{"doi":"10.1093/pm/pnae093","title":"Strategies for working with pragmatic clinical trial observational data—lessons learned from the Pain Management Collaboratory","abstract":"In 2017, an inter-governmental agency partnership between the National Institutes of Health (NIH), the Department of Defense (DOD), and the Department of Veteran Affairs (VA) was announced to support multimodal pragmatic clinical trials (PCTs) targeting nonpharmacologic management of chronic non-cancer pain among active service members and Veterans, entitled the NIH–DOD–VA Pain Management Collaboratory (PMC).1,2 PCTs are usually embedded in routine healthcare workflows and leverage routinely collected data from electronic health records (EHRs) to reduce data collection costs and facilitate replication.3,4 While the DOD and VA have long-established EHR systems, there were significant limitations in the collection and use of EHR data within the PMC PCTs. These data are largely limited to routinely documented ratings of pain severity and pain-relevant diagnoses, tests and procedures, clinical encounters, and medications, with a large portion of the information in narrative text. For the PMC Coordinating Center (PMC3), the EHR work group (WG) was 1 of 7 WGs established to support the program. The WG’s responsibilities included supporting the PCTs understanding, optimizing, and documenting the use of EHR data and supporting prospective data collection and EHR-aligned interaction with clinical care delivery. Here, we describe key activities and lessons learned within the EHR WG of the PMC3 as they evolved based on client research project use, interest, and engagement. The WG membership was represented by personnel funded by the coordinating center and each of the participating projects (supported through the projects). The WG leadership team included 2 co-chairs who were VA clinicians with expertise in VA EHR infrastructure and systems, a DOD representative with expertise in the DOD EHR and Military Health System Data Repository (MDR), and a PMC3 project manager to provide organization. The remaining WG membership included PMC project principal investigators and technical faculty and staff involved with EHR data collection, integration, and synthesis. All projects used EHR data in some way, such as demographics, medication, or laboratory data.1 EHR WG support was the most frequent during the initial 2 years, and meetings were initially monthly, then bimonthly, and lastly as needed. WG activities were communicated to PMC-wide audiences through meetings with leadership and PMC sponsors, monthly reports to the PMC3 Steering Committee, and cross-WG coordination meetings. The EHR WG leadership team coordinated with projects to compile key observational data elements each intended to use. During initial meetings, the WG updated the scope and goals to reflect client project needs, which were: (1) information and knowledge for retrospective and prospective EHR and patient-reported outcomes data collection,5 (2) guidance on harmonization of definitions for data elements to align between VA and DOD projects where possible, and (3) the need to support cross-project harmonization of data element definitions and transformation processes. We found this was a critical step to establish the working goals and processes to support projects. This allowed us to understand the general data requirements for each project, when EHR data support was needed, and identified special needs for information gathering or data collection support. During this project, the VA and DOD were modernizing their EHRs and migrating to commercial applications. Both chose Oracle Health (previously Cerner) as the vendor, but implementation strategies differed in timelines and how each organization modeled and harmonized data. Because of concerns for unexpected project impacts, the WG provided regular updates on changes to legacy and Cerner systems in both environments. WG co-chairs held organizational leadership roles that facilitated inviting national EHR technical leaders to provide updates directly to researchers in the WG meetings and facilitated individual project meeting","journal":"Pain Medicine","year":2024,"id":483807,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9453,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":263472,"name":"Cynthia Brandt","orcid":"0000-0001-8179-1796","position":1,"is_corresponding":false},{"id":1324791,"name":"Kalyn C Jannace","orcid":"0000-0001-8119-6962","position":2,"is_corresponding":false},{"id":537191,"name":"William T. Roddy","orcid":null,"position":3,"is_corresponding":false},{"id":794497,"name":"Michael Raffanello","orcid":null,"position":4,"is_corresponding":false},{"id":794498,"name":"Norman Silliker","orcid":null,"position":5,"is_corresponding":false},{"id":1324792,"name":"Joseph Erdos","orcid":"0000-0003-4442-0683","position":6,"is_corresponding":false},{"id":11398,"name":"Michael E. Matheny","orcid":"0000-0003-3217-4147","position":0,"is_corresponding":true}],"reference_count":8,"raw_metadata":null,"created_at":"2026-07-19T02:07:33.718973Z","pmid":"39514883","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}