Use of real world data to improve drug coverage decisions in China

Gaps in evidence for coverage decisions

Substantial challenges arise in assessing the value of drugs to inform coverage decisions. One problem is inadequate clinical evidence. Traditionally, the assessment process largely relies on evidence derived from randomised controlled trials, which are typically designed with strict patient selection criteria, implemented with reinforced compliance to treatments, and have relatively short follow-up. The drug performance in randomised trials may differ from that in the real world. Furthermore, the trials are often multicentre international trials in populations that might not fully represent the Chinese population.

Obtaining clinical evidence is particularly challenging for oncology and orphan drugs because they are often approved through expedited review pathways and use data from single arm trials. For instance, 52.5% of new drugs were approved through expedited pathways from 2017 to 2020 in China.4 Consequently, the effectiveness and comparative effectiveness was often uncertain at the time of approval. Moreover, these trials often had relatively short follow-up periods and evaluated short term treatment outcomes. This raises concerns about the clinical benefits of the drugs, especially in the long term.

Lack of clinical evidence is the tip of the iceberg. Some of the data required for economic modelling are not available from randomised trials, or the evidence is often weak or lacking. In many cases, for example, the data on disease burden and treatment patterns are primarily based on data from populations outside China,56 where the dose and course of treatments may differ from those in other countries.78

Economic models are commonly used to incorporate the data from multiple sources to produce cost effectiveness evidence to inform coverage decisions. However, the models are often criticised for lacking transparency and robustness, especially when locally relevant data are limited.9 Indeed, the lack of locally relevant data can substantially compromise the economic models as well as affecting estimations of budget impact. The expected usage, duration, and dosage of drugs in highly controlled trial settings are likely to differ from those in routine practice.

Use of real world data for coverage decisions

In the past several years, the extensive use of information technologies in healthcare and public health practices has boosted the generation of diverse real world data sources in China, including both national and local data sources.10 Electronic medical records, patient registries, and claims databases are now well established across the country. Together with sound epidemiological designs and robust analyses, these data can provide locally applicable evidence for assessing drug value.111213141516 Typically, these data are observational in nature and are used in observational study designs. However, randomised trials that are built on real world settings and make use of the strengths of these data systems are more able to control for different sources of biases than observational studies. Consequently, these randomised trials may offer better real world evidence about the value of drugs.17

In China, real world data may provide an array of local evidence to support decisions about whether a drug should be included in the reimbursement list and whether it should be renewed.

Use of real world data to support initial coverage decisions

Decisions about including a drug in the list for the first time require extensive and broad local evidence, ranging from disease epidemiology to treatment costs (table 1). Some of this evidence may be readily available from real world data, such as on treatment patterns, healthcare costs, and disease courses. These data are often embedded in electronic medical records and healthcare claims, and studies have shown the potential usefulness of these data for generating evidence.192526 However, when new drugs are approved under accelerated coverage review, they have not been used in the routine care. Thus, the evidence on efficacy, comparative effectiveness, and safety is often limited, particularly if only single arm trials are available.

One solution is to generate evidence about comparative effectiveness before the initial coverage decision. This would require drug manufacturers to produce evidence from routine use of these drugs. However, this is unlikely to be feasible for all new drugs given the current healthcare security policy in China. We thus propose using real world evidence generated from the Hainan Boao Lecheng international medical tourism pilot zone, known as the Hainan model.27

In 2019, the Chinese government issued a policy to accelerate access to new and clinically demanding medical products. Under this policy, Chinese patients can receive new medical products that have been licensed by major regulatory authorities overseas in Boao’s healthcare institutions before the products are approved by the NMPA. The medicines are granted special approval for use in Boao for the indications approved overseas, and patients with a confirmed diagnosis are treated in the routine healthcare setting rather than as part of a trial. After treatment, they return home with discharge medications and are followed up at local medical institutions. Currently, the longest follow-up is three years. The data collected during routine use of the new medical products at Boao and follow-up information generated at local medical institutions are integrated through a patient registry.

Data from Boao can be used to assess the comparative effectiveness of new treatments through observational study designs or pragmatic randomised trials. Although randomised trials overcome the problem of confounding, observational designs may be more appropriate for rare diseases or when an urgent decision is needed.

Using data generated from Boao may have limitations, particularly that the travelling population receiving these new products may differ from general residents. As a result, the data may not be fully representative of the Chinese population. However, the special policy measures at Boao have created supportive conditions for new medical products to speed up their launch in the China market, and tens of thousands of people have received these new medical products at Boao.

So far real world data from Boao have been used to support regulatory approval without conducting a trial in China. This type of evidence could also be used to support reimbursement decisions to minimise delay to market entry. When no local trial is conducted, the real world data can be used to support regulatory approval and coverage decisions concurrently. In such a scenario, the main contribution of real world evidence is to provide evidence on effectiveness and safety of these drugs. If the registry contains information on clinical care and treatment outcomes of patients receiving standard care as well as those receiving the new drugs, statistical methods can be used to compare the two approaches. Additionally, these data can provide evidence on treatment patterns and costs.

When a local trial has been conducted for regulatory approval, real world data from Boao would be used primarily to support coverage decisions. In this case, real world data from Boao can provide an array of evidence for coverage decisions, including on real world effectiveness and safety, treatment patterns, and costs, which would inform economic modelling.

Use of real world data to support renewal

The reimbursement of new drugs often results in important changes in clinical practice, patient outcomes, and use of healthcare resources. In such cases, real world data can provide critical information on decisions about renewals (table 2). As new drugs are increasingly used over time a broader array of evidence may be accumulated. Various data sources are readily available under such circumstances and may cover all aspects of information for renewal. In particular, claims databases may offer unequivocal advantages over electronic medical records in the reassessment of treatment patterns, resources use, and budget impact. Other databases such as electronic medical records and patient registries can be important sources for assessing real world effectiveness and safety.23031 Notably, pragmatic randomised trials may offer stronger evidence on comparative effectiveness than observational studies, as well as providing data on economic impact to support coverage renewal.

Show me the data: improving real world data

Despite the great potential of real world data in informing coverage decisions in China, important challenges remain. Data relevance and quality are probably the primary obstacles. Available data may not be able to answer questions of interest for decisions, and data inaccuracy and incompleteness are not uncommon.323334 Databases from single institutions often have incomplete outpatient data and lack information on patient follow-up, limiting their usefulness for assessing long term effectiveness and safety. In addition, data sharing and access are also limited, making linkage of data from multiple medical institutions and subsequent use less likely. As a result, research questions for coverage decisions may not be well addressed.

Another challenge lies in the limited research capacity to produce trustworthy real world evidence. Data quality is often suboptimal because of lack of transparent and appropriate data collection. These are issues not only about data collection, but also about appropriate use of data for research purposes. Although several advanced methods have been proposed, selecting an appropriate method to adequately disentangle confounding is a challenge.3536 Currently, few research groups have received training in methodology. The process of handling data remains obscure. Development of quality standards is a high priority for the production of real world evidence, and transparency also needs to be improved.

A few important initiatives to address these problems have emerged in China. National policies on the development and application of “big” healthcare data have been issued, facilitating the production and application of real world data.37 Population based healthcare data systems have been increasingly established in large municipal cities, with data linkage put in place.2538 These linked data can provide important information for assessing the value of drugs. A working panel consisting of experts from academic institutions and authorities has also been formed to develop technical guidance documents to improve the transparency and quality of real world evidence. In the future, a real world evidence community should be developed that consists of policy makers, healthcare providers, patients, academic institutions, and industry. Such a community would be likely to result in better use of real world evidence to support coverage decisions in China.