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Disparities in access to percutaneous coronary intervention (PCI) for patients with acute myocardial infarction may result from openings and closures of PCI-providing hospitals, potentially leading to low hospital PCI volume, which is associated with poor outcomes. The authors sought to determine whether openings and closures of PCI hospitals have differentially impacted patient health outcomes in high- vs average-capacity PCI markets. In this retrospective cohort study, the authors identified PCI hospital availability within a 15-minute driving time of zip code communities. The authors categorized communities by baseline PCI capacity and identified changes in outcomes associated with PCI-providing hospital openings and closures using community fixed-effects regression models. From 2006 to 2017, 20% and 16% of patients in average- and high-capacity markets, respectively, experienced a PCI hospital opening within a 15-minute drive. In average-capacity markets, openings were associated with a 2.6 percentage point decrease in admission to a high-volume PCI facility; high-capacity markets saw an 11.6 percentage point decrease. After an opening, patients in average-capacity markets experienced a 5.5% and 7.6% relative increase in likelihood of same-day and in-hospital revascularization, respectively, as well as a 2.5% decrease in mortality. PCI hospital closures were associated with a 10.4% relative increase in admission to high-volume PCI hospitals and a 1.4 percentage point decrease in receipt of same-day PCI. There was no change observed in high-capacity PCI markets. After openings, patients in average-capacity markets derived significant benefits, whereas those in high-capacity markets did not. This suggests that past a certain threshold, facility opening does not improve access and health outcomes. [Display omitted] [ABSTRACT FROM AUTHOR]

The Surgical Treatment for Ischemic Heart Failure (STICH) trial found that routine use of coronary artery bypass surgery (CABG) improved mean quality of life (QoL) scores relative to guideline-directed medical therapy (GDMT) in patients with ischemic cardiomyopathy. However, mean differences in QoL scores do not provide what patients want to know when facing a high-risk/high-benefit treatment choice. We analyzed Kansas City Cardiomyopathy Questionnaire (KCCQ) Overall Summary scores in CABG and GDMT patients over 36 months using a combination of statistical methods to group QoL data into clinically relevant outcome patterns (phenotype trajectories) and to then identify the main baseline predictors of each phenotype. QoL outcome phenotypes were developed using mixture models to define the dominant phenotype trajectories present in STICH QoL data. Logistic regression models were used to predict each patient's probability of achieving each outcome pattern with each treatment. In STICH, 592 patients underwent CABG and 607 were managed with GDMT. Our analyses identified 3 phenotype trajectory patterns in both treatment groups. Two of the 3 trajectories showed improving patterns, and were classified as "good QoL trajectories," seen in 498 (84.1%) CABG and 449 (73.9%) GDMT patients. Defining a consequential CABG-GDMT treatment difference as a >10% higher absolute predicted probability of belonging to good QoL trajectories, 277 (23.5%) patients were more likely to have good outcome with CABG while 45 (3.8%) patients were more likely to have a good outcome with GDMT. For 644 (54.7%) patients, CABG and GDMT probabilities of a good outcome were within 5% of each other. The pattern of QoL outcomes after CABG compared with GDMT in STICH followed 3 main phenotypic trajectories, which could be predicted based on individual baseline features. Patient-specific predictions about expected QoL outcomes with different treatment choices provide an intuitive framework for personalizing patient decision making. [ABSTRACT FROM AUTHOR]

Objectives: The objectives of this study were to compare risk-standardized hospital visit ratios of the predicted to expected number of unplanned hospital visits within 7 days of same-day surgeries performed at US hospital outpatient departments (HOPDs) and to describe the causes of hospital visits. Summary of Background Data: More than half of procedures in the US are performed in outpatient settings, yet little is known about facility-level variation in short-term safety outcomes. Methods: The study cohort included 1,135,441 outpatient surgeries performed at 4058 hospitals between October 1, 2015 and September 30, 2016 among Medicare Fee-for-Service beneficiaries aged ≥65 years. Hospital-level, risk-standardized measure scores of unplanned hospital visits (emergency department visits, observation stays, and unplanned inpatient admissions) within 7 days of hospital outpatient surgery were calculated using hierarchical logistic regression modeling that adjusted for age, clinical comorbidities, and surgical procedural complexity. Results: Overall, 7.8% of hospital outpatient surgeries were followed by an unplanned hospital visit within 7 days. Many of the leading reasons for unplanned visits were for potentially preventable conditions, such as urinary retention, infection, and pain. We found considerable variation in the risk-standardized ratio score across hospitals. The 203 best-performing HOPDs, at or below the 5th percentile, had at least 22% fewer unplanned hospital visits than expected, whereas the 202 worst-performing HOPDs, at or above the 95th percentile, had at least 29% more post-surgical visits than expected, given their case and surgical procedure mix. Conclusions: Many patients experience an unplanned hospital visit within 7 days of hospital outpatient surgery, often for potentially preventable reasons. The observed variation in performance across hospitals suggests opportunities for quality improvement. [ABSTRACT FROM AUTHOR]

We are now on the cusp of massive adoption of digital health technologies. Medicine is becoming an information science intertwined with technology and data science. This talk aims to describe the current state of digital transformation in healthcare, to identify reasons for enthusiasm and caution, and to provide a framework for thinking about what is necessary for hospitals and health systems to be confident about incorporating these innovations into practice. I have three key recommendations. First, we should buy results, not claims. Those in positions that influence decisions about endorsing or purchasing digital products designed to improve care or outcomes ought to buy results, not claims or intermediate results. Moreover, although analytic validity and clinical validity are important, they sometimes do not reflect the impact of a product in its entirety. Ultimately, we need to know whether patients benefit. Second, we should insist on transparency. The performance of a product cannot be a secret. The basis on which developers make claims about their products should be open to all, including patients. Better yet, data on which experts reach a conclusion should be shared, just as many companies share research data on drugs and devices. Third, we should be aware of unintended adverse consequences. We should evaluate every intervention for unintended adverse consequences. Changes to systems, with all good intentions, can always go awry. In conclusion, insistence on good and evolving evidence is the best way to arrive at our destination: the use of innovations to improve outcomes. [ABSTRACT FROM AUTHOR]

Poor hypertension awareness and underuse of guideline-recommended medications are critical factors contributing to poor hypertension control. Using data from 8095 hypertensive people aged ≥18 years from the National Health and Nutrition Examination Survey (2011-2018), we examined recent trends in racial and ethnic differences in awareness and antihypertensive medication use, and their association with racial and ethnic differences in hypertension control. Between 2011 and 2018, age-adjusted hypertension awareness declined for Black, Hispanic, and White individuals, but the 3 outcomes increased or did not change for Asian individuals. Compared with White individuals, Black individuals had a similar awareness (odds ratio, 1.20 [0.96-1.45]) and overall treatment rates (1.04 [0.84-1.25]), and received more intensive antihypertensive medication if treated (1.41 [1.27-1.56]), but had a lower control rate (0.72 [0.61-0.83]). Asian and Hispanic individuals had significantly lower awareness rates (0.69 [0.52-0.85] and 0.74 [0.59-0.89]), overall treatment rates (0.72 [0.57-0.88] and 0.69 [0.55-0.82]), received less intensive medication if treated (0.60 [0.50-0.72] and 0.86 [0.75-0.96]), and had lower control rates (0.66 [0.54-0.79] and 0.69 [0.57-0.81]). The racial and ethnic differences in awareness, treatment, and control persisted over the study period and were consistent across age, sex, and income strata. Lower awareness and treatment were significantly associated with lower control in Asian and Hispanic individuals (P<0.01 for all) but not in Black individuals. These findings highlight the need for interventions to improve awareness and treatment among Asian and Hispanic individuals, and more investigation into the downstream factors that may contribute to the poor hypertension control among Black individuals. [ABSTRACT FROM AUTHOR]

The regionalization of care for ST elevation myocardial infarction (STEMI) may unintentionally concentrate patients with non-ST elevation myocardial infarction (NSTEMI) into percutaneous coronary intervention (PCI) capable hospitals. This could lead to benefits such as increased access to PCI-capable hospitals, but could cause harms such as crowding in some hospitals with decreased patient volume and revenue in others. We set out to assess whether STEMI regionalization programs concentrated patients with NSTEMI at STEMI-receiving hospitals. [ABSTRACT FROM AUTHOR]

Background: New methods such as machine learning techniques have been increasingly used to enhance the performance of risk predictions for clinical decision-making. However, commonly reported performance metrics may not be sufficient to capture the advantages of these newly proposed models for their adoption by health care professionals to improve care. Machine learning models often improve risk estimation for certain subpopulations that may be missed by these metrics.Methods and Results: This article addresses the limitations of commonly reported metrics for performance comparison and proposes additional metrics. Our discussions cover metrics related to overall performance, discrimination, calibration, resolution, reclassification, and model implementation. Models for predicting acute kidney injury after percutaneous coronary intervention are used to illustrate the use of these metrics.Conclusions: We demonstrate that commonly reported metrics may not have sufficient sensitivity to identify improvement of machine learning models and propose the use of a comprehensive list of performance metrics for reporting and comparing clinical risk prediction models. [ABSTRACT FROM AUTHOR]

Background: Slow uptake of sacubitril/valsartan in patients with heart failure with reduced ejection fraction has been reported, which may negatively impact clinical outcomes. We characterized prior authorization (PA) burden, prescription copayment, and utilization of sacubitril/valsartan by insurance plan type to identify potential barriers to its use.Methods: We conducted a national population-level, cross-sectional study using PA data from an insurance coverage website accessed in March 2019 and IQVIA National Prescription Audit data from August 2018 to July 2019. Primary outcomes were proportion of plans requiring PA, frequency of specific PA criteria, number of sacubitril/valsartan prescriptions, and copayments per insurance plan type.Results: Overall, 48.1% (1394/2896) of insurance plans required PA for sacubitril/valsartan. Fewer Medicare (27.7%) than commercial (57.2%) plans required PA (P<0.001). For both plan types, the most frequently required PA criteria were ejection fraction (71.6%, 90.9%) and New York Heart Association class (60.4%, 90.8%) for Medicare and commercial plans, respectively. Copayment amounts varied by plan type, with more sacubitril/valsartan prescriptions for commercial plans not requiring a patient copayment (32.4%) compared with Medicare plans (19.3%; P<0.001). There were 814 437 sacubitril/valsartan prescriptions for Medicare and 822 292 for commercial plans dispensed from August 2018 to July 2019. Based on estimated heart failure with reduced ejection fraction populations for each plan type, 4-fold more sacubitril/valsartan prescriptions were dispensed in commercial than in Medicare plans (820 versus 215 prescriptions/1000 individuals in the heart failure with reduced ejection fraction population). The estimated proportion of heart failure with reduced ejection fraction patients prescribed sacubitril/valsartan was 3.6% (1.5%-6.8%) for Medicare and 13.7% (4.9%-31.8%) for commercial plan populations.Conclusions: Despite commercial plans having greater PA requirements than Medicare, population-adjusted use of sacubitril/valsartan was higher in commercial plans. Given that commercial plans had more prescriptions with low copayments than Medicare, copayment policies may be more influential on sacubitril/valsartan use than its PA policies. Low sacubitril/valsartan use in both plan types highlights the multifactorial nature of medication underutilization that includes factors beyond the drug policies that we evaluated. [ABSTRACT FROM AUTHOR]

[Figure: see text]. [ABSTRACT FROM AUTHOR]

Background: Better understanding of recent sacubitril/valsartan prescription patterns may help identify factors that influence its use. The aim of the study was to characterize sacubitril/valsartan use and dosage patterns nationally.Methods and Results: We conducted a population-level cohort study using IQVIA Inc. National Prescription Audit™ data in the United States from August 2016 to July 2019. Over 3 years, there was a 5.6-fold increase in the number of sacubitril/valsartan prescriptions dispensed per month, totaling 3.3 million prescriptions. For the most recent year, this extrapolates to a best-case scenario of 13.8% of patients with heart failure with reduced ejection fraction using sacubitril/valsartan, representing at most one-half of those eligible for sacubitril/valsartan use. During the most recent year, 48.7% of dispensed prescriptions were for the lowest strength (24/26 mg) and only 20.6% for the target strength (97/103 mg). A greater proportion of the target strength was used in younger patients (< 65years: 24.6%; ≥ 85: 11.1%; P<0.0001). Cardiologists prescribed 59.0% of all dispensed prescriptions, and noncardiologists showed a greater increase (7.5-fold vs 4.9-fold; P<0.0001) over time.Conclusions: Recent use of sacubitril/valsartan has increased greatly in the United States; however, a substantial proportion of eligible patients with heart failure with reduced ejection fraction did not receive treatment, and only 1 in 5 prescriptions dispensed were for the target strength. Further exploration of barriers to the use of sacubitril/valsartan and dosing uptitration and their clinical implications warrant further evaluation. [ABSTRACT FROM AUTHOR]

Background: Rural communities face challenges in accessing healthcare services due to physician shortages and limited unscheduled care capabilities in office settings. As a result, rural hospital-based Emergency Departments (ED) may disproportionately provide acute, unscheduled care needs. We sought to examine differences in ED utilization and the relative role of the ED in providing access to unscheduled care between rural and urban communities.Methods: Using a 20% sample of the 2012 Medicare Chronic Condition Warehouse, we studied the overall ED visit rate and the unscheduled care rate by geography using the Dartmouth Atlas' hospital referral regions (HRR). We calculated HRR urbanicity as the proportion of beneficiaries residing in an urban zip code within each HRR. We report descriptive statistics and utilize K-means clustering based on the ED visit rates and unscheduled care rates.Results: We found rural ED use is more common and disproportionately the site of unscheduled care delivery when compared to urban communities. The ED visit and. unscheduled care proportions were negatively correlated with increased urbanicity (r =. -0.48, p < 0.001; r = -0.58, p < 0.001).Conclusion: The use and role of EDs by Medicare beneficiaries appears to be substantially different between urban and rural areas. This suggests that the ED may play a distinct role within the healthcare delivery system of rural communities that face disproportionate barriers to care access. [ABSTRACT FROM AUTHOR]

Background: Intraoperative data may improve models predicting postoperative events. We evaluated the effect of incorporating intraoperative variables to the existing preoperative model on the predictive performance of the model for coronary artery bypass graft.Methods: We analyzed 378 572 isolated coronary artery bypass graft cases performed across 1083 centers, using the national Society of Thoracic Surgeons Adult Cardiac Surgery Database between 2014 and 2016. Outcomes were operative mortality, 5 postoperative complications, and composite representation of all events. We fitted models by logistic regression or extreme gradient boosting (XGBoost). For each modeling approach, we used preoperative only, intraoperative only, or pre+intraoperative variables. We developed 84 models with unique combinations of the 3 variable sets, 2 variable selection methods, 2 modeling approaches, and 7 outcomes. Each model was tested in 20 iterations of 70:30 stratified random splitting into development/testing samples. Model performances were evaluated on the testing dataset using the C statistic, area under the precision-recall curve, and calibration metrics, including the Brier score.Results: The mean patient age was 65.3 years, and 24.7% were women. Operative mortality, excluding intraoperative death, occurred in 1.9%. In all outcomes, models that considered pre+intraoperative variables demonstrated significantly improved Brier score and area under the precision-recall curve compared with models considering pre or intraoperative variables alone. XGBoost without external variable selection had the best C statistics, Brier score, and area under the precision-recall curve values in 4 of the 7 outcomes (mortality, renal failure, prolonged ventilation, and composite) compared with logistic regression models with or without variable selection. Based on the calibration plots, risk restratification for mortality showed that the logistic regression model underestimated the risk in 11 114 patients (9.8%) and overestimated in 12 005 patients (10.6%). In contrast, the XGBoost model underestimated the risk in 7218 patients (6.4%) and overestimated in 0 patients (0%).Conclusions: In isolated coronary artery bypass graft, adding intraoperative variables to preoperative variables resulted in improved predictions of all 7 outcomes. Risk models based on XGBoost may provide a better prediction of adverse events to guide clinical care. [ABSTRACT FROM AUTHOR]

Background: China has seen a burgeoning epidemic of obesity in recent decades, but few studies reported nationally on obesity across socio-demographic subgroups. We sought to assess the prevalence and socio-demographic associations of obesity nationwide.Methods: We assessed the prevalence of overall obesity (body mass index ≥28 kg/m2) and abdominal obesity (waist circumference ≥85/90 cm for women/men) among 2.7 million community-dwelling adults aged 35 to 75 years in the China PEACE Million Persons Project from 2014 to 2018 and quantified the socio-demographic associations of obesity using multivariable mixed models.Results: Age-standardized rates of overall and abdominal obesity were 14.4% (95% CI, 14.3%-14.4%) and 32.7% (32.6%-32.8%) in women and 16.0% (15.9%-16.1%) and 36.6% (36.5%-36.8%) in men. Obesity varied considerably across socio-demographic subgroups. Older women were at higher risk for obesity (eg, adjusted relative risk [95% CI] of women aged 65-75 versus 35-44 years: 1.29 [1.27-1.31] for overall obesity, 1.76 [1.74-1.77] for abdominal obesity) while older men were not. Higher education was associated with lower risk in women (eg, adjusted relative risk [95% CI] of those with college or university education versus below primary school: 0.47 [0.46-0.48] for overall obesity, 0.61 [0.60-0.62] for abdominal obesity) but higher risk in men (1.07 [1.05-1.10], 1.17 [1.16-1.19]).Conclusions: In China, over 1 in 7 individuals meet criteria for overall obesity, and 1 in 3 for abdominal obesity. Wide variation exists across socio-demographic subgroups. The associations of age and education with obesity are significant and differ by sex. Understanding obesity in contemporary China has broad domestic policy implications and provides a valuable international reference. [ABSTRACT FROM AUTHOR]

[Figure: see text]. [ABSTRACT FROM AUTHOR]

BACKGROUND: Quasi-experimental methods (QEMs) are a family of techniques used to estimate causal relationships when randomized controlled trials are unfeasible or unethical. They offer a powerful alternative to observational studies by introducing random assignment of individuals or groups into their design, thereby offering stronger means of establishing causation. The use of QEMs in cardiovascular research has not been systematically examined to determine steps toward improving and expanding their use. METHODS: We identified 4 main techniques using a systematic search strategy from 2016 to 2021: instrumental variable analysis, interrupted time series analysis, difference-in-differences analysis, and regression discontinuity designs. QEMs are examined as alternatives to randomized controlled trials and traditional observational studies; as more observational data becomes available to researchers, there are more opportunities to apply these techniques. Eligible articles were selected based on publication in high-ranked journals. The quality of eligible articles was appraised using the Joanna Briggs Institute checklist for quasi-experimental studies. RESULTS: Data from 380 studies were extracted based on our inclusion criteria. Forty-two of these studies were published in the top 10 medical or top 20 cardiovascular disease journals, and 25 studies were included after quality appraisal. The review identifies the main features and limitations associated with each technique, providing readers with practical guidance on how to apply these to their research. A graphical decision aid was developed to facilitate the routine use of QEMs. CONCLUSIONS: The use of QEMs in cardiovascular research published in contemporary, high-impact articles was examined. Findings are biased toward this segment of literature, which represents the latest developments in this growing area of cardiovascular research. The decision aid is a novel schematic that researchers can adopt into practice. [ABSTRACT FROM AUTHOR]

Functional status and health-related quality of life (HRQoL) are important outcomes, particularly among older patients. However, data on such patient-centered outcomes after cardiac surgery are limited. We evaluated the incidence and predictors of decline in functional status and HRQoL among older patients hospitalized for acute myocardial infarction (AMI). Participants were age 75 years or older hospitalized for AMI at 94 US sites. We examined decline in functional status (defined as decline in 1 or more activities of daily living, ADLs), as well as mental (MCS) and physical component scales (PCS) of the SF-12 to assess HRQoL (5-point decline or greater in each scale) between 1 month prior to the hospitalization and 6 months after. Multivariable model compared the risk of decline after coronary artery bypass graft (CABG), percutaneous coronary intervention (PCI) and medical management. Among 3041 patients (1708 PCI, 362 CABG, and 971 medical management), 1525 (50.2%) experienced decline in 1 or more domain: 633 (20.8%) declined in ADLs, 786 (25.9%) declined in the MCS, and 1078 (35.5%) declined in the PCS. The unadjusted incidence of ADL decline was the lowest among patients who underwent CABG (n = 50, 13.8%) compared with PCI (n = 271, 15.9%) or medical management (n = 312, 32.1%). Patients who underwent CABG and PCI had lower adjusted risk of decline in functional and HRQoL compared with those who received medical therapy. The risks after CABG and PCI were not significantly different. Over half of older patients significantly declined in function or HRQoL after AMI. Compared with medical management, risk of decline was lower in those who underwent revascularization. [ABSTRACT FROM AUTHOR]

Background: Coronary artery bypass graft (CABG) surgery is a focus of bundled and alternate payment models that capture outcomes up to 90 days postsurgery. While clinical registry risk models perform well, measures encompassing mortality beyond 30 days do not currently exist. We aimed to develop a risk-adjusted hospital-level 90-day all-cause mortality measure intended for assessing hospital performance in payment models of CABG surgery using administrative data.Methods: Building upon Centers for Medicare and Medicaid Services hospital-level 30-day all-cause CABG mortality measure specifications, we extended the mortality timeframe to 90 days after surgery and developed a new hierarchical logistic regression model to calculate hospital risk-standardized 90-day all-cause mortality rates for patients hospitalized for isolated CABG. The model was derived from Medicare claims data for a 3-year cohort between July 2014 to June 2017. The data set was randomly split into 50:50 development and validation samples. The model performance was evaluated with C statistics, overfitting indices, and calibration plot. The empirical validity of the measure result at the hospital level was evaluated against the Society of Thoracic Surgeons composite star rating.Results: Among 137 819 CABG procedures performed in 1183 hospitals, the unadjusted mortality rate within 30 and 90 days were 3.1% and 4.7%, respectively. The final model included 27 variables. Hospital-level 90-day risk-standardized mortality rates ranged between 2.04% and 11.26%, with a median of 4.67%. C statistics in the development and validation samples were 0.766 and 0.772, respectively. We identified a strong positive correlation between 30- and 90-day risk-standardized mortality rates, with a regression slope of 1.09. Risk-standardized mortality rates also showed a stepwise trend of lower 90-day mortality with higher Society of Thoracic Surgeons composite star ratings.Conclusions: We present a measure of hospital-level 90-day risk-standardized mortality rates following isolated CABG. This measure complements Centers for Medicare and Medicaid Services' existing 30-day CABG mortality measure by providing greater insight into the postacute recovery period. It offers a balancing measure to ensure efforts to reduce costs associated with CABG recovery and rehabilitation do not result in unintended consequences. [ABSTRACT FROM AUTHOR]

This study sought to evaluate the association and burden of coronary artery calcium (CAC) with long-term, cause-specific mortality across the spectrum of baseline risk. Although CAC is a known predictor of short-term, all-cause mortality, data on long-term and cause-specific mortality are inadequate. The CAC Consortium cohort is a multicenter cohort of 66,636 participants without coronary heart disease (CHD) who underwent CAC testing. The following risk factors (RFs) were considered: 1) current cigarette smoking; 2) dyslipidemia; 3) diabetes mellitus; 4) hypertension; and 5) family history of CHD. During the 12.5-years median follow-up, 3,158 (4.7%) deaths occurred; 32% were cardiovascular disease (CVD) deaths. Participants with CAC scores ≥400 had a significantly increased risk for CHD and CVD mortality (hazard ratio [HR]: 5.44; 95% confidence interval [CI]: 3.88 to 7.62; and HR: 4.15; 95% CI: 3.29 to 5.22, respectively) compared with CAC of 0. Participants with ≥3 RFs had a smaller increased risk for CHD and CVD mortality (HR: 2.09; 95% CI: 1.52 to 2.85; and HR: 1.84; 95% CI: 1.46 to 2.31, respectively) compared with those without RFs. Across RF strata, CAC added prognostic information. For example, participants without RFs but with CAC ≥400 had significantly higher all-cause, non-CVD, CVD, and CHD mortality rates compared with participants with ≥3 RFs and CAC of 0. Across the spectrum of RF burden, a higher CAC score was strongly associated with long-term, all-cause mortality and a greater proportion of deaths due to CVD and CHD. Absence of CAC identified people with a low risk over 12 years of follow-up, with most deaths being non-CVD in nature, regardless of RF burden. [ABSTRACT FROM AUTHOR]