BACKGROUND: Scientific advances and cost efficiencies in genetics and genomics are expanding clinical application for prevention, diagnosis, and treatment. OBJECTIVE: PCORnet®, a research network that includes participat...BACKGROUND: Scientific advances and cost efficiencies in genetics and genomics are expanding clinical application for prevention, diagnosis, and treatment. OBJECTIVE: PCORnet®, a research network that includes participation from 78 health systems nationally and is linked to more than 47 million unique patients with at least one encounter annually, can help (1) understand the ability of genetics/genomics to predict health outcomes, (2) identify diseases impacted by genetic/genomic factors, (3) evaluate pharmacogenomics' role in medication optimization, (4) evaluate emerging gene therapies, and (5) compare clinical genetic or genomic strategies within learning health systems to improve outcomes, while (6) facilitating patient and other partner engagement across these areas. MAIN ARGUMENTS: The breadth of data accessible via PCORnet represents a unique opportunity to study relationships among genetic markers and clinical and exposome-based disease risk factors, particularly as more genomic data become available. The network's experience developing computable phenotypes for identifying specific diseases can be leveraged to evaluate the role of genetics/genomics in health. The PCORnet infrastructure can be used to identify patients with particular conditions for predictive modeling or comparative clinical effectiveness research using electronic health record data. The network can also recruit patients for observational cohorts or pragmatic clinical trials on pharmacogenomics or the return of genetic results, evaluation of emerging gene therapies, or embedded research into learning health systems to compare clinical genetics/genomics implementation approaches in health care. The partner engagement focus of the PCORnet® Network Partners can enrich research and improve health care delivery and outcomes. The rise of clinical genetics and genomics will profoundly impact health care in the next decade, and the PCORnet® Network Partners are primed to make a leading contribution in this area.
Franklin MS, Dolor RJ, Hendren S
… +12 more, Jelliffe-Pawlowski L, Wiley S, Myers SM, Quiñones A, Nowell K, Kanne SM, Kramer JM, Thompson B, Thomas E, Bello J, Pham HMH, Maslow GR
OBJECTIVE: This project sought to (1) identify critical gaps in knowledge of intellectual/developmental disabilities (IDD) clinical care and accelerate research by identifying a set of high-priority patient-centered comp...OBJECTIVE: This project sought to (1) identify critical gaps in knowledge of intellectual/developmental disabilities (IDD) clinical care and accelerate research by identifying a set of high-priority patient-centered comparative clinical effectiveness research (CER) questions that may be answered using PCORnet and (2) provide recommendations to advance CER for people with IDD (PwIDD). BACKGROUND: National-scale research is needed to better identify PwIDD, determine appropriate interventions, and evaluate care quality throughout individuals' life course to improve health outcomes and address health inequities. METHODS: PCORnet® Network Partners convened Workgroup members who: (1) provided input on research gaps based on their research, clinical work, and/or lived experiences, (2) conducted a literature scan, (3) examined the current capabilities through a data query of PCORnet data resources, (4) surveyed PCORnet® partner sites to describe current infrastructure, (5) identified gaps in knowledge, (6) prioritized unanswered patient-centered CER questions, and (7) characterized infrastructure needs to address CER questions. RESULTS: Sites participating in PCORnet® collectively serve many individuals across the range of IDD conditions, including more than 300,000 individuals with diagnosed autism. There is high utilization of the emergency department (19%-35%) and inpatient setting (8%-31%) across IDD conditions. We identified 3 broad evidence gaps and generated CER questions to address them. CONCLUSIONS: Our findings provide insight into the current gaps in knowledge of IDD clinical care, the use of the PCORnet infrastructure to improve cohort ascertainment for IDD CER, and opportunities to enhance the PCORnet® Common Data Model (CDM) to standardize additional patient-centered and IDD-focused data elements for future CER.
The PCORnet vision to accelerate progress towards a learning health system by enabling more efficient generation of evidence is shared by the US Food and Drug Administration, where we recently served. One way of achievin...The PCORnet vision to accelerate progress towards a learning health system by enabling more efficient generation of evidence is shared by the US Food and Drug Administration, where we recently served. One way of achieving this goal is to develop national networks capable of running streamlined clinical trials in the postmarket setting. In this invited commentary, we discuss how PCORnet® and similar networks could facilitate streamlined trials integrated into clinical practice across their sites.
BACKGROUND: The COVID-19 pandemic exposed differences in health care outcomes, including the prescription of COVID-19 antiviral medications. This analysis aimed to describe prescribing patterns in outpatient COVID-19 tre...BACKGROUND: The COVID-19 pandemic exposed differences in health care outcomes, including the prescription of COVID-19 antiviral medications. This analysis aimed to describe prescribing patterns in outpatient COVID-19 treatment and assess factors that contributed to these differences. METHODS: A cross-sectional analysis was conducted using electronic health record data from August 2022 through March 2024 from health care institutions participating in PCORnet,® the National Patient-Centered Clinical Research Network. Descriptive statistics were used to characterize COVID-19 outpatients eligible for treatment, and regression models were used to calculate adjusted prevalence ratios (aPR) of prescribed COVID-19 outpatient treatment. Interaction terms assessed the interactions between race and ethnicity and the combined comorbidity index (CCI), age and sex, and age and race and ethnicity. RESULTS: Of 1,247,420 patients eligible for COVID-19 treatment, 334,947 (26.9%) were prescribed outpatient treatment. In adjusted analyses, compared with White patients, all other racial and ethnic groups had lower aPR for treatment (aPRs:0.89-0.99), except patients who reported being multiracial (aPR:1.00; 95% CI: 0.93-1.08). Those aged 65-74 were prescribed treatment more often (aPR: 1.13; 95% CI: 1.12-1.13) compared with patients aged 20-49. Patients with a CCI of 1-3 and ≥4 were prescribed treatment less often (aPR: 0.99, 95% CI: 0.97-1.01 and aPR: 0.91, 95% CI: 0.89-0.94, respectively), compared with those with a CCI of ≤0. These differences were sustained when considering the interactions between race and age and race and CCI. CONCLUSIONS: We found differences in recommended outpatient treatment by several sociodemographic variables. Addressing COVID-19 prescription barriers is essential to slow preventable differences from unmet COVID-19 outpatient care.
This study analyzed COVID-19 disease severity distributions among different age, racial, and ethnic groups for pre-Omicron and Omicron variant periods from May 2020 to October 2022. Disease severity categories were defin...This study analyzed COVID-19 disease severity distributions among different age, racial, and ethnic groups for pre-Omicron and Omicron variant periods from May 2020 to October 2022. Disease severity categories were defined by ICD-10-CM diagnostic codes recorded in the electronic health record in the 7 days preceding and 13 days following the SARS-CoV-2 positive laboratory record (index date) and were grouped into 4 mutually exclusive categories: severe complications, high, moderate, and low disease severity. Low severity was defined as the absence of codes for any of the other categories. Among 1,613,706 included patients, there was a lower prevalence of disease severity during the Omicron variant period across all race and ethnicity groups (P<0.001) compared with the pre-Omicron variant period; however, the Omicron period had a higher prevalence of severe complications (P<0.05). Relative to White patients with high disease severity, Black patients and patients of other races had 37.1% and 52.4% (Pt<0.0001) greater risk of having high disease severity, respectively, in the pre-Omicron period, but high disease severity was similar across racial groups during the Omicron period. During pre-Omicron, mean monthly relative differences among Hispanic patients with high disease severity and severe complications compared with non-Hispanic patients were -5.17% and -39.4%, respectively, which shifted to 24.4% and 44.1% in the Omicron period (Pt<0.0001). These findings provide valuable insight into patterns of COVID-19 disease severity, especially for marginalized populations, and highlight the need for targeted public health strategies as variant-specific trends evolve over time.
OBJECTIVE: The PATHWAYS Study utilized data from the PCORnet® Common Data Model (CDM) at 4 sites participating in the STAR Clinical Research Network to assess the frequency of cardiology encounters for under-represented...OBJECTIVE: The PATHWAYS Study utilized data from the PCORnet® Common Data Model (CDM) at 4 sites participating in the STAR Clinical Research Network to assess the frequency of cardiology encounters for under-represented racial and ethnic minority group people living with Human Immunodeficiency Virus and to evaluate the determinants associated with specialty encounters from 2014 to 2020. This study dealt with several factors that other projects leveraging PCORnet might face. We describe benefits of working with the network, challenges, and recommendations for future study teams. METHODS: PATHWAYS used a mix of queries through the study, including study-specific data quality and analytic queries. A "sidecar" table was created for the PCORnet® Common Data Model to support the inclusion of referral data. Linkage to the National Death Index was incorporated into the study to allow for more comprehensive information on participant deaths. RESULTS: Data quality assessments identified several issues over the course of the study that needed to be addressed by the data teams at each site. The referral data proved not to be robust enough to support the proposed analyses, so an alternative strategy was required that leveraged encounter information. The National Data Index included information on participant deaths that were not part of each site's PCORnet® CDM. CONCLUSION: Incorporating study-specific data characterization into the overall analysis plan is important. When working with new data, or variables not commonly used within studies, teams should include time and effort for site resources to investigate their local clinical workflows and potential mappings to the PCORnet® CDM.
OBJECTIVE: To examine telehealth care utilization during pregnancy and in the 6 months postpartum during the COVID-19 pandemic. RESEARCH DESIGN: We used a repeated cross-sectional design to assess aggregated and standard...OBJECTIVE: To examine telehealth care utilization during pregnancy and in the 6 months postpartum during the COVID-19 pandemic. RESEARCH DESIGN: We used a repeated cross-sectional design to assess aggregated and standardized electronic health records (EHR) from 28 participating US health systems in the PCORnet®, National Patient-Centered Clinical Research Network. SUBJECTS: We studied women aged 18-55 years with delivery records from 2018 to 2019 (prepandemic), 2020-2021 (early pandemic), and 2022-2023 (late/postpandemic). Women with hypertension in pregnancy (HTN-PREG) were identified as those with documented hypertension 1 year prepregnancy or during pregnancy (40 wk predelivery). MEASURES: We used the International Classification of Disease Clinical Modification/Procedure Classification codes, a normalized naming system for drug names (RXnorm), and the Current Procedural Terminology/Healthcare Common Procedure Coding System to identify deliveries, hypertension, and telehealth visits. RESULTS: We examined 1,028,426 deliveries, of which 108,606 had HTN-PREG. The proportion of women with 1+ pregnancy telehealth use was higher in the early pandemic (15.8%) and late/postpandemic (16.4%) periods compared with prepandemic (0.2%). Telehealth use among HTN-PREG women was higher than among all women (0.24% prepandemic, 24.9% early pandemic, 26.8% late/postpandemic).. Among HTN-PREG women, telehealth use was lower among Hispanic women (19.2% and 23.2%) compared with NH Black (26.5% and 29.3%) or NH White (24.5% and 26.1%) women during the early and late/postpandemic periods, respectively. We observed similar patterns postpartum. All P values for comparisons were <0.001. CONCLUSIONS: These findings underscore the value of aggregate PCORnet® data infrastructure and other standardized electronic health records in analyzing health care utilization trends and racial and ethnic differences among pregnant women.
The maternal mortality rate in the United States is higher than peer countries throughout the world. There is a critical need to implement and evaluate the effectiveness of interventions to address factors that contribut...The maternal mortality rate in the United States is higher than peer countries throughout the world. There is a critical need to implement and evaluate the effectiveness of interventions to address factors that contribute to maternal mortality and morbidity (MMM). Legislation passed by the US Congress in 2019 reauthorized funding for the Patient-Centered Outcomes Research Institute (PCORI) and identified maternal morbidity and mortality as a research priority. PCORnet® is a large, distributed "network of networks" funded by PCORI to improve the nation's capacity to efficiently conduct definitive health research. PCORnet® Network Partners convened a workgroup of experts in topics related to MMM-including patient stakeholders-and developed an exploratory query to identify and characterize the cohort of patients with pregnancy-related health events served by health systems participating in PCORnet. This article presents query results for 1.1 million pregnancies resulting in delivery or interruption that occurred between July 28, 2021, and July 28, 2023 among patients receiving care at 72 sites participating in PCORnet. Three percent of patients experienced severe maternal morbidity, and 357 cases of mortality were recorded. The results also include occurrence of mental and physical comorbidities in the prenatal, peripartum, and postpartum periods. These data are intended to support use of the PCORnet research infrastructure to produce evidence that matters to patients, caregivers, and the broader public health and health care communities. We also discuss ways to enhance the PCORnet infrastructure to accelerate maternal health research, including work that is currently underway to augment data pertinent to studying MMM.
BACKGROUND: PRECIDENTD (PRevention of CardIovascular and DiabEtic KidNey Disease in Type 2 Diabetes) is a PCORnet® Study evaluating 2 classes of medications, SGLT2 inhibitors and GLP-1 receptor agonists, among people wit...BACKGROUND: PRECIDENTD (PRevention of CardIovascular and DiabEtic KidNey Disease in Type 2 Diabetes) is a PCORnet® Study evaluating 2 classes of medications, SGLT2 inhibitors and GLP-1 receptor agonists, among people with type 2 diabetes. Participants obtain their assigned medication through their health insurance and complete semi-annual study assessments. OBJECTIVE: We engaged multiple partners to develop a centralized text message-based program to facilitate adherence and retention in PRECIDENTD and evaluated its performance from April 2024 to April 2025. METHODS: The PRECIDENTD study team applied best practices in digital health tool design and built the program with technology company MEMOTEXT. Patient partners identified program goals, co-wrote message content, and completed internal testing. We then deployed the program to PRECIDENTD participants and analyzed responses. MEASURES: We assessed response rate to interactive text messages, proportion of messages flagging participants needing additional support, and the adherence problems identified. RESULTS: The text messaging program includes interactive messages querying if participants are taking the study medication, as well as one-way study timeline messages. During the first year, 450 PRECIDENTD participants across 20 sites received texts. Interactive message response rate was 80%, and 25% of responses identified problems (ie, trouble getting fills/refills and experiencing a health concern or side effect), prompting an outreach call. CONCLUSIONS: We co-designed a digital tool that engaged participants and helped identify study participants needing assistance obtaining and adhering to study medications. Collaborative development of similar centralized tools may augment the capacity of national studies to answer important comparative effectiveness research questions.
BACKGROUND: Institutions that participate in PCORnet® transform their local electronic health record (EHR) data into the PCORnet® Common Data Model (CDM), which is then used to generate data extracts for PCORnet® Studies...BACKGROUND: Institutions that participate in PCORnet® transform their local electronic health record (EHR) data into the PCORnet® Common Data Model (CDM), which is then used to generate data extracts for PCORnet® Studies. PCORnet® Studies can also include institutions that do not participate in PCORnet, and for these organizations, the cost of instantiating a PCORnet® CDM can be prohibitive. Fast Health care Interoperability Resources (FHIR) provides an alternative method of obtaining EHR data. OBJECTIVE: To determine whether data obtained through FHIR might be a viable study solution for those sites that do not participate in PCORnet.® This mixed-methods project had 2 objectives: (1) survey sites participating in PCORnet on the availability of FHIR (FHIR survey); (2) compare the coverage of a FHIR-based data extract using REDCap with one from the PCORnet® CDM across 3 sites (FHIR extract). METHODS: (1) FHIR survey: A series of questions were asked about the use of FHIR in a production capacity. (2) FHIR extract: REDCap FHIR and PCORnet® CDM extracts were created based on study variables from 2 prior PCORnet® Studies. Data were extracted for 40 patients and concordance measures were computed between the 2 sources. RESULTS: (1) FHIR survey: Of responding organizations, 73% (n=49) reported that FHIR was deployed in a production capacity. (2) FHIR extract: Results were highly variable. Cohen kappa ranged from 0.01 to 0.76 for certain diagnoses, 0.24 to 0.84 for laboratory results, and 0.1 to 0.87 for medications. CONCLUSIONS: Despite differences in data, certain studies may be well-suited for FHIR-based extracts.
BACKGROUND: A national clinical research network such as PCORnet® must, by design, accommodate myriad approaches to support effective and efficient multisite and multinetwork research activities. Therefore, visualizing t...BACKGROUND: A national clinical research network such as PCORnet® must, by design, accommodate myriad approaches to support effective and efficient multisite and multinetwork research activities. Therefore, visualizing the architecture of clinical research networks is imperative to improve their utility for national scale research. OBJECTIVES: (1) To present a methodological approach to apply system mapping methods to characterize the key actors, relationships, and exchanges within the PCORnet infrastructure for data activities. (2) To describe the findings of the PCORnet infrastructure mapping project and characterize the commonalities and heterogeneity between CRN infrastructures based on their data management and sharing activities. METHODS AND DESIGN: System mapping methods were applied in this paper to provide a more accurate and nuanced methodology to visualize the complex infrastructure provided by health research networks in order to support national-scale health research, specifically patient-centered comparative clinical effectiveness research (CER) using PCORnet. RESULTS: To make PCORnet more accessible to investigators, patient partners, research funders, and other collaborators, the mapping methods and maps presented in this paper offer a new tool to visualize the design and architecture of the PCORnet infrastructure to fulfill distributed queries. CONCLUSIONS: Critically, the methodology and approach to system mapping offer a new path forward to support Network collaboration as a learning health system (LHS) by improving transparency and dialogue with patient partners regarding the strengths and potential limitations of infrastructure for evidence generation and informing health care decisions.
PCORnet® is a large, complex network that may appear intimidating for new investigators and funders, posing a perceived barrier to expanding the use of this powerful resource for research. In this commentary, I highlight...PCORnet® is a large, complex network that may appear intimidating for new investigators and funders, posing a perceived barrier to expanding the use of this powerful resource for research. In this commentary, I highlight the importance of mentorship, immersion, and didactic training to build the future cadre of investigators leveraging the PCORnet infrastructure and expand the impact of PCORnet® Studies, while sharing personal experience navigating the opportunities and challenges offered by this network.
Health plans and public payers (ie, Medicare and Medicaid) maintain records of millions of transactions between patients and health care providers from claims submitted by hospitals, clinics, pharmacies, and other care s...Health plans and public payers (ie, Medicare and Medicaid) maintain records of millions of transactions between patients and health care providers from claims submitted by hospitals, clinics, pharmacies, and other care settings. A major use of claims data in research is to supplement the information contained in patients' medical records. PCORnet is a large, distributed "network of networks" funded by the Patient-Centered Outcomes Research Institute (PCORI) to improve the nation's capacity to efficiently conduct definitive health research. Seventy-eight partner health systems nationwide map clinical data from their electronic health records to the PCORnet® Common Data Model (CDM) so that the data may be efficiently used for research purposes. The ability to link data from electronic health records in the PCORnet infrastructure with complementary data from other sources, such as health insurance claims, further enhances the capacity for comparative clinical effectiveness research (CER). This commentary showcases the health plan partnerships of 3 PCORnet® Clinical Research Networks (CRNs)-REACHnet, PaTH, and OneFlorida+-that enhance the capacity for CER involving linked clinical and claims data. We describe the transferable regulatory and technical infrastructures in place to efficiently link data for research purposes. To demonstrate these partnerships and data linkage in action, we also discuss research use cases pertaining to weight-related outcomes and diabetes that align with payers' interests in chronic disease management.
BACKGROUND: The Accelerating Data Value Across a National Community Health Center Network (ADVANCE) collaborative is 1 of 8 clinical research networks participating in PCORnet®, the National Patient-Centered Clinical Res...BACKGROUND: The Accelerating Data Value Across a National Community Health Center Network (ADVANCE) collaborative is 1 of 8 clinical research networks participating in PCORnet®, the National Patient-Centered Clinical Research Network. Providing data, engagement, and regulatory infrastructure, ADVANCE facilitates the inclusion of people who receive primary care in community-based health centers (CHC) across over 90 patient-centered research studies. Centrally coordinated by OCHIN, in partnership with Fenway Health, Health Choice Network, Oregon Health & Science University, and the University of Washington, ADVANCE comprises the nation's most comprehensive network for health care and outcomes research in community-based primary care and hospital-based settings. OBJECTIVE: This manuscript discusses ADVANCE's unique past, present, and future approaches to strengthen infrastructure and capacity to enhance research in community-based primary care settings. MAIN ARGUMENTS: As community-based primary care organizations, CHCs have relationships, trust, and expertise with the communities they serve. ADVANCE provides critical data and engagement resources for including CHCs and their patients in research to improve patient-centered care and outcomes. Despite past investment, there is a recognized need for additional engagement, investment, capacity building, and research infrastructure to realize the full potential of CHC partnerships in clinical research and PCORnet® studies. By partnering with CHCs and tertiary hospitals, ADVANCE and the PCORnet infrastructure can provide enhanced access to clinical research opportunities that further support patient-centered, high-quality care delivery, and positive health outcomes while meeting CHCs' priorities and goals, progressing their own research capacity and infrastructure, and contributing to scalable research readiness models.
John AS, Leezer S, Rudov L
… +25 more, Jackson JL, Messmer M, Saraf S, Mehta R, Papneja S, Saidi AS, Marlin A, Hile D, Agarwal A, Lewis MJ, Kanter RJ, Sandhu S, Young T, Jacobsen R, Ruckdeschel ES, Lubert AM, Singh HS, Zaidi AN, Halpern DG, Krasuski RA, Asfaw K, Marsolo K, Phillippi R, Owolabi A, Carton T
BACKGROUND: The Congenital Heart Initiative-Redefining Outcomes and Navigation to Adult-Centered Care (CHI-RON) study is a unique collaboration between the PCORnet and Congenital Heart Initiative (CHI), the first patient...BACKGROUND: The Congenital Heart Initiative-Redefining Outcomes and Navigation to Adult-Centered Care (CHI-RON) study is a unique collaboration between the PCORnet and Congenital Heart Initiative (CHI), the first patient powered registry for adult congenital heart disease (ACHD) patients. The CHI-RON study examines the effects of gaps in recommended care in ACHD. OBJECTIVE: Recruitment of racially diverse, younger, out-of-care, and male participants has been challenging in ACHD studies. Our goal was to design patient engagement and recruitment strategies to improve representation. RESEARCH DESIGN: Launched in December 2020, patients from any location can self-enroll in the CHI registry, while the CHI-RON study (5/2022 - 10/2023) recruited ACHD patients at 12 sites participating in PCORnet. CHI-RON Recruitment methodology included a patient partner engagement toolkit and a recruitment algorithm using the PCORnet® Common Data Model designed specifically to improve diversity and reduce self-enrollment biases in comparison to the CHI registry. SUBJECTS: ACHD patients, age 18 years or older, with the ability to complete PROs independently. MEASURES: Demographic/Recruitment Statistics for study participants and Patient Engagement in Research Scale (PEIRS-22) for the study team partners. RESULTS: As of October 2023, a total of 2652 participants were recruited through CHI-RON recruitment methodology while 1326 were self-enrolled in the CHI. CHI-RON recruitment methodologies have increased representation when compared with self-enrolled CHI participants in terms of ethnicity (10.9% vs. 7.4% Hispanic, P<0.001), race (5.4% vs. 2.6%, Black/African American, P<0.001), sex (41% vs. 28% male, P<0.001), younger age (35.5 +/-12.8 y vs. 43.5±14.5 y, P<0.001), and education (33.4% vs. 24% high school equivalent or less, P<0.001).Most study team patient partners (n=12, 86%) reported a very to extremely high degree of engagement (PEIRS-22 average score 101.6), especially in the subdomains of contributions, support, feeling valued, and benefits. CONCLUSIONS: Patient engagement and novel recruitment strategies are critical to improving the inclusion of under-represented populations in clinical research and ensuring alignment with the needs of ACHD patients.
As the 8 patient partners serving on the PCORnet® Steering Committee, we stand at the forefront of a transformative movement in clinical research. PCORnet® Network Partners have been pioneers in integrating patient voice...As the 8 patient partners serving on the PCORnet® Steering Committee, we stand at the forefront of a transformative movement in clinical research. PCORnet® Network Partners have been pioneers in integrating patient voices into every aspect of the research process, and we applaud the progress in operationalizing the Patient-Centered Outcomes Research Institute's (PCORI) Framework for Patient Engagement and for leading the way as funders to change how to effectively involve patients and other interested parties in research. However, we believe that now is the time to amplify our efforts and call for a fundamental shift in how health research is conducted across the board. This commentary serves as both a reflection on our journey and a rallying cry for deeper, more authentic patient engagement and partnership in clinical research. The landscape of clinical research has undergone significant changes over the past decade, with patient engagement emerging as a cornerstone of patient-centered outcomes research. This shift is evidenced by major funding agencies now requiring patient engagement and a growing body of literature demonstrating improved study quality, recruitment, and relevance when patients are engaged as partners. As patient partners participating in PCORnet®, we have been at the forefront of this evolution, witnessing firsthand the progress made and the challenges and learnings that remain. Drawing on our experiences and evidence from the literature, we propose strategies to enhance patient involvement across all stages of research. We introduce and explore the concept that clinical research should be "careful, kind, and connected." Our reflections underscore that meaningful patient involvement is essential for advancing health outcomes and achieving a truly patient-partnered research ecosystem.
Cohen LW, Dolor RJ, Weiner M
… +13 more, Zemon N, Bailey C, Carton T, Cottrell E, Forrest CB, Hernandez AF, Kaushal R, Marsolo K, McTigue K, Rothman RL, Shenkman E, Waitman LR,
on behalf of the PCORnet
Steering Committee
BACKGROUND: The PCORnet® infrastructure was funded by PCORI in 2014 to streamline clinical trials, increase patient-centered research, and generate knowledge that leads to improved health care and outcomes. In this paper...BACKGROUND: The PCORnet® infrastructure was funded by PCORI in 2014 to streamline clinical trials, increase patient-centered research, and generate knowledge that leads to improved health care and outcomes. In this paper, we summarize the significant achievements of the infrastructure over the last decade as well as recent accomplishments. We also provide an update on the expanded patient population who receive care at sites participating in PCORnet® Clinical Research Networks (CRNs) and share priorities for the future. METHODS: The electronic health records of 71 health systems participating in PCORnet® CRNs as of July 2024 were queried, and data were analyzed to describe 10 common health conditions, stratified by demographic characteristics of age, sex, race, ethnicity, and an index of social deprivation. RESULTS: Out of over 100M total patients with activity in the last 10 years, health systems participating in PCORnet® CRNs had over 47 million unique patients with at least one encounter in 2023. The most common chronic conditions among these patients were hypertension (18%), anxiety disorders (10%), type 2 diabetes (8%), and asthma (5%). Over 20% of patients receiving care at a site participating in PCORnet were in the top 50% of metrics for area deprivation. The PCORnet infrastructure supported 51 PCORnet® studies, all of which met established guidelines for use of the PCORnet® Common Data Model (CDM), patient-engagement, and commitment to return of results. DISCUSSION: PCORnet® CRNs represent a diverse and expanding patient population and often include data on the socioeconomic status of the communities. Through continued efforts to engage communities and patients and national-scale research, the PCORnet® infrastructure can help improve care and outcomes for patients affected by common and rare conditions.
PCORnet®, a national resource funded by the Patient-Centered Outcomes Research Institute, is designed to enhance the nation's capacity to conduct efficient, patient-centered health research. The robust and adaptable PCOR...PCORnet®, a national resource funded by the Patient-Centered Outcomes Research Institute, is designed to enhance the nation's capacity to conduct efficient, patient-centered health research. The robust and adaptable PCORnet infrastructure can be leveraged to support a variety of study designs. Within this framework, PCORnet® Studies, a distinguished subset of research studies that meets specific criteria and approval, serve as exemplary models of patient-centered research, standing out for their rigorous adherence to criteria that elevate the quality and impact of research. Over the past 10 years, over 300 studies have been completed using the PCORnet infrastructure, including 58 studies that have earned the distinction of being a meritorious PCORnet® Study, of which 19 have been completed. We explore several of these efforts, highlighting the study archetypes supported by the PCORnet infrastructure, as well as the clinical therapeutic areas of these studies, funding sources, and breadth of PCORnet institutional users. We also provide lessons learned from our accumulated experience that translates the PCORnet infrastructure into a continuously learning framework and highlight unique capabilities of the PCORnet infrastructure supporting innovation in future trials.
BACKGROUND: PCORnet is a large, federated "network of networks" that facilitates innovative patient-centered comparative clinical effectiveness research (CER) and other health research at a national scale. As a flagship...BACKGROUND: PCORnet is a large, federated "network of networks" that facilitates innovative patient-centered comparative clinical effectiveness research (CER) and other health research at a national scale. As a flagship infrastructure program funded by the Patient-Centered Outcomes Research Institute® (PCORI®), an independent, nonprofit research organization, PCORnet is unique among national clincial research networks given the scale of the network. With linkages to more than 47 million unique patients, strong governance, research expertise, and commitment to keeping the patient at the center of all activities, PCORnet can be used to conduct a range of study types, from pragmatic trials to observational studies. Since 2015, PCORnet has been used to conduct more than 250 studies, ranging from observational research to pragmatic trials. OBJECTIVE: The main objective of this commentary is to provide PCORI's perspective on the importance of clinical research infrastructure, the unique contributions of the PCORnet infrastructure to patient-centered research, and PCORI's approach to continuous evaluation and evolution of PCORnet. RELEVANCE TO THE SPECIAL ISSUE: This commentary aims to be useful to readers in understanding PCORI's vision for PCORnet and approach to monitoring progress and measuring success.