, PhD, MPH1,2,3
[+] Author Affiliations
1Department of Ophthalmology, University of California San Francisco
2F. I. Proctor Foundation, University of California San Francisco
3Department of Epidemiology and Biostatistics, University of California San Francisco
4Global Health Sciences, University of California San Francisco
5Massachusetts Eye and Ear Infirmary, Department of Ophthalmology, Harvard Medical School, Boston
JAMA Ophthalmol. 2016;134(9):1024-1030. doi:10.1001/jamaophthalmol.2016.2267.
Text Size: A A A
Published online

Importance  Internet-based search engine and social media data may provide a novel complementary source for better understanding the epidemiologic factors of infectious eye diseases, which could better inform eye health care and disease prevention.

Objective  To assess whether data from internet-based social media and search engines are associated with objective clinic-based diagnoses of conjunctivitis.

Design, Setting, and Participants  Data from encounters of 4143 patients diagnosed with conjunctivitis from June 3, 2012, to April 26, 2014, at the University of California San Francisco (UCSF) Medical Center, were analyzed using Spearman rank correlation of each weekly observation to compare demographics and seasonality of nonallergic conjunctivitis with allergic conjunctivitis. Data for patient encounters with diagnoses for glaucoma and influenza were also obtained for the same period and compared with conjunctivitis. Temporal patterns of Twitter and Google web search data, geolocated to the United States and associated with these clinical diagnoses, were compared with the clinical encounters. The a priori hypothesis was that weekly internet-based searches and social media posts about conjunctivitis may reflect the true weekly clinical occurrence of conjunctivitis.

Main Outcomes and Measures  Weekly total clinical diagnoses at UCSF of nonallergic conjunctivitis, allergic conjunctivitis, glaucoma, and influenza were compared using Spearman rank correlation with equivalent weekly data on Tweets related to disease or disease-related keyword searches obtained from Google Trends.

Results  Seasonality of clinical diagnoses of nonallergic conjunctivitis among the 4143 patients (2364 females [57.1%] and 1776 males [42.9%]) with 5816 conjunctivitis encounters at UCSF correlated strongly with results of Google searches in the United States for the term pink eye (ρ, 0.68 [95% CI, 0.52 to 0.78]; P < .001) and correlated moderately with Twitter results about pink eye (ρ, 0.38 [95% CI, 0.16 to 0.56]; P < .001) and with clinical diagnosis of influenza (ρ, 0.33 [95% CI, 0.12 to 0.49]; P < .001), but did not significantly correlate with seasonality of clinical diagnoses of allergic conjunctivitis diagnosis at UCSF (ρ, 0.21 [95% CI, −0.02 to 0.42]; P = .06) or with results of Google searches in the United States for the term eye allergy (ρ, 0.13 [95% CI, −0.06 to 0.32]; P = .19). Seasonality of clinical diagnoses of allergic conjunctivitis at UCSF correlated strongly with results of Google searches in the United States for the term eye allergy (ρ, 0.44 [95% CI, 0.24 to 0.60]; P < .001) and eye drops (ρ, 0.47 [95% CI, 0.27 to 0.62]; P < .001).

Conclusions and Relevance  Internet-based search engine and social media data may reflect the occurrence of clinically diagnosed conjunctivitis, suggesting that these data sources can be leveraged to better understand the epidemiologic factors of conjunctivitis.

Figures in this Article

Sign in

Purchase Options

• Buy this article
• Subscribe to the journal
• Rent this article ?

Figures

Place holder to copy figure label and caption
Figure 1.
Number of Diagnoses of Nonallergic and Allergic Conjunctivitis

Number of diagnoses of nonallergic and allergic conjunctivitis in the University of California San Francisco electronic medical record, June 3, 2012, to April 26, 2014, based on all 5816 diagnoses (data for April 2014 end on the 26th; the total for full month would likely be higher than shown). Diagnoses of nonallergic conjunctivitis were those without the string “allerg” in the electronic medical record; diagnoses of allergic conjunctivitis were those with the string “allerg” in the electronic medical record.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Selected Weekly Results of Google Searches and Conjunctivitis Diagnoses

Google USA results for pink eye, Google Australia results for conjunctivitis (apparent inverse seasonality), diagnoses of nonallergic conjunctivitis (those without the string “allerg” in the electronic medical record), and all conjunctivitis diagnoses.

Graphic Jump Location

Tables

References

Correspondence

CME
Also Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
Please click the checkbox indicating that you have read the full article in order to submit your answers.
Your answers have been saved for later.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.

Multimedia

Some tools below are only available to our subscribers or users with an online account.

709 Views
0 Citations
×

Sign in

Purchase Options

• Buy this article
• Subscribe to the journal
• Rent this article ?

Related Content

Customize your page view by dragging & repositioning the boxes below.

See Also...
Articles Related By Topic
Related Collections
PubMed Articles
Jobs
brightcove.createExperiences();