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The association between current use of oral contraceptives (OCs) among women younger than 50 years (n  = 306 541), and hormone therapy (HT) among women aged 50 years or older (n  = 323 203), and coronavirus 2019 (COVID-19) infection and hospitalization was evaluated in this population-based cohort. Current OC/HT use was recorded monthly using prescription dispensing data. COVID-19 infections were identified from March 2020 through February 2021. COVID-19 infections and hospitalizations were identified through diagnosis codes and laboratory tests. We used weighted generalized estimating equations models to estimate multivariable adjusted odds ratios (aORs) for COVID-19 infection associated with time-varying OC/HT use. Among women with COVID-19, logistic regression models were used to evaluate OC/HT use and COVID-19 hospitalization. Over 12 months, 11 727 (3.8%) women younger than 50 years and 8661 (2.7%) women aged 50 years or older experienced COVID-19 infections. There was no evidence of an association between OC use and infection (aOR = 1.05; 95% CI, 0.97-1.12). There was a modest association between HT use and infection (aOR = 1.19; 95% CI, 1.03-1.38). Women using OCs had a 39% lower risk of hospitalization (aOR = 0.61; 95% CI, 0.38-1.00), but there was no association of HT use with hospitalization (aOR = 0.89; 95% CI, 0.51-1.53). These findings do not suggest a meaningfully greater risk of COVID-19 infection associated with OC or HT use. OC use may be associated with lower COVID-19 hospitalization risk. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to examine the association between portal use and end-of-life (EOL) outcomes in the last year of life. Methods: A retrospective cohort (n = 6,517) study at Kaiser Permanente Colorado among adults with serious illness deceased between January 1, 2016, and June 30, 2019. Portal use was categorized into engagement types: no use, nonactive, active without a provider, and active with a provider. EOL outcomes were hospitalizations in the month before death, last-year advance directive completion, and hospice use. Association between EOL outcomes and levels of portal use was assessed using χ2 statistics and generalized linear models. Results: Higher portal engagement types were associated with higher rates of hospitalizations (p = 0.0492), advance directive completion (p = 0.0226), and hospice use (p = 0.0070). Conclusion: Portal use in the last year of life was associated with increases in a poor EOL outcome, hospitalizations, and beneficial EOL outcomes, advance directives, and hospice care. [ABSTRACT FROM AUTHOR]

PURPOSE: Lung cancer screening (LCS) guidelines in the United States recommend LCS for those age 50-80 years with at least 20 pack-years smoking history who currently smoke or quit within the last 15 years. We tested the performance of simple smoking-related criteria derived from electronic health record (EHR) data and developed and tested the performance of a multivariable model in predicting LCS eligibility. METHODS: Analyses were completed within the Population-based Research to Optimize the Screening Process Lung Consortium (PROSPR-Lung). In our primary validity analyses, the reference standard LCS eligibility was based on self-reported smoking data collected via survey. Within one PROSPR-Lung health system, we used a training data set and penalized multivariable logistic regression using the Least Absolute Shrinkage and Selection Operator to select EHR-based variables into the prediction model including demographics, smoking history, diagnoses, and prescription medications. A separate test data set assessed model performance. We also conducted external validation analysis in a separate health system and reported AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy metrics associated with the Youden Index. RESULTS: There were 14,214 individuals with survey data to assess LCS eligibility in primary analyses. The overall performance for assigning LCS eligibility status as measured by the AUC values at the two health systems was 0.940 and 0.938. At the Youden Index cutoff value, performance metrics were as follows: accuracy, 0.855 and 0.895; sensitivity, 0.886 and 0.920; specificity, 0.896 and 0.850; PPV, 0.357 and 0.444; and NPV, 0.988 and 0.992. CONCLUSION: Our results suggest that health systems can use an EHR-derived multivariable prediction model to aid in the identification of those who may be eligible for LCS. This EHR-based algorithm can help health systems employ a population management approach to lung cancer screening. [ABSTRACT FROM AUTHOR]

Retention in hypertension care, medication adherence, and blood pressure (BP) may have been affected by the COVID‐19 pandemic. In a retrospective cohort study of 64 766 individuals with treated hypertension from an integrated health care system, we compared hypertension care during the year pre‐COVID‐19 (March 2019–February 2020) and the first year of COVID‐19 (March 2020–February 2021). Retention in hypertension care was defined as receiving clinical BP measurements during COVID‐19. Medication adherence was measured using prescription refills. Clinical care was assessed by in‐person and virtual visits and changes in systolic and diastolic BP. The cohort had a mean age of 67.8 (12.2) years, 51.2% were women, and 73.5% were White. In 60 757 individuals with BP measurements pre‐COVID‐19, 16618 (27.4%) had no BP measurements during COVID‐19. Medication adherence declined from 86.0% to 80.8% (p <.001). In‐person primary care visits decreased from 2.7 (2.7) to 1.4 (1.9) per year, while virtual contacts increased from 9.5 (12.2) to 11.2 (14.2) per year (both p <.001). Among individuals with BP measurements, mean (SD) systolic BP was 126.5 mm Hg (11.8) pre‐COVID‐19 and 127.3 mm Hg (12.6) during COVID‐19 (p =.14). Mean diastolic BP was 73.5 mm Hg (8.5) pre‐COVID‐19 and 73.5 mm Hg (8.7) during COVID‐19 (p =.77). Even in this integrated health care system, many individuals did not receive clinical BP monitoring during COVID‐19. Most individuals who remained in care maintained pre‐COVID BP. Targeted outreach may be necessary to restore care continuity and hypertension control at the population level. [ABSTRACT FROM AUTHOR]

We measured the frequency of clinicians' assessments for access to lethal means, including firearms and medications in patients at risk of suicide from electronic medical and mental health records in outpatient and emergency settings. We included adult patients who reported suicide ideation on the PHQ-9 depression screener in behavioral health and primary care outpatient settings of a large integrated health system in the U.S. and those with suicidal behavior treated in the emergency department. Two separate natural language processing queries were developed on medical record text documentation: (1) assessment for access to firearms (8,994 patients), (2) assessment for access to medications (4,939 patients). Only 35% of patients had documentation of firearm or medication assessment in the month following treatment for suicidal behavior in the emergency setting. Among those reporting suicidal ideation in outpatient setting, 31% had documentation of firearm assessment and 23% for medication assessment. The accuracy of the estimates was very good for firearm assessment (F1 = 89%) and medication assessment in the outpatient setting (F1 = 91%) and fair for medication assessment in the emergency setting (F1 = 70%) due to more varied documentation styles. Lethal means assessment following report of suicidal ideation or behavior is low in a nonacademic health care setting. Until health systems implement more structured documentation to measure lethal means assessment, such as discrete data field, NLP methods may be used to conduct research and surveillance of this important prevention practice in real-world settings. [ABSTRACT FROM AUTHOR]

Background: Breast cancer survivors are at increased risk for developing second primary cancers compared with the general population. Little is known about whether body mass index (BMI) increases this risk. We examined the association between BMI and second cancers among women with incident invasive breast cancer.Methods: This retrospective cohort included 6481 patients from Kaiser Permanente Colorado and Washington of whom 822 (12.7%) developed a second cancer (mean follow-up was 88.0 months). BMI at the first cancer was extracted from the medical record. Outcomes included: 1) all second cancers, 2) obesity-related second cancers, 3) any second breast cancer, and 4) estrogen receptor-positive second breast cancers. Multivariable Poisson regression models were used to estimate relative risks (RRs) and 95% confidence intervals (CIs) for second cancers associated with BMI adjusted for site, diagnosis year, treatment, demographic, and tumor characteristics.Results: The mean age at initial breast cancer diagnosis was 61.2 (SD = 11.8) years. Most cases were overweight (33.4%) or obese (33.8%) and diagnosed at stage I (62.0%). In multivariable models, for every 5 kg/m2 increase in BMI, the risk of any second cancer diagnosis increased by 7% (RR = 1.07, 95% CI = 1.01 to 1.14); 13% (RR = 1.13, 95% CI = 1.05 to 1.21) for obesity-related cancers, 11% (RR = 1.11, 95% CI = 1.02 to 1.21) for a second breast cancer, and 15% (RR = 1.15, 95% CI = 1.04 to 1.27) for a second estrogen receptor-positive breast cancer.Conclusions: We observed a statistically significant increased risk of second cancers associated with increasing BMI. These findings have important public health implications given the prevalence of overweight and obesity in breast cancer survivors and underscore the need for effective prevention strategies. [ABSTRACT FROM AUTHOR]

BACKGROUND: Although combustible cigarette use is an established risk factor for severe COVID-19 disease, there is conflicting evidence for the association of electronic cigarette use with SARS-CoV-2 infection and COVID-19 disease severity. METHODS: Study participants were from the Kaiser Permanente Research Bank (KPRB), a biorepository that includes adult Kaiser Permanente members from across the United States. Starting in April 2020, electronic surveys were sent to KPRB members to assess the impact of the COVID-19 pandemic. These surveys collected information on self-report of SARS-CoV-2 infection and COVID-related risk factors, including electronic cigarette and combustible cigarette smoking history. We also used electronic health records data to assess COVID-19 diagnoses, positive PCR lab tests, hospitalizations, and death. We used multivariable Cox proportional hazards regression to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) comparing the risk of SARS-CoV-2 infection between individuals by e-cigarette use categories (never, former, and current). Among those with SARS-CoV-2 infection, we used multivariable logistic regression to estimate adjusted odds ratios (ORs) and 95% CIs comparing the odds of hospitalization or death within 30 days of infection between individuals by e-cigarette use categories. RESULTS: There were 126,475 individuals who responded to the survey and completed questions on e-cigarette and combustible cigarette use (48% response rate). Among survey respondents, 819 (1%) currently used e-cigarettes, 3,691 (3%) formerly used e-cigarettes, and 121,965 (96%) had never used e-cigarettes. After adjustment for demographic, behavioral, and clinical factors, there was no association with SARS-CoV-2 infection and former e-cigarette use (hazard ratio (HR) = 0.99; CI: 0.83–1.18) or current e-cigarette use (HR = 1.08; CI: 0.76–1.52). Among those with SARS-CoV-2 infection, there was no association with hospitalization or death within 30 days of infection and former e-cigarette use (odds ratio (OR) = 1.19; CI: 0.59–2.43) or current e-cigarette use (OR = 1.02; CI: 0.22–4.74). CONCLUSIONS: Our results suggest that e-cigarette use is not associated with an increased risk of SARS-CoV-2 infection or severe COVID-19 illness. [ABSTRACT FROM AUTHOR]

BACKGROUND: Although combustible cigarette use is an established risk factor for severe COVID-19 disease, there is conflicting evidence for the association of electronic cigarette use with SARS-CoV-2 infection and COVID-19 disease severity. METHODS: Study participants were from the Kaiser Permanente Research Bank (KPRB), a biorepository that includes adult Kaiser Permanente members from across the United States. Starting in April 2020, electronic surveys were sent to KPRB members to assess the impact of the COVID-19 pandemic. These surveys collected information on self-report of SARS-CoV-2 infection and COVID-related risk factors, including electronic cigarette and combustible cigarette smoking history. We also used electronic health records data to assess COVID-19 diagnoses, positive PCR lab tests, hospitalizations, and death. We used multivariable Cox proportional hazards regression to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) comparing the risk of SARS-CoV-2 infection between individuals by e-cigarette use categories (never, former, and current). Among those with SARS-CoV-2 infection, we used multivariable logistic regression to estimate adjusted odds ratios (ORs) and 95% CIs comparing the odds of hospitalization or death within 30 days of infection between individuals by e-cigarette use categories. RESULTS: There were 126,475 individuals who responded to the survey and completed questions on e-cigarette and combustible cigarette use (48% response rate). Among survey respondents, 819 (1%) currently used e-cigarettes, 3,691 (3%) formerly used e-cigarettes, and 121,965 (96%) had never used e-cigarettes. After adjustment for demographic, behavioral, and clinical factors, there was no association with SARS-CoV-2 infection and former e-cigarette use (hazard ratio (HR) = 0.99; CI: 0.83-1.18) or current e-cigarette use (HR = 1.08; CI: 0.76-1.52). Among those with SARS-CoV- 2 infection, there was no association with hospitalization or death within 30 days of infection and former e-cigarette use (odds ratio (OR) = 1.19; CI: 0.59-2.43) or current e-cigarette use (OR = 1.02; CI: 0.22-4.74). CONCLUSIONS: Our results suggest that e-cigarette use is not associated with an increased risk of SARS-CoV-2 infection or severe COVID-19 illness. [ABSTRACT FROM AUTHOR]

Background: Both hyperkalemia and hypokalemia can lead to cardiac arrhythmias and are associated with increased mortality. Information on the predictors of potassium in individuals with diabetes in routine clinical practice is lacking. Objective: To identify predictors of hyperkalemia and hypokalemia in adults with diabetes. Design: Retrospective cohort study, with classification and regression tree (CART) analysis. Participants: 321,856 individuals with diabetes enrolled in four large integrated health care systems from 2012 to 2013. Main Measures: We used a single serum potassium result collected in 2012 or 2013. Hyperkalemia was defined as a serum potassium ≥ 5.5 mEq/L and hypokalemia as < 3.5 mEq/L. Predictors included demographic factors, laboratory measurements, comorbidities, medication use, and health care utilization. Key Results: There were 2556 hypokalemia events (0.8%) and 1517 hyperkalemia events (0.5%). In univariate analyses, we identified concordant predictors (associated with increased probability of both hyperkalemia and hypokalemia), discordant predictors, and predictors of only hyperkalemia or hypokalemia. In CART models, the hyperkalemia "tree" had 5 nodes and a c-statistic of 0.76. The nodes were defined by prior potassium results and eGFRs, and the 5 terminal "leaves" had hyperkalemia probabilities of 0.2 to 7.2%. The hypokalemia tree had 4 nodes and a c-statistic of 0.76. The hypokalemia tree included nodes defined by prior potassium results, and the 4 terminal leaves had hypokalemia probabilities of 0.3 to 17.6%. Individuals with a recent potassium between 4.0 and 5.0 mEq/L, eGFR ≥ 45 mL/min/1.73m2, and no hypokalemia in the previous year had a < 1% rate of either hypokalemia or hyperkalemia. Conclusions: The yield of routine serum potassium testing may be low in individuals with a recent serum potassium between 4.0 and 5.0 mEq/L, eGFR ≥ 45 mL/min/1.73m2, and no recent history of hypokalemia. We did not examine the effect of recent changes in clinical condition or medications on acute potassium changes. [ABSTRACT FROM AUTHOR]

Background: As more states legalize cannabis for medical and recreational use, people increasingly use cannabis to treat medical conditions and associated symptoms. The prevalence and utility of cannabis for cancer-related symptoms may be clarified by examining cannabis use among patients with a common cancer diagnosis. We aimed to determine the prevalence of cannabis use among colorectal cancer (CRC) survivors and its associations with quality of life (QoL) and cancer-related symptomatology.Methods: A cross-sectional survey of patient-reported QoL outcomes and behaviors, including cannabis use, was conducted within the Patient Outcomes To Advance Learning network's (PORTAL) CRC Cohort. The cohort included a population-based sample of healthcare system members ≥18 years old diagnosed with adenocarcinoma of the colon or rectum from 2010 through 2016. We assessed the association between cannabis use and QoL using the European Organization for Research and Treatment of Cancer QLQ-C30 summary score.Results: Of the 1784 respondents, 293 (16.4%) reported cannabis use following CRC diagnosis. Current tobacco smokers were more likely to use cannabis compared to former or never tobacco smokers (adjusted odds ratio [aOR] 2.71, 95% confidence interval [CI] 1.56 to 4.70). Greater alcohol use (> 4 drinks per month versus ≤4 drinks per month) was associated with cannabis use (aOR 2.17, 95% CI 1.65 to 2.85). There was an association between cannabis use and cancer stage at diagnosis, with stage 3 or 4 CRC patients more likely to use cannabis than stage 1 or 2 CRC patients (aOR 1.68, 95% CI 1.25 to 2.25). After adjusting for demographics, medical comorbidities, stage and site of CRC diagnosis, and prescription opioid use, people who used cannabis had significantly lower QoL than people who did not use cannabis (difference of - 6.14, 95% CI - 8.07 to - 4.20).Conclusion: Among CRC survivors, cannabis use was relatively common, associated with more advanced stages of disease, associated with tobacco and alcohol use, and not associated with better QoL. Clinicians should inquire about cannabis use among their patients and provide evidence-based recommendations for cancer-related symptoms. [ABSTRACT FROM AUTHOR]

Purpose: Our objective was to describe differences in treatment patterns and survival between early-onset (< 50 years old) and late-onset colorectal cancer (CRC) patients in community-based health systems.Methods: We used tumor registry and electronic health record data to identify and characterize patients diagnosed with adenocarcinoma of the colon or rectum from 2010 to 2014 at six US health systems in the patient outcomes to advance learning (PORTAL) network. We used logistic regression to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) comparing the distribution of tumor characteristics and treatment patterns in early-onset versus late-onset CRC. Cox regression models were used to estimate adjusted hazard ratios (HRs) and CIs comparing survival between early- and late-onset CRC patients.Results: There were 1,424 early-onset and 10,810 late-onset CRC cases in our analyses. Compared to late-onset CRC, early-onset CRC was significantly associated with advanced-stage disease, high-grade histology, signet ring histology, and rectal or left colon location. After adjusting for differences in tumor and patient characteristics, early-onset patients were more likely than late-onset patients to have > 12 lymph nodes examined (OR 1.60, CI 1.37-1.87), to receive systemic therapy (chemotherapy or immunotherapy) within 6 months of diagnosis (OR 2.84, CI 2.40-3.37), and to have a reduced risk of CRC-specific death (HR 0.66, CI 0.56-0.79).Conclusions: Early-onset CRC is associated with aggressive tumor characteristics, distal location, and systemic therapy use. Despite some adverse risk factors, these patients tend to have better survival than older onset patients. [ABSTRACT FROM AUTHOR]

Objective: The goal of this study was to determine whether the reduction in cancer risk after bariatric surgery is due to weight loss.Methods: A retrospective matched cohort study of patients undergoing bariatric surgery was conducted using data from a large integrated health insurance and care delivery system with five sites in four states. The study included 18,355 bariatric surgery subjects and 40,524 nonsurgical subjects matched on age, sex, BMI, site, and Elixhauser comorbidity index. Multivariable Cox proportional hazards models examined the relationship between weight loss at 1 year and incident cancer during up to 10 years of follow-up.Results: The study identified 1,196 cases of incident cancer. The average 1-year postsurgical weight loss was 27% among patients undergoing bariatric surgery versus 1% in matched nonsurgical patients. Percent weight loss at 1 year was significantly associated with a reduced risk of any cancer in adjusted models (HR 0.897, 95% CI: 0.832-0.968, P = 0.005 for every 10% weight loss) while bariatric surgery was not a significant independent predictor of cancer incidence.Conclusions: Weight loss after bariatric surgery was associated with a lower risk of incident cancer. There was no apparent independent effect of the bariatric surgery itself on cancer risk that was independent of weight loss. [ABSTRACT FROM AUTHOR]

Purpose: The goal of this study was to determine response rates and associated costs of different survey methods among colorectal cancer (CRC) survivors.Methods: We assembled a cohort of 16,212 individuals diagnosed with CRC (2010-2014) from six health plans, and randomly selected 4000 survivors to test survey response rates across four mixed-mode survey administration protocols (in English and Spanish): arm 1, mailed survey with phone follow-up; arm 2, interactive voice response (IVR) followed by mail; arm 3; email linked to web-based survey with mail follow-up; and arm 4, email linked to web-based survey followed by IVR.Results: Our overall response rate was 50.2%. Arm 1 had the highest response rate (59.9%), followed by arm 3 (51.9%), arm 2 (51.2%), and arm 4 (37.9%). Response rates were higher among non-Hispanic whites in all arms than other racial/ethnic groups (p < 0.001), among English (51.5%) than Spanish speakers (36.4%) (p < 0.001), and among higher (53.7%) than lower (41.4%) socioeconomic status (p < 0.001). Survey arms were roughly comparable in cost, with a difference of only 8% of total costs between the most (arm 2) and least (arm 3) expensive arms.Conclusions: Mailed surveys followed by phone calls achieved the highest response rate; email invitations and online surveys cost less per response. Electronic methods, even among those with email availability, may miss important populations including Hispanics, non-English speakers, and those of lower socioeconomic status.Implications For Cancer Survivors: Our results demonstrate effective methods for capturing patient-reported outcomes, inform the relative benefits/disadvantages of the different methods, and identify future research directions. [ABSTRACT FROM AUTHOR]

Purpose: Identifying care needs for newly enrolled or newly insured individuals is important under the Affordable Care Act. Systematically collected patient-reported information can potentially identify subgroups with specific care needs prior to service use. Methods: We conducted a retrospective cohort investigation of 6,047 individuals who completed a 10-question needs assessment upon initial enrollment in Kaiser Permanente Colorado (KPCO), a not-for-profit integrated delivery system, through the Colorado State Individual Exchange. We used responses from the Brief Health Questionnaire (BHQ), to develop a predictive model for cost for receiving care in the top 25 percent, then applied cluster analytic techniques to identify different high-cost subpopulations. Per-member, per-month cost was measured from 6 to 12 months following BHQ response. Results: BHQ responses significantly predictive of high-cost care included self-reported health status, functional limitations, medication use, presence of 0-4 chronic conditions, self-reported emergency department (ED) use during the prior year, and lack of prior insurance. Age, gender, and deductible-based insurance product were also predictive.The largest possible range of predicted probabilities of being in the top 25 percent of cost was 3.5 percent to 96.4 percent. Within the top cost quartile, examples of potentially actionable clusters of patients included those with high morbidity, prior utilization, depression risk and financial constraints; those with high morbidity, previously uninsured individuals with few financial constraints; and relatively healthy, previously insured individuals with medication needs. Conclusions: Applying sequential predictive modeling and cluster analytic techniques to patient-reported information can identify subgroups of individuals within heterogeneous populations who may benefit from specific interventions to optimize initial care delivery. [ABSTRACT FROM AUTHOR]

The article presents information on a cohort study to evaluate health care utilization by both users and nonusers of online access to health records before and after initiation of the patient online access system MyHealthManager (MHM). The method includes an analysis of the use of health care services by the members of age more than 18 years who were continuously enrolled for at least 24 months in the Kaiser Permanente Medical Center, Denver, Colorado. According to the conclusion, online access to medical records was associated with increased use of clinical services.