Chamberlain, Alanna M.

PURPOSE: Gender disparity persists in academic medicine. Female faculty are underrepresented in leadership positions and have lower research output. We studied gender differences in faculty rank and departmental leadership and contributing factors among academic hematologists and oncologists in the United States. METHODS: For clinical faculty at 146 hematology or oncology fellowship programs listed in the Fellowship and Residency Electronic Interactive Database, we collected data on demographics, academic rank, and research output using the Doximity and Scopus databases. We compared unadjusted characteristics of men and women by using 2-sided t tests and χ2 tests where appropriate. To predict probability of full professorship or leadership position among men versus women, we performed multivariable logistic regression analysis adjusted for clinical experience in years, number of publications, h-index, clinical trial investigator status, National Institutes of Health funding, and workplace ranking (top 20 v not). RESULTS: Two thousand one hundred sixty academic hematologists and oncologists were included. Women composed 21.9% (n = 142) of full professors, 35.7% (n = 169) of associate professors, and 45.4% (n = 415) of assistant professors. Thirty percent (n = 70) of departmental leaders were women. Female faculty, compared with male faculty, had a lower mean h-index (12.1 v 20.9, respectively; P < .001) and fewer years of professional experience since fellowship (10 v 16 years, respectively; P < .001). After adjusting for duration of clinical experience, academic productivity, and workplace ranking, the odds of obtaining professorship (odds ratio [OR], 1.05; 95% CI, 0.71 to 1.57; P = .85) or divisional leadership (OR, 0.57; 95% CI, 0.20 to 1.58; P = .28) for female physicians were not different compared with male physicians. CONCLUSION: Gender disparity exists in senior ranks of academic hematology and oncology; however, gender is not a significant predictor in achieving professorship or department leadership position.

Introduction: We have previously reported underrepresentation of female faculty at senior academic ranks in hematology/oncology (H/O). In this analysis we aimed to investigate the influence of sex in attaining leadership positions amongst academic hematologists/oncologists in United States. Methods: Faculty members were identified at 146 H/O fellowship programs listed on fellowship and residency electronic interactive database (FREIDA.) Data was collected on demographics, academic rank and research output using Doximity and Scopus databases. We compared the unadjusted characteristics of men and women by using two-sided t-tests and χ2 tests where appropriate. In primary analysis, logistic regression models were used to evaluate sex differences on probability of having full professorship (versus assistant and associate professorship) and of achieving leadership positions including division chief, Program Director (PD) and Associate Program Director (APD). Adjusted models included the following variables: clinical experience in years, number of publications, h-index, appointment at top 20 hospital, clinical trial investigator status and National Institutes of Health funding. Stratified analysis was performed adjusting for duration of clinical experience (≤15 vs >15 years) Results: Fewer women were full Professors (21.9% vs 78.1%), division chiefs (16.7% vs 83.3%), and PDs (30.5% vs 69.5) but the number was similar for Associate Program Directors (47.1% vs 52.9%). In a univariate unadjusted model, women were less likely to be full professors compared to men (OR 0.39; 95% confidence interval [CI], 0.31-0.48; P<.001). However, in the multivariable adjusted model no statistically significant sex difference in full professorship was found (OR 1.05; 95% CI 0.71, 1.57; P=.85; Table). The likelihood of full professorship was positively associated with clinical experience in years, number of first/last author publications, h-index, and being a primary investigator on at least one clinical trial.In a univariate unadjusted model, women were less likely to be division chiefs as compared to males (OR 0.35; 95% CI, 0.16, 0.80; P=.01). However, in the multivariable adjusted model, there was no statistically significant sex difference in achieving the position of division chief (OR 0.57; 95% CI 0.20, 1.58; P=.28; Table). No significant difference was found between females and males for being program directors or associate program directors in both univariate and multivariate analysis. Similarly, a stratified analysis adjusting for duration of clinical experience (≤15 vs >15 years) found no significant sex differences in attaining leadership position (Table) Conclusion: We found that women are underrepresented at higher academic ranks and in leadership positions in hematology/oncology, but that sex is not a significant negative predictor to women obtaining leadership positions after correcting for traditional predictors of academic success. However, "non-traditional" and therefore less measurable and analyzable factors such as networking, mentorship, sponsorship, gender bias, balancing work and home responsibilities and many others may contribute and should be further investigated. Disclosures No relevant conflicts of interest to declare.

AbstractIntroductionMyocardial infarction (MI) is associated with an increase in subsequent heart failure (HF), recurrent ischemic events, sudden cardiac arrest, and ventricular arrhythmias (SCA‐VA). The primary objective of the study to determine the role of intercurrent HF and ischemic events on the development of SCA‐VA following first type I MI.Methods and resultsA retrospective cohort study of patients experiencing first type 1 MI in Olmsted County, Minnesota (2002‐2012) was conducted by identifying patients using the medical records linkage system (Rochester epidemiology project). Patients aged ≥18 years were followed from the time of MI till death or 31 July, 2017. Intercurrent HF and ischemic events were the primary exposures following MI and their association with outcome SCA‐VA was assessed. Eight hundred and sixty‐seven patients (mean age was 63 ± 14.5 years; 69% male; 49.8% ST‐elevation myocardial infarction) who had their first type I MI during the study period were included. Majority of acute MI patients were revascularized using percutaneous coronary intervention and bypass surgery (628 [72.43%] and 87 [10.03%] respectively). During a mean follow‐up of 7.69 ± 4.17 years, HF, recurrent ischemic events and SCA‐VA occurred in 155 (17.9%), 245 (28.3%), and 40 (4.61%) patients respectively. Low ejection fraction (adjusted hazard ratio [HR] 0.95; 95% confidence interval [CI], 0.93‐0.98; P < .001), intercurrent HF (adjusted HR 3.11; 95% CI, 1.39‐6.95; P = .006) and recurrent ischemic events (adjusted HR 3.47; 95% CI, 1.68‐7.18; P < .001) were associated with subsequent SCA‐VA.ConclusionSCA‐VA occurred in a small proportion of patients after MI and is associated with intercurrent HF and recurrent ischemic events.

Objective: To understand the interaction of multimorbidity and functional limitations in determining health-care utilization and survival in older adults. Methods: Olmsted County, Minnesota, residents aged 60–89 years in 2005 were categorized into four cohorts based on the presence or absence of multimorbidity (≥3 chronic conditions from a list of 18) and functional limitations (≥1 limitation in an activity of daily living from a list of 9), and were followed through December 31, 2016. Andersen–Gill and Cox regression estimated hazard ratios (HRs) for emergency department (ED) visits, hospitalizations, and death using persons with neither multimorbidity nor functional limitations as the reference (interaction analyses). Results: Among 13,145 persons, 34% had neither multimorbidity nor functional limitations, 44% had multimorbidity only, 4% had functional limitations only, and 18% had both. Over a median follow-up of 11 years, 5906 ED visits, 2654 hospitalizations, and 4559 deaths occurred. Synergistic interactions on an additive scale of multimorbidity and functional limitations were observed for all outcomes; however, the magnitude of the interactions decreased with advancing age. The HR (95% confidence interval) for death among persons with both multimorbidity and functional limitations was 5.34 (4.40–6.47) at age 60–69, 4.16 (3.59–4.83) at age 70–79, and 2.86 (2.45–3.35) at age 80–89 years. Conclusion: The risk of ED visits, hospitalizations, and death among persons with both multimorbidity and functional limitations is greater than additive. The magnitude of the interaction was strongest for the youngest age group, highlighting the importance of interventions to prevent and effectively manage multimorbidity and functional limitations early in life.

Background: New technology and healthcare delivery approaches may help improve blood pressure (BP) control. Randomized controlled trials (RCTs) can demonstrate effectiveness of these emerging approaches, both overall and especially within underserved populations, but RCTs are expensive. Our objective is to establish a national platform to support BP control surveillance and efficient RCTs. Methods: The PCORnet BP Control Laboratory, designed and launched in partnership with the American Heart Association (AHA) and the American Medical Association (AMA), leverages electronic health record (EHR) systems throughout the US, the National Patient-Centered Outcomes Research Network (PCORnet), and the NIH-funded Eureka Research Platform, which enables direct-to-participant research including collection of patient-reported outcomes and mHealth data from wearable devices and smartphones. We will use these resources to 1) Conduct national surveillance through quarterly EHR data queries to calculate and track institution- and clinic-level BP control metrics across 23 PCORnet institutions, overall and within key subgroups, and support participation in the AHA/AMA’s Target:BP recognition program (BP Track); 2) Compare effectiveness of a Full Support versus Self-Guided version of the AMA’s Measure Accurately, Act Rapidly, and Partner with Patients (MAP) program at improving BP control in a cluster randomized trial of 24 safety net clinics (BP MAP); and 3) Compare effectiveness of Smartphone-linked versus standard home BP monitoring at reducing systolic BP in an individual-level, direct-to-participant RCT of 2000 patients with uncontrolled BP (BP Home). Results: Preliminary BP Track queries demonstrate an overall BP control rate of 56%, lower control in Black patients (51%), substantial heterogeneity in clinic-level metrics (e.g., 33% vs. 64% BP control), and low rates of medication intensification (9% prescribed a new medication class when BP was high). BP Track will launch PCORnet-wide queries in June; BP MAP in May; and BP Home in August 2019. Conclusions: Feasibility testing is underway to determine if the PCORnet BP Control Laboratory will be useful for investigators interested in conducting efficient RCTs of BP control interventions.

Background PCSK9 (proprotein convertase subtilisin/kexin type 9) inhibitors effectively lower LDL (low‐density lipoprotein) cholesterol and have been shown to reduce cardiovascular outcomes in high‐risk patients. We used real‐world electronic health record data to characterize use of PCSK9 inhibitors, in addition to standard therapies, according to cardiovascular risk status. Methods and Results Data were obtained from 18 health systems with data marts within the National Patient‐Centered Clinical Research Network (PCORnet) using a common data model. Participating sites identified >17.5 million adults, of whom 3.6 million met study criteria. Patients were categorized into 3 groups: (1) dyslipidemia, (2) untreated LDL ≥130 mg/dL, and (3) coronary artery disease or coronary heart disease. Demographics, comorbidities, estimated 10‐year atherosclerotic cardiovascular disease risk, and lipid‐lowering pharmacotherapies were summarized for each group. Participants’ average age was 62 years, 50% were female, and 11% were black. LDL cholesterol ranged from 85 to 151 mg/dL. Among patients in groups 1 and 3, 54% received standard lipid‐lowering therapies and a PCSK9 inhibitor was prescribed in <1%. PCSK9 inhibitor prescribing was greatest for patients with coronary artery disease or coronary heart disease and, although prescribing increased during the study period, overall PCSK9 inhibitor prescribing was low. Conclusions We successfully used electronic health record data from 18 PCORnet data marts to identify >3.6 million patients meeting criteria for 3 patient groups. Approximately half of patients had been prescribed lipid‐lowering medication, but <1% were prescribed PCSK9 inhibitors. PCSK9 inhibitor prescribing increased over time for patients with coronary artery disease or coronary heart disease but not for those with dyslipidemia.

Background: Patient reported measures are fundamental to patient centered research and are often collected by questionnaires. Low participation can compromise the validity of the results; transparent reporting and comparing characteristics of participants to nonparticipants is important to assess the generalizability of survey results. We analyzed participation in a survey of social determinants of health among a population-based sample of patients with heart failure (HF). Methods: A total of 7920 residents from 11 Minnesota counties were identified with a first-ever code for HF (ICD-9 428 and ICD-10 I50) between 1/1/2013 and 12/31/2016. Participants completed a battery of 12 questionnaires by mail or telephone. Characteristics and outcomes data were extracted from medical records and compared between participants and nonparticipants. Response rate (RR) was calculated using guidelines of the American Association for Public Opinion Research (AAPOR). The association between nonparticipation and outcomes was examined by Cox proportional hazards regression for death and Andersen-Gill modeling for hospitalizations. Results: Among 7920 patients, 3438 responded to the survey (AAPOR RR#2= 43%). Numerous clinical and demographic differences between participants and non-participants were noted (Table), particularly for education, marital status, and neuropsychiatric conditions. After a mean (±SD) of 1.5±1 years after survey administration, 1,577 deaths and 5,873 hospitalizations had occurred. Nonparticipation was associated with a two-fold increased risk of death (HR: 2.30; 95% CI: 2.06-2.57; p<0.001) and a 10% increased risk of hospitalizations (HR: 1.10; 95% CI: 1.01-1.21; p=0.03) after adjusting for age, sex, marital status, coronary disease, arrhythmia, hyperlipidemia, cancer, chronic kidney disease, depression and anxiety. Conclusions: In a large survey of patients with HF, participation was associated with large differences in clinical and demographic characteristics and outcomes. Examining the impact of participation is critical to draw inference from studies of patient reported measures.

Background: The decline in cardiovascular disease (CVD) mortality in the United States noted since the mid 1970s has recently leveled off. This has generated concern and a need for further analyses to understand geographic variation, cause-specific deaths, location of death, and age-specific trends. Methods: Death certificate data obtained from the Minnesota Department of Health were used for analysis. The American Heart Association (AHA) classification was applied to the underlying cause of death to generate the following CVD categories: coronary heart disease (CHD), non-CHD diseases of the heart, and non-cardiac circulatory diseases. Temporal trends in death rates were explored by negative binomial regression, which enables estimates of age- and sex-adjusted average annual percentage changes (AAPCs). Differences in AAPCs between 2000-2009 and 2010-2017 were tested overall and across demographic, CVD, and location of death categories. Results: CVD mortality rates, which were declining in 2000-2009, have leveled off in 2010-2017 (Table). These trends were observed across all subgroups. After adjusting for sex, the age group that drove the decline in rates from 2000-2009 was the 65-84 year old group, which experienced no change in rates from 2010-2017. Across CVD categories, after adjusting for age and sex, the decline in rates from 2000-2009 was largely attributable to steep reductions in CHD and non-cardiac circulatory diseases, with lesser reduction in non-CHD diseases of the heart. In 2010-2017, CHD and non-cardiac circulatory diseases rates showed no change, whereas the rate of non-CHD diseases of the heart increased. The rates for in- and out-of-hospital deaths improved in 2000-2009 with no further improvement observed in 2010-2017. Conclusions: CVD mortality rates are no longer declining in Minnesota, paralleling national trends. These trends are particularly concerning for non-CHD diseases of the heart.

Background: Previous studies have indicated that living in a rural or non-urban area may be associated with poor health outcomes. However, data on rurality and death in heart failure (HF) are scarce. Methods: Residents from 11 southeast MN counties with a first-ever code for HF (including codes ICD-9 428 and ICD-10 I50) between 1/1/2013 and 12/31/2016 were identified. Resident address was geo-coded and classified according to the Rural-Urban Commuting Area (RUCA) codes, which classifies US census tracts to measure population density, urbanization and daily commuting. Rurality was defined as living in a non-metropolitan area. Cox proportional hazards regression was used to determine the association between living in a rural vs. urban area and death. Results: Among 6,996 patients (mean age 73 years, 52% male), 54% of patients lived in a rural area. These patients were older and had a lower level of educational attainment and comorbidity burden (p<0.001). After a mean (SD) follow-up of 2.9 (1.3) years, 1,856 deaths occurred. Living in a rural area was univariately associated with a higher risk of death (HR 1.20, 95% CI: 1.09-1.31; Table). After adjustment for age, sex, education status and comorbidity burden, rurality remained associated with an increased risk of death (HR 1.15; 95% CI: 1.04-1.27). Conclusions: Among patients with HF, living in a rural area is associated with an increased risk of death. Further study to identify and address the mechanisms through which rural residence influences mortality in patients with HF is needed.

Introduction: The prevalence of atrial fibrillation (AF) and multimorbidity increase with age; however, the burden imposed by concurrent conditions on outcomes is unknown. Therefore, we aimed to determine the effect of the number and type of comorbid conditions on outcomes in elderly individuals with incident AF. Methods: Patients with non-valvular AF 75 years and older were identified in the MarketScan Medicare Supplemental database from 2007-2015. Fourteen chronic conditions, defined by two occurrences of a diagnostic code from inpatient and outpatient claims prior to or at the time of AF diagnosis, were obtained and classified into two categories: cardiovascular (CV) or non-CV (listed in Table footnote). We used Cox regression to estimate the associations of the number and type of conditions with stroke, severe bleeding, and heart failure hospitalizations (HF). Results: Among 275,617 patients with AF (mean age 83 years, 51% women), 90% had at least one or more additional chronic conditions. The mean (SD) number of conditions per participant was 1.8 (0.9) for CV conditions and 2.1 (1.2) for non-CV conditions. Over a mean follow-up of 23 months, 7,814 strokes, 13,622 severe bleeds, and 19,252 HF events occurred. After adjustment for age, sex, the number of conditions in the other comorbidity group, an increase of one CV condition was associated with greater risk of stroke, severe bleeding, and HF (Table). In contrast, an increase in one non-CV condition was associated with a lower risk of stroke, and a small increase in bleeding and HF risk (Table). After further adjustments for frailty and medications, the strength of the associations within each group decreased across outcomes. Conclusion: CV conditions in AF patients 75 years and older are more strongly associated with stroke, HF, and bleeding than non-CV conditions. This underscores the effect of CV conditions on CV outcomes in a population in which multimorbidity is most common and health care management and delivery is complex.