How digital transformation can accelerate data use in health systems.

Introduction: We are in an era of rapid technological advance and digitalization. Countries around the world want to leverage technology to improve health outcomes by accelerating data use and increasing evidence-based decision-making to inform action in the health sector. Yet, there is no "one size fits all" approach to achieving this.

[Predicting major bleeding events in patients with peripheral arterial disease: the OAC-PAD risk score].

Although patients with peripheral arterial disease (PAD) are at a high risk of major bleeding owing to their comorbidity and risk profile, no validated tools exist to predict bleeding risk. To make matters worse, several randomized and controlled trials have excluded patients who are at a high risk of bleeding. Using routine health insurance claims data and machine learning methods, a pragmatic prediction model was developed and internally validated.

Understanding price growth in the market for targeted oncology therapies.

Objectives: The causes of oncology drug price growth remain unclear. Analyzing corresponding trends in revenue can help understand these causes. This study seeks to assess changes over time in prices, patient counts, and drug-level revenues in the US market for oncology therapies and to investigate whether price growth is driven by an increased ability by pharmaceutical firms to capture profits.

Cost-Effectiveness Analysis of Pertuzumab With Trastuzumab and Chemotherapy Compared to Trastuzumab and Chemotherapy in the Adjuvant Treatment of HER2-Positive Breast Cancer in the United States.

Objective: The APHINITY trial assessed the effectiveness and the safety of adding pertuzumab to trastuzumab and chemotherapy (THP) compared to trastuzumab and chemotherapy (TH) in the adjuvant management of human epidermal growth factor 2-positive (HER2+) breast cancer. We performed a study to project the potential cost-effectiveness of THP vs. TH.

Most impactful factors on the health-related quality of life of a geriatric population with cancer.

Background: As the population of older adults with cancer continues to grow, the most important factors contributing to their health-related quality of life (HRQOL) remain unclear.

Methods: A total of 1457 older adults (aged ≥65 years) with cancer participated in a telephone survey. Outcomes were measured using the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores of the 12-Item Short Form Survey (SF-12) from the Medical Outcomes Study (version 2).