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Abstract Background Pragmatic primary care trials aim to test interventions in “real world” health care settings, but clinics willing and able to participate in trials may not be representative of typical clinics. This analysis compared patients in participating and non-participating clinics from the same health systems at baseline in the PRimary care Opioid Use Disorders treatment (PROUD) trial. Methods This observational analysis relied on secondary electronic health record and administrative claims data in 5 of 6 health systems in the PROUD trial. The sample included patients 16–90 years at an eligible primary care visit in the 3 years before randomization. Each system contributed 2 randomized PROUD trial clinics and 4 similarly sized non-trial clinics. We summarized patient characteristics in trial and non-trial clinics in the 2 years before randomization (“baseline”). Using mixed-effect regression models, we compared trial and non-trial clinics on a baseline measure of the primary trial outcome (clinic-level patient-years of opioid use disorder (OUD) treatment, scaled per 10,000 primary care patients seen) and a baseline measure of the secondary trial outcome (patient-level days of acute care utilization among patients with OUD). Results Patients were generally similar between the 10 trial clinics (n = 248,436) and 20 non-trial clinics (n = 341,130), although trial clinics’ patients were slightly younger, more likely to be Hispanic/Latinx, less likely to be white, more likely to have Medicaid/subsidized insurance, and lived in less wealthy neighborhoods. Baseline outcomes did not differ between trial and non-trial clinics: trial clinics had 1.0 more patient-year of OUD treatment per 10,000 patients (95% CI: − 2.9, 5.0) and a 4% higher rate of days of acute care utilization than non-trial clinics (rate ratio: 1.04; 95% CI: 0.76, 1.42). Conclusions trial clinics and non-trial clinics were similar regarding most measured patient characteristics, and no differences were observed in baseline measures of trial primary and secondary outcomes. These findings suggest trial clinics were representative of comparably sized clinics within the same health systems. Although results do not reflect generalizability more broadly, this study illustrates an approach to assess representativeness of clinics in future pragmatic primary care trials.

Abstract Background Pragmatic trials provide the opportunity to study the effectiveness of health interventions to improve care in real-world settings. However, use of open-cohort designs with patients becoming eligible after randomization and reliance on electronic health records (EHRs) to identify participants may lead to a form of selection bias referred to as identification bias. This bias can occur when individuals identified as a result of the treatment group assignment are included in analyses. Methods To demonstrate the importance of identification bias and how it can be addressed, we consider a motivating case study, the PRimary care Opioid Use Disorders treatment (PROUD) Trial. PROUD is an ongoing pragmatic, cluster-randomized implementation trial in six health systems to evaluate a program for increasing medication treatment of opioid use disorders (OUDs). A main study objective is to evaluate whether the PROUD intervention decreases acute care utilization among patients with OUD (effectiveness aim). Identification bias is a particular concern, because OUD is underdiagnosed in the EHR at baseline, and because the intervention is expected to increase OUD diagnosis among current patients and attract new patients with OUD to the intervention site. We propose a framework for addressing this source of bias in the statistical design and analysis. Results The statistical design sought to balance the competing goals of fully capturing intervention effects and mitigating identification bias, while maximizing power. For the primary analysis of the effectiveness aim, identification bias was avoided by defining the study sample using pre-randomization data (pre-trial modeling demonstrated that the optimal approach was to use individuals with a prior OUD diagnosis). To expand generalizability of study findings, secondary analyses were planned that also included patients newly diagnosed post-randomization, with analytic methods to account for identification bias. Conclusion As more studies seek to leverage existing data sources, such as EHRs, to make clinical trials more affordable and generalizable and to apply novel open-cohort study designs, the potential for identification bias is likely to become increasingly common. This case study highlights how this bias can be addressed in the statistical study design and analysis. Trial registration ClinicalTrials.gov , NCT03407638 . Registered on 23 January 2018.

In low-income countries (LICs), there are multiple barriers for children with epilepsy (CWE) to attend school. We examined potentially modifiable associations with poor school performance in CWE in the West African Republic of Guinea. Children with epilepsy of school age were recruited using public announcements and a clinical register of people with epilepsy at the Ignace Deen Hospital in Conakry in 2018. A team of Guinean and U.S. neurologists and neurologists-in-training interviewed each CWE and parent for his/her epilepsy history, household finances, educational attainment level, and perceived stigma using the Stigma Scale of Epilepsy (SSE). Each child was also tested using the Wechsler Nonverbal Scale of Ability (WNV). Low school performance was defined as either not attending school or being held back a grade level at least once. Potential predictors of low school performance were analyzed. Of 128 CWE (mean age: 11.6 years, 48.4% female), 11.7% (n = 15) never attended school, 23.3% (n = 30) dropped out, and 64.8% (n = 83) were currently enrolled. Of CWE attending school, 46.9% (n = 39) were held back a grade level. Overall, 54 children were defined as low performers (LPs) (42%). ;Greater than 100 lifetime seizures (odds ratio (OR) = 8.81; 95% confidence interval (CI) = 2.51, 37.4; p = 0.001) and lower total WNV score (OR = 0.954; 95% CI = 0.926, 0.977; p < 0.001) were significantly associated with poor school performance in separate models, when controlling for potential confounders. Given the strong relationship between seizure freedom and school performance, we estimated that 38 additional CWE (33.6%) could become high performers (HPs) if all CWE were adequately treated to achieve the lifetime seizure category of < 10 seizures and could be cognitively intact again. Models examining SSE and household wealth quintile were not significantly associated with school performance. Higher lifetime seizures and lower WNV score were significantly associated with low school performance in CWE in Guinea. In spite of our conservative definition of high school performance (attending without failing) and risk of referral bias at an academic center where patients were allowed to self-refer, we demonstrate that seizure control in this setting could increase the number of CWE who could attend and stay in school. • Educational outcomes are poor for children with epilepsy in Guinea. • > 30% of children were not attending school. • > 40% of those in school had been held back at least once. • More lifetime seizures and worse cognition were associated with poor educational status. [ABSTRACT FROM AUTHOR]