Real-World Research on Retinal Diseases Using Health Claims Database: A Narrative Review.
Seong Joon AhnPublished in: Diagnostics (Basel, Switzerland) (2024)
Real-world data (RWD) has emerged as a crucial component in understanding and improving patient outcomes across various medical conditions, including retinal diseases. Health claims databases, generated from healthcare reimbursement claims, offer a comprehensive source of RWD, providing insights into patient outcomes, healthcare utilization, and treatment effectiveness. However, the use of these databases for research also presents unique challenges. This narrative review explores the role of real-world research on retinal diseases using health claims databases, highlighting their advantages, limitations, and potential contributions to advancing our understanding and management of the diseases. The review examines the applications of health claims databases in retinal disease research, including epidemiological studies, comparative effectiveness and safety analyses, economic burden assessments, and evaluations of patient outcomes and quality of care. Previous findings demonstrate the value of these databases in generating prevalence and incidence estimates, identifying risk factors and predictors, evaluating treatment effectiveness and safety, and understanding healthcare utilization patterns and costs associated with retinal diseases. Despite their strengths, health claims databases face challenges related to data limitations, biases, privacy concerns, and methodological issues. Accordingly, the review also explores future directions and opportunities, including advancements in data collection and analysis, integration with electronic health records, collaborative research networks and consortia, and the evolving regulatory landscape. These developments are expected to enhance the utility of health claims databases for retinal disease research, resulting in more comprehensive and impactful findings across diverse retinal disorders and robust real-world insights from a large population.
Keyphrases
- healthcare
- optical coherence tomography
- big data
- health insurance
- diabetic retinopathy
- electronic health record
- public health
- health information
- risk factors
- mental health
- optic nerve
- systematic review
- human health
- quality improvement
- artificial intelligence
- social media
- risk assessment
- transcription factor
- adverse drug
- deep learning
- climate change