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Validation of an Automated Electronic Algorithm and “Dashboard” to Identify and Characterize Decompensated Heart Failure Admissions across a Medical Center

The American heart journal, 2017-01, Vol.183, p.40-48

2017

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Together nurses have a renewed focus on ethical issues

Heart & lung, 2015-07, Vol.44 (4), p.269-269

Lewis, Connie M., MSN, ACNP-BC, NP-C, CCRN, CHFN

2015

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WARNING: Advanced heart failure

Heart & lung, 2015-01, Vol.44 (1), p.1-1

Lewis, Connie M., MSN, ACNP-BC, NP-C, CCRN, CHFN

2015

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Is there a “one size fits all” strategy for reducing heart failure readmissions?

Heart & lung, 2014-07, Vol.43 (4), p.269-269

Lewis, Connie M., MSN, ACNP-BC, NP-C, CCRN, CHFN

2014

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Body mass index and all-cause readmissions following acute heart failure hospitalization

International Journal of Obesity, 2020-06, Vol.44 (6), p.1227-1235

2020

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Change in admission blood glucose from chronic glycemic status in acute heart failure hospitalization and 30-day outcomes: A retrospective analysis

International journal of cardiology, 2020-01, Vol.299, p.180-185

2020

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Implications for heart failure prevention and treatment of cardiotoxicity in the cancer patient

Heart & lung, 2013, Vol.42 (1), p.4-4

Lewis, Connie M., RN, MSN, ANP-C, ACNP-BC, CCRN, CHFN

2013

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American Association of Heart Failure Nurses Best Practices paper: Literature synthesis and guideline review for dietary sodium restriction

Heart & lung, 2015-07, Vol.44 (4), p.289-298

2015

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Specialized heart failure nurses in a high-tech world

Heart & lung, 2011-07, Vol.40 (4), p.276-277

Lewis, Connie M., RN, MSN, ANP-C, ACNP-BC, CCRN

2011

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Heart failure nurses play a pivotal role in linking clinical research to clinical practice: Translational research

Heart & lung, 2012, Vol.41 (1), p.4-4

Lewis, Connie M., RN, MSN, ANP-C, ACNP-BC, CCRN, CHFN

2012

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Centers for Medicare and Medicaid Services’ readmission reports inaccurately describe an institution's decompensated heart failure admissions

Clinical cardiology (Mahwah, N.J.), 2017-09, Vol.40 (9), p.620-625

2017

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Customizing national models for a medical center's population to rapidly identify patients at high risk of 30-day all-cause hospital readmission following a heart failure hospitalization

Heart & lung, 2018-07, Vol.47 (4), p.290-296

2018

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Decompensated Heart Failure Admissions are Inaccurately Identified by Centers for Medicare and Medicaid Services’ Administrative Data

Journal of cardiac failure, 2015-08, Vol.21 (8), p.S10-S10

2015

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A BMI-Adjusted BNP Threshold Improves Automated Electronic Decompensated Heart Failure Identification

Journal of cardiac failure, 2016-08, Vol.22 (8), p.S98-S99

2016

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Creation of a New Readmission Risk Model Utilizing Variables from CMS Risk Models and Regional Risk Variables Improves Readmission Risk Discernment in Heart Failure

Journal of cardiac failure, 2016-08, Vol.22 (8), p.S103-S103

2016

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Evaluation of Two Different Models to Predict Heart Failure Readmissions

Heart & lung, 2016-07, Vol.45 (4), p.374-374

2016

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Centers for Medicare and Medicaid Services’ Heart Failure Report is Not Representative of a Hospital’s Heart Failure Population

Journal of cardiac failure, 2015-08, Vol.21 (8), p.S56-S57

2015

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Demographics of Heart Failure Patients 18-64 Admitted to An Academic Center: Lessons Learned

Heart & lung, 2014-07, Vol.43 (4), p.374-374

2014

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Take-CHARGE: Heart Failure Discharge Checklist, Communication, and Data Collection Tool

Heart & lung, 2014-07, Vol.43 (4), p.373-374

2014

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HF Positive Dashboard: Electronic Indicators Can Accurately Identify Inpatient Heart Failure Patients

Heart & lung, 2014-07, Vol.43 (4), p.375-375

2014

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Young adults with heart failure: Who are they? What is their clinical profile?

Heart & lung, 2015-11, Vol.44 (6), p.549-549

2015

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Take-CHARGE: Heart Failure Discharge Electronic Form for Admission Characterization and Quality Improvement

Journal of cardiac failure, 2014-08, Vol.20 (8), p.S61-S61

2014

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Utilization of galectin-3 in case management across the spectrum of heart failure

Reviews in cardiovascular medicine, 2014-01, Vol.15 (3), p.197-207

2014

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Change in Patient Signs-Symptoms at 90 Days and Caregiver Burden, QoL and ADL Support Needs

Journal of cardiac failure, 2018-08, Vol.24 (8), p.S72-S72

2018

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Real-time Application of an Inpatient Heart Failure Mortality Model to Predict 30-Day Mortality

Journal of cardiac failure, 2018-08, Vol.24 (8), p.S106-S107

2018

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Validation of an Automated Electronic Algorithm and “Dashboard” to Identify and Characterize Decompensated Heart Failure Admissions across a Medical Center

Together nurses have a renewed focus on ethical issues

WARNING: Advanced heart failure

Is there a “one size fits all” strategy for reducing heart failure readmissions?

Body mass index and all-cause readmissions following acute heart failure hospitalization

Change in admission blood glucose from chronic glycemic status in acute heart failure hospitalization and 30-day outcomes: A retrospective analysis

Implications for heart failure prevention and treatment of cardiotoxicity in the cancer patient

American Association of Heart Failure Nurses Best Practices paper: Literature synthesis and guideline review for dietary sodium restriction

Specialized heart failure nurses in a high-tech world

Heart failure nurses play a pivotal role in linking clinical research to clinical practice: Translational research

Centers for Medicare and Medicaid Services’ readmission reports inaccurately describe an institution's decompensated heart failure admissions

Customizing national models for a medical center's population to rapidly identify patients at high risk of 30-day all-cause hospital readmission following a heart failure hospitalization

Decompensated Heart Failure Admissions are Inaccurately Identified by Centers for Medicare and Medicaid Services’ Administrative Data

A BMI-Adjusted BNP Threshold Improves Automated Electronic Decompensated Heart Failure Identification

Creation of a New Readmission Risk Model Utilizing Variables from CMS Risk Models and Regional Risk Variables Improves Readmission Risk Discernment in Heart Failure

Evaluation of Two Different Models to Predict Heart Failure Readmissions

Centers for Medicare and Medicaid Services’ Heart Failure Report is Not Representative of a Hospital’s Heart Failure Population

Demographics of Heart Failure Patients 18-64 Admitted to An Academic Center: Lessons Learned

Take-CHARGE: Heart Failure Discharge Checklist, Communication, and Data Collection Tool

HF Positive Dashboard: Electronic Indicators Can Accurately Identify Inpatient Heart Failure Patients

Young adults with heart failure: Who are they? What is their clinical profile?

Take-CHARGE: Heart Failure Discharge Electronic Form for Admission Characterization and Quality Improvement

Utilization of galectin-3 in case management across the spectrum of heart failure

Change in Patient Signs-Symptoms at 90 Days and Caregiver Burden, QoL and ADL Support Needs

Real-time Application of an Inpatient Heart Failure Mortality Model to Predict 30-Day Mortality

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