The Institute for Health Sciences of Aragon (IACS) has coordinated the development of a clinical practice guideline (CPG), funded by the Spanish Ministry of Health, for managing antidiabetic drugs in patients with type 2 diabetes mellitus. We conducted a living systematic review to provide a continuously updated evidence summary for formulating living recommendations on intensifying basal insulin therapy by comparing glucagon-like peptide-1 (GLP-1) receptor agonists with rapid-acting insulin.

In 2021, the IACS joined the Living Evidence to Inform Health Decisions (LE-IHD) project, which includes the use of technological tools to identify early emerging evidence on a defined topic. We conducted searches in the centralized Living Overview of Evidence (LOVE) and Epistemonikos databases. Specifically, the LOVE topic of interest from which the articles were selected was “glucagon-like peptide analogs and agonists for diabetes mellitus”. We applied the GRADE approach to rate the certainty of evidence and to develop clinical practice recommendations.

The initial baseline report included six randomized controlled trials (RCTs). We have continuously monitored the evidence and performed a monthly screening. Only one RCT was identified in the first update. The Guideline Development Group (GDG) decided to formulate a strong recommendation in favor of GLP-1 receptor agonists. The GDG considered the reduction in the risk of severe hypoglycemia events among patients treated with GLP-1 receptor agonists, compared with rapid insulin, particularly significant as well as the greater improvement in patient quality of life. Since the guideline was formulated, no new evidence has been identified that would change the recommendation.

Adoption of the living systematic approach underscores the commitment to providing continuously updated recommendations within CPGs. Utilizing the GRADE approach, the Guideline Development Group decided to formulate a strong recommendation in favor of GLP-1 receptor agonists over rapid insulin. No new evidence has emerged to alter this recommendation. The living systematic review will remain active, ensuring continuous monitoring until the final draft CPG is disseminated.

Preadoption assessments are the most frequent type of evaluation conducted by the Spanish Network of Agencies for Health Technology Assessment and Services of the National Health System (RedETS). RedETS aimed to develop a framework to utilize real-world data (RWD) to better adjust its assessments to the Spanish population’s context and provide live assessments throughout the lifecycle of health technologies.

A working group within RedETS was set up, which held several meetings to define the primary uses of RWD in the short term. Next, a manual review was conducted on national and international initiatives that provided guidance on the use of RWD in HTA. Common pathways for utilizing RWD in HTA were identified. The working group agreed to outline and explain the key overarching steps and provide general guidelines for working with RWD, developing as illustration a use case for an interventional technology. The Big Data project of Aragon (BIGAN) was chosen as the data source for the use case.

We formulated a case for leveraging RWD in the assessment of implantable cardiac defibrillators (ICDs) for the prevention of sudden cardiac death (SCD). Based on this scenario, we developed a methodological framework outlining a workflow consistent with RedETS practices. RWD complemented the usual process of systematic review of a technology. Crucial steps comprised the definition of data requirements through a data model specification, an exploratory data analysis, and the construction of a decision model. We presented solutions for dealing with unavailable data on essential variables and unstructured records. We discussed the main limitations to account for when working with RWD.

The task ahead holds great hope but requires overcoming some challenges to fully deploy RWD-driven methods. This entails fostering collaboration with health authorities and designated data holders to address data access challenges. In the short term, it is essential to include data scientists in assessment teams and provide appropriate capacity-building to encompass RWD tools and modeling techniques.