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Computerized system for tracking health conditions of users

  • US 7,720,696 B1
  • Filed: 02/26/2007
  • Issued: 05/18/2010
  • Est. Priority Date: 02/26/2007
  • Status: Expired due to Fees
First Claim
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1. A computerized system for tracking health conditions and diagnosing sleep apnea of a plurality of users associated with a client, the system comprising:

  • a. a server comprising;

    (i) a data storage; and

    (ii) a processor in communication with the data storage;

    b. an encrypted web based questionnaire resident on the server, wherein the web based questionnaire comprises computer instructions for receiving input information from a user, wherein the input information comprises;

    (i) company employee information;

    (ii) personal health information that includes a prior health condition of the user, a prior operation of the user, a medication taken by the user, user self admitted sleep apnea, user reported diabetes, user reported emphysema or lung disease, user reported asthma, user reported depression, user reported snoring, user reported heart burn, user reported frequent urination at night;

    witnessed sleep apnea of the user, excessive daytime sleepiness of the user, and restless sleep reported by the user; and

    (iii) individual personal information that includes gender of the user, social security number of the user, the age of the user, the weight of the user, the height of the user, the date of birth of the user;

    c. computer instructions stored on the data storage to display the encrypted web based questionnaire resident on the server and to accept input information from the encrypted web based questionnaire from the user;

    d. computer instructions stored on the data storage to categorize the user into one of six categories based on the input information, wherein the categories comprise a male witnessed apnea positive category, a female witnessed apnea category positive, a males excessive daytime sleepiness positive with negative witnessed apnea category, a female excessive daytime sleepiness positive with negative witnessed apnea category, a male witnessed apnea negative and excessive daytime sleepiness negative category, and a female witnessed apnea negative and excessive daytime sleepiness negative category;

    e. computer instructions stored on the data storage to perform an odds ratio calculation in combination with a linear regression model on the personal health information and the individual personal information to determine a rating that relates to the risk of sleep apnea for the user having input information in the category of males excessive daytime sleepiness positive with negative witnessed apnea;

    f. computer instructions on the data storage to perform an odds ratio calculation on the personal health information and the individual personal information to determine a rating that relates to the risk of sleep apnea for the user having input information in the category of female excessive daytime sleepiness positive with negative witnessed apnea;

    g. computer instructions on the data storage to perform an odds ratio calculation on the personal health information and the individual personal information to determine a rating that relates to the risk of sleep apnea for the user having input information in the category of male witnessed apnea negative and excessive daytime sleepiness negative;

    h. computer instructions on the data storage to perform an odds ratio calculation on the personal health information and the individual personal information to determine a rating that relates to the risk of sleep apnea for the user having input information in the category of female witnessed apnea negative and excessive daytime sleepiness negative; and

    i. computer instructions stored on the data storage to allow a client to generate a list and view the status of a plurality of users, wherein the list displays each user'"'"'s risk of sleep apnea, a means to contact each user, and an indication of whether the user has been scheduled for a sleep studyj. wherein the odds ratio calculation in combination with a linear regression model comprises exploring models with main effects and pair-wise interactions with two or more of the following variables;

    body mass index, age, hypertension, diabetes, heartburn, heart conditions, snoring, asthma, depression, frequent urination at night and painful sleep.

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