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BackgroundObesity affects nearly half of adults in the United States and is contributing substantially to a pandemic of obesity-associated chronic conditions such as type 2 diabetes, hypertension, and arthritis. The obesity-associated chronic condition pandemic is particularly severe in low-income, medically underserved, predominantly African-American areas in the southern United States. Little is known regarding the impact of geographic, income, and racial disparities in continuity of care on major health outcomes for patients with obesity-associated chronic conditions. ObjectiveThe aim of this study is to assess, among patients with obesity-associated chronic conditions, and within this group, patients with type 2 diabetes, (1) whether continuity of care is associated with lower overall and potentially preventable emergency department and hospital utilization, (2) the effect of geographic, income, and racial disparities on continuity of care and on health care utilization, (3) whether continuity of care particularly protects individuals at risk for disparities from adverse health outcomes, and (4) whether characteristics of health systems are associated with higher continuity of care and better outcomes. MethodsUsing 2015-2018 data from 4 practice-based research networks participating in the Southern Obesity and Diabetes Coalition, we will conduct a retrospective cohort analysis and distributed meta-analysis. Patients with obesity-associated chronic conditions and with type 2 diabetes will be assessed within each health system, following a standardized study protocol. The primary study outcomes are overall and preventable emergency department visits and hospitalizations. Continuity of care will be calculated at the facility level using a modified version of the Bice-Boxerman continuity of care index. Race will be assessed using electronic medical record data. Residence in a low-income area or a health professional shortage area respectively will be assessed by linking patient residence ZIP codes to the Centers for Medicare & Medicaid Services database. ResultsIn 4 regional health systems across Tennessee, Mississippi, Louisiana, and Arkansas, a total of 53 adult hospitals were included in the study. A total of 147,889 patients with obesity-associated chronic conditions who met study criteria were identified in these health systems, of which 45,453 patients met the type 2 diabetes criteria for inclusion. Results are expected by the end of 2020. ConclusionsThis study should reveal whether health system efforts to increase continuity of care for patients with obesity and diabetes have potential to improve outcomes and reduce costs. Analyzing disparities in continuity of care and their effect on major health outcomes can help demonstrate how to improve care and use of health care resources for vulnerable patients with obesity-associated chronic conditions, and within this group, patients with type 2 diabetes. Better understanding of the association between continuity and health care utilization for these vulnerable populations will contribute to the development of higher-value health systems in the southern United States. International Registered Report Identifier (IRRID)DERR1-10.2196/20788

OBJECTIVE: Clinical decision support (CDS) can contribute to quality and safety. Prior work has shown that errors in CDS systems are common and can lead to unintended consequences. Many CDS systems use Boolean logic, which can be difficult for CDS analysts to specify accurately. We set out to determine the prevalence of certain types of Boolean logic errors in CDS statements. METHODS: Nine health care organizations extracted Boolean logic statements from their Epic electronic health record (EHR). We developed an open-source software tool, which implemented the Espresso logic minimization algorithm, to identify three classes of logic errors. RESULTS: Participating organizations submitted 260,698 logic statements, of which 44,890 were minimized by Espresso. We found errors in 209 of them. Every participating organization had at least two errors, and all organizations reported that they would act on the feedback. DISCUSSION: An automated algorithm can readily detect specific categories of Boolean CDS logic errors. These errors represent a minority of CDS errors, but very likely require correction to avoid patient safety issues. This process found only a few errors at each site, but the problem appears to be widespread, affecting all participating organizations. CONCLUSION: Both CDS implementers and EHR vendors should consider implementing similar algorithms as part of the CDS authoring process to reduce the number of errors in their CDS interventions.

We previously reported results from a seroprevalence study conducted in New Orleans, Louisiana, USA, which was hit hard early in the coronavirus disease (COVID-19) pandemic (1). Baton Rouge is a [...]

Seroprevalence studies around the world have estimated the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to range from 1.79% (1) in Boise, Idaho, USA, to 25% in Breves, [...]

Objective: This article describes the implementation of a privacy-preserving record linkage (PPRL) solution across PCORnet®, the National Patient-Centered Clinical Research Network.Material and Methods: Using a PPRL solution from Datavant, we quantified the degree of patient overlap across the network and report a de-duplicated analysis of the demographic and clinical characteristics of the PCORnet population.Results: There were ∼170M patient records across the responding Network Partners, with ∼138M (81%) of those corresponding to a unique patient. 82.1% of patients were found in a single partner and 14.7% were in 2. The percentage overlap between Partners ranged between 0% and 80% with a median of 0%. Linking patients' electronic health records with claims increased disease prevalence in every clinical characteristic, ranging between 63% and 173%.Discussion: The overlap between Partners was variable and depended on timeframe. However, patient data linkage changed the prevalence profile of the PCORnet patient population.Conclusions: This project was one of the largest linkage efforts of its kind and demonstrates the potential value of record linkage. Linkage between Partners may be most useful in cases where there is geographic proximity between Partners, an expectation that potential linkage Partners will be able to fill gaps in data, or a longer study timeframe. [ABSTRACT FROM AUTHOR]

Objectives: "Clopidogrel resistance," also defined as heightened platelet reactivity (HPR) while on clopidogrel therapy, may lead to a sub-optimal antiplatelet effect and a potential thrombotic event. There is limited literature addressing the prevalence of HPR in a large cohort of patients receiving either coronary or endovascular interventions. Methods: In a large integrated healthcare system, patients with a P2Y12 reaction units (PRU) test were identified. HPR was defined as a PRU ≥ 200 during clopidogrel therapy. Vascular and coronary interventions were identified utilizing CPT codes, HPR prevalence was calculated, and Fischer's exact test was used to determine significance. Results: From an initial cohort of 2,405,957 patients (October 2014 to January 2020), we identified 3301 patients with PRU tests administered. Of these, 1789 tests had a PRU ≥ 200 (HPR overall prevalence, 54%). We then identified 1195 patients who underwent either an endovascular or coronary procedure and had a PRU measurement. This corresponded to 935 coronary and 260 endovascular interventions. In the coronary cohort, the HPR prevalence was 54% (503/935). In the vascular cohort, the HPR prevalence was 53% (137/260); there was no difference between cohorts in HPR prevalence (p = 0.78). Conclusion: "Clopidogrel resistance" or HPR was found to be present in nearly half of patients with cardiovascular disease undergoing intervention. Our data suggest HPR is more common in the cardiovascular patient population than previously appreciated. Evaluating patients for HPR is both inexpensive ($25) and rapid (< 10 min). Future randomized studies are warranted to determine whether HPR has a clinically detectable effect on revascularization outcomes. [ABSTRACT FROM AUTHOR]

Objective Centralized remote fetal monitoring (CRFM) has been proposed as a method to improve the performance of intrapartum fetal heart rate (FHR) monitoring and perinatal outcomes. The purpose of this study is to determine whether CRFM was associated with a reduction in unexpected term neonatal intensive care unit (NICU) admissions. Study Design A pre–post design was used to examine the effectiveness of CRFM which was implemented in stages across five hospitals. The exposure group was all women who underwent intrapartum monitoring via CRFM. The unexposed group was of women who delivered at the same hospitals prior to implementation of CRFM. Pregnancies with expected NICU admissions, gestational age <37 weeks, birth weight <2,500 g, or major fetal anomalies detected prenatally were excluded. The primary outcome was unexpected term NICU admission; secondary outcomes were cesarean and operative vaginal delivery (OVD), and 5-minute Apgar's score of <7 rates. Maternal and delivery characteristics were examined with Student's t , Wilcoxon's, Chi-square, and Fisher's exact tests. Multivariable logistic regression was performed to control for potential confounders. Results There were 19,392 live births included in this analysis. In the univariable analysis, the odds of unexpected term NICU admission was lower among the CRFM exposed group compared with the unexposed group (odds ratio [OR] = 0.86, 95% confidence interval [CI]: 0.75–0.99; p = 0.038). In multivariable analysis, this did not reach statistical significance (OR = 0.92, 95% CI: 0.79–1.06; p = 0.24). Cesarean and OVD were less likely in the exposed group (OR = 0.91, 95% CI: 0.85–0.97; p = 0.008) and (OR = 0.70, 95% CI: 0.59–0.83, p < 0.001), respectively, in univariable analysis. When adjusted for potential confounders, the effect remained statistically significant for cesarean delivery (OR = 0.92, 95% CI: 0.85–0.98; p = 0.012). When adjusted for hospital, OVD rate was lower at the highest volume and highest acuity site (OR = 0.48, 95% CI: 0.36–0.65, p < 0.001). Conclusion In some practice settings, utilization of a CRFM system may decrease the risk of unexpected term NICU admission, cesarean, and OVD rate. Key Points CRFM may decrease unexpected term NICU admissions in some clinical settings. CRFM may decrease cesarean delivery rates in some clinical settings. CRFM may decrease OVD rates in some clinical settings. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to determine whether a secure, privacy-preserving record linkage (PPRL) methodology can be implemented in a scalable manner for use in a large national clinical research network. Results: We established the governance and technical capacity to support the use of PPRL across the National Patient-Centered Clinical Research Network (PCORnet®). As a pilot, four sites used the Datavant software to transform patient personally identifiable information (PII) into de-identified tokens. We queried the sites for patients with a clinical encounter in 2018 or 2019 and matched their tokens to determine whether overlap existed. We described patient overlap among the sites and generated a "deduplicated" table of patient demographic characteristics. Overlapping patients were found in 3 of the 6 site-pairs. Following deduplication, the total patient count was 3,108,515 (0.11% reduction), with the largest reduction in count for patients with an "Other/Missing" value for Sex; from 198 to 163 (17.6% reduction). The PPRL solution successfully links patients across data sources using distributed queries without directly accessing patient PII. The overlap queries and analysis performed in this pilot is being replicated across the full network to provide additional insight into patient linkages among a distributed research network. [ABSTRACT FROM AUTHOR]