ArticlePain medicine (Malden, Mass.)2023
NIH HEAL Clinical Data Elements (CDE) implementation: NIH HEAL Initiative IMPOWR network IDEA-CC.
Article in Pain medicine (Malden, Mass.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT06060925 (Multimodal Imaging Biomarkers for Investigating Fascia, Muscle and Vasculature in Myofascial Pain), which is not on this map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Multimodal Imaging Biomarkers for Investigating Fascia, Muscle and Vasculature in Myofascial Pain
Who cites it
27 citing papers in PubMed, 30 citations in OpenAlex.
- Study Protocol for a Pain Self-Management Intervention to Reduce Pain and Improve MOUD Engagement in Primary Care: A Randomized Trial.Substance use & addiction journal · 2026Trial
- A new AI assisted approach aligns data standards and accelerates interoperability in biomedical research.NPJ digital medicine · 2026Article
- Pain assessment tools in patients with substance use disorders: a systematic scoping review.Addiction science & clinical practice · 2026Article
- Multidimensional analysis of the clinical spectrum and symptom burden of unexplained myofascial pain.medRxiv : the preprint server for health sciences · 2026Article
- Extending the Observational Medical Outcomes Partnership (OMOP) Common Data Model for Critical Care Medicine: A Framework for Standardizing Complex ICU Data Using the Society of Critical Care Medicine's Critical Care Data Dictionary (C2D2).Critical care medicine · 2026Article
- Expanding rural access to chronic pain care through nurse care management: A hybrid type I effectiveness-implementation trial protocol.PloS one · 2026Article
- Review
- Article
- Leveraging the Rural-Urban Commuting Area Tool to Address Geographic Disparities in Cancer Care: A Dual-Application Framework for Institutional and National Initiatives.JCO clinical cancer informatics · 2025Article
- A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements.Current opinion in anaesthesiology · 2025Review
- A guide to developing harmonized research workflows in a team science context.Experimental neurology · 2025Review
- Patient-Reported Outcomes Among an Observational Cohort of Individuals With Chronic Low Back Pain.JOR spine · 2025Article
- Navigating the new NIH Data Management Sharing plan: the NIH HEAL Initiative Data2Action DMPTool template.JAMIA open · 2025Article
- Building community through data: the value of a researcher driven open science ecosystem.Pain medicine (Malden, Mass.) · 2025Article
- Automated multi-instance REDCap data synchronization for NIH clinical trial networks.JAMIA open · 2025Article
- Breaking Digital Health Barriers Through a Large Language Model-Based Tool for Automated Observational Medical Outcomes Partnership Mapping: Development and Validation Study.Journal of medical Internet research · 2025Article
- The NIH HEAL pain common data elements (CDE): a great start but a long way to the finish line.Pain medicine (Malden, Mass.) · 2025Review
- Article
- Enhancing Gen3 for clinical trial time series analytics and data discovery: a data commons framework for NIH clinical trials.Frontiers in digital health · 2025Article
- Designing and implementing solution-oriented team science initiatives-a chronic pain example.Frontiers in pain research (Lausanne, Switzerland) · 2025Review
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveThe National Institutes of Health (NIH) HEAL Initiative is making data findable, accessible, interoperable, and reusable (FAIR) to maximize the value of the unprecedented federal investment in pain and opioid-use disorder research. This involves standardizing the use of common data elements (CDE) for clinical research.
methodsThis work describes the process of the selection, processing, harmonization, and design constraints of CDE across a pain and opioid use disorder clinical trials network (NIH HEAL IMPOWR).
resultsThe network alignment allowed for incorporation of newer data standards across the clinical trials. Specific advances included geographic coding (RUCA), deidentified patient identifiers (GUID), shareable clinical survey libraries (REDCap), and concept mapping to standardized concepts (UMLS).
conclusionsWhile complex, harmonization across a network of chronic pain and opioid use disorder clinical trials with separate interventions can be optimized through use of CDEs and data standardization processes. This standardization process will support the robust secondary data analyses. Scaling this process could standardize CDE results across interventions or disease state which could help inform insurance companies or government organizations about coverage determinations. The development of the HEAL CDE program supports connecting isolated studies and solutions to each other, but the practical aspects may be challenging for some studies to implement. Leveraging tools and technology to simplify process and create ready to use resources may support wider adoption of consistent data standards.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.