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Background: Medication adherence is generally low and challenging to address because patient actions control healthcare delivery outside of medical environments. Behavioral nudging changes clinician behavior, but nudging patient decision-making requires further testing. This trial evaluated whether behavioral nudges can increase statin adherence, measured as the proportion of days covered (PDC)., Methods: In a 12-month parallel-group, unblinded, randomized controlled trial, adult patients in Intermountain Healthcare cardiology clinics were enrolled. Inclusion required an indication for statins and membership in SelectHealth insurance. Subjects were randomized 1:1 to control or nudges. Nudge content, timing, frequency, and delivery route were personalized by CareCentra using machine learning of subject motivations and abilities from psychographic assessment, demographics, social determinants, and the Intermountain Mortality Risk Score. PDC calculation used SelectHealth claims data., Results: Among 182 subjects, age averaged 63.2±8.5 years, 25.8% were female, baseline LDL-C was 82.5±32.7 mg/dL, and 93.4% had coronary disease. Characteristics were balanced between nudge (n = 89) and control arms (n = 93). The statin PDC was greater at 12 months in the nudge group (PDC: 0.742±0.318) compared to controls (PDC: 0.639±0.358, P = 0.042). Adherent subjects (PDC ≥80%) were more concentrated in the nudge group (66.3% vs controls: 50.5%, P = 0.036) while a composite of death, myocardial infarction, stroke, and revascularization was non-significant (nudges: 6.7% vs control: 10.8%, P = 0.44)., Conclusions: Persuasive behavioral nudges driven by artificial intelligence resulted in a clinically important increase in statin adherence in general cardiology patients. This precision patient decision support utilized computerized nudge design and delivery with minimal on-going human input., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: Using augmented intelligence clinical decision tools and a risk score-guided multidisciplinary team-based care process (MTCP), this study evaluated the MTCP for heart failure (HF) patients' 30-day readmission and 30-day mortality across 20 Intermountain Healthcare hospitals., Background: HF inpatient care and 30-day post-discharge management require quality improvement to impact patient health, optimize utilization, and avoid readmissions., Methods: HF inpatients (N = 6182) were studied from January 2013 to November 2016. In February 2014, patients began receiving care via the MTCP based on a phased implementation in which the 8 largest Intermountain hospitals (accounting for 89.8% of HF inpatients) were crossed over sequentially in a stepped manner from control to MTCP over 2.5 years. After implementation, patient risk scores were calculated within 24 hours of admission and delivered electronically to clinicians. High-risk patients received MTCP care (n = 1221), while lower-risk patients received standard HF care (n = 1220). Controls had their readmission and mortality scores calculated retrospectively (high risk: n = 1791; lower risk: n = 1950)., Results: High-risk MTCP recipients had 21% lower 30-day readmission compared to high-risk controls (adjusted P = .013, HR = 0.79, CI = 0.66, 0.95) and 52% lower 30-day mortality (adjusted P < .001, HR = 0.48, CI = 0.33, 0.69). Lower-risk patients did not experience increased readmission (adjusted HR = 0.88, P = .19) or mortality (adjusted HR = 0.88, P = .61). Some utilization was higher, such as prescription of home health, for MTCP recipients, with no changes in length of stay or overall costs., Conclusions: A risk score-guided MTCP was associated with lower 30-day readmission and 30-day mortality in high-risk HF inpatients. Further evaluation of this clinical management approach is required., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Improving 30-day readmission continues to be problematic for most hospitals. This study reports the creation and validation of sex-specific inpatient (i) heart failure (HF) risk scores using electronic data from the beginning of inpatient care for effective and efficient prediction of 30-day readmission risk., Methods: HF patients hospitalized at Intermountain Healthcare from 2005 to 2012 (derivation: n=6079; validation: n=2663) and Baylor Scott & White Health (North Region) from 2005 to 2013 (validation: n=5162) were studied. Sex-specific iHF scores were derived to predict post-hospitalization 30-day readmission using common HF laboratory measures and age. Risk scores adding social, morbidity, and treatment factors were also evaluated., Results: The iHF model for females utilized potassium, bicarbonate, blood urea nitrogen, red blood cell count, white blood cell count, and mean corpuscular hemoglobin concentration; for males, components were B-type natriuretic peptide, sodium, creatinine, hematocrit, red cell distribution width, and mean platelet volume. Among females, odds ratios (OR) were OR=1.99 for iHF tertile 3 vs. 1 (95% confidence interval [CI]=1.28, 3.08) for Intermountain validation (P-trend across tertiles=0.002) and OR=1.29 (CI=1.01, 1.66) for Baylor patients (P-trend=0.049). Among males, iHF had OR=1.95 (CI=1.33, 2.85) for tertile 3 vs. 1 in Intermountain (P-trend <0.001) and OR=2.03 (CI=1.52, 2.71) in Baylor (P-trend < 0.001). Expanded models using 182-183 variables had predictive abilities similar to iHF., Conclusions: Sex-specific laboratory-based electronic health record-delivered iHF risk scores effectively predicted 30-day readmission among HF patients. Efficient to calculate and deliver to clinicians, recent clinical implementation of iHF scores suggest they are useful and useable for more precise clinical HF treatment., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Vitamin D (Vit D) deficiency has been associated with prevalent and incident cardiovascular (CV) disease, suggesting a role for bioregulators of bone and mineral metabolism in CV health. Vitamin D deficiency leads to secondary hyperparathyroidism, and both primary and secondary hyperparathyroidism are associated with CV pathology. Parathyroid hormone (PTH) is an important regulator of calcium homeostasis, and its impact on CV disease risk is of interest. We tested whether elevated PTH is associated with CV disease and whether risk associations depend on Vit D status and renal function., Methods: Patients in the Intermountain Healthcare system with concurrent PTH and Vit D as 25-hydroxy-vitamin D (25[OH]D) levels were studied (N = 9,369, age 63 ± 16 years, 36% male). Parathyroid hormone levels were defined as low (<15 pg/mL), normal (15-75 pg/mL), or elevated (>75 pg/mL). Prevalence and incidence of hypertension, diabetes, hyperlipidemia, coronary artery disease/myocardial infarction, heart failure, stroke, and peripheral vascular disease were determined by the International Classification of Diseases, Ninth Revision codes documented in electronic medical records at baseline and, for incident events, during an average of 2.0 ± 1.5 years (maximum 7.5 years) of follow-up., Results: Parathyroid hormone elevation at baseline was noted in 26.1% of the study population. Highly significant differential CV prevalence/incidence rates for most CV risk factors, disease diagnoses, and mortality were noted for PTH >75 pg/mL (by 1.25- to 3-fold). Parathyroid hormone correlated only weakly (r = -0.15) with 25(OH)D and moderately with glomerular filtration rate (r = -0.36). 25(OH)D, standard risk factors, and renal dysfunction variably attenuated PTH risk associations, but risk persisted after full multivariable adjustment., Conclusions: Elevated PTH is associated with a greater prevalence and incidence of CV risk factors and predicts a greater likelihood of prevalent and incident disease, including mortality. Risk persists when adjusted for 25(OH)D, renal function, and standard risk factors. Parathyroid hormone represents an important new CV risk factor that adds complementary and independent predictive value for CV disease and mortality., (Copyright © 2011 Mosby, Inc. All rights reserved.)

Background: Depression is associated with cardiovascular (CV) disease, and it has been hypothesized that vitamin (vit)D deficiency may be associated with depression and a contributing factor to excess CV events. Therefore, we evaluated whether there is an association between vitD and incident depression among a CV population., Methods: Patients (N = 7,358) > or =50 years of age, with a CV diagnosis (coronary artery disease, myocardial infarction, congestive heart failure, cerebrovascular accident, transient ischemic accident, atrial fibrillation, or peripheral vascular disease), no prior depression diagnosis, and a measured vitD level were studied. Vitamin D (ng/mL) was stratified into 4 categories: >50 (optimal [O] n = 367), 31 to 50 (normal [N] n = 2,264), 16 to 30 (low [L] n = 3,402), and > or =15 (very low [VL] n = 1,325). Depression was defined by International Classification of Diseases, Ninth Edition, codes: 296.2 to 296.36, 311. VitD categories were evaluated by Cox hazard regression with adjustment by standard CV risk factors., Results: Age averaged 73.1 +/- 10.2 years, and 58.8% were female. When compared to O, VL, L, and N were associated with depression (adjusted: VL, hazard ratio [HR] 2.70 [1.35-5.40], P = .005; L, HR 2.15 [1.10-4.21], P = .03; N, HR 1.95 [0.99-3.87], P = .06). This association remained even after adjustment by parathyroid hormone levels. Parathyroid hormone was significantly associated with depression, however, became nonsignificant after adjustment by vitD. Winter (December-February) enhanced this association. Significant associations remained when stratifications were made by age (<65, > or =65), sex, and diabetes, although the associations among those age > or =65 and male sex were enhanced., Conclusion: Among a CV population > or =50 years with no history of depression, vitD levels were shown to be associated with incident depression after vitD draw. This study strengthens the hypothesis of the association between vitD and depression., (Copyright 2010 Mosby, Inc. All rights reserved.)

Background: The basic metabolic profile (BMP) is a common blood test containing information about standard blood electrolytes and metabolites. Although individual variables are checked for cardiovascular health and risk, combining them into a total BMP-derived score, as to maximize BMP predictive ability, has not been previously attempted., Methods: Patients (N = 279,337) that received a BMP and had long-term follow-up for death were studied. Risk models were created in a training group (60% of study population, n = 167,635), validated in a test group (40% of study population, n = 111,702), and confirmed in the NHANES III (Third National Health and Nutrition Examination Survey) participants (N = 17,752). The BMP models were developed for 30-day, 1-year, and 5-year death using logistic regression with adjustment for age and sex. The BMP parameters were categorized as low, normal, or high based on the standard range of normal. Glucose was categorized as normal, intermediate, and high. Creatinine >or=2 mg/dL was further categorized as very high., Results: Average age was 53.2 +/- 20.1 years, and 44.3% were male. The areas under the curve for the training and test groups for 30-day, 1-year, and 5-year death were 0.887 and 0.882, 0.850 and 0.848, and 0.858 and 0.847, respectively. The predictive ability of these risk scores was further confirmed in the NHANES III population and independent of the Framingham Risk Score., Conclusion: In large, prospectively followed populations, a highly significant predictive ability for death was found for a BMP risk model. We propose a total BMP score as an optimization of this routine baseline test to provide an important new addition to risk prediction.