Central Journal of Dermatology and Clinical Research

Research Article *Corresponding author Rachael Cayce, Department of Dermatology, University of Texas Southwestern Medical Center at Internet Search Trend Analysis Dallas, 5323 Harry Hines Blvd, Dallas, TX 75390-9069, USA, Tel: 214-633-2024; Fax: 214-645-2405, Email: [email protected] Tools Provide Insight into Submitted: 29 October 2013 Accepted: 31 October 2013 Disease Healthcare Utilization Published: 02 November 2013 Copyright 1 1 1 Rachael Cayce *, Shauna Goldman , Dominique van Beest and Justin © 2013 Cayce et al. Davis2 OPEN ACCESS 1Department of Dermatology, University of Texas Southwestern Medical Center at Dallas, USA 2Department of Dermatology, Tulane University, USA Keywords • Internet search analysis Abstract • Google trends • Healthcare utilization Background: About eight million adults search online for health information each day • Epidemiology in the United States; the majority start their search at a search engine. In recent years, search • Dermatology engine query data has emerged as a potentially reliable source of epidemiological data. In the • Rheumatology field of dermatology, there is a paucity of data indicating which types of provider’s patients • Plastic surgery seek for care. Knowledge of such trends would be an important gauge of dermatologists’ impact on skin diseases. Objective: We sought to determine whether Web-based search queries could provide insight into trends in skin disease healthcare utilization. Methods: We catalogued diseases treated by dermatologists, then performed Google Trends queries for each condition alongside dermatology and other pre-specified non- dermatologist providers(s), to determine whether conditions would correlate with searches for dermatology or non-dermatologist providers. Results: Overall, the majority of skin conditions searched for did not trend with searches for dermatology. Limitations: It is unknown whether the same individuals are searching for both diseases and providers. Conclusion: Our findings underscore the importance of future education of the public regarding the role of the dermatologist in the management of certain skin conditions.

INTRODUCTION (google.com/trends/correlate). Of these, GT seems to be the most versatile tool available at this time for An estimated eight million adults search online for health generationGoogle Correlate of epidemiological analyses, including infectious information each day in the United States (U.S.), and 66% begin their internet session at a search engine. [1] In 2008, search engine queries began to emerge as a reliable source of diseases and the occurrence of kidney stones [2,3,5]. population-based health information when a leading search between dermatologists and non-dermatologist providers in The scope of skin disease is broad, and there is often overlap engine provider, Google, demonstrated that queries

for influenza- the diagnosis and treatment of conditions of the hair, skin, and nails. For example, a recent study which analyzed population- surveillancerelated symptoms data could [2,3]. predict Recently, an Schusterinfluenza etoutbreak al. demonstrated one to two based data from the National Foundation reported thatweeks search faster enginethan the query Centers data for accuratelyDisease Control predicted and Prevention trends in rheumatologists, internists, family practitioners, and other medicalthat patients providers seek [6]. treatment In the realm for ofpsoriasis cosmetic from dermatology, dermatologists, plastic metropolitan areas [4]. These examples underscore the potential surgeons and other non-dermatology physicians performed utilitypharmaceutical for search revenues engine analysis and Medicare tools in utilizationidentifying, in and several possibly U.S. the majority of ambulatory cosmetic dermatologic procedures predicting, healthcare trends. These tools are available to the public in various formats: Google Trends (GT) (google.com/ dermatologists [7]. For some dermatologic conditions such as from 1995 to 2010, with just one-third being performed by trends), Google Flu Trends ), Google , there is a paucity of data indicating which specialist google.org/denguetrends) and the related (google.com/flutrends Dengue Trends ( patients seek for care. Supply constraints in dermatology, along Cite this article: Cayce R, Goldman S, van Beest D, Davis J (2013) Internet Search Trend Analysis Tools Provide Insight into Skin Disease Healthcare Utiliza- tion. J Dermatolog Clin Res 1(1): 1005. Cayce et al. (2013) Email: [email protected] Central with economic, geographic, and psychosocial elements may all Sarcoidosis R It is our opinion (sarcoid+sarcoidosis) Infectious Disease 0.0435 -0.0501 play a role in skincare-seeking patterns [6,8]. time, would be an important gauge of dermatologists’ impact Bed bugs ("bed bugs"+"bed 0.7663 0.7188 that knowledge of such trends, and how they have changed over bug bites") P, I, F on skin diseases. We postulate that Google search queries could mouth"+"hand foot mouth 0.1870 0.0399 HFMD ("hand foot provide insight into consumer trends for skin-directed health disease") P, F care utilization among providers. Thus, we analyzed GT query Leprosy (leprosy+"leprosy with queries for dermatologists and other non-dermatologist -0.0223 data for a wide array of skin diseases to compare their correlation symptoms") 0.0561 P, I, F disease"+"lyme disease 0.0768 providers. Specifically, we sought to determine if searches for Lyme Disease ("lyme non-dermatologists. rash") specific skin disease(s) correlate more with dermatologists or 0.2935 P, I, F Mites ("mites"-animal+ METHODS 0.1863 "mite infestation"-animal) Data Collection using GT Technology Scabies ("scabies 0.4025 P, I, F 0.7033 0.6703 rash"+scabies) Shingles ("herpes P, I, F from the scope of dermatology (Table 1) and selected non- We catalogued 47 dermatologic conditions thought to sample 0.6168 I, F roof) zoster"+zoster+"shingles"- 0.4325 Syphilis (syphilis+"syphilis 0.3267 I, F 0.1810 Tabledermatologist 1: providers likely to care for each condition. Then, we rash") Correlation Non- 0.0391 -0.0082 Skin disease-related Correlation with with non- "+"warts treatment") dermatologist Warts (warts+"skin search term Dermatology* dermatologist P, I, F provider(s)◊ Miscellaneous provider§ 0.8724 0.6690 Blistering diseases Spider Bite ("spider Blisters Rash (rash+"skin rash") P, I, F 0.3336 bite"+"spider bite rash") - 0.43000.7615 P,R I 0.22180.5313 0.89710.5333 P, I, F 0.3976 phigoid" + pemphigoid) Pemphigoid ("bullous pem “StretchNeoplasms marks” PS 0.0829 R -0.0466 "pemphigus vulgaris") 0.8847 0.8018 Pemphigus (pemphigus + Diseases Cyst P, I, F Lupus 0.1381 R (keloids+" 0.3732 "+"keloid 0.1323 R -0.02120.2145 removal") PS 0.3352 treatment"+"keloid 0.1886 R -0.2316 Melanoma (melanoma+ "melanoma signs"+ Cosmetic 0.0094 Onc "melanoma symptoms"+ Botox 0.3611 0.2700 "malignant melanoma") 0.4785 Fillers (juvederm+restylan Mole ("mole"-animal-rat- 0.4177 A, VSPS 0.3292 0.0391 e+radiesse+sculptra) chemistry-recipe-food) Sclerotherapy ("vericose 0.3625 PS vein treatment"+"varicose 0.6378 0.3204 Skin Cancer ("skin 0.1021 I -0.1746 veins"+sclerotherapy) PS, VS cancer"+"skin cancer symptoms") 0.3909 0.1491 signs"+"skin cancer 0.1776 PS, A 0.1482 -0.114 Skin growth ("skin “Laser hair removal” PS, A 0.3257 PS growth"+"skin tumor") 0.0060 Laser skin resurface ("laser spots"+"sun spots") peel"+"co2 laser Sun spots ("skin sun skin resurfacing"+"laser Sun damage ("sun PS -0.0658 resurfacing"+"erbium laser 0.0828 damage"+"sun damaged resurfacing"+"fraxel laser 0.3877 0.1064 PS, A 0.1537 resurfacing") treatment") PS Follicular Disorders skin"+"sun damage Papulosquamous Disorders Acne (acne+"acne 0.8909 A 0.6130 treatment") 0.6641 0.6429 Rosacea (rosacea+"rosacea Eczema ("dry 0.0120 I -0.0119 treatment") treatment") skin"+eczema+"eczema P, I, F Hair loss ("hair loss"+"hair 0.1306 I 0.0149 0.2011 loss treatment"+alopecia) PS 0.1359 ivy"+"poison ivy Granulomatous Disease Poison Ivy ("poison 0.3836 rash"+"poison ivy 0.4824 R treatment") P, I, F 0.1522 “ Annulare” 0.2885 J Dermatolog Clin Res 1(1): 1005 (2013) 2/5 Cayce et al. (2013) Email: [email protected] Central

cost), the results of GT queries can be downloaded as a comma- (psoriasis+"psoriasis R Psoriasis treatment") [3]. 0.5208 0.5071 Seborrheic (seb separated value file for subsequent statistical analysis (Figure 1) orrhea+seborrheic+"seborr The use of symbols removes ambiguity in GT searches. For heic dermatitis") example, an addition (+) sign combines searches whereas a 0.5618 P, I, F 0.5386 Pediatric Skin Diseases subtraction (-) excludes searches. For example, a GT query for

0.2307 0.2627 Birth mark("birth “shingles– roof” includes queries for shingles but excludes mark"+"birthmark"+"birth P, PS Hemangioma ("strawberry queries that include roof, thereby increasing the likelihood that mark removal") hemangioma"+hemangiom the query refers to herpes zoster rather than home repair or a+"hemangioma removal") construction-related queries. A quotation mark will restrict the 0.1715 P, PS 0.1275 queries used in this study can be found in Table 1. query to Google searches with words in that order. The specific Statistical Analysis Kawasaki Disease ("kawasaki 0.1018 disease"+"kawasaki P, Card 0.1045 disease rash"+"kawasaki symptoms") For each queried skin condition, Pearson correlation rash"+"kawasaki disease coefficient analyses were performed to determine the correlation Pigmentary Disorders particular providers (dermatology versus non-dermatologist between queries for each skin condition and queries for Melasma 0.4208 0.1470 providers). Specifically, we sought to determine whether search (melasma+" skin Ob, PS Vitiligo (vitiligo+"vitiligo queriestrends for for each an alternative condition wouldnon-dermatologist correlate (R provider(s), > 0.50) with or darkening") 0.2082 0.0897 treatment") searches for “dermatology” and not correlate (R <0.50) with Ulcerative Skin Disorders PS Foot ("foot ulcer" queryvice versa. values For for calculation, dermatology weekly and non-dermatologist GT relative query providers.values for -0.0076 all skin-related conditions were compared to weekly GT relative treatment") +"skin ulcer" +"foot ulcer I, Po 0.7559 a whole, and subsequently divided into four-year increments *Search terms used: dermatology + dermatologist. (2004Weekly to data 2008 from and January2009 to 20042013) to to Junesee whether 2013 was correlations, analyzed as if The following search terms were used for non-dermatologist specialists: present, had changed over time. The correlation values obtained ◊ were subsequently entered into a cluster analysis to explore the Obstetrics+Aesthetician obstetrician+ +esthetician (A);gynecology+ Cardiology+ gynecologist cardiologist (Ob); (Card), Oncology+ “Family oncologist doctor” +”family practice” +”family practice doctor” (F); “Internal medicine” +internist (I); condition and particular provider(s). statistical relationship, if any, between Web-based searches for a (Onc); Pediatrics +Pediatrician (P); “Plastic surgery” +”plastic surgeon” (PS); RESULTS §Podiatry +Podiatrist (Po); Rheumatology +Rheumatologist (R), “Vascular surgery”+ ”Vascularhighest correlation surgeon” among(VS) all non-dermatology specialists queried for comparison. Correlations represent the search terms for non-dermatologist specialists with condition and queries for particular providers from 2004 to performed GT queries for each condition alongside dermatology 2013.Table If multiple1 lists the non-dermatologist correlation among providers queries were for each used skin for comparison, the R-value of the highest correlating provider was listed in Table 1 and used for subsequent statistical analysis. withinand each the United pre-specified States. non-dermatologist provider(s). We obtained weekly GT query data from January 2004 to June 2013 Table 2 lists those queries for skin conditions which correlated set by its largest variable to allow for comparisons between (R > 0.50) with searches for “dermatology” and did not correlate All query outputs from GT are normalized by dividing a data provider, and vice versa, for each of the three time periods variables. To increase sensitivity for detection of future changes (R <0.50) with queries for an alternative non-dermatologist in search volume index (SVI), GT also divides by an unrelated analyzed (2004-13, 2004-8, 2009-13). Overall, the majority the effect of a larger population on SVI. For such purposes, GT of queried skin conditions for did not trend with searches for usesand commonInternet protocolWeb search addresses query. from Normalization server logs also to establish factors outthe searchesdermatology. for dermatology Searches for oversix of two the skintime conditions periods, 2004-2008 (blisters, cyst, and rash, shingles, spider bite, and stretch marks) correlated with with searches for alternative non-dermatologist providers). The origin of Web-based queries. 2009-2013 (R > 0.50 with searches for dermatology and R <0.50 entry relative to its average search volume over the time period selected.After GT normalization, displays a relative GT scales SVI the graph result based for on each a fraction query dermatology more than doubled between 2004-2008 and 2009- number of searches for skin conditions that correlated with and extrapolates the data to estimate total search volume. This correlated with non-dermatologist providers remained stable of total Google Web searches over a specified period of time over2013, time. while the number of searches for skin conditions that individual queries and limit searches to certain locations, as well Multiple clustering analysis algorithms were applied to the information is currently updated daily. Users may enter up to five logged in to a Google account (available to Internet users at no to detect outliers. Each clustering algorithm demonstrated as apply category filters such as “Health” or “Finance.” For users data sets, including k-means and single linkage with docking

J Dermatolog Clin Res 1(1): 1005 (2013) 3/5 Cayce et al. (2013) Email: [email protected] Central

Figure 1

Table 2:

2004-2013 2004-2008 2009-2013 Queries that correlated Queries that correlated Queries that correlated Queries that correlated with Queries that correlated with Queries that correlated with with dermatology* non-dermatologist with dermatology non-dermatologist with dermatology non-dermatologist provider** provider provider Sclerotherapy Foot ulcer Blisters Laser hair removal Blisters Foot ulcer

Shingles Seborrheic dermatitis

Spider bite CystRash Dermabrasion CystRash Shingles Shingles

Stretch marks Spider bite Spider bite

Stretch marks StretchHand, Foot marks and Mouth

DiseaseKeloids

LymeLaser hairDisease removal Mites

PoisonSclerotherapy Ivy

* R>0.5 for dermatology, R<0.5 for alternative non-dermatologist provider; ** R>0.5 for non-dermatologist provider, R<0.5Warts for dermatology substantially different clusters such that overall, our analysis providers (family medicine and pediatrics) prior to 2010. After 2010, however, queries for bed bugs failed to associate as strongly (R = 0.40) with queries for dermatologists or non- orfailed pigmentary to reveal disorders, statistically and significant either dermatology distinctions betweenor non- dermatologist providers. Analysis of queries for the following dermatologistqueries for particular providers. groups of skin conditions, such as follicular conditions demonstrated an increased association with queries for dermatology over the course of this study: acne, blister, cysts,

Despite the lack of groups of skin disorders to cluster with particular specialties, results for individual skin-related DISCUSSIONmites, scleroderma, stretch marks, warts, and herpes zoster. throughoutconditions were the time noteworthy. course included For example, in the studyWeb-based (R = 0.72, searches 0.81 for 04-08 “skin and rashes” 09-13 were respectively). highly associated Also, bed with bugs dermatologywere highly the U.S. that is being increasingly met by non-dermatologists [9]. associated (R = 0.76) with dermatology and non-dermatologist Currently, there is a demand for skin disease-related care in

The treatment approach to common skin conditions can differ J Dermatolog Clin Res 1(1): 1005 (2013) 4/5 Cayce et al. (2013) Email: [email protected] Central

from the same user group. Further, data extraction from GT is result in decreased quality of care received by these patients largely dependent on user-generated search terms, and thus, [10,11].significantly GT dependingis a potential on the useful physician source provider, of population-based which may healthcare data capable of accurately and expeditiously gauging analysis. Nonetheless, the substantial, and near real-time, data Our data supports that GT availablemore relevant through and Googlecorrelated is aterms potentially may not useful be recognized analysis toolfor query analysis is a potentially useful tool for evaluating searching worthy of further exploration. patient health care utilization [2,3]. search query data can provide behaviorsThe cluster related analysis to skin data disease failed and to skin-directedreveal meaningful healthcare. clusters exploredWe have whether demonstrated the trends how differ by provider. The treatment dermatologist providers. These results suggest that people approachinsight into and healthcare quality of utilization care may trends substantially for skin differ disease among and between groups of skin conditions and dermatology or non- forperforming particular Web-based providers. searches for information related to thoseareas that providing need improved care for patient skin disease,education [10,11] regarding and the thus role anof ofparticular future types education of skin of disease the public are not regarding searching the chronologically role of the theunderstanding dermatologist. of patient health seeking behavior can help gauge These findings indicate the importance associated with dermatology throughout the course of the REFERENCES studydermatologist. indicates that The there finding is public that queriesawareness for of skin the rashrole of were the 1. dermatologist in the treatment of this condition. Moreover, the 2006. Fox S. Pew Internet & American Life Project. 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Cite this article Cayce R, Goldman S, van Beest D, Davis J (2013) Internet Search Trend Analysis Tools Provide Insight into Skin Disease Healthcare Utilization. J Dermatolog Clin Res 1(1): 1005.

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