Implementation of Machine Learning Applications in Health Care Organizations: Systematic Review of Empirical Studies.

Background: There is a growing enthusiasm for machine learning (ML) among academics and health care practitioners. Despite the transformative potential of ML-based applications for patient care, their uptake and implementation in health care organizations are sporadic. Numerous challenges currently impede or delay the widespread implementation of ML in clinical practice, and limited knowledge is available regarding how these challenges have been addressed.

Mapping Payment and Pricing Schemes for Health Innovation: Protocol of a Scoping Literature Review.

Introduction: Innovative pricing and payment/reimbursement schemes have been proposed as one part of the solution to the problem of patient access to new health technologies or to the uncertainty about their long-term effectiveness. As part of a Horizon Europe research project on health innovation next generation pricing and payment models (HI-PRIX), this protocol illustrates the conceptual and methodological steps related to a scoping review aiming at investigating nature and scope of pricing and payment/reimbursement schemes applied to, or proposed for, existing or new health technologies.

Methods: A scoping review of literature will be performed according to the PRISMA guidelines for scoping reviews (PRISMA-ScR) guidelines.

Promoting the systematic use of real-world data and real-world evidence for digital health technologies across Europe: a consensus framework.

Despite the acceleration in the use of digital health technologies across different aspects of the healthcare system, the full potential of real-world data (RWD) and real-world evidence (RWE) arising from the technologies is not being utilised in decision-making. We examine current national efforts and future opportunities to systematically use RWD and RWE in decision-making in five countries (Estonia, Finland, Germany, Italy and the United Kingdom), and then develop a framework for promotion of the systematic use of RWD and RWE. A review assesses current national efforts, complemented with a three-round consensus-building exercise among an international group of experts (1 = 44, 2 = 24, 3 = 24) to derive key principles.

Implementation of Machine Learning Applications in Health Care Organizations: Protocol for a Systematic Review of Empirical Studies.

Background: An increasing interest in machine learning (ML) has been observed among scholars and health care professionals. However, while ML-based applications have been shown to be effective and have the potential to change the delivery of patient care, their implementation in health care organizations is complex. There are several challenges that currently hamper the uptake of ML in daily practice, and there is currently limited knowledge on how these challenges have been addressed in empirical studies on implemented ML-based applications.

Implementing shared decision-making interventions in breast cancer clinical practice: a scoping review.

Background: Shared decision-making (SDM) is a collaborative process whereby patients and clinicians jointly deliberate on the best treatment option that takes into account patients' preferences and values. In breast cancer care, different treatment options have become available to patients in the last decade. Various interventions, including patient decision aids (PtDAs), have been designed to promote SDM in this disease area.

Impella Versus VA-ECMO for Patients with Cardiogenic Shock: Comprehensive Systematic Literature Review and Meta-Analyses.

Impella and VA-ECMO are two possible therapeutic courses for the treatment of patients with cardiogenic shock (CS). The study aims to perform a systematic literature review and meta-analyses of a comprehensive set of clinical and socio-economic outcomes observed when using Impella or VA-ECMO with patients under CS. A systematic literature review was performed in Medline, and Web of Science databases on 21 February 2022.

Evaluating Barriers and Facilitators to the Uptake of mHealth Apps in Cancer Care Using the Consolidated Framework for Implementation Research: Scoping Literature Review.

Background: Mobile health (mHealth) solutions have proven to be effective in a wide range of patient outcomes and have proliferated over time. However, a persistent challenge of digital health technologies, including mHealth, is that they are characterized by early dropouts in clinical practice and struggle to be used outside experimental settings or on larger scales.

Objective: This study aimed to explore barriers and enablers to the uptake of mHealth solutions used by patients with cancer undergoing treatment, using a theory-guided implementation science model, that is, the Consolidated Framework for Implementation Research (CFIR).