This article focuses on patient-reported outcomes (PROs) and their role in decision making in patient-centred healthcare. Let»s look at how PRO can be used in clinical trials, to evaluate the effectiveness of treatment, to validate a claim on a product label by regulatory authorities, and in clinical practice to monitor patient conditions.

Currently, information technologies are being actively introduced in the healthcare of the Russian Federation. The share of state and municipal medical organizations that have implemented various medical information systems increased from 3.9 % in 2007 to 91 % in 2021. One of the key tasks of informatization is the introduction of electronic medical records (EMRs), which accumulate large amounts of Real-World Data (RWD). Despite the importance of EHR as a source of RWD, they have a number of shortcomings, such as the decentralized nature of database management systems, unstructured information storage, etc. The article describes the sequential processes for collecting high-quality RWD based on EHR, including the use of artificial intelligence technologies, for the purposes of scientific research, the creation of decision support systems, statistical analysis, etc. The basis of the proposed methodology is the centralized collection of information from EMR in the so-called data lakes, where as much as possible of raw data on the patient is accumulated and subsequent extraction of data from unstructured records through natural language processing (NLP) models. The proposed technology, subject to continuous improvement, will provide a correct and comprehensive solution for the skilful understanding of any text from any medical record.

Randomized controlled trials (RCTs) are the gold standard for testing the efficacy of cancer therapy. Although the results of clinical trials have high internal validity, their generalizability, that is, the ability to transfer the results to a wide patient population, is limited. Therefore, users and health care workers may experience less effective intervention in real practice than stated in the RCT. There are many reasons for the formation of a gap between efficacy and effectiveness (efficacyeffectiveness gap; EEG), that is, the measure of impact on RCTs and the real-world. These reasons include, for example, different characteristics of patients in the trial and real practice, compliance to treatment, features of medical care, and others. To illustrate this problem, a review of some studies on the estimation of the magnitude and analysis of the possible causes of this gap is presented. In most of the studies cited, EEG was identified, its probable explanations were proposed, and additional estimates were made to establish the contribution of various factors to its magnitude. These publications» authors show that real-world patients are older, have worse functional status, and have a greater number of comorbidities. They are women mostly and are less likely to complete the treatment they have started or move to the next line of therapy, in contrast to participants in RCTs. Additionally, this article proposes various analytical approaches to determine the weight of the main causal factors in the formation of a discrepancy between efficacy and effectiveness, which can be used in the development of the methodology of relevant studies.

Knowing the size of the EEG when using different treatment regimens in their region and understanding the extent to which one or another factor can influence the size of this gap, the clinician will be able to predict the effectiveness of treatment and choose the best therapy for a particular patient.

The need to use more and more data to generate evidence in response to new challenges in clinical medicine requires a specific response from the healthcare system. The high pace of development of medicine, the acceleration of the development of new drugs in response to the increasing needs of clinicians for treating patients leads to the need for a rapid assessment of treatment outcomes, efficacy and safety of new drugs. The development of a tool for centralized collection of data on efficacy and safety, capable of connecting as many clinical centers as possible: hospitals, private medical centers, scientific institutions — is a priority for the health system to implement these responses. An example of this type of data collection and analysis coordination system development is the 2007 Food a nd Drug Administration (FDA) Sentinel initiative.

Sentinel is a national electronic system that has changed the way researchers monitor the safety of FDA-regulated medical products, including drugs, vaccines, biologics, and medical devices. Monitoring the safety of regulated products is an important part of the FDA»s mission to protect public health.

This review is devoted to the history of development, organizational structure, principles of operation and demonstration of some projects of the Sentinel system. The review will consider both projects developed for application within the framework of general clinical problems (use in vulnerable groups of patients, patients with kidney diseases, etc.), and projects developed in response to the needs of researchers that have arisen in the era of the COVID-19 pandemic.

This article is devoted to an ethical review of planned real-world studies. The legal basis of such examinations has also been considered. Most real-world studies are non-interventional, so the ethical review of such studies is similar to that of observational studies.