مناقشات

How to manage the health system through Covid 19

Managing Health Services During a Pandemic

During a pandemic like COVID-19, health systems across the globe are overwhelmed. This can lead to high mortality both directly from the outbreak as well as indirect mortality from otherwise preventable and treatable conditions. Health systems need to draw a fine balance between the demands of responding directly to the pandemic, while simultaneously engaging in strategic planning and coordinated action to maintain essential health service delivery.

This lecture will discuss how health services respond to this dual, and often conflicting, set of demands.

The first part of the lecture will touch upon the operational planning guidelines based on the World Health Organization (WHO) guidelines as well as best practices employed by some of the more mature health systems in the developed world. This provides guidance on a set of targeted immediate actions that countries should consider at national, regional, and international levels to reorganize and maintain access to high-quality essential health services for all.

In the second part, the lecture will cover some of the more advanced techniques that utilize modern technology including mobile and AI.

Speaker:

Dr. Faisal Farooq

Speaker Bio:
  • Faisal Farooq

    PhD is a Principal Scientist and leads the Digital Health group within the Qatar Computing Research Institute (QCRI) at HBKU. Faisal is an established research leader with over 15 years of experience in applying machine learning in the healthcare domain, managing large research teams with multimillion dollar R&D portfolios. Faisal’s general areas of interest are machine learning and specifically applications for healthcare analytics including clinical informatics, health economics outcomes research, signal detection, disease progression modeling, predictive modeling and risk stratification.

If you've enjoyed this content, click below to find out more about the Publisher: Qatar Computing Research Institute (QCRI)
Tags
artificial-intelligence
covid-19
data-analytics
epidemiological-modeling
Age Group
Adults
Language
english

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