Cora Sears Roggeveen Papers

Scrapbook of Cora Sears Roggeveen who homesteaded two miles west of Abercrombie, North Dakota

Stakeholder outcome prioritization in the Biologic Abatement and Capturing Kids' Outcomes and Flare Frequency in Juvenile Spondyloarthritis (BACK‐OFF JSpA) trial

Abstract Background The Biologic Abatement and Capturing Kids’ Outcomes and Flare Frequency in Juvenile Spondyloarthritis (BACK‐OFF JSpA) study is a randomized, pragmatic trial investigating different tumour necrosis factor inhibitor de‐escalation strategies for children with sustained inactive disease. In this project, we elicited concept rankings that aided in the selection of the patient‐reported outcome (PRO) measures that should be examined as part of the BACK‐OFF JSpA trial. Methods We conducted a discrete choice experiment to evaluate individuals' preferences regarding PROs. Stakeholders assessed a discrete list of 21 outcome concepts, each of which had a Patient‐Reported Outcome Measurement Information System (PROMIS) measure associated with it. PROMIS measures are self‐ or proxy‐reported instruments that are universally applicable to the general population and all chronic conditions. Stakeholders were required to make choices instead of expressing the strength of a preference. Results Fourteen caregivers, 12 patients (9–22 years old), 16 rheumatologists and three executives from health insurance companies completed the exercise, which took approximately 10 min. The discrete choice experiment resulted in an estimate of the relative importance of each outcome and rank. All stakeholder groups agreed that the primary PRO should be ‘Pain Interference’, a measure that evaluates the effect of pain on a child's everyday activities, including its impact on social, emotional, mental and physical functioning. Patients and caregivers were mostly aligned in their top priorities, with patients valuing physical health (50% of the top 10) whereas caregivers were more interested in mental health (60% of the top 10). Rheumatologists and health insurance executives were most interested in physical health outcomes, which were ranked 80% and 60% of their top 10 PROs, respectively. Overall, the patients had the most diverse set of prioritized outcomes, including at least one of each category in their top 10 rank order of importance. Patients were also the only stakeholders to prioritize ‘social’ health. Conclusions Patients and caregivers were mostly aligned in their outcome priority rankings. The rank‐order list directly informed the creation of a profile of PRO measures for our upcoming trial. Patient or Public Contribution Stakeholder partners helped with acquisition of data and lead parent partners helped interpret data

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes

BACKGROUND AND OBJECTIVES: Performing adequately powered clinical trials in pediatric diseases, such as SLE, is challenging. Improved recruitment strategies are needed for identifying patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Electronic health record algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single-center electronic health record data to develop computable phenotypes composed of diagnosis, medication, procedure, and utilization codes. These were evaluated iteratively against a manually assembled database of patients with SLE. The highest-performing phenotypes were then evaluated across institutions in PEDSnet, a national health care systems network of \u3e6.7 million children. Reviewers blinded to case status used standardized forms to review random samples of cases (=350) and noncases (=350). RESULTS: Final algorithms consisted of both utilization and diagnostic criteria. For both, utilization criteria included two or more in-person visits with nephrology or rheumatology and ≥60 days follow-up. SLE diagnostic criteria included absence of neonatal lupus, one or more hydroxychloroquine exposures, and either three or more qualifying diagnosis codes separated by ≥30 days or one or more diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 100% (95% confidence interval [95% CI], 99 to 100), specificity was 92% (95% CI, 88 to 94), positive predictive value was 91% (95% CI, 87 to 94), and negative predictive value was 100% (95% CI, 99 to 100). Lupus nephritis diagnostic criteria included either three or more qualifying lupus nephritis diagnosis codes (or SLE codes on the same day as glomerular/kidney codes) separated by ≥30 days or one or more SLE diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 90% (95% CI, 85 to 94), specificity was 93% (95% CI, 89 to 97), positive predictive value was 94% (95% CI, 89 to 97), and negative predictive value was 90% (95% CI, 84 to 94). Algorithms identified 1508 children with SLE at PEDSnet institutions (537 with lupus nephritis), 809 of whom were seen in the past 12 months. CONCLUSIONS: Electronic health record-based algorithms for SLE and lupus nephritis demonstrated excellent classification accuracy across PEDSnet institutions