Events Calendar

Mon
Tue
Wed
Thu
Fri
Sat
Sun
M
T
W
T
F
S
S
1
2
3
4
5
6
7
8
12:00 AM - DEVICE TALKS
9
11
12
13
14
16
18
19
20
21
22
23
24
26
27
28
29
30
31
1
2
3
4
DEVICE TALKS
DEVICE TALKS BOSTON 2018: BIGGER AND BETTER THAN EVER! Join us Oct. 8-10 for the 7th annual DeviceTalks Boston, back in the city where it [...]
6th Annual HealthIMPACT Midwest
2018-10-10    
All Day
REV1 VENTURES COLUMBUS, OH The Provider-Patient Experience Summit - Disrupting Delivery without Disrupting Care HealthIMPACT Midwest is focused on technologies impacting clinician satisfaction and performance. [...]
15 Oct
2018-10-15 - 2018-10-16    
All Day
Conference Series Ltd invites all the participants from all over the world to attend “3rd International Conference on Environmental Health” during October 15-16, 2018 in Warsaw, Poland which includes prompt keynote [...]
17 Oct
2018-10-17 - 2018-10-19    
7:00 am - 6:00 pm
BALANCING TECHNOLOGY AND THE HUMAN ELEMENT In an era when digital technologies enable individuals to track health statistics such as daily activity and vital signs, [...]
Epigenetics Congress 2018
2018-10-25 - 2018-10-26    
All Day
Conference: 5th World Congress on Epigenetics and Chromosome Date: October 25-26, 2018 Place: Istanbul, Turkey Email: epigeneticscongress@gmail.com About Conference: Epigenetics congress 2018 invites all the [...]
Events on 2018-10-08
DEVICE TALKS
8 Oct 18
425 Summer Street
Events on 2018-10-10
Events on 2018-10-17
17 Oct
Events on 2018-10-25
Epigenetics Congress 2018
25 Oct 18
Istanbul
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