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Policy evaluation during a pandemic. [PDF]
National and local governments have implemented a large number of policies in response to the Covid-19 pandemic. Evaluating the effects of these policies, both on the number of Covid-19 cases as well as on other economic outcomes is a key ingredient for policymakers to be able to determine which policies are most effective as well as the relative costs
Callaway B, Li T.
europepmc +5 more sources
Modelling and Evaluation of Policies [PDF]
NCDs (non-communicable diseases) are considered an important social issue and a financial burden to the health care systems in the EU which can be decreased if cost-effective policies are implemented, along with proactive interventions. The CrowdHEALTH project recognizes that NCD poses a burden for the healthcare sector and society and aims at focusing
Moutselos, Konstantinos +9 more
openaire +2 more sources
Empirical Policy Evaluation With Supergraphs [PDF]
We devise and analyze algorithms for the empirical policy evaluation problem in reinforcement learning. Our algorithms explore backward from high-cost states to find high-value ones, in contrast to forward approaches that work forward from all states.
Daniel Vial, Vijay G. Subramanian
openaire +2 more sources
Evaluating the Robustness of Off-Policy Evaluation [PDF]
Accepted at ...
Yuta Saito +5 more
openaire +2 more sources
Researchers explored how 13 states in which policymakers have adopted an A-F school letter grade accountability system performed on the National Assessment of Educational Progress (NAEP) post-policy implementation.
Audrey Amrein-Beardsley +2 more
doaj +1 more source
Background Choosing Wisely (CW) is an international movement comprised of campaigns in more than 20 countries to reduce low-value care (LVC). De-implementation, the reduction or removal of a healthcare practice that offers little to no benefit or causes ...
Gillian Parker +4 more
doaj +1 more source
Background Paucity of RCTs of non-drug technologies lead to widespread dependence on non-randomized studies. Relationship between nonrandomized study design attributes and biased estimates of treatment effects are poorly understood.
Saerom Youn +10 more
doaj +1 more source
Background Implementation theories, models and frameworks offer guidance when implementing and sustaining healthcare evidence-based interventions. However, selection can be challenging given the myriad of potential options.
Lisa Strifler +3 more
doaj +1 more source
Evaluating Macroprudential Policies [PDF]
Macroprudential policy is a relatively new policy field. Its goal is to preserve financial stability and to prevent the build-up of systemic risk that may have adverse effects for the functioning of the financial system and for the real economy. New institutions have been tasked with the implementation of macroprudential policies, and new policy ...
Buch, Claudia M. +2 more
openaire +2 more sources
Many reinforcement learning algorithms use value functions to guide the search for better policies. These methods estimate the value of a single policy while generalizing across many states. The core idea of this paper is to flip this convention and estimate the value of many policies, for a single set of states.
Jean Harb +3 more
openaire +2 more sources

