Real-world evidence (RWE) is clinical evidence on a medical product's safety and efficacy that is generated using real-world data (RWD) resulting from routine healthcare delivery. There are several sources of RWD, including electronic health records (EHRs), registries, claims/billing data, and patient-generated data, as well as those from mobile health applications and wearable devices. Real-world data from these sources can be collected and analysed through different study designs such as prospective and retrospective cohort studies, case-control studies, and pragmatic clinical trials. Real-world evidence in the form of post-marketing surveillance has been extensively used to generate pharmacovigilance data. Of late, it has been realised that, apart from safety, RWE has additional applications in different stages of the drug approval cycle, and can be used to optimize the design of randomised controlled trials (RCTs). There has been an increasing awareness and acceptance of RWE from different stakeholders, including physicians, pharmaceutical companies, payers, regulators, and patients. Several regulatory authorities have also created frameworks and guidelines for efficient harnessing of RWE while acknowledging several challenges in RWD collection and analysis. The purpose of this review is to offer an outline of the current information on RWE, its advantages and disadvantages, as well as the associated challenges and ways to overcome them, while also throwing some light on the future of RWE.
Keyphrases
- electronic health record
- healthcare
- big data
- clinical trial
- adverse drug
- end stage renal disease
- clinical decision support
- primary care
- clinical practice
- chronic kidney disease
- data analysis
- blood pressure
- newly diagnosed
- emergency department
- public health
- case report
- prognostic factors
- machine learning
- health insurance
- study protocol
- deep learning
- artificial intelligence