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12:00 AM - 29th ECCMID
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29th ECCMID
2019-04-13 - 2019-04-16    
All Day
Welcome to ECCMID 2019! We invite you to the 29th European Congress of Clinical Microbiology & Infectious Diseases, which will take place in Amsterdam, Netherlands, [...]
4th International Conference on  General Practice & Primary Care
2019-04-15 - 2019-04-16    
All Day
The 4th International Conference on General Practice & Primary Care going to be held at April 15-16, 2019 Berlin, Germany. Designation Statement The theme of [...]
Digital Health Conference 2019
2019-04-24 - 2019-04-25    
12:00 am
An Innovative Bridging for Modern Healthcare About Hosting Organization: conference series llc ltd |Conference Series llc ltd Houston USA| April 24-25,2019 Conference series llc ltd, [...]
International Conference on  Digital Health
2019-04-24 - 2019-04-25    
All Day
Details of Digital Health 2019 conference in USA : Conference Name                              [...]
16th Annual World Health Care Congress -WHCC19
2019-04-28 - 2019-05-01    
All Day
16th Annual World Health Care Congress will be organized during April 28 - May 1, 2019 at Washington, DC Who Attends Hospitals, Health Systems, & [...]
Events on 2019-04-13
29th ECCMID
13 Apr 19
Amsterdam
Events on 2019-04-24
Events on 2019-04-28
Articles

Algorithm Uses EHR Data To Identify Diabetes at Earliest Possible Date

diabetes

Researchers have developed an algorithm that can evaluate electronic health records to determine whether the patient has diabetes, FierceHealthIT reports.

Details of Algorithm

The algorithm, published in BioMedCentral, focuses on determining the earliest possible data of diagnosis in close to real time.

It evaluates information that is regularly documented and can be extracted from structured data fields, including:

  • Past medical history;
  • Problem list;
  • Medications; and
  • Laboratory results.

Each element is given a point value. After reaching a certain threshold, the algorithm identifies the presence of diabetes and calculates the earliest date that the disease could have been diagnosed.

Algorithm’s Accuracy

The researchers compared the algorithm’s findings with the opinion of a physician and found that the algorithm agreed on the date of diagnosis in 78.4% of cases.

It established a date of diagnosis that was within three months of the physician’s date in 94% of cases.

Experts say the algorithm could be effective in reaching patients who do not visit a physician regularly (Hall, FierceHealthIT, 8/2). Source