The role of the National Council on Pricing and Reimbursement of Medicinal Products (NCPR)

Owing to cutting edge digital technologies and analytical solutions leveraging the capabilities of artificial intelligence and machine self-learning, health data is becoming increasingly accessible to assist regulatory decision-making related to medicines. Vast amounts of health data are generated every second, providing healthcare stakeholders and researchers with the opportunity to draw deeper and more valuable conclusions.

Clinical trials remain the primary method for establishing the safety and efficacy of medicines during the authorization phase, with a trend towards conducting them solely on a placebo rather than an active comparative alternative. In addition, clinical trials are being conducted in a fewer and fewer number of patients, particularly for drugs intended to treat rare diseases or which target a specific mutation. In this sense, studies do not provide robust and long-term data on the efficacy and safety of the investigational medicinal product and do not reflect application in real-world practice. This leads to gaps between regulatory dossiers and the subsequent clinical evidence needed by stakeholders along the chain, such as health technology assessment bodies (HTABs), payers and ultimately clinicians and patients.

As innovative medicines whose clinical trials present limited information enter the market in the EU member states, the issue of using data derived from real-world practice is becoming increasingly relevant. There is a growing need to create conditions for collecting and analyzing data derived from real-world practice which would represent long-term treatment outcomes, both in terms of efficacy and safety, and comparative effectiveness against well-established treatment standards.

Health data can help achieve more effective, higher quality, safer and more personalized health care. Health data and data science could dramatically transform public health and improve healthcare systems. Health data can also play a critical role in accelerating the development of new drug treatments for patients who need them most.

In this respect, the European regulation aims at creating a framework with rules and standards to ensure the reliability, quality and security of the collected health data used subsequently in decision-making.

In the guidelines of the project of the European Commission "Towards the European Health Data Space" (TEHDAS) and of the European Medicines Agency - Heads of Medicines Agencies (EMA-HMA) on data quality, quality is defined as "fitness for purpose and users’ needs in relation to the secondary use of data for health research, policy making and regulation, and that the data reflect the reality they are intended to represent."

The definition suggests an approach to data quality that includes elements of technical quality and utility. These are relevance, accuracy and reliability, coherence, coverage, completeness and timeliness. The approach is applied in two aspects: the first focuses on data quality and utility at the level of the dataset; and the second focuses on data quality management procedures at the level of the data owner.

The dataset that can potentially be used for regulatory purposes comprises different data sources, each generated through different processes and suitable for different primary uses. When considering the overall quality of a dataset at the point of regulatory decision making, it is important to distinguish what contributes to quality and at what stage what can be measured or controlled.

Data quality management and quality assurance are an integral part of the data management of an organization. The data quality assurance framework should cover all data management processes, including monitoring, incident detection and resolution, and data enrichment procedures.

Data quality management should be applied throughout the data lifecycle, focusing on (a) data collection, curation, storage, and staging, (b) data integration with relevant sources and systems, (c) data description and meta-data management (i.e., use of meta-data standards), (e) data quality assessment, profiling, and remediation, (d) data modeling, transformation, operationalization, and servicing.

Data quality during the evidence generation process (data lifecycle).

The data that is available for evidence generation goes through a process that is specific to the type of data, and to the processes and organizations that produce it. The stages of the common lifecycle include: defining the data requirements, collecting or generating the data, managing and processing the data, publishing the data, procuring and aggregating the data, testing and accepting it, delivering for consumption. It is not necessary that all phases are present in each process for processing and using data.

The proposal for the Regulation of the European Parliament and of the Council on the European Health Data Area and the TEHDAS and EMA-HMA guidance on data quality address primary and secondary data use.

The primary use of electronic health data is the processing of personal electronic health data to provide health services for the assessment, maintenance, and restoration of the state of health of a patient to whom they relate, including the prescription and dispensing of drugs and medical devices, as well as social insurance, administrative, and reimbursement services.

The secondary use of electronic health data aims at the provision of health or care or for public health, research, innovation, policy-making, official statistics, patient safety or regulatory purposes collected by entities and bodies in the health or care sectors, including public and private sector health or care providers, entities or bodies carrying out research in relation to those sectors, and the institutions, bodies, offices and agencies of the Union.


The establishment of initiatives such as the DARWIN EU platform (Data Analytics and Real World Interrogation Network) and the European Health Data Space-EHDS are evidence of the growing importance of using real-world data in healthcare regulation. The aim of these initiatives is to collect as much real-world evidence (RWE) as possible from EU Member States for secondary use and to generate evidence that can subsequently guide regulatory decision-making and support the evaluation of health technologies.

The European Health Data Space (EHDS) defines a common EU framework enabling the use of health data for research, innovation, public health, policy-making, regulatory activities and personalized medicine. It is based on the creation of a new and decentralized EU infrastructure for secondary use of health data (HealthData@EU), which will connect the responsible bodies for access to health data that are to be set up in all Member States. Member States will ensure that electronic prescriptions, images, laboratory results, discharge reports are issued and accepted in a common European format. Under strict conditions, researchers, innovators, public institutions or industry will have access to large amounts of high-quality health data that are crucial for developing life-saving treatments, vaccines or medical devices and for ensuring better access to healthcare and more sustainable health systems.

In the report "Real-world evidence framework to support EU regulatory decision-making", the EMA and HMA share the experience gained from several pilot studies conducted with evidence from real practice led by regulatory institutions. The studies responded to the needs of the EMA committees and national competent assessors and assessed the opportunities and challenges of providing real-world data (RWD) for decision support.

The review demonstrates that the current RWE framework with its three evidence generation pathways (internal studies, DARWIN EU studies, studies provided through the EMA Framework Contract (FWC)) is able to address a wide range of research questions and support decision making in different regulatory contexts and procedures.

RWD research poses challenges and requires a good understanding of the methods involved, terminology as well as a thorough knowledge of the characteristics of the data source and the organization of the health system in the countries concerned.

The main findings in this report focus on the importance of the suitability of available RWD sources, the regulatory context and timing, collaborative working, capacity building, decision usefulness and applicability, and awareness and transparency of the process.

The generation and use of RWD/RWE is also finding application in health technology assessment, contributing to objectivity and certainty of the results of the assessments conducted, as well as better predictability about the outcomes and value of the technologies being assessed. 

The practice in European countries shows that HTA institutions require the submission of additional data from actual practice, but assign this obligation to the marketing authorization holders. It is entirely their responsibility to design how the data will be collected, the statistical methods by which the data will be processed and how the data will be presented. Guidance documents have been developed by the leading European HTA agencies which provide detailed descriptions of the conduct of real-world studies related to the evaluation of health technologies (medicines and medical devices) (France-HAS) to support the use of real-world data, in cases where information/data is lacking and to speed up and facilitate patient access to innovation (UK-NICE) and to collect data that cannot be attributed to a 'randomised clinical trial' to enable quantification of additional benefit (Germany-IQWiG, G-BA). This data is also used in the subsequent evaluation of the efficacy, long-term benefits and safety of medicinal products in real therapeutic practice.

The role of the National Council for the Pricing and Reimbursement of Medicinal Products (NCPR)

In recent years, Bulgaria has been faced with the challenge of meeting scientific developments with a limited budget for drug treatment, as more and more innovative medicines have entered the market with high prices and limited data on their effectiveness. In this context, collecting data from real-world practice is crucial for the efficient and appropriate use of public funds, namely treating patients in a timely manner with the most effective and safe therapy for them. To this end, a process for monitoring the effect of therapy has been adopted and developed in Bulgaria, which is carried out by the National Council for the Pricing and Reimbursement of Medicinal Products (NCPR). Unlike in other European countries, in Bulgaria this process is entirely led by the state institution by extracting data from the hospital information systems of the medical institutions where the patients are treated. The process is fully automated in order to avoid further burdening the work of specialist doctors. The data collected are those that the paying institution uses, evaluates and validates for payment (primary use of electronic health data). Subsequent processing, structuring and analysis of the data is carried out by the NCPR (secondary use of electronic health data).

Similar to the regulator-led RWD studies, in Bulgaria, the NCCRP is collecting, storing, analyzing and using real-world data on innovative medicines that have undergone health technology assessment but have not presented data on therapeutic effectiveness or the cost/benefit ratio is cost ineffective.

To ensure the quality of the data collected, they undergo an assessment of the metrics of relevance - which of the data collected are relevant to monitoring the effect of therapy with a given medicine, accuracy and reliability - are the data correctly completed, coherence, coverage - do they cover all the necessary information, completeness and timeliness - are all the necessary data completed and in what time period. Data management processes monitoring, incident detection and resolution and data enrichment procedures are also assessed.

The health data in monitoring the effect of medicines in Bulgaria corresponds to the steps that the life cycle of data, used to generate evidence, goes through:

Data lifecycle table

Data lifecycle

Practice in Bulgaria

defining the necessary data

development of criteria for monitoring the effect of therapy

data collection/generation

from the hospital by transferring XML files from the hospital systems

data management and processing

NCPR/Danny Platform (Sqilline) - data extraction, anonymization and structuring

data procurement and aggregation

NCPR analyses the data

testing and acceptance

data validation, qualitative analysis

delivery for consumption

annual reports, publications

The methodology applied by the NCPR meets the evolving data quality framework of TEHDAS and EMA-HMA, resulting in reliable data for secondary use, which would lead to certainty in regulatory decision making.

Secondary data use: the data collected, processed and systematized are used in two ways:

  1. Use of data (data consumption) - preparation of an annual report "Annual report on the monitoring of the effect of therapy of medicinal products", annually submitted to the NHIF/MH for the purpose of effective and appropriate spending of public funds and use of the collected and analyzed information from real practice in maintaining the reimbursement status of medicinal products, in the evaluation of efficacy, therapeutic effectiveness, safety and pharmacoeconomic indicators of medicinal products.
  2. Publications - the first article "Adequate effectiveness of ribociclib plus letrozole or fulvestrant in patients with advanced or metastatic hormone receptor- positive, human epidermal growth factor receptor 2-negative breast cancer treated in routine Bulgarian clinical practice" written by a team of authors, with the participation of the NCPR, was prepared using the collected and analyzed data from real practice and published in the journal "Biotechnology & Biotechnological Equipment".

The process has been carried out by the NCPR since 1 April 2019 and for this period four annual reports with collected, statistically processed and analyzed information on the effect of the use of medicinal products in real practice, comparison between the effects and results achieved by the evaluated products in real practice and those achieved in clinical trials, and comparison between the results achieved by the evaluated products against their comparative alternatives according to the Bulgarian therapeutic guidelines have been prepared and submitted to the paying institutions. In the last report prepared, an additional alignment of the characteristics of the real population to those of the clinical trial was performed using the Iterative Proportional Fitting (IPF) algorithm. This method was used for the drugs where a sufficiently large cohort of patients was available in the real practice data.

During the four-year follow-up period, sufficiently meaningful and qualitative data from the treatment of Bulgarian patients were collected and experience was gained in data collection and processing, which allowed the first publication with real-world data in Bulgaria. It serves as a basis for the development of further publications in the field of oncology and rare diseases.

The accumulated personal experience, together with the main conclusions from the experience and the recommendations from leading European agencies gives Bulgaria the certainty to continue its path towards evidence-based medicine. The methodology used by the NCPR is in line with the developed European recommendations. This gives confidence to publicly share the methodological guidance on the collection, processing and use of real practice data in decision making, defining concepts such as RWD and RWE also in the Bulgarian practice, as these processes are implemented and are used when making informed decision by state authorities.