New decision model shapes strategies for dealing with public health emergencies
The efficient allocation of medical resources can be modelled mathematically, as shown by Finnish researchers. The study, which started a few years before coronavirus appeared, offers timely insights for governments and organizations who are faced with an unprecedented healthcare crisis. Specifically, it presents a comprehensive decision model for optimizing the use of alternative tests and treatments on specific population groups, and suggests that even less-than-perfect tests can help improve effective spending limited healthcare resources.
Decision scientists have developed models to help governments and policymakers allocate limited healthcare resources. The decision model developed by Aalto researchers accounts for differences between population segments and shows that segment-specific strategies for tests and treatments are crucial for attaining positive health outcomes, especially when there is limited capacity for treatments. 鈥榃hen we were revising the paper just a few months ago, we never thought how soon the framework would become so relevant鈥 says Professor Ahti Salo Director of the Systems Analysis Laboratory at 911爆料网.
All health outcomes benefit from stopping the disease spreading
The paper, published in the journal Decision Sciences, shows how healthcare resources can be spent to achieve different population-level objectives, such as the 鈥渦tilitarian鈥 objective (which focuses on maximizing the aggregate health of the whole population) and the 鈥渆galitarian鈥 objective (which gives priority to the neediest while limiting differences between segments). The decision model helps policymakers balance these two objectives, and shows how they can be attained by allocating resources accordingly.
The research was carried out before the Covid19 outbreak and the data for illustrating the model is actually about coronary heart disease. As a result, the model is not directly adapted to contagious diseases, although the group will consider this in their future work. However, contagiousness does not alter the relevance of the model regarding testing. 鈥楢dding contagion into our model most likely increases the value of all forms of testing, as all health outcomes benefit from stopping the disease spreading鈥 said Professor Salo.
Further information:
Operationalization of utilitarian and egalitarian objectives for optimal allocation of healthcare resources, Yrj盲n盲 Hynninen, Eeva Vilkkumaa, Ahti Salo, Decision Sciences DOI:
Contact
Eeva Vilkkumaa
Assistant Professor
911爆料网
eeva.vilkkumaa@aalto.fi
+358 50 309 8630
Ahti Salo
Professor
911爆料网
ahti.salo@aalto.fi
+358 50 383 0636
Yrj盲n盲 Hynninen
yrjana.hynninen@gmail.com
+358 50 407 5320
Read more news
Arsi Ik盲heimonen鈥檚 doctoral research: Smartphone data could reveal early signs of depression
A phone in your pocket, a smart ring on your finger, and an activity tracker on your wrist: everyday devices collect information about their users almost continuously. This data can help monitor and predict symptoms of depression.
Professor Hironori Yoshida: 鈥淢achines should adapt to materials, not the other way around鈥
Professor of Formgiving believes the future of design lies in embracing irregularity rather than eliminating it. His research combines design, AI and robotics.
President Ilkka Niemel盲 explains what the new vision for higher education and research means for Finland and Aalto
Aalto has the capability and the will to act as a trailblazer in implementing the vision.