realise-guidance

The REAL World Data In ASia for HEalth Technology Assessment in Reimbursement (REALISE) working group is pleased to present the non-binding guidance document: 

Use of Real-World Data and Real-World Evidence to Support Drug Reimbursement Decision-Making in Asia (Version 1.1).

Download the full guidance

We thank all who contributed to the development and refinement of the guidance through public feedback consultation! We have tried our best to address the comments or incorporate the suggestions received. Some of the comments/ suggestions will need time and resources to address. We will work on these in our subsequent revisions.  For details of the consultation please refer to the summary below.

Download the public feedback consultation document

REALISE is a collaboration between global experts and 11 Asian health systems, established with the aim of developing a framework to generate and use real-world data (RWD) / real-world evidence (RWE) in a consistent and efficient manner for drug reimbursement decision-making in Asia. The guidance document is the product of this collaboration. It focuses on drug assessments and the use of RWD/RWE as complementary evidence to randomized controlled trials (RCTs), the current gold standard for generating evidence on treatment efficacy.

To date, two abridged versions of the guidance have been developed:

Abridged guidance for generators of RWD (e.g. clinicians, clinical administrators, hospital researchers)

Download the Abridged guidance (version 1.0) for generators of RWD

Abridged guidance for users of HTA (e.g. policy makers)

Download the Abridged guidance (version 1.0) for users of HTA

To help you better understand and implement the quantitative methods described in this guidance we have provided the following links to resources you may find useful:

Stata resources and support

https://www.stata.com/links/video-tutorials/

UCLA IDRE statistical resources

https://stats.idre.ucla.edu/other/mult-pkg/seminars/statteach/resources-for-teaching-statistics/

Implementing matching methods and propensity score in R

http://sekhon.berkeley.edu/matching/

Future work:

Our work does not end here. We are looking for funding to support the development of guidance documents for the use of RWD/ RWE in other areas such as rare disease and medical devices. Please contact hiper@nus.edu.sg if you are interested to support our work.

The NUS Saw Swee Hock School of Public Health and the Health Intervention and Technology Assessment Program (HITAP), Thailand, lead this project with the support of the International Decision Support Initiative (iDSI) and the Bill and Melinda Gates Foundation.

For information and clarifications, please email: hiper@nus.edu.sg