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This feature predicts an individual patient’s level of risk for developing certain chronic diseases or suffering from acute events. The technology behind the Malafi risk management solution uses advanced artificial intelligence techniques and machine learning algorithms to build predictive risk models based on emirate-level demographic and clinical data available in Malafi.
Dr Jamal Mohammed Al Kaabi, Deputy Minister of Health, said: “We are committed to developing a healthcare ecosystem that has become one of the world’s leading and innovative systems by deploying the latest artificial intelligence digital technologies to improve the quality of healthcare for the local population. Abu Dhabi and the region. This innovation is critical in moving to a prevention-based approach to healthcare, which will facilitate the transition to value-based healthcare while delivering on our vision for a healthy Abu Dhabi.”
Robert Denson, Acting CEO of Malaffi, said: “We can now maximize the clinical big data and population risk platforms already available at DOH to deliver even more value to Malaffi users. We are proud to be one of the few HIEs [health information exchanges] Extend such capabilities to clinicians worldwide through the Provider Portal. This will allow providers to gain actionable insights to improve patient health by proactively and preventively addressing their health needs. “
Dr Bakr Saadoon Ismail, Informatics Physician, Health Operations Management, Abu Dhabi Health Services (SEHA) Outpatient Healthcare; member of the Malaffi Clinical Advisory Board, said: “This predictive tool will help us effectively assess individual patient risk and help Make decisions about treatment, medication and advice specific to their individual situation.”
Malaffi Patient Risk Profile shows each patient’s risk score with a list of prevalent chronic diseases such as diabetes, congestive heart failure (CHF), chronic kidney disease (CKD), high blood pressure; sudden events such as heart attack, stroke, etc. Personal risk scores help clinicians make informed decisions and interventions to manage and prevent an individual from developing an underlying illness or hospitalization.
To identify at-risk patients, the solution currently leverages clinical data such as diagnoses, chronic diseases and laboratory results. To further improve accuracy, drug information will be added to the model in a future release.
Malaffi connects almost the entire sector in Abu Dhabi, including all hospitals and 2,000 public and private healthcare facilities, and provides access to over 45,000 authorized users “to the highest standards” to 900 million patient records for over 7 million patients Privacy and Information Security.
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