Faculty Bibliography

IMPORTANCE/OBJECTIVE:Patients with poor glycaemic control have a high risk for major cardiovascular events. Improving glycaemic monitoring in patients with diabetes can improve morbidity and mortality. OBJECTIVE:To assess the effectiveness of a patient portal message in prompting patients with poorly controlled diabetes without a recent glycated haemoglobin (HbA1c) result to have their HbA1c repeated. DESIGN/METHODS:A pragmatic, randomised clinical trial. SETTING/METHODS:A large academic health system consisting of over 350 ambulatory practices. PARTICIPANTS/METHODS:Patients who had an HbA1c greater than 10% who had not had a repeat HbA1c in the prior 6 months. EXPOSURES/METHODS:A single electronic health record (EHR)-based patient portal message to prompt patients to have a repeat HbA1c test versus usual care. MAIN OUTCOMES/RESULTS:The primary outcome was a follow-up HbA1c test result within 90 days of randomisation. RESULTS:The study included 2573 patients with a mean (SD) HbA1c of 11.2%. Among 1317 patients in the intervention group, 24.2% had follow-up HbA1c tests completed within 90 days, versus 21.1% of 1256 patients in the control group (p=0.07). Patients in the intervention group were more likely to log into the patient portal within 60 days as compared with the control group (61.2% vs 52.3%, p<0.001). CONCLUSIONS:Among patients with poorly controlled diabetes and no recent HbA1c result, a brief patient portal message did not significantly increase follow-up testing but did increase patient engagement with the patient portal. Automated patient messages could be considered as a part of multipronged efforts to involve patients in their diabetes care.

IMPORTANCE/UNASSIGNED:It remains unclear whether children and adolescents with SARS-CoV-2 infection are at heightened risk for long-term kidney complications. OBJECTIVE/UNASSIGNED:To investigate whether SARS-CoV-2 infection is associated with an increased risk of postacute kidney outcomes among pediatric patients, including those with preexisting kidney disease or acute kidney injury (AKI). DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This retrospective cohort study used data from 19 health institutions in the National Institutes of Health Researching COVID to Enhance Recovery (RECOVER) initiative from March 1, 2020, to May 1, 2023 (follow-up ≤2 years completed December 1, 2024; index date cutoff, December 1, 2022). Participants included children and adolescents (aged <21 years) with at least 1 baseline visit (24 months to 7 days before the index date) and at least 1 follow-up visit (28 to 179 days after the index date). EXPOSURES/UNASSIGNED:SARS-CoV-2 infection, determined by positive laboratory test results (polymerase chain reaction, antigen, or serologic) or relevant clinical diagnoses. A comparison group included children with documented negative test results and no history of SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Outcomes included new-onset chronic kidney disease (CKD) stage 2 or higher or CKD stage 3 or higher among those without preexisting CKD; composite kidney events (≥50% decline in estimated glomerular filtration rate [eGFR], eGFR ≤15 mL/min/1.73 m2, dialysis, transplant, or end-stage kidney disease diagnosis), and at least 30%, 40%, or 50% eGFR decline among those with preexisting CKD or acute-phase AKI. Hazard ratios (HRs) were estimated using Cox proportional hazards regression models with propensity score stratification. RESULTS/UNASSIGNED:Among 1 900 146 pediatric patients (487 378 with and 1 412 768 without COVID-19), 969 937 (51.0%) were male, the mean (SD) age was 8.2 (6.2) years, and a range of comorbidities was represented. SARS-CoV-2 infection was associated with higher risk of new-onset CKD stage 2 or higher (HR, 1.17; 95% CI, 1.12-1.22) and CKD stage 3 or higher (HR, 1.35; 95% CI, 1.13-1.62). In those with preexisting CKD, COVID-19 was associated with an increased risk of composite kidney events (HR, 1.15; 95% CI, 1.04-1.27) at 28 to 179 days. Children with acute-phase AKI had elevated HRs (1.29; 95% CI, 1.21-1.38) at 90 to 179 days for composite outcomes. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this large US cohort study of children and adolescents, SARS-CoV-2 infection was associated with a higher risk of adverse postacute kidney outcomes, particularly among those with preexisting CKD or AKI, suggesting the need for vigilant long-term monitoring.

Pediatric Long COVID has been associated with a wide variety of symptoms, conditions, and organ systems, but distinct clinical presentations, or subphenotypes, are still being elucidated. In this exploratory analysis, we identified a cohort of pediatric (age <21) patients with evidence of Long COVID and no pre-existing complex chronic conditions using electronic health record data from 38 institutions and used an unsupervised machine learning-based approach to identify subphenotypes. Our method, an extension of the Phe2Vec algorithm, uses tens of thousands of clinical concepts from multiple domains to represent patients' clinical histories to then identify groups of patients with similar presentations. The results indicate that cardiorespiratory presentations are most common (present in 54% of patients) followed by subphenotypes marked (in decreasing order of frequency) by musculoskeletal pain, neuropsychiatric conditions, gastrointestinal symptoms, headache, and fatigue.

BACKGROUND:Medication non-adherence, which is common in chronic diseases such as heart failure, is often estimated using proportion of days covered (PDC). PDC is typically calculated using medication fill information from pharmacy or insurance claims data, which lack information on when medications are prescribed. Many electronic health records (EHRs) have prescription and pharmacy fill data available, enabling enhanced PDC assessment that can be utilized in routine clinical care. OBJECTIVE:To describe our approach to calculating PDC using linked EHR-pharmacy data and to compare to PDC calculated using pharmacy-only data for patients with heart failure. METHODS:We performed a retrospective cohort study of adult patients with heart failure who were prescribed guideline-directed medical therapy (GDMT) and seen in a large health system. Using linked EHR-pharmacy data, we estimated medication adherence by PDC as the percent of days in which a patient possessed GDMT based on medication pharmacy fills over the number of days the prescription order was active. We also calculated PDC using pharmacy-only data, calculated as medications possessed over days with continued medication fills. We compared these two approaches for days observed and PDC using a paired t-test. RESULTS:Among 33,212 patients with heart failure who were prescribed GDMT, 2226 (6.7%) never filled their medications, making them unavailable in the assessment of PDC using pharmacy-only data (n = 30,995). Linked EHR-pharmacy data had slightly longer days observed for PDC assessment (164.7 vs. 163.4 days; p < 0.001) and lower PDC (78.5 vs. 90.6, p < 0.001) as compared to assessment using pharmacy-only data. CONCLUSIONS:Linked EHR-pharmacy data can be used to identify patients who never fill their prescriptions. Estimating adherence using linked EHR-pharmacy data resulted in a lower mean PDC as compared to estimates using pharmacy-only data.

IMPORTANCE/OBJECTIVE:Prior studies have demonstrated the effectiveness of COVID-19 vaccines in children and adolescents. However, the benefits of vaccination in these age groups with prior infection remain underexplored. OBJECTIVE:To evaluate the effectiveness of COVID-19 vaccination in preventing reinfection with various Omicron subvariants (BA.1/2, BA.4/5, XBB, and later) among 5- to 17-year-olds with prior SARS-CoV-2 infection. DESIGN/METHODS:A target trial emulation through nested designs with distinct study periods. SETTING/METHODS:The study utilized data from the Research COVID to Enhance Recovery (RECOVER) initiative, a national electronic health record (EHR) database comprising 37 U.S. children's hospitals and health institutions. PARTICIPANTS/METHODS:Individuals aged 5-17 years with a documented history of SARS-CoV-2 infection prior to the study start date during a specific variant-dominant period (Delta, BA.1/2, or BA.4/5) who received a subsequent dose of COVID-19 vaccine during the study periods were compared with those with a documented history of infection who did not receive SARS-CoV-2 vaccine during the study period. Those infected within the Delta-Omicron composite period (December 1, 2021, to December 31, 2021) were excluded. The study period was from January 1, 2022, to August 30, 2023, and focused on adolescents aged 12 to 17 years and children aged 5 to 11 years. EXPOSURES/METHODS:At least received one COVID-19 vaccination during the study period vs. no receipt of any COVID-19 vaccine during the study period. MAIN OUTCOMES AND MEASURES/METHODS:The primary outcome is documented SARS-CoV-2 reinfection during the study period (both asymptomatic and symptomatic cases). The effectiveness of the COVID-19 vaccine was estimated as (1- hazard ratio) *100%, with confounders adjusted by a combination of propensity score matching and exact matching. RESULTS:The study analyzed 87,573 participants during the BA.1/2 period, 229,326 during the BA.4/5 period, and 282,981 during the XBB or later period. Among vaccinated individuals, significant protection was observed during the BA.1/2 period, with effectiveness rates of 62% (95% CI: 38%-77%) for children and 65% (95% CI: 32%-81%) for adolescents. During the BA.4/5 period, vaccine effectiveness was 57% (95% CI: 25%-76%) for children, but not statistically significant for adolescents (36%, 95% CI: -16%-65%). For the XBB period, no significant protection was observed in either group, with effectiveness rates of 22% (95% CI: -36%-56%) in children and 34% (95% CI: -10%-61%) in adolescents. CONCLUSIONS AND RELEVANCE/CONCLUSIONS:COVID-19 vaccination provides significant protection against reinfection for children and adolescents with prior infections during the early and mid-Omicron periods. This study also highlights the importance of addressing low vaccination rates in pediatric populations to enhance protection against emerging variants.

BACKGROUND:Cardiometabolic comorbidities such as obesity, diabetes, and hypertension are highly prevalent in heart failure (HF). We aimed to examine the association between severity of cardiometabolic comorbidities and hospitalization in patients with HF. METHODS: RESULTS: CONCLUSIONS:Greater cardiometabolic comorbidity burden was associated with increased risk of all-cause hospitalization in HF. This reinforces the role for targeting severely uncontrolled cardiometabolic comorbidities to reduce morbidity in HF.

PURPOSE/UNASSIGNED:We aimed to determine whether implementation of clinical decision support (CDS) tool integrated into the electronic health record of a multisite academic medical center increased the proportion of patients with AUA "high-risk" microscopic hematuria (MH) who receive guideline concordant evaluations. MATERIALS AND METHODS/UNASSIGNED:We conducted a two-arm cluster randomized quality improvement project in which 202 ambulatory sites from a large health system were randomized to either have their physicians receive at time of test results an automated CDS alert for patients with "high-risk" MH with associated recommendations for imaging and cystoscopy (intervention) or usual care (control). Primary outcome was met if a patient underwent both imaging and cystoscopy within 180 days from MH result. Secondary outcomes assessed individual completion of imaging, cystoscopy, or placement of imaging orders. RESULTS/UNASSIGNED:= .09). CONCLUSIONS/UNASSIGNED:Implementing an electronic health record-integrated CDS tool to promote evaluation of patients with high-risk MH did not lead to improvements in patient completion of a full guideline-concordant evaluation. The development of an algorithm to trigger a CDS alert was demonstrated to be feasible and effective. Further multilevel assessment of barriers to evaluation is necessary to continue to improve the approach to evaluating high-risk patients with MH.

Despite progress to define primary care practice transformation models, there remain gaps in translating evidence-based guidelines into routine clinical care. Primary care providers (MD, DO, NP, PA) and researchers need tools to assess modifiable factors that improve practice performance to inform practice transformation efforts. We aimed to develop a pragmatic tool for assessing practice-level primary care structures and processes that are associated with better care quality and clinical outcomes. We generated 314 candidate items for the Tool for Advancing Practice Performance (TAPP) using data from a comprehensive literature review, Delphi study, and qualitative interviews with high-performing practices. We used empirical criteria and expert review to eliminate redundancy and improve clarity via removing and retaining items. The retained items were formatted into a survey tool, and we further revised the tool based on feedback elicited from cognitive interviews and pilot testing with primary care providers and staff. The final candidate pool comprised 126 items after refinement and expert review. For the survey tool, we adapted and developed survey questions for each of the 126 items. Eight cognitive interview participants reviewed the tool and provided feedback on its content and language. Based on this feedback, we eliminated 13 items because they were poorly or incorrectly understood by participants, resulting in a 113-item tool. Fifteen participants pilot tested the tool and no additional items were eliminated. The TAPP is a novel, low-burden tool that researchers and primary care providers can use to identify areas for improvement at the practice-level. Practices and health systems could use the TAPP to assess their own performance and identify gaps in their structures and processes, and practice networks and health systems can use the tool to assess structures and processes at individual clinics, track this information over time, and evaluate its relationship to care quality and clinical outcomes.

BACKGROUND/UNASSIGNED:Despite the exponential growth in telemedicine visits in clinical practice due to the COVID-19 pandemic, it remains unknown if telemedicine visits achieved similar adherence to prescribed medications as in-person office visits for patients with heart failure. OBJECTIVE/UNASSIGNED:Our study examined the association between telemedicine visits (vs in-person visits) and medication adherence in patients with heart failure. METHODS/UNASSIGNED:This was a retrospective cross-sectional study of adult patients with a diagnosis of heart failure or an ejection fraction of ≤40% using data between April 1 and October 1, 2020. This period was used because New York University approved telemedicine visits for both established and new patients by April 1, 2020. The time zero window was between April 1 and October 1, 2020, then each identified patient was monitored for up to 180 days. Medication adherence was measured by the mean proportion of days covered (PDC) within 180 days, and categorized as adherent if the PDC was ≥0.8. Patients were included in the telemedicine exposure group or in-person group if all encounters were video visits or in-person office visits, respectively. Poisson regression and logistic regression models were used for the analyses. RESULTS/UNASSIGNED:A total of 9521 individuals were included in this analysis (telemedicine visits only: n=830 in-person office visits only: n=8691). Overall, the mean age was 76.7 (SD 12.4) years. Most of the patients were White (n=6996, 73.5%), followed by Black (n=1060, 11.1%) and Asian (n=290, 3%). Over half of the patients were male (n=5383, 56.5%) and over half were married or living with partners (n=4914, 51.6%). Most patients' health insurance was covered by Medicare (n=7163, 75.2%), followed by commercial insurance (n=1687, 17.7%) and Medicaid (n=639, 6.7%). Overall, the average PDC was 0.81 (SD 0.286) and 71.3% (6793/9521) of patients had a PDC≥0.8. There was no significant difference in mean PDC between the telemedicine and in-person office groups (mean 0.794, SD 0.294 vs mean 0.812, SD 0.285) with a rate ratio of 0.99 (95% CI 0.96-1.02; P=.09). Similarly, there was no significant difference in adherence rates between the telemedicine and in-person office groups (573/830, 69% vs 6220/8691, 71.6%), with an odds ratio of 0.94 (95% CI 0.81-1.11; P=.12). The conclusion remained the same after adjusting for covariates (eg, age, sex, race, marriage, language, and insurance). CONCLUSIONS/UNASSIGNED:We found similar rates of medication adherence among patients with heart failure who were being seen via telemedicine or in-person visits. Our findings are important for clinical practice because we provide real-world evidence that telemedicine can be an approach for outpatient visits for patients with heart failure. As telemedicine is more convenient and avoids transportation issues, it may be an alternative way to maintain the same medication adherence as in-person visits for patients with heart failure.