Faculty Bibliography

OBJECTIVE:To examine the associations between patient out-of-pocket (OOP) costs and nonadherence to glucagon-like peptide 1 receptor agonists (GLP-1a), and the consequent impact on adverse outcomes, including hospitalizations and emergency department (ED) visits. RESEARCH DESIGN AND METHODS/METHODS:This retrospective cohort study used MarketScan Commercial data (2016-2021). The cohort included nonpregnant adults aged 18-64 years with type 2 diabetes who initiated GLP-1a therapy. Participants were continuously enrolled in the same private insurance plan for 6 months before the prescription date and 1 year thereafter. Exposures included average first 30-day OOP costs for GLP-1a, categorized into quartiles (lowest [Q1] to highest [Q4]). Primary outcomes were the annual proportion of days covered (PDC) for GLP-1a and nonadherence, defined as PDC <0.8. Secondary outcomes included diabetes-related and all-cause hospitalizations and ED visits 1 year post-GLP-1a initiation. RESULTS:Among 61,907 adults who initiated GLP-1a, higher 30-day OOP costs were associated with decreased adherence. Patients in the highest OOP cost quartile (Q4: $80-$3,375) had significantly higher odds of nonadherence (odds ratio [OR]1.25; 95% CI 1.19-1.31) compared with those in Q1 ($0-$21). Nonadherence was linked to increased incidence rates of diabetes-related hospitalizations or ED visits (incidence rate ratio [IRR] 1.86; 95% CI 1.43-2.42), cumulative length of hospitalization (IRR 1.56; 95% CI 1.41-1.72), all-cause ED visits (IRR 1.38; 95% CI 1.32-1.45), and increased ED-related costs ($69.81, 95% CI $53.54-$86.08). CONCLUSIONS:Higher OOP costs for GLP-1a were associated with reduced adherence and increased rates of adverse outcomes among type 2 diabetes patients.

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.

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.

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.

OBJECTIVE:To identify primary care structures and processes that have the highest and lowest impact on chronic disease management and screening and prevention outcomes as well as to assess the feasibility of implementing these structures and processes into practice. DESIGN/METHODS:A two-round Delphi study was conducted to establish consensus on the impact and feasibility of 258 primary care structures and processes. PARTICIPANTS/METHODS:29 primary care providers, health system leaders and health services researchers in the USA. OUTCOMES/RESULTS:Primary outcomes were (1) consensus on the impact of each structure and process on chronic disease management and screening and prevention outcomes, separately and (2) consensus on feasibility of implementation by primary care practices. RESULTS:Consensus on high impact and feasibility of implementation was reached on four items for chronic disease management: 'Providers use motivational interviewing to help patients set goals', 'Practice has designated staff to manage patient panel', 'Practice has onsite providers or staff that speak the most dominant, non-English language spoken by patients' and 'Practice includes mental health providers and/or behavioural health specialists in care team' and seven items for screening and prevention: 'Practice utilizes standing protocols and orders', 'Practice generates reports to alert clinicians to missed targets and to identify gaps in care, such as overdue visits, needed vaccinations, screenings or other preventive services', 'Practice has designated staff to manage patient panel', 'Practice sets performance goals and uses benchmarking to track quality of care', 'Practice uses performance feedback to identify practice-specific areas of improvement', 'Practice builds quality improvement activities into practice operations' and 'Pre-visit planning data are reviewed during daily huddles'. Only 'Practice has designated staff to manage patient panel' appeared on both lists. CONCLUSION/CONCLUSIONS:Findings suggest that practices need to focus on implementing mostly distinct, rather than common, structures and processes to optimise chronic disease and preventive care.