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25th International Conference on Dermatology & Skin Care
2020-04-27 - 2020-04-28    
All Day
About Conference Derma 2020 Derma 2020 welcomes all the attendees, lecturers, patrons and other research expertise from all over the world to 25th International Conference on Dermatology & [...]
Insurance AI and Innovative Tech Virtual
2020-05-27 - 2020-05-28    
All Day
In light of the rapidly evolving impact of COVID-19 globally, we have made the decision to turn Insurance AI and Innovative Tech 2020 into a [...]
Insurance AI and Innovative Tech USA Virtual
2020 has seen the insurance industry change in an unprecedented fashion. What was once viewed as long-term development strategies have now been fast-tracked into today’s [...]
27 May
2020-05-27 - 2020-05-28    
All Day
2020 has seen the insurance industry change in an unprecedented fashion. What was once viewed as long-term development strategies have now been fast-tracked into today’s [...]
Events on 2020-04-27
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