The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge.

Objectives: The machine learning prediction model Pacmed Critical (PC), currently under development, may guide intensivists in their decision-making process on the most appropriate time to discharge a patient from the intensive care unit (ICU). Given the financial pressure on healthcare budgets, this study assessed whether PC has the potential to be cost-effective compared with standard care, without the use of PC, for Dutch patients in the ICU from a societal perspective.

Methods: A 1-year, 7-state Markov model reflecting the ICU care pathway and incorporating the PC decision tool was developed.

The Potential Cost-Effectiveness of a Cell-Based Bioelectronic Implantable Device Delivering Interferon-β1a Therapy Versus Injectable Interferon-β1a Treatment in Relapsing-Remitting Multiple Sclerosis.

Background: Current first-line disease-modifying therapies (DMT) for multiple sclerosis (MS) patients are injectable or oral treatments. The Optogenerapy consortium is developing a novel bioelectronic cell-based implant for controlled release of beta-interferon (IFNβ1a) protein into the body. The current study estimated the potential cost effectiveness of the Optogenerapy implant (hereafter: Optoferon) compared with injectable IFNβ1a (Avonex).

Health-related quality of life of multiple sclerosis patients: a European multi-country study.

Background: Inconsistent use of generic and disease-specific health-related quality of life (HRQOL) instruments in multiple sclerosis (MS) studies limits cross-country comparability. The objectives: 1) investigate real-world HRQOL of MS patients using both generic and disease-specific HRQOL instruments in the Netherlands, France, the United Kingdom, Spain, Germany and Italy; 2) compare HRQOL among these countries; 3) determine factors associated with HRQOL.

Methods: A cross-sectional, observational online web-based survey amongst MS patients was conducted in June-October 2019.

The Methodological Quality and Challenges in Conducting Economic Evaluations of Newborn Screening: A Scoping Review.

Introduction: Cost-effectiveness (CEA) and cost-utility analyses (CUA) have become popular types of economic evaluations (EE) used for evidence-based decision-making in healthcare resource allocation. Newborn screening programs (NBS) can have significant clinical benefits for society, and cost-effectiveness analysis may help to select the optimal strategy among different screening programs, including the no-screening option, on different conditions. These economic analyses of NBS, however, are hindered by several methodological challenges.