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Objective We identified challenges and solutions to using electronic health record (EHR) systems for the design and conduct of pragmatic research. Materials and Methods Since 2012, the Health Care Systems Research Collaboratory has served as the resource coordinating center for 21 pragmatic clinical trial demonstration projects. The EHR Core working group invited these demonstration projects to complete a written semistructured survey and used an inductive approach to review responses and identify EHR-related challenges and suggested EHR enhancements. Results We received survey responses from 20 projects and identified 21 challenges that fell into 6 broad themes: (1) inadequate collection of patient-reported outcome data, (2) lack of structured data collection, (3) data standardization, (4) resources to support customization of EHRs, (5) difficulties aggregating data across sites, and (6) accessing EHR data. Discussion Based on these findings, we formulated 6 prerequisites for PCTs that would enable the conduct of pragmatic research: (1) integrate the collection of patient-centered data into EHR systems, (2) facilitate structured research data collection by leveraging standard EHR functions, usable interfaces, and standard workflows, (3) support the creation of high-quality research data by using standards, (4) ensure adequate IT staff to support embedded research, (5) create aggregate, multidata type resources for multisite trials, and (6) create re-usable and automated queries. Conclusion We are hopeful our collection of specific EHR challenges and research needs will drive health system leaders, policymakers, and EHR designers to support these suggestions to improve our national capacity for generating real-world evidence.

Background The heterogeneity of migraine has been reported extensively, with identified subgroups usually based on symptoms. Grouping individuals with migraine and similar comorbidity profiles has been suggested, however such segmentation methods have not been tested using real-world clinical data. Objective To gain insights into natural groupings of patients with migraine using latent class analysis based on electronic health record-determined comorbidities. Methods Retrospective electronic health record data analysis of primary-care patients at Sutter Health, a large open healthcare system in Northern California, USA. We identified migraine patients over a five-year time period (2015–2019) and extracted 29 comorbidities. We then applied latent class analysis to identify comorbidity-based natural subgroups. Results We identified 95,563 patients with migraine and found seven latent classes, summarized by their predominant comorbidities and population share: fewest comorbidities (61.8%), psychiatric (18.3%), some comorbidities (10.0%), most comorbidities – no cardiovascular (3.6%), vascular (3.1%), autoimmune/joint/pain (2.2%), and most comorbidities (1.0%). We found minimal demographic differences across classes. Conclusion Our study found groupings of migraine patients based on comorbidity that have the potential to be used to guide targeted treatment strategies and the development of new therapies.

Arterial blood oxygen saturation as measured by pulse oximetry (peripheral oxygen saturation (SpO2)) may be differentially less accurate for people with darker skin pigmentation, which could potentially affect the course of coronavirus disease 2019 (COVID-19) treatment. We analyzed pulse oximeter accuracy and its association with COVID-19 treatment outcomes using electronic health record data from Sutter Health, a large, mixed-payer, integrated health-care delivery system in Northern California. We analyzed 2 cohorts: 1) 43,753 non-Hispanic White (NHW) or non-Hispanic Black/African-American (NHB) adults with concurrent arterial blood gas oxygen saturation/SpO2 measurements taken between January 2020 and February 2021; and 2) 8,735 adults who went to a hospital emergency department with COVID-19 between July 2020 and February 2021. Pulse oximetry systematically overestimated blood oxygenation by 1% more in NHB individuals than in NHW individuals. For people with COVID-19, this was associated with lower admission probability (−3.1 percentage points), dexamethasone treatment (−3.1 percentage points), and supplemental oxygen treatment (−4.5 percentage points), as well as increased time to treatment: 37.2 minutes before dexamethasone initiation and 278.5 minutes before initiation of supplemental oxygen. These results call for additional investigation of pulse oximeters and suggest that current guidelines for development, testing, and calibration of these devices should be revisited, investigated, and revised.

6530 Background: Only a small fraction of patients with cancer participate in treatment trials. Patients identifying as members of racial and ethnic minority groups are consistently underrepresented in these trials. A recent systematic review reported that patients, regardless of race and ethnicity, are willing to enroll in trials if asked to participate by their treating clinician. Prospective and longitudinal data and metrics at the site- and clinician-level are necessary to understand whether patients are equitably considered for clinical trials. Methods: ASCO and Association of Community Cancer Centers (ACCC) developed a self-assessment for trial sites to record and gauge the number of patients across races and ethnicities screened, offered, and enrolled into clinical trials. Research sites, from across the US, were recruited through an open call to apply to participate in the ASCO-ACCC Pilot Project. There were 65 sites assigned to this pilot study, which tested the feasibility and utility of the site assessment. Sites were asked to enter 2019 and 2020 aggregate data for each step along the clinical trial enrollment continuum by select races and ethnicities (Black, Hispanic/Latinx, White) and overall. Results: 62 of 65 sites completed the study and represented a range of settings and practice types (61% academic, 26% hospital/health system, 13% independent). Only 2 sites (3%) were able to provide the data requested at each enrollment step in the assessment (table). Sites that collected the data did not do so routinely (table) and most had to compile data through multiple sources and/or manual extraction (40-100% across enrollment steps). Sites with missing data reported they did not collect data at all (36-64% across enrollment steps), did not collect data in a systematic way (0-29% across enrollment steps), or stated it would be too burdensome to manually review charts to extract data (12-29% across enrollment steps). Conclusions: Data collection and routine evaluation of participation metrics, by race and ethnicity, are necessary to assess and monitor equity and diversity in clinical trials. Most sites in this study did not collect, or routinely collect, data for screening, offering, and consenting patients to clinical trials. Without these data, sites are unable to evaluate and monitor whether their patients have equitable access to clinical trials or establish strategies to address any inequities. ASCO and ACCC will continue to partner with sites to better understand their processes and the feasibility of collecting such data in a systematic and automated way, such as through electronic health record systems. [Table: see text]