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CFAs: Improving Methods for Conducting Patient-Centered Comparative Clinical Effectiveness Research (US)

Researchers using advanced technologies and methods, including AI and machine learning, to improve patient-centered comparative clinical effectiveness research. The image illustrates activities related to study design, data analysis, and ethical considerations in clinical research.


The Patient Centered Outcomes Research Institute (PCORI) aims to fund studies addressing high-priority methodological gaps in patient-centered comparative clinical effectiveness research (CER).

Category

Grant

Programmatic Priorities

For the 2024 Methods PFA, PCORI has identified several programmatic priorities to improve the strength and quality of evidence generated by CER studies:

  • Methods to Improve the Use of Artificial Intelligence (AI) and Machine Learning (ML) in Clinical Research
  • Methods to Improve Study Design
  • Methods to Support Data Research Networks
  • Methods Related to Ethical and Human Subjects Protections Issues in Patient-Centered CER

Priorities

Methods Related to Ethical and Human Subjects Protections (HSP) Issues

PCORI is interested in projects that address ethical and HSP issues related to patient-centered CER. Priorities include:

  • Measures Recruitment and informed consent processes for various types of clinical trials and studies
  • Assessing the concept of minimal risk in clinical research
  • Review and monitoring activities, protocol adherence, and outcome adjudication

Methods to Improve Study Design

PCORI aims to foster improvements in clinical research study designs, particularly for patient-centered CER. Priorities include:

  • Design and conduct of Sequential Multiple Assignment Randomized Trials (SMART)
  • Design and conduct of decentralized clinical trials (DCTs)
  • Methods to manage treatment strategy adaptation in studies of complex interventions

Methods to Support Data Research Networks

  • Improving distributed analyses in data research networks
  • Improving data quality in data research networks
  • Promoting interoperability of data science methods and data across research networks

Methods to Improve Use of Artificial Intelligence and Machine Learning in Clinical Research

PCORI seeks to improve how data from electronic health sources can be analyzed and integrated into clinical care and healthcare delivery systems. Topics include:

  • Approaches to integrating heterogeneous data sources and extracting representations from unstructured data
  • Methods for causal inference machine learning
  • Approaches to improving transparency and resilience of algorithms

Topic & Themes

The Topic Themes aim to encourage submissions in the following areas:

Populations

  • Improving outcomes for people with intellectual and developmental disabilities (IDDs)
  • Promoting health for older adults
  • Promoting healthy children and youth

Health Behaviors

  • Addressing substance use
  • Addressing violence and trauma

Health Conditions

  • Addressing COVID-19
  • Improving cardiovascular health
  • Improving mental and behavioral health

Funding Information

  • Funds Available: Up to $12 million
  • Total Direct Costs: Up to $750,000
  • Maximum Project Period: Up to three years

Eligibility Criteria

Applications may be submitted by appropriate academic research, private sector research, or study-conducting entities. This may include:

  • Agencies and instrumentalities of the federal government
  • Nonprofit and for-profit research organizations
  • Colleges and universities

Highlights

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