{"id":20629,"date":"2016-11-18T17:57:33","date_gmt":"2016-11-18T22:57:33","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/can-a-smart-thermometer-stop-the-spread-of-contagious-diseases\/"},"modified":"2016-11-20T17:08:44","modified_gmt":"2016-11-20T22:08:44","slug":"can-a-smart-thermometer-stop-the-spread-of-contagious-illnesses","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/can-a-smart-thermometer-stop-the-spread-of-contagious-illnesses\/","title":{"rendered":"Can a Smart Thermometer Stop the Spread of Contagious Illnesses?"},"content":{"rendered":"

We spend billions of dollars each year trying to stop the spread of contagious illnesses. Take the recent Ebola epidemic, for example: in December 2015, the World Bank collected over $8 billion in pledges to combat the disease globally.<\/span>[1]<\/a> The US alone spends nearly $200 million annually trying to fight the flu.<\/span>[2]<\/a> But how can you effectively allocate money when you don\u2019t know when and where these illnesses are spreading?<\/p>\n

Kinsa<\/span> is a startup solving this information gap by connecting one of the world\u2019s most common medical devices \u2013 the thermometer \u2013 to the mobile web.<\/p>\n

Why a smart thermometer?<\/strong><\/p>\n

The earliest sign of most contagious illnesses is a fever (just check WebMD). The first action many take to confirm they are sick is checking their temperature. With its consumer-friendly, mobile-connected thermometer and app, Kinsa leverages this behavior to collect real-time, geo<\/span>-located fever and symptom information. In other words, the company can begin to understand when and where people are getting sick before they\u2019ve even entered the healthcare system. When this data is aggregated and anonymized, Kinsa can create a real-time map of health, empowering individuals and officials to track the start and potentially stop the spread of disease. In public health, this \u201cearly detection, early response\u201d is the holy grail.<\/span>[3]<\/a><\/p>\n

How do we currently track infectious diseases?<\/strong><\/p>\n

The current gold standard in outbreak tracking is provider<\/span>-initiated reporting. Public health officials optimize for strong signals with low noise and are willing to compromise on the immediacy of results to ensure their data is certified by trusted sources such as hospitals or laboratories. Each year, the CDC publishes a weekly influenza surveillance report on its website called \u201cFluView.\u201d[4]<\/a> These reports often lag the rate of disease spread by weeks due to the time it takes for local, state, and CDC health workers to collect and analyze the data.<\/p>\n

Technology has already shown promise in improving our ability to predict the onset and spread of disease more quickly than provider-initiated reporting. In 2008, Google Flu Trends mined illness-related search queries to model and monitor the flu in a more timely manner.<\/span>[5]<\/a> Unfortunately, these efforts have suffered from low signal-to-noise ratios (SNRs) due to errors in natural language processing (NLP) and other limitations.<\/span>[6]<\/a>,[7]<\/a><\/sup><\/p>\n

\"CDC
Figure 1. CDC FluView, as of November 18, 2016<\/figcaption><\/figure>\n

Kinsa\u2019s<\/span> business model<\/strong><\/p>\n

Kinsa<\/span> is betting that its approach can address the limitations of both provider-initiated reporting and recent computational efforts. By selling the Kinsa Smart Thermometer directly to consumers, the company overcomes the time lag inherent in the current gold standard. Getting FDA 510(<\/span>k) clearance for the device ensures the company is collecting medically accurate data, facilitating a higher SNR and combatting errors inherent in crowd-sourced data and NLP.<\/p>\n

Like other Internet-of-Things companies, however, the success of Kinsa\u2019s mission is dependent on the company\u2019s ability to 1) drive distribution of its hardware, and 2) drive user engagement.<\/p>\n

 <\/p>\n

Understanding Kinsa\u2019s operations<\/strong>\u00a0<\/strong><\/p>\n

\"tempfeaturetb1_031115-jpg\"
Figure 2. Kinsa<\/span> Smart Thermometer and app (bubble feature).<\/figcaption><\/figure>\n

Knowing how important it was to get the thermometer in the hands of users, Kinsa designed the product to be competitive on price and user experience. To keep manufacturing costs low, Kinsa<\/span> worked with suppliers in China. The company also used the headphone jack, a component costing 1\/20th<\/span><\/sup> of<\/span> what would be required for Bluetooth. [8]<\/a>,<\/span>[9]<\/a>,<\/span>[10]<\/a> Connecting via the headphone jack allowed Kinsa<\/span> to create a \u201cmagical\u201d user experience for kids. Whereas parents used to complain that kids would fidget and hate having their temperature taken, Kinsa<\/span> used the smartphone screen to gamify<\/span> the experience. Once completed, parents could track symptoms and medications via the app and receive alerts as to what they to do.<\/span>[11]<\/a><\/p>\n

 <\/p>\n

\"grp-2\"
Figure 3. Snapshot of Kinsa Groups.<\/figcaption><\/figure>\n

 <\/p>\n

While the company sold the thermometer through retailers such as Apple, Target, and CVS and online at a $19.95 price point, the low bill of materials costs allowed Kinsa<\/span> to experiment with other distribution models. FLUency\u2122 was a free public school give-away<\/span> program that increased usage of the thermometer, provided positive press, and served as early testing of the health<\/span> map through a feature called Kinsa<\/span> Groups\u2122.<\/span>[12]<\/a> Groups empowered school officials and parents to see what symptoms and illnesses were going around their school, in real-time.<\/span>[13]<\/a><\/p>\n

 <\/p>\n

What\u2019s next?<\/strong><\/p>\n

Kinsa<\/span> is a prime example of a company that was born out of the proliferation of mobile technology, the lowered cost of sensors, and the promise of big data. As a startup, it will face increasing strategic and operational challenges. For example, Apple removed the headphone jack in<\/span> the iPhone 7. As computational technology improves, Kinsa itself risks being disrupted by software-only competitors such as Sickweather who don\u2019t need to worry about hardware complexities. And the ultimate question remains: will the various distribution models and innovations in user experience be sufficient to penetrate enough households to collect the data needed? Only time will tell.<\/p>\n

\"Figure
Figure 4. Map data provided by Kinsa<\/span>, designed by Fortune Magazine. Data represents approximately 3,000 temperature readings.<\/figcaption><\/figure>\n

Word count:<\/strong> 778<\/p>\n

 <\/p>\n

Sources<\/strong><\/p>\n

[1]<\/a> World Bank Group. \u201cGlobal Ebola Response Resource Tracking,\u201d 2015. Http:\/\/www.worldbank.org\/en\/topic\/ebola\/brief\/global-ebola-response-resource-tracking<\/p>\n

[2]<\/a> Center For Disease Control. \u201cCDC FY 2016 Congressional Justification: Overview of the Budget Request.\u201d https:\/\/www.cdc.gov\/budget\/documents\/fy2016\/fy-2016-overview-and-detail-table.pdf<\/p>\n

[3]<\/a> World Health Organization. \u201cEarly detection, assessment and response to acute public health events,\u201d 2014. http:\/\/www.who.int\/ihr\/publications\/WHO_HSE_GCR_LYO_2014.4\/en\/<\/p>\n

[4]<\/a> Center for Disease Control. \u201cFluView<\/span>,\u201d accessed November 17, 2016. http:\/\/www.cdc.gov\/flu\/weekly\/<\/p>\n

[5]<\/a> Jeremy Ginsberg, Matthew H. Mohebbi<\/span>, Rajan S. Patel, Lynnette Brammer, Mark S. Smolinski & Larry Brilliant, “Detecting influenza epidemics using search engine query data,”\u00a0Nature, <\/em>457: 1012-1014 (19 February 2009). http:\/\/www.nature.com\/nature\/journal\/v457\/n7232\/full\/nature07634.html<\/p>\n

[6]<\/a> Declan Butler, \u201cWhen Google Got Flu Wrong,\u201d Nature, <\/em>13 February 2013, accessed November 17, 2016. http:\/\/www.nature.com\/news\/when-google-got-flu-wrong-1.12413<\/p>\n

[7]<\/a> David Lazer and Ryan Kennedy, \u201cWhat We Can Learn From the Epic Failure of Google Flu Trends,\u201d WIRED,<\/em> 1 October 2015, accessed November 18, 2016. https:\/\/www.wired.com\/2015\/10\/can-learn-epic-failure-google-flu-trends\/<\/p>\n

[8]<\/a> Leah Hunter, \u201cWhy The Best Way Into Your Customer’s iPhone Is The Headphone Jack,\u201d Fast Company,<\/em> 7 May, 2014, accessed November 18, 2016. https:\/\/www.fastcompany.com\/3030202\/why-the-best-way-into-your-customers-iphone-is-the-headphone-jack<\/p>\n

[9]<\/a> https:\/\/www.alibaba.com\/product-detail\/Good-quality-3-5mm-trrs-plug_2022458492.html<\/p>\n

[10]<\/a> https:\/\/www.alibaba.com\/product-detail\/BLE-4-0-nordic-chip-nRF51822_60337045055.html<\/p>\n

[11]<\/a> Lauren Kay, \u201cKinsa Smart Stick Thermometer Review: See why this digital thermometer might deserve a place in your medicine cabinet,\u201d accessed November 18, 2016. http:\/\/www.thebump.com\/a\/kinsa-smart-stick-thermometer-review<\/p>\n

[12]<\/a> Kinsa. https:\/\/www.kinsahealth.com\/fluency<\/p>\n

[13]<\/a> Zina Moukheiber, \u201cOn A Mission To Detect The Flu And Other Infectious Diseases With A Thermometer,\u201d Forbes, 11 December 2014, accessed November 18, 2016. http:\/\/www.forbes.com\/sites\/zinamoukheiber\/2014\/12\/11\/on-a-mission-to-track-the-flu-and-other-infectious-diseases-with-a-thermometer\/#1ad2cee92603<\/p>\n","protected":false},"excerpt":{"rendered":"

In a world where we can instantly find the fastest route to the airport via Google Maps or get real-time Twitter updates on Trump\u2019s presidential transition plan, we are still in the dark ages when it comes to understanding when and where diseases start and spread. Can a simple thermometer change that?<\/p>\n","protected":false},"author":2125,"featured_media":20742,"comment_status":"open","ping_status":"closed","template":"","categories":[298,669,690,2062,2852,208,2019,1503,2851,2794,1388,2853],"class_list":["post-20629","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-big-data","category-consumer-health","category-consumer-products","category-digital-health","category-google-flu","category-health","category-internet-of-things","category-iot","category-kinsa","category-mobile-health","category-public-health","category-thermometer"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/digitization-challenge-2016\/","yoast_head":"\nCan a Smart Thermometer Stop the Spread of Contagious Illnesses? - Technology and Operations Management<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/can-a-smart-thermometer-stop-the-spread-of-contagious-illnesses\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Can a Smart Thermometer Stop the Spread of Contagious Illnesses? - Technology and Operations Management\" \/>\n<meta property=\"og:description\" content=\"In a world where we can instantly find the fastest route to the airport via Google Maps or get real-time Twitter updates on Trump\u2019s presidential transition plan, we are still in the dark ages when it comes to understanding when and where diseases start and spread. 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