Events Calendar

Mon
Tue
Wed
Thu
Fri
Sat
Sun
M
T
W
T
F
S
S
1
2
3
4
5
6
7
8
9
11
12
13
14
15
16
17
18
19
20
22
23
25
26
27
28
29
30
31
1
2
3
Electronic Medical Records Boot Camp
2025-06-30 - 2025-07-01    
10:30 am - 5:30 pm
The Electronic Medical Records Boot Camp is a two-day intensive boot camp of seminars and hands-on analytical sessions to provide an overview of electronic health [...]
AI in Healthcare Forum
2025-07-10 - 2025-07-11    
10:00 am - 5:00 pm
Jeff Thomas, Senior Vice President and Chief Technology Officer, shares how the migration not only saved the organization millions of dollars but also led to [...]
28th World Congress on  Nursing, Pharmacology and Healthcare
2025-07-21 - 2025-07-22    
10:00 am - 5:00 pm
To Collaborate Scientific Professionals around the World Conference Date:  July 21-22, 2025
5th World Congress on  Cardiovascular Medicine Pharmacology
2025-07-24 - 2025-07-25    
10:00 am - 5:00 pm
About Conference The 5th World Congress on Cardiovascular Medicine Pharmacology, scheduled for July 24-25, 2025 in Paris, France, invites experts, researchers, and clinicians to explore [...]
Events on 2025-06-30
Events on 2025-07-10
AI in Healthcare Forum
10 Jul 25
New York
Events on 2025-07-21
Events on 2025-07-24

Events

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