Reduced Likelihood of Hospitalization with the JN.1 or HV.1 SARS-CoV-2 Variants Compared to the EG.5 Variant.

Within a multi-state viral genomic surveillance program, we evaluated whether proportions of SARS-CoV-2 infections attributed to the JN.1 variant and to XBB-lineage variants (including HV.1 and EG.5) differed between inpatient and outpatient care settings during periods of cocirculation. Both JN.1 and HV.1 were less likely than EG.5 to account for infections among inpatients versus outpatients (aOR=0.60 [95% CI: 0.43-0.84; p=0.003] and aOR=0.35 [95% CI: 0.21-0.58; p<0.001], respectively). JN.1 and HV.1 variants may be associated with a lower risk of severe illness. The severity of COVID-19 may have attenuated as predominant circulating SARS-CoV-2 lineages shifted from EG.5 to HV.1 to JN.1.

Identifying factors and causal chains associated with optimal implementation of Lynch syndrome tumor screening: An application of coincidence analysis.

PURPOSE: This study compared Lynch syndrome universal tumor screening (UTS) across multiple health systems (some of which had 2 or more distinct UTS programs) to understand multilevel factors that may affect the successful implementation of complex programs. METHODS: Data from 66 stakeholder interviews were used to conduct multivalue coincidence analysis and identify key factors that consistently make a difference in whether UTS programs were implemented and optimized at the system level. RESULTS: The selected coincidence analysis model revealed combinations of conditions that distinguish 4 optimized UTS programs, 10 nonoptimized programs, and 4 systems with no program. Fully optimized UTS programs had both a maintenance champion and a positive inner setting. Two independent paths were unique to nonoptimized programs: (1) positive attitudes and a mixed inner setting or (2) limited planning and engaging among stakeholders. Negative views about UTS evidence or lack of knowledge about UTS led to a lack of planning and engaging, which subsequently prevented program implementation. CONCLUSION: The model improved our understanding of program implementation in health care systems and informed the creation of a toolkit to guide UTS implementation, optimization, and changes. Our findings and toolkit may serve as a use case to increase the successful implementation of other complex precision health programs.

A power-based sliding window approach to evaluate the clinical impact of rare genetic variants in the nucleotide sequence or the spatial position of the folded protein.

Systematic determination of novel variant pathogenicity remains a major challenge, even when there is an established association between a gene and phenotype. Here we present Power Window (PW), a sliding window technique that identifies the impactful regions of a gene using population-scale clinico-genomic datasets. By sizing analysis windows on the number of variant carriers, rather than the number of variants or nucleotides, statistical power is held constant, enabling the localization of clinical phenotypes and removal of unassociated gene regions. The windows can be built by sliding across either the nucleotide sequence of the gene (through 1D space) or the positions of the amino acids in the folded protein (through 3D space). Using a training set of 350k exomes from the UK Biobank (UKB), we developed PW models for well-established gene-disease associations and tested their accuracy in two independent cohorts (117k UKB exomes and 65k exomes sequenced at Helix in the Healthy Nevada Project, myGenetics, or In Our DNA SC studies). The significant models retained a median of 49% of the qualifying variant carriers in each gene (range 2%-98%), with quantitative traits showing a median effect size improvement of 66% compared with aggregating variants across the entire gene, and binary traits' odds ratios improving by a median of 2.2-fold. PW showcases that electronic health record-based statistical analyses can accurately distinguish between novel coding variants in established genes that will have high phenotypic penetrance and those that will not, unlocking new potential for human genomics research, drug development, variant interpretation, and precision medicine.

Risk of Arterial and Venous Thrombotic Events Among Patients with COVID-19: A Multi-National Collaboration of Regulatory Agencies from Canada, Europe, and United States.

Purpose: Few studies have examined how the absolute risk of thromboembolism with COVID-19 has evolved over time across different countries. Researchers from the European Medicines Agency, Health Canada, and the United States (US) Food and Drug Administration established a collaboration to evaluate the absolute risk of arterial (ATE) and venous thromboembolism (VTE) in the 90 days after diagnosis of COVID-19 in the ambulatory (eg, outpatient, emergency department, nursing facility) setting from seven countries across North America (Canada, US) and Europe (England, Germany, Italy, Netherlands, and Spain) within periods before and during COVID-19 vaccine availability. Patients and Methods: We conducted cohort studies of patients initially diagnosed with COVID-19 in the ambulatory setting from the seven specified countries. Patients were followed for 90 days after COVID-19 diagnosis. The primary outcomes were ATE and VTE over 90 days from diagnosis date. We measured country-level estimates of 90-day absolute risk (with 95% confidence intervals) of ATE and VTE. Results: The seven cohorts included 1,061,565 patients initially diagnosed with COVID-19 in the ambulatory setting before COVID-19 vaccines were available (through November 2020). The 90-day absolute risk of ATE during this period ranged from 0.11% (0.09-0.13%) in Canada to 1.01% (0.97-1.05%) in the US, and the 90-day absolute risk of VTE ranged from 0.23% (0.21-0.26%) in Canada to 0.84% (0.80-0.89%) in England. The seven cohorts included 3,544,062 patients with COVID-19 during vaccine availability (beginning December 2020). The 90-day absolute risk of ATE during this period ranged from 0.06% (0.06-0.07%) in England to 1.04% (1.01-1.06%) in the US, and the 90-day absolute risk of VTE ranged from 0.25% (0.24-0.26%) in England to 1.02% (0.99-1.04%) in the US. Conclusion: There was heterogeneity by country in 90-day absolute risk of ATE and VTE after ambulatory COVID-19 diagnosis both before and during COVID-19 vaccine availability.

SARS-CoV-2 Antiviral Prescribing Gaps Among Nonhospitalized High-Risk Adults.

Within a multistate clinical cohort, SARS-CoV-2 antiviral prescribing patterns were evaluated from April 2022-June 2023 among nonhospitalized patients with SARS-CoV-2 with risk factors for severe COVID-19. Among 3247 adults, only 31.9% were prescribed an antiviral agent (87.6% nirmatrelvir/ritonavir, 11.9% molnupiravir, 0.5% remdesivir), highlighting the need to identify and address treatment barriers.

Protocol of a patient randomized clinical trial to improve medication adherence in primary care.

BACKGROUND: Enhanced awareness of poor medication adherence could improve patient care. This article describes the original and adapted protocols of a randomized trial to improve medication adherence for cardiometabolic conditions. METHODS: The original protocol entailed a cluster randomized trial of 28 primary care clinics allocated to either (i) medication adherence enhanced chronic disease care clinical decision support (eCDC-CDS) integrated within the electronic health record (EHR) or (ii) usual care (non-enhanced CDC-CDS). Enhancements comprised (a) electronic interfaces printed for patients and clinicians at primary care encounters that encouraged discussion about specific medication adherence issues that were identified, and (b) pharmacist phone outreach. Study subjects were individuals who at an index visit were aged 18-74 years and not at evidence-based care goals for hypertension (HTN), diabetes mellitus (DM), or lipid management, along with low medication adherence (proportion of days covered [PDC] <80%) for a corresponding medication. The primary study outcomes were improved medication adherence and clinical outcomes (BP and A1C) at 12 months. Protocol adaptation became imperative in response to major implementation challenges: (a) the availability of EHR system-wide PDC calculations that superseded our ability to limit PDC adherence information solely to intervention clinics; (b) the unforeseen closure of pharmacies committed to conducting the pharmacist outreach; and (c) disruptions and clinic closures due to the Covid-19 pandemic. CONCLUSION: This manuscript details the protocol of a study to assess whether enhanced awareness of medication adherence issues in primary care settings could improve patient outcomes. The need for protocol adaptation arose in response to multiple implementation challenges.

"Go ahead and screen" - advice to healthcare systems for routine lynch syndrome screening from interviews with newly diagnosed colorectal cancer patients.

BACKGROUND: Lynch syndrome (LS) is the most common cause of inherited colorectal cancer (CRC). Universal tumor screening (UTS) of newly diagnosed CRC cases is recommended to aid in diagnosis of LS and reduce cancer-related morbidity and mortality. However, not all health systems have adopted UTS processes and implementation may be inconsistent due to system and patient-level complexities. METHODS: To identify barriers, facilitators, and suggestions for improvements of the UTS process from the patient perspective, we conducted in-depth, semi-structured interviews with patients recently diagnosed with CRC, but not screened for or aware of LS. Patients were recruited from eight regionally diverse US health systems. Interviews were conducted by telephone, 60-minutes, audio-recorded, and transcribed. An inductive, constant comparative analysis approach was employed.  RESULTS: We completed 75 interviews across the eight systems. Most participants were white (79%), about half (52%) were men, and the mean age was 60 years. Most self-reported either no (60%) or minimal (40%) prior awareness of LS. Overall, 96% of patients stated UTS should be a routine standard of care for CRC tumors, consistently citing four primary motivations for wanting to know their LS status and engage in the process for LS identification: "knowledge is power"; "family knowledge"; "prevention and detection"; and "treatment and surveillance." Common concerns pertaining to the process of screening for and identifying LS included: creating anticipatory worry for patients, the potential cost and the accuracy of the genetic test, and possibly having one's health insurance coverage impacted by the LS diagnosis. Patients suggested health systems communicate LS results in-person or by phone from a trained expert in LS; offer proactive verbal and written education about LS, the screening steps, and any follow-up surveillance recommendations; and support patients in communicating their LS screening to any of their blood relatives. CONCLUSION: Our qualitative findings demonstrate patients with CRC have a strong desire for healthcare systems to regularly implement and offer UTS. Patients offer key insights for health systems to guide future implementation and optimization of UTS and other LS screening programs and maximize diagnosis of individuals with LS and improve cancer-related surveillance and outcomes. TRIAL REGISTRATION: Not available: not a clinical trial.

Examining sociodemographic correlates of opioid use, misuse, and use disorders in the All of Us Research Program.

BACKGROUND: The All of Us Research Program enrolls diverse US participants which provide a unique opportunity to better understand the problem of opioid use. This study aims to estimate the prevalence of opioid use and its association with sociodemographic characteristics from survey data and electronic health record (EHR). METHODS: A total of 214,206 participants were included in this study who competed survey modules and shared EHR data. Adjusted logistic regressions were used to explore the associations between sociodemographic characteristics and opioid use. RESULTS: The lifetime prevalence of street opioids was 4%, and the nonmedical use of prescription opioids was 9%. Men had higher odds of lifetime opioid use (aOR: 1.4 to 3.1) but reduced odds of current nonmedical use of prescription opioids (aOR: 0.6). Participants from other racial and ethnic groups were at reduced odds of lifetime use (aOR: 0.2 to 0.9) but increased odds of current use (aOR: 1.9 to 9.9) compared with non-Hispanic White participants. Foreign-born participants were at reduced risks of opioid use and diagnosed with opioid use disorders (OUD) compared with US-born participants (aOR: 0.36 to 0.67). Men, Younger, White, and US-born participants are more likely to have OUD. CONCLUSIONS: All of Us research data can be used as an indicator of national trends for monitoring the prevalence of receiving prescription opioids, diagnosis of OUD, and non-medical use of opioids in the US. The program employs a longitudinal design for routinely collecting health-related data including EHR data, that will contribute to the literature by providing important clinical information related to opioids over time. Additionally, this data will enhance the estimates of the prevalence of OUD among diverse populations, including groups that are underrepresented in the national survey data.

Risk of admission to hospital with arterial or venous thromboembolism among patients diagnosed in the ambulatory setting with covid-19 compared with influenza: retrospective cohort study.

Objective: To measure the 90 day risk of arterial thromboembolism and venous thromboembolism among patients diagnosed with covid-19 in the ambulatory (ie, outpatient, emergency department, or institutional) setting during periods before and during covid-19 vaccine availability and compare results to patients with ambulatory diagnosed influenza. Design: Retrospective cohort study. Setting: Four integrated health systems and two national health insurers in the US Food and Drug Administration's Sentinel System. Participants: Patients with ambulatory diagnosed covid-19 when vaccines were unavailable in the US (period 1, 1 April-30 November 2020; n=272 065) and when vaccines were available in the US (period 2, 1 December 2020-31 May 2021; n=342 103), and patients with ambulatory diagnosed influenza (1 October 2018-30 April 2019; n=118 618). Main outcome measures: Arterial thromboembolism (hospital diagnosis of acute myocardial infarction or ischemic stroke) and venous thromboembolism (hospital diagnosis of acute deep venous thrombosis or pulmonary embolism) within 90 days after ambulatory covid-19 or influenza diagnosis. We developed propensity scores to account for differences between the cohorts and used weighted Cox regression to estimate adjusted hazard ratios of outcomes with 95% confidence intervals for covid-19 during periods 1 and 2 versus influenza. Results: 90 day absolute risk of arterial thromboembolism with covid-19 was 1.01% (95% confidence interval 0.97% to 1.05%) during period 1, 1.06% (1.03% to 1.10%) during period 2, and with influenza was 0.45% (0.41% to 0.49%). The risk of arterial thromboembolism was higher for patients with covid-19 during period 1 (adjusted hazard ratio 1.53 (95% confidence interval 1.38 to 1.69)) and period 2 (1.69 (1.53 to 1.86)) than for patients with influenza. 90 day absolute risk of venous thromboembolism with covid-19 was 0.73% (0.70% to 0.77%) during period 1, 0.88% (0.84 to 0.91%) during period 2, and with influenza was 0.18% (0.16% to 0.21%). Risk of venous thromboembolism was higher with covid-19 during period 1 (adjusted hazard ratio 2.86 (2.46 to 3.32)) and period 2 (3.56 (3.08 to 4.12)) than with influenza. Conclusions: Patients diagnosed with covid-19 in the ambulatory setting had a higher 90 day risk of admission to hospital with arterial thromboembolism and venous thromboembolism both before and after covid-19 vaccine availability compared with patients with influenza.

A picture is worth a thousand words: advancing the use of visualization tools in implementation science through process mapping and matrix heat mapping.

BACKGROUND: Identifying key determinants is crucial for improving program implementation and achieving long-term sustainment within healthcare organizations. Organizational-level complexity and heterogeneity across multiple stakeholders can complicate our understanding of program implementation. We describe two data visualization methods used to operationalize implementation success and to consolidate and select implementation factors for further analysis. METHODS: We used a combination of process mapping and matrix heat mapping to systematically synthesize and visualize qualitative data from 66 stakeholder interviews across nine healthcare organizations, to characterize universal tumor screening programs of all newly diagnosed colorectal and endometrial cancers and understand the influence of contextual factors on implementation. We constructed visual representations of protocols to compare processes and score process optimization components. We also used color-coded matrices to systematically code, summarize, and consolidate contextual data using factors from the Consolidated Framework for Implementation Research (CFIR). Combined scores were visualized in a final data matrix heat map. RESULTS: Nineteen process maps were created to visually represent each protocol. Process maps identified the following gaps and inefficiencies: inconsistent execution of the protocol, no routine reflex testing, inconsistent referrals after a positive screen, no evidence of data tracking, and a lack of quality assurance measures. These barriers in patient care helped us define five process optimization components and used these to quantify program optimization on a scale from 0 (no program) to 5 (optimized), representing the degree to which a program is implemented and optimally maintained. Combined scores within the final data matrix heat map revealed patterns of contextual factors across optimized programs, non-optimized programs, and organizations with no program. CONCLUSIONS: Process mapping provided an efficient method to visually compare processes including patient flow, provider interactions, and process gaps and inefficiencies across sites, thereby measuring implementation success via optimization scores. Matrix heat mapping proved useful for data visualization and consolidation, resulting in a summary matrix for cross-site comparisons and selection of relevant CFIR factors. Combining these tools enabled a systematic and transparent approach to understanding complex organizational heterogeneity prior to formal coincidence analysis, introducing a stepwise approach to data consolidation and factor selection.

Identification of cancer chemotherapy regimens and patient cohorts in administrative claims: challenges, opportunities, and a proposed algorithm.

BACKGROUND: Real-world evidence is a valuable source of information in healthcare. This study describes the challenges and successes during algorithm development to identify cancer cohorts and multi-agent chemotherapy regimens from claims data to perform a comparative effectiveness analysis of granulocyte colony stimulating factor (G-CSF) use. METHODS: Using the Biologics and Biosimilars Collective Intelligence Consortium's Distributed Research Network, we iteratively developed and tested a de novo algorithm to accurately identify patients by cancer diagnosis, then extract chemotherapy and G-CSF administrations for a retrospective study of prophylactic G-CSF. RESULTS: After identifying patients with cancer and subsequent chemotherapy exposures, we observed only 12% of patients with cancer received chemotherapy, which is fewer than expected based on prior analyses. Therefore, we reversed the initial inclusion criteria to identify chemotherapy receipt, then prior cancer diagnosis, which increased the number of patients from 2,814 to 3,645, or 68% of patients receiving chemotherapy had diagnoses of interest. Additionally, we excluded patients with cancer diagnoses that differed from those of interest in the 183 days before the index date of G-CSF receipt, including early-stage cancers without G-CSF or chemotherapy exposure. By removing this criterion, we retained 77 patients who were previously excluded. Finally, we incorporated a 5-day window to identify all chemotherapy drugs administered (excluding oral prednisone and methotrexate, as these medications may be used for other non-malignant conditions) as patients may fill oral prescriptions days to weeks prior to infusion. This increased the number of patients with chemotherapy exposures of interest to 6,010. The final cohort of included patients, based on G-CSF exposure, increased from 420 from the initial algorithm to 886 using the final algorithm. CONCLUSIONS: Medications used for multiple indications, sensitivity and specificity of administrative codes, and relative timing of medication exposure must all be evaluated to identify patient cohorts receiving chemotherapy from claims data.

Using the IMEDS distributed database for epidemiological studies in type 2 diabetes mellitus.

INTRODUCTION: This study aimed to assess data relevancy and data quality of the Innovation in Medical Evidence Development and Surveillance System Distributed Database (IMEDS-DD) for diabetes research and to evaluate comparability of its type 2 diabetes cohort to the general type 2 diabetes population. RESEARCH DESIGN AND METHODS: A retrospective study was conducted using the IMEDS-DD. Eligible members were adults with a medical encounter between April 1, 2018 and March 31, 2019 (index period). Type 2 diabetes and co-existing conditions were determined using all data available from April 1, 2016 to the most recent encounter within the index period. Type 2 diabetes patient characteristics, comorbidities and hemoglobin A1c (HbA1c) values were summarized and compared with those reported in national benchmarks and literature. RESULTS: Type 2 diabetes prevalence was 12.6% in the IMEDS-DD. Of 4 14 672 patients with type 2 diabetes, 52.8% were male, and the mean age was 65.0 (SD 13.3) years. Common comorbidities included hypertension (84.5%), hyperlipidemia (82.8%), obesity (45.3%), and cardiovascular disease (44.7%). Moderate-to-severe chronic kidney disease was observed in 20.2% patients. The most commonly used antihyperglycemic agents included metformin (35.7%), sulfonylureas (14.8%), and insulin (9.9%). Less than one-half (48.9%) had an HbA1c value recorded. These findings demonstrated the notable similarity in patient characteristics between type 2 diabetes populations identified within the IMEDS-DD and other large databases. CONCLUSIONS: Despite the limitations related to HbA1c data, our findings indicate that the IMEDS-DD contains robust information on key data elements to conduct pharmacoepidemiological studies in diabetes, including member demographic and clinical characteristics and health services utilization.

Should Health Systems Share Genetic Findings With At-Risk Relatives When the Proband Is Deceased? Interviews With Individuals Diagnosed With Lynch Syndrome.

Purpose: Genetic information has health implications for patients and their biological relatives. Death of a patient before sharing a genetic diagnosis with at-risk relatives is a missed opportunity to provide important information that could guide interventions to minimize cancer-related morbidity and mortality in relatives. Methods: We performed semi-structured interviews with individuals diagnosed with Lynch syndrome at 1 of 4 health systems to explore their perspectives on whether health systems should share genetic risk information with relatives following a patient's death. An inductive, open-coding approach was used to analyze audio-recorded content, with software-generated code reports undergoing iterative comparative analysis by a qualitative research team to identify broad themes and representative participant quotes. Results: Among 23 participating interviewees, 19 supported health systems informing relatives about their Lynch syndrome risk while the remaining 4 were conflicted about patient privacy. Most (n=22) wanted their Lynch syndrome diagnosis shared with relatives if they were unable to share and to be informed of their own risk if a diagnosed relative was unable to share. The most common issues noted regarding information-sharing with relatives included patient privacy and privacy laws (n=8), potential anxiety (n=5), and lack of contact information for relatives (n=3). Interviewee perspectives on how health systems could communicate genetic findings generated a consensus: When - a few months after but within a year of the patient's death; How - explanatory letter and follow-up phone call; and Who - a knowledgeable professional. Conclusions: Interviews demonstrated strong and consistent perspectives from individuals diagnosed with Lynch syndrome that health systems have a role and responsibility to inform relatives of genetic findings following a patient's death.

Comparing Pharmacist-Led Telehealth Care and Clinic-Based Care for Uncontrolled High Blood Pressure: The Hyperlink 3 Pragmatic Cluster-Randomized Trial.

BACKGROUND: A team approach is one of the most effective ways to lower blood pressure (BP) in uncontrolled hypertension, but different models for organizing team-based care have not been compared directly. METHODS: A pragmatic, cluster-randomized trial compared 2 interventions in adult patients with moderately severe hypertension (BP≥150/95 mm Hg): (1) clinic-based care using best practices and face-to-face visits with physicians and medical assistants; and (2) telehealth care using best practices and adding home BP telemonitoring with home-based care coordinated by a clinical pharmacist or nurse practitioner. The primary outcome was change in systolic BP over 12 months. Secondary outcomes were change in patient-reported outcomes over 6 months. RESULTS: Participants (N=3071 in 21 primary care clinics) were on average 60 years old, 47% male, and 19% Black. Protocol-specified follow-up within 6 weeks was 32% in clinic-based care and 27% in telehealth care. BP decreased significantly during 12 months of follow-up in both groups, from 157/92 to 139/82 mm Hg in clinic-based care patients (adjusted mean difference -18/-10 mm Hg) and 157/91 to 139/81 mm Hg in telehealth care patients (adjusted mean difference -19/-10 mm Hg), with no significant difference in systolic BP change between groups (-0.8 mm Hg [95% CI, -2.84 to 1.32]). Telehealth care patients were significantly more likely than clinic-based care patients to report frequent home BP measurement, rate their BP care highly, and report that BP care visits were convenient. CONCLUSIONS: Telehealth care that includes extended team care is an effective and safe alternative to clinic-based care for improving patient-centered care for hypertension. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02996565.

Patient characteristics, pain treatment patterns, and incidence of total joint replacement in a US population with osteoarthritis.

BACKGROUND: Currently available medications for chronic osteoarthritis pain are only moderately effective, and their use is limited in many patients because of serious adverse effects and contraindications. The primary surgical option for osteoarthritis is total joint replacement (TJR). The objectives of this study were to describe the treatment history of patients with osteoarthritis receiving prescription pain medications and/or intra-articular corticosteroid injections, and to estimate the incidence of TJR in these patients. METHODS: This retrospective, multicenter, cohort study utilized health plan administrative claims data (January 1, 2013, through December 31, 2019) of adult patients with osteoarthritis in the Innovation in Medical Evidence Development and Surveillance Distributed Database, a subset of the US FDA Sentinel Distributed Database. Patients were analyzed in two cohorts: those with prevalent use of "any pain medication" (prescription non-steroidal anti-inflammatory drugs [NSAIDs], opioids, and/or intra-articular corticosteroid injections) using only the first qualifying dispensing (index date); and those with prevalent use of "each specific pain medication class" with all qualifying treatment episodes identified. RESULTS: Among 1 992 670 prevalent users of "any pain medication", pain medications prescribed on the index date were NSAIDs (596 624 [29.9%] patients), opioids (1 161 806 [58.3%]), and intra-articular corticosteroids (323 459 [16.2%]). Further, 92 026 patients received multiple pain medications on the index date, including 71 632 (3.6%) receiving both NSAIDs and opioids. Altogether, 20.6% of patients used an NSAID at any time following an opioid index dispensing and 17.2% used an opioid following an NSAID index dispensing. The TJR incidence rates per 100 person-years (95% confidence interval [CI]) were 3.21 (95% CI: 3.20-3.23) in the "any pain medication" user cohort, and among those receiving "each specific pain medication class" were NSAIDs, 4.63 (95% CI: 4.58-4.67); opioids, 7.45 (95% CI: 7.40-7.49); and intra-articular corticosteroids, 8.05 (95% CI: 7.97-8.13). CONCLUSIONS: In patients treated with prescription medications for osteoarthritis pain, opioids were more commonly prescribed at index than NSAIDs and intra-articular corticosteroid injections. Of the pain medication classes examined, the incidence of TJR was highest in patients receiving intra-articular corticosteroids and lowest in patients receiving NSAIDs.

Comparison of explanatory and pragmatic design choices in a cluster-randomized hypertension trial: effects on enrollment, participant characteristics, and adherence.

BACKGROUND: Explanatory trials are designed to assess intervention efficacy under ideal conditions, while pragmatic trials are designed to assess whether research-proven interventions are effective in "real-world" settings without substantial research support. METHODS: We compared two trials (Hyperlink 1 and 3) that tested a pharmacist-led telehealth intervention in adults with uncontrolled hypertension. We applied PRagmatic Explanatory Continuum Indicator Summary-2 (PRECIS-2) scores to describe differences in the way these studies were designed and enrolled study-eligible participants, and the effect of these differences on participant characteristics and adherence to study interventions. RESULTS: PRECIS-2 scores demonstrated that Hyperlink 1 was more explanatory and Hyperlink 3 more pragmatic. Recruitment for Hyperlink 1 was conducted by study staff, and 2.9% of potentially eligible patients enrolled. Enrollees were older, and more likely to be male and White than non-enrollees. Study staff scheduled the initial pharmacist visit and adherence to attending this visit was 98%. Conversely for Hyperlink 3, recruitment was conducted by clinic staff at routine encounters and 81% of eligible patients enrolled. Enrollees were younger, and less likely to be male and White than non-enrollees. Study staff did not assist with scheduling the initial pharmacist visit and adherence to attending this visit was only 27%. Compared to Hyperlink 1, patients in Hyperlink 3 were more likely to be female, and Asian or Black, had lower socioeconomic indicators, and were more likely to have comorbidities. Owing to a lower BP for eligibility in Hyperlink 1 (>140/90 mm Hg) than in Hyperlink 3 (>150/95 mm Hg), mean baseline BP was 148/85 mm Hg in Hyperlink 1 and 158/92 mm Hg in Hyperlink 3. CONCLUSION: The pragmatic design features of Hyperlink 3 substantially increased enrollment of study-eligible patients and of those traditionally under-represented in clinical trials (women, minorities, and patients with less education and lower income), and demonstrated that identification and enrollment of a high proportion of study-eligible subjects could be done by usual primary care clinic staff. However, the trade-off was much lower adherence to the telehealth intervention than in Hyperlink 1, which is likely to reflect uptake under real-word conditions and substantially dilute intervention effect on BP. TRIAL REGISTRATION: The Hyperlink 1 study (NCT00781365) and the Hyperlink 3 study (NCT02996565) are registered at ClinicalTrials.gov.

Association of COVID-19 vs Influenza With Risk of Arterial and Venous Thrombotic Events Among Hospitalized Patients.

Importance: The incidence of arterial thromboembolism and venous thromboembolism in persons with COVID-19 remains unclear. Objective: To measure the 90-day risk of arterial thromboembolism and venous thromboembolism in patients hospitalized with COVID-19 before or during COVID-19 vaccine availability vs patients hospitalized with influenza. Design, Setting, and Participants: Retrospective cohort study of 41 443 patients hospitalized with COVID-19 before vaccine availability (April-November 2020), 44 194 patients hospitalized with COVID-19 during vaccine availability (December 2020-May 2021), and 8269 patients hospitalized with influenza (October 2018-April 2019) in the US Food and Drug Administration Sentinel System (data from 2 national health insurers and 4 regional integrated health systems). Exposures: COVID-19 or influenza (identified by hospital diagnosis or nucleic acid test). Main Outcomes and Measures: Hospital diagnosis of arterial thromboembolism (acute myocardial infarction or ischemic stroke) and venous thromboembolism (deep vein thrombosis or pulmonary embolism) within 90 days. Outcomes were ascertained through July 2019 for patients with influenza and through August 2021 for patients with COVID-19. Propensity scores with fine stratification were developed to account for differences between the influenza and COVID-19 cohorts. Weighted Cox regression was used to estimate the adjusted hazard ratios (HRs) for outcomes during each COVID-19 vaccine availability period vs the influenza period. Results: A total of 85 637 patients with COVID-19 (mean age, 72 [SD, 13.0] years; 50.5% were male) and 8269 with influenza (mean age, 72 [SD, 13.3] years; 45.0% were male) were included. The 90-day absolute risk of arterial thromboembolism was 14.4% (95% CI, 13.6%-15.2%) in patients with influenza vs 15.8% (95% CI, 15.5%-16.2%) in patients with COVID-19 before vaccine availability (risk difference, 1.4% [95% CI, 1.0%-2.3%]) and 16.3% (95% CI, 16.0%-16.6%) in patients with COVID-19 during vaccine availability (risk difference, 1.9% [95% CI, 1.1%-2.7%]). Compared with patients with influenza, the risk of arterial thromboembolism was not significantly higher among patients with COVID-19 before vaccine availability (adjusted HR, 1.04 [95% CI, 0.97-1.11]) or during vaccine availability (adjusted HR, 1.07 [95% CI, 1.00-1.14]). The 90-day absolute risk of venous thromboembolism was 5.3% (95% CI, 4.9%-5.8%) in patients with influenza vs 9.5% (95% CI, 9.2%-9.7%) in patients with COVID-19 before vaccine availability (risk difference, 4.1% [95% CI, 3.6%-4.7%]) and 10.9% (95% CI, 10.6%-11.1%) in patients with COVID-19 during vaccine availability (risk difference, 5.5% [95% CI, 5.0%-6.1%]). Compared with patients with influenza, the risk of venous thromboembolism was significantly higher among patients with COVID-19 before vaccine availability (adjusted HR, 1.60 [95% CI, 1.43-1.79]) and during vaccine availability (adjusted HR, 1.89 [95% CI, 1.68-2.12]). Conclusions and Relevance: Based on data from a US public health surveillance system, hospitalization with COVID-19 before and during vaccine availability, vs hospitalization with influenza in 2018-2019, was significantly associated with a higher risk of venous thromboembolism within 90 days, but there was no significant difference in the risk of arterial thromboembolism within 90 days.

Demographic differences in willingness to share electronic health records in the All of Us Research Program.

OBJECTIVE: Participant willingness to share electronic health record (EHR) information is central to success of the National Institutes of Health All of Us Research Program (AoURP). We describe the demographic characteristics of participants who decline access to their EHR data. MATERIALS AND METHODS: We included participants enrolling in AoURP between June 6, 2017 and December 31, 2019 through the Trans-American Consortium for the Health Care Systems Research Network (TACH). TACH is a consortium of health care systems spanning 6 states, and an AoURP research partner. RESULTS: We analyzed data for 25 852 participants (89.3% of those enrolled). Mean age = 52.0 years (SD 16.8), with 66.5% White, 18.7% Black/African American, 7.7% Hispanic, 32.5% female, and 76% with >a high school diploma. Overall, 2.3% of participants declined to share access to their EHR data (range across TACH sites = 1.3% to 3.5%). Younger age, female sex, and education >high school were significantly associated with decline to share EHR data, odds ratio (95% confidence interval) = 1.26 (1.19-1.33), 1.74 (1.42-2.14), and 2.44 (1.86-3.21), respectively. Results were similar when several sensitivity analyses were performed. DISCUSSION: AoURP seeks a dataset reflecting our nation's diversity in all aspects of participation. Those under-represented in biomedical research may be reluctant to share access to their EHR data. CONCLUSION: In our data, race and ethnicity were not independently related to participant decision to decline access to their EHR information. Results suggest that the value of the AoURP dataset is unlikely to be constrained by the size or the racial/ethnic composition of this subgroup.

Developing an algorithm across integrated healthcare systems to identify a history of cancer using electronic medical records.

OBJECTIVE: Tumor registries in integrated healthcare systems (IHCS) have high precision for identifying incident cancer but often miss recently diagnosed cancers or those diagnosed outside of the IHCS. We developed an algorithm using the electronic medical record (EMR) to identify people with a history of cancer not captured in the tumor registry to identify adults, aged 40-65 years, with no history of cancer. MATERIALS AND METHODS: The algorithm was developed at Kaiser Permanente Colorado, and then applied to 7 other IHCS. We included tumor registry data, diagnosis and procedure codes, chemotherapy files, oncology encounters, and revenue data to develop the algorithm. Each IHCS adapted the algorithm to their EMR data and calculated sensitivity and specificity to evaluate the algorithm's performance after iterative chart review. RESULTS: We included data from over 1.26 million eligible people across 8 IHCS; 55 601 (4.4%) were in a tumor registry, and 44848 (3.5%) had a reported cancer not captured in a registry. The common attributes of the final algorithm at each site were diagnosis and procedure codes. The sensitivity of the algorithm at each IHCS was 90.65%-100%, and the specificity was 87.91%-100%. DISCUSSION: Relying only on tumor registry data would miss nearly half of the identified cancers. Our algorithm was robust and required only minor modifications to adapt to other EMR systems. CONCLUSION: This algorithm can identify cancer cases regardless of when the diagnosis occurred and may be useful for a variety of research applications or quality improvement projects around cancer care.

Validation of diagnosis codes to identify hospitalized COVID-19 patients in health care claims data.

PURPOSE: Health plan claims may provide complete longitudinal data for timely, real-world population-level COVID-19 assessment. However, these data often lack laboratory results, the standard for COVID-19 diagnosis. METHODS: We assessed the validity of ICD-10-CM diagnosis codes for identifying patients hospitalized with COVID-19 in U.S. claims databases, compared to linked laboratory results, among six Food and Drug Administration Sentinel System data partners (two large national insurers, four integrated delivery systems) from February 20-October 17, 2020. We identified patients hospitalized with COVID-19 according to five ICD-10-CM diagnosis code-based algorithms, which included combinations of codes U07.1, B97.29, general coronavirus codes, and diagnosis codes for severe symptoms. We calculated the positive predictive value (PPV) and sensitivity of each algorithm relative to laboratory test results. We stratified results by data source type and across three time periods: February 20-March 31 (Time A), April 1-30 (Time B), May 1-October 17 (Time C). RESULTS: The five algorithms identified between 34 806 and 47 293 patients across the study periods; 23% with known laboratory results contributed to PPV calculations. PPVs were high and similar across algorithms. PPV of U07.1 alone was stable around 93% for integrated delivery systems, but declined over time from 93% to 70% among national insurers. Overall PPV of U07.1 across all data partners was 94.1% (95% CI, 92.3%-95.5%) in Time A and 81.2% (95% CI, 80.1%-82.2%) in Time C. Sensitivity was consistent across algorithms and over time, at 94.9% (95% CI, 94.2%-95.5%). CONCLUSION: Our results support the use of code U07.1 to identify hospitalized COVID-19 patients in U.S. claims data.