Business Brief

A total of 102 countries and regions use a systematic, formal decision-making process to evaluate health interventions, according to a 2020-21 survey by the World Health Organization (WHO).⁴ Most European nations apply some aspects of an HTA approach to decisions about pharmaceuticals, and more than two-thirds use an HTA to support decisions about other health technologies (e.g., medical devices).⁵ Major public and individual health and economic consequences flow from HTA findings.

An HTA can be conducted at any point in a health intervention’s life cycle (see figure 1). It can be done before or after market introduction, or when a new indication for a marketed pharmaceutical is under consideration. As the focus on evidence-based decision-making in health care has increased, the role and scope of the HTA has evolved and demand for assessments grown. These factors create pressure to improve the efficiency of HTA processes.

Figure 1: Health Intervention’s Life Cycle

Literature gathered for an HTA can therefore cover a variety of topics, including the epidemiology and clinical burden of the disease or condition impacted by the health technology evaluated; the clinical efficacy, safety, and cost of available interventions and the intervention under evaluation; and organizational, social, and legal considerations.

Systematic reviews therefore may search not only peer-reviewed biomedical literature but also gray literature (e.g., non-peer-reviewed publications, unpublished material, government or association documents) and de-identified real-world evidence from government, nation-based, or payer claims databases describing the intervention’s clinical and cost impact on the target population.

There are acute challenges associated with HTA SLRs, which organizations are confronted with in their work.

• Information overload
• Time constraints
• The need for transparency and accuracy

The rising number of new pharmaceuticals, medical devices, and other health innovations, along with their novelty and increasing complexity, have led to an increased workload for HTA agencies.

Human reviewers may not apply criteria for literature assessment, retrieval, data extraction, and bias evaluation consistently to each study they screen. Systematic reviews are often conducted by teams organized by subject matter expertise. Multiple professionals may apply search and assessment criteria in slightly different ways, introducing inconsistency, error, and inadvertent bias.

Only 51% of 152 reviews evaluated in a recent study reported the use of a standardized extraction form. Only 20% reported using software for study selection, and just 12% for extraction.¹⁷ Data extraction errors are common — a recent analysis of 201 systematic reviews found an error rate of 85%.¹⁸ Spreadsheets, a common tool in developing an SLR, are prone to manual data entry errors and duplicate references that can be difficult to detect.

DistillerSR, for example, automates the entire literature review life cycle, from search and screening to full-text retrieval, data extraction, and reporting. The software automates the management of literature collection, triage, and assessment using intelligent workflows. The workflow is configured based on the literature review methods of any study protocol, and the user can modify the workflow to suit their needs.

Specifically, DistillerSR automates the conduct of HTA by:

Literature searching and screening

• Imports references from native search platforms and from a variety of sources including gray literature
• Integrates with PubMed, Ovid, and EBSCO
• Automates literature searching, de-duping, and updates
• Applies AI to continuously reorder references based on relevance, so that team members are presented with those deemed most pertinent first

An example is a customer who uses the LitConnect feature on DistillerSR to reduce time spent updating searches by 50%. This allows for newly published references to be imported automatically. DistillerSR applies AI to determine inclusion and exclusion patterns, reordering references based on relevance and thereby producing a more efficient overall review process and faster completion rates.

Full-text retrieval

• Connects directly to full-text open-access and paid subscription sources

DistillerSR allows customers to focus on key tasks, such as capturing high-quality data from the literature, while the administrative tasks, such as copyright management, are conducted by integrated software partners in the platform. DistillerSR’s integration with these partners allows access to free full-text or purchased subscriptions, further reducing time spent searching for articles while lowering overall literature costs.

Data extraction and bias assessment

• Validates data before submission to avoid errors
• Converts data with built-in calculations
• Automates compilation of tables

An example of DistillerSR’s automation of data extraction is its ability to capture and analyze complex data such as time points across multiple studies. All the collected data can be analyzed, shaped, and exported using the data reporting tool, either in real time or as a scheduled job.

Multiple teams within HTA agencies work together to develop assessments, and many HTA agencies outsource to external groups.²⁴ As a web-based platform, DistillerSR acts as the nerve center for systematic review for HTA projects, making data accessible to all team members across different, often global, locations for analysis. It tracks which references have been screened and what data has been extracted to avoid duplication of effort.

It can classify references and assign them to the relevant subject matter expert for screening via a standard workflow configured by the project’s administrator. It also notifies relevant team members when new references are available for screening.

DistillerSR also has a module called CuratorCR. Integrated seamlessly with DistillerSR, CuratorCR is a research knowledge center that centrally and dynamically manages an organization’s evidence-based research, allowing you to continuously collect, update, share, and reuse its data. As a result, CuratorCR eliminates re-analyzing and extracting the same data from already screened and processed references throughout an organization — speeding screening and data extraction times while reducing overall subscription costs for references. Moreover, teams can create segmented project or subject-based databases consisting of previously collected data for reuse in other reviews, or for joint research consortia between private and public sector organizations.

The data reuse approach is timely. A movement in Europe toward joint clinical assessments and scientific consultations for the most technical and demanding innovations places a premium on technology or structures that facilitate collaboration across HTA bodies. National HTA agencies often evaluate the same technologies within the same time frame, resulting in duplicate effort. The Council of the EU and the European Parliament have adopted the EU HTA Regulation, which “aims to harmonize methodological standards and to foster collaboration among European HTA bodies.”²⁵

New oncology medications and advanced therapy medicinal products will be assessed jointly as of 2025, though each country makes the final HTA appraisals and reimbursement decisions. Orphan medical products will be jointly assessed as of 2028.

Software such as DistillerSR and its add-on module CuratorCR, which enable the integration of assessments by the EUnetHTA 21 consortium with the systems of member states, could only be beneficial.

Automating some of the most time-consuming and error-prone functions of a systematic review can increase the efficiency and accuracy of HTA development at a time when HTA agencies are under pressure to produce more and better-quality assessments. Literature review automation software that facilitates collaboration is especially desirable in this team-based industry where outsourcing is common.

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