Our Evidence Synthesis Initiative falls within our broader research synthesis efforts, which take advantage of a wide variety of tools to pull together and analyze results for public use. We are using two key approaches. One is conducting systematic reviews of results of already completed comparative clinical effectiveness research (CER) studies and other methodologic approaches that share an underlying foundational method on topics of critical concern to patients and other healthcare stakeholders. The other is reanalyzing data from already completed studies to discover which specific patient groups gain the most or least benefits—or are at greater or lesser risk for harms—from an intervention.
Once we have synthesized the evidence, we will disseminate it through products designed to meet the needs of our various stakeholder groups.
Types of Evidence Synthesis
The most common type of evidence synthesis is the systematic review. According to the National Academy of Medicine (formerly the Institute of Medicine) and PCORI, a systematic review features a set of clearly specified, rigorous, reproducible, and transparent methods. These reviews provide answers to specific clinical questions by analyzing published and unpublished results from all relevant studies on a given topic. They identify, select, and summarize findings of available research to make clear what is known about a topic—and what is still not known.
Based on input we have received from stakeholders, our initial efforts include systematic reviews of treatment options for:
- Psychological and Pharmacological Treatments for Adults with Posttraumatic Stress Disorder (PTSD): A Systematic Review Update
- Nonsurgical Treatments for Urinary Incontinence in Women: A Systematic Review Update
- Drug Therapy for Early Rheumatoid Arthritis: A Systematic Review Update
- Stroke Prevention in Atrial Fibrillation Patients: A Systematic Review Update
Our goal is to produce up-to-date, actionable evidence to inform important healthcare choices. We’re implementing this initial effort in coordination with the Agency for Healthcare Research and Quality.
PCORI aims to demonstrate that a patient-centered, stakeholder-driven approach to clinical research has value to researchers, payers, policy makers and other members of the healthcare community by improving the quality, relevance, and usability of study findings. To help accomplish this, we are harnessing information in various forms, such as evidence maps, which help synthesize large amounts of data and can be produced in less time than a traditional systematic evidence review, while using many of the same processes.
Emerging Technologies and Therapeutics Reports
These reports provide timely summaries of evidence supporting new drugs, devices, and other healthcare technologies that are recently in use or may be available in the near term in the United States. The documents also identify gaps that need to be addressed for the technologies or therapeutics to move forward.
PCORI Health Care Horizon Scanning System
The Health Care Horizon Scanning System (HCHSS) provides a systematic process to identify healthcare interventions that have high potential to disrupt the current standard of care. The technologies and innovations of interest in this program are those that have yet to become an established part of healthcare practices, and are often in the later stages of research and development.
This approach uses statistical methods to combine published or unpublished study findings to produce estimates of an intervention’s effect and to illustrate how consistent and strong the effect is across the research. Meta-analyses typically summarize the average treatment effect for the entire study population.
Individual Participant-level Data (IPD) Meta-analysis
This approach obtains and synthesizes all relevant measured characteristics of each participant in multiple related studies. It is a powerful method to identify the ways in which treatments may have varying benefits and risks for people with different characteristics. It is a way to see whether treatments should be targeted for use in specific groups of individuals. It is also an important method to reconcile differences between studies examining the same treatments that have conflicting results. We have to date awarded one IPD meta-analysis.
Other Secondary Data Reuse Opportunities
Besides IPD meta-analyses, a statistical approach called predictive analytics can be applied to previous trials or other research data to provide more-personalized results that can optimize the use of specific treatments. This approach can be helpful in studies with a diverse group of people and a wide range in individual responses to an intervention. We have to date awarded one secondary data reuse project.
- Predictive Analytics Pilot Study: Assessment of Heterogeneity of Treatment Effects in Two Major Clinical Trials
Posted: October 27, 2017; Updated: May 2, 2019