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SmartData Collective > Big Data > The Potential of Big Data in Sleep Medicine
Big DataExclusive

The Potential of Big Data in Sleep Medicine

Big data is fundamental to the development of cutting-edge sleep medications for people with major sleep disorders.

Ryan Ayers
Ryan Ayers
5 Min Read
big data sleep medicine
Shutterstock Photo License - By Marcos Mesa Sam Wordley
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A better night?s sleep can lead to a lot of good in an individual?s life, and it can even add years to that life! There are plenty of classic remedies to try to get a little more shut eye, and though some may work from person to person, most of the ?expertise? comes from word of mouth. With big data being an integral part of almost every industry in the U.S., especially pertaining to the growth of a given industry, sleep data is no different. 

Contents
  • Understanding the Importance of Big Data in Sleep Medication
  • Sleep Apnea
  • Insomnia
  • Narcolepsy 

There is still some debate as to whether big data is beneficial or harmful for sleep overall. However, it is clearly useful in regards to the study and development of sleep medicine specifically.

Understanding the Importance of Big Data in Sleep Medication

Big data as it pertains to a good night?s sleep has been responsible for evolutions in bedding, evolutions in determining why people are having trouble sleeping (genetics, for instance), and in curative measures such as gadgets like light therapy alarm clocks that help people slowly go to sleep and slowly wake up, to make their hours in la-la land more beneficial. These gadgets can change sleep patterns in unfortunate ways if they aren’t used properly.

Medicine is another field run by data, and marrying sleep data and health data can also lead to improvements in sleep medication for those individuals who can?t seem to fight off insomnia by any other means. Here is a look at some advancements in sleep medication that stemmed from discoveries by data analysts. 

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Sleep Apnea

Sleep apnea is considered a chronic disease in the health field, requiring long-term treatment, most of which is done at home. Formerly, most patients received the same treatments for their sleep apnea, but studies focused on different phenotypes in these patients have resulted in more focused medications for patients, depending on those phenotypes. The greater the accumulation of data regarding these patients is, the more focused those medications can become, ultimately resulting in an almost unique treatment for each and every patient. 

Insomnia

Insomnia is something developed by a whopping one in four Americans ever single year, and with the new normal related to the pandemic flipping most people?s lives upside down, this year resulted in even more individuals struggling to fall asleep at night and staring at their ceilings for hours. Reasons for insomnia are aplenty, to put it lightly, but just as with sleep apnea, the quicker one can determine the ?why? in regards to their insomnia, the quicker they can be treated correctly. Wearable trackers for individuals who can?t sleep can relay data directly to companies focused in developing ways to fight that insomnia, including medication. When determined that a given patient?s reason for insomnia is chemical, medication can be prescribed correctly and safely, rather than as a blanket attempt given to everyone. 

Narcolepsy 

Narcolepsy is arguably the most threatening of sleep disorders, as individuals with it can fall asleep unexpectedly. This is labeled as an autoimmune disorder, meaning medication is the primary means of treatment. However, advances in narcolepsy medication were few and far between before big data allowed for sweeping collections of data on narcolepsy patients that ultimately allowed for the determinations of commonalities among patients, making for the advancements in the medication. There are two major types of narcolepsy, NT1 and NT2, and thanks to accumulated data, doctors can quickly determine which is in a given patient, and provide medication accordingly.  

Big data keeps becoming more and more useful, and the brains behind it are coming up with more and more ways to advance the ways it can be used for medicine. With sleep issues being so common in the United States, and abroad, evolution in treatment is expected to continue at a quick pace, giving plenty of reason for optimism for those 1 in 4 Americans who suffer from a sleep disorder.

TAGGED:big data medicinebig data researchbig data sleep
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ByRyan Ayers
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Ryan Ayers has consulted a number of Fortune 500 companies within multiple industries including information technology and big data. After earning his MBA in 2010, Ayers also began working with start-up companies and aspiring entrepreneurs, with a keen focus on data collection and analysis.

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