Medical Care最新文献

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.

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.

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.

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.

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.

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.

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.

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.