Physician Attitudes Toward End-Stage Heart Failure: A National Survey

Hauptman, Paul J.; Swindle, Jason; Hussain, Zainal; Biener, Lois; Burroughs, Thomas E.

doi:10.1016/j.amjmed.2007.08.035

Cited by 93 publications

(63 citation statements)

References 45 publications

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“…However, Hauptman et al 16 found that fewer than one fifth of a cohort of clinicians caring for patients with HF believed they could accurately predict death, and, in fact, clinicians frequently incorrectly estimate risk in patients with HF. 17,18 Generally, clinicians substantially over estimate risk, resulting in overutilization of critical care resources.…”

Section: Discussionmentioning

confidence: 99%

A Validated Risk Score for In-Hospital Mortality in Patients With Heart Failure From the American Heart Association Get With the Guidelines Program

Peterson

Rumsfeld

et al. 2010

Circ: Cardiovascular Quality and Outcomes

449

345

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Background— Effective risk stratification can inform clinical decision-making. Our objective was to derive and validate a risk score for in-hospital mortality in patients hospitalized with heart failure using American Heart Association Get With the Guidelines–Heart Failure (GWTG-HF) program data. Methods and Results— A cohort of 39 783 patients admitted January 1, 2005, to June 26, 2007, to 198 hospitals participating in GWTG-HF was divided into derivation (70%, n=27 850) and validation (30%, n=11 933) samples. Multivariable logistic regression identified predictors of in-hospital mortality in the derivation sample from candidate demographic, medical history, and laboratory variables collected at admission. In-hospital mortality rate was 2.86% (n=1139). Age, systolic blood pressure, blood urea nitrogen, heart rate, sodium, chronic obstructive pulmonary disease, and nonblack race were predictive of in-hospital mortality. The model had good discrimination in the derivation and validation datasets (c-index, 0.75 in each). Effect estimates from the entire sample were used to generate a mortality risk score. The predicted probability of in-hospital mortality varied more than 24-fold across deciles (range, 0.4% to 9.7%) and corresponded with observed mortality rates. The model had the same operating characteristics among those with preserved and impaired left ventricular systolic function. The morality risk score can be calculated on the Web-based calculator available with the GWTG-HF data entry tool. Conclusions— The GWTG-HF risk score uses commonly available clinical variables to predict in-hospital mortality and provides clinicians with a validated tool for risk stratification that is applicable to a broad spectrum of patients with heart failure, including those with preserved left ventricular systolic function.

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Section: Discussionmentioning

confidence: 99%

A Validated Risk Score for In-Hospital Mortality in Patients With Heart Failure From the American Heart Association Get With the Guidelines Program

Peterson

Rumsfeld

et al. 2010

Circ: Cardiovascular Quality and Outcomes

449

345

View full text Add to dashboard Cite

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“…Despite a strong majority of HF patients expressing a wish to discuss life expectancy and philosophy of care decisions with their physicians, [22][23][24][25][26] this is not always recognized or acted on by their physicians. 27 Although discomfort in predicting the trajectory of disease for patients with HF has often been cited as a major barrier to such discussions, 28,29 recently developed risk prediction models will hopefully simplify this task. We hope that this study will stimulate clinicians to incorporate goals of care discussions into their standard approach to hospitalized patients with HF.…”

Section: Discussionmentioning

confidence: 99%

Influence of Patient Goals of Care on Performance Measures in Patients Hospitalized for Heart Failure

McAlister

Wang

Donovan

et al. 2015

Circ: Heart Failure

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Background-Pay for performance programs compare metrics that are risk-adjusted, but goals of care are not considered in current models. We conducted this study to explore the associations between do not resuscitate (DNR) designations, quality of care, and outcomes. Methods and Results-Retrospective cohort study with chart review for inpatient quality metrics, 30 day mortality, and readmissions or death within 30 days of discharge in 96 Ontario hospitals participating in the Enhanced Feedback For Effective Cardiac Treatment (EFFECT) study in 2004/05. Of 8339 patients (mean age 77 years) with new heart failure, 1220 (15%) had DNR documented at admission (admission DNR, varying from 0% to 36% between hospitals) and 892 (11%) were switched from full resuscitation to DNR during their index hospitalization (later DNR). Death at 30 days was more common in patients with admission DNR (27%) or later DNR (35%) than full resuscitation (3%)-admission DNR was a stronger predictor (adjusted OR 8.6, 95% confidence interval 6.8-10.7) than any of the variables currently included in heart failure 30 day mortality risk models. Hospital-level rankings differed considerably if DNR patients were excluded: 22 of the 39 EFFECT hospitals in the top and bottom quintiles for 30 day mortality rates (the usual thresholds for rewards/penalties in current performance-based reimbursement schemes) would not have been in those same quintiles if admission DNR patients were excluded. Conclusions-Alternate goals of care are frequent and important confounders in heart failure comparative studies.Philosophy of care discussions should be considered for inclusion as a potential quality of care indicator. (Circ Heart Fail. 2015;8:481-488.

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“…Hauptman et al 34 reported that only 15.7% of 734 physicians surveyed felt they could reliably predict the timing of death, whereas the majority admitted to being able to formulate such an assessment rarely (25.2%) or only sometimes (59.1%). Confidence in predictive capabilities was higher in geriatricians than cardiologists or family physicians and was more common in those with palliative care training.…”

Section: Perceived Barriers To Icd Deactivation Discussionmentioning

confidence: 99%

“…Furthermore, participating in a formal palliative care rotation may help build skills in both prognostication and communicating this information to patients and their families. 34,37 It would also be prudent to institute a conversational protocol, whereby physicians are provided with a guideline for ICD deactivation. These formats have been shown to increase the rate of ICD deactivation among patients when delivered at the time of hospice admission.…”

Section: Develop and Implement A Conversational Protocol For Icd Deacmentioning

confidence: 99%

Lost in Translation

Mitar

Alba

MacIver

et al. 2012

Circ: Heart Failure

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Physician Attitudes Toward End-Stage Heart Failure: A National Survey

Cited by 93 publications

References 45 publications

A Validated Risk Score for In-Hospital Mortality in Patients With Heart Failure From the American Heart Association Get With the Guidelines Program

A Validated Risk Score for In-Hospital Mortality in Patients With Heart Failure From the American Heart Association Get With the Guidelines Program

Influence of Patient Goals of Care on Performance Measures in Patients Hospitalized for Heart Failure

Lost in Translation

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