Profile of Patients Hospitalized for Heart Failure Who Leave Against Medical Advice

Mitchell, Judith E.; Chesler, Roseann; Zhang, Shuaiqi; Matsouaka, Roland; DeVore, Adam D.; Allen, Larry A.; Albert, Nancy M.; Fraser, Marilyn; Yancy, Clyde W.; Chang, Nai–Lun; Fonarow, Gregg C.

doi:10.1016/j.cardfail.2021.03.011

Cited by 5 publications

(7 citation statements)

References 20 publications

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“…The U.S. National Trauma Bank on adult trauma showed that patient’s insurance status (uninsured: odds ratio [OR], 2.72 versus Medicaid insured: OR, 2.5), race (African Americans: OR, 1.6) were associated with higher odds of the patient leaving AMA. A similar association was noted in a study including 74,502 patients with heart failure, showing that heart failure patients leaving AMA were younger, minorities, uninsured, or Medicaid covered 3,4 . In patients with acute myocardial infarction after percutaneous coronary intervention, AMA has been reported in 0.5%.…”

Section: Discussionsupporting

confidence: 77%

“…Leaving AMA is also associated with higher odds of readmission to a different hospital (OR, 2.35) and to repeat discharge AMA after readmission (OR, 18.41). Against medical advice is reported to be associated with increased readmission, readmission to a different hospital, and repeat discharge AMA after readmission, like this study 4,5,8–10 . In this study, the IE patients leaving AMA had higher morbidity, including recurrent bacteremia, recruiting new emboli, recurrent admissions, and requirement of prolonged antibiotics.…”

Section: Discussionmentioning

confidence: 50%

“…Against medical advice is reported to be associated with increased readmission, readmission to a different hospital, and repeat discharge AMA after readmission, like this study. 4,5,[8][9][10] In this study, the IE patients leaving AMA had higher morbidity, including recurrent bacteremia, recruiting new emboli, recurrent admissions, and requirement of prolonged antibiotics. According to Vilacosta et al, 11 among patients with IE on treatment, presence of embolic phenomenon before initiating antibiotics was an independent predictor of increased risk of emboli (OR, 1.73).…”

Section: Risk Factorsmentioning

confidence: 74%

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Harms and Contributors of Leaving Against Medical Advice in Patients With Infective Endocarditis

et al. 2022

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IntroductionPatients leaving against medical advice (AMA) are commonly encountered in hospital medicine. The problem is prevalent worldwide and across all fields of medicine. A retrospective study of 47,583 patients reported a 3.3% AMA rate in 2015.ObjectivesIn this retrospective study, we aimed (1) to study the demographic, clinical, and laboratory parameters of infective endocarditis (IE) patients leaving AMA. We also compared (2) the various risk factors and outcomes of these patients with IE patients who completed treatment.ResultsA total of 111 patients diagnosed with IE were recruited for 36 months. Of the 74 patients with available details, 32 patients (29%) left AMA during their treatment. The mean age of patients leaving AMA was 39, and among those who left AMA, 66% were females. As compared with patients completing therapy, patients leaving AMA tend to have higher comorbidities, including injection drug use (68.1% versus 31.9%), prior IE (83.3% versus 16.7%), and chronic hepatitis C (72.4% versus 27.8%). Rates of consumption of substances of abuse were higher among those who left AMA. Patients leaving AMA also had higher psychiatric comorbidities (63% versus 37.5%), history of leaving AMA (70.5% versus 29.5%), and consumption of more than 2 substances of abuse. Morbidity was higher in patients leaving AMA. There was a statistically significant association between the development of distal embolus (P < 0.001), the need for recurrent admissions (P = 0.002), recurrent bacteremia (P < 0.001), developing new embolus (P < 0.001), and overall morbidity (P = 0.002) among IE patients leaving AMA.ConclusionsInfective endocarditis patients leaving AMA tend to be younger females. These patients have prior comorbidities of injection drug use, prior IE, multiple psychiatric comorbidities, drug use, and multiple socioeconomic issues. Patients leaving AMA tend to develop further non–Central nervous system embolic events, recurrent bacteremia, and require frequent admissions. Morbidity in these patients was higher.

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Section: Discussionsupporting

confidence: 77%

Section: Discussionmentioning

confidence: 50%

Section: Risk Factorsmentioning

confidence: 74%

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Harms and Contributors of Leaving Against Medical Advice in Patients With Infective Endocarditis

et al. 2022

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“…One to two percent of patients hospital-ized in acute care leave on their own. [1][2][3] When patients withdraw their consent for healthcare and elect to leave, nurses can become concerned about patients missing out on expected treatment benefits and/or incurring harm as a result of nontreatment. Evidence supports some of these concerns: In addition to any missed treatment benefits and harm from nontreatment, patientinitiated discharge increases the risk of hospital readmissions, repeated ED visits, and mortality.…”

Section: What Is a Patient-initiated Discharge?mentioning

confidence: 99%

“…A patient-initiated discharge can be ethically challenging for nurses. One to two percent of patients hospitalized in acute care leave on their own 1-3. When patients withdraw their consent for healthcare and elect to leave, nurses can become concerned about patients missing out on expected treatment benefits and/or incurring harm as a result of nontreatment.…”

Section: What Is a Patient-initiated Discharge?mentioning

confidence: 99%

Ethical considerations when patients initiate their own discharge

Gibson¹

2021

Nursing

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A study of “left against medical advice” emergency department patients: an optimized explainable artificial intelligence framework

Ahmed,

Aram,

Tutun

et al. 2024

Health Care Manag Sci

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The issue of left against medical advice (LAMA) patients is common in today’s emergency departments (EDs). This issue represents a medico-legal risk and may result in potential readmission, mortality, or revenue loss. Thus, understanding the factors that cause patients to “leave against medical advice” is vital to mitigate and potentially eliminate these adverse outcomes. This paper proposes a framework for studying the factors that affect LAMA in EDs. The framework integrates machine learning, metaheuristic optimization, and model interpretation techniques. Metaheuristic optimization is used for hyperparameter optimization-one of the main challenges of machine learning model development. Adaptive tabu simulated annealing (ATSA) metaheuristic algorithm is utilized for optimizing the parameters of extreme gradient boosting (XGB). The optimized XGB models are used to predict the LAMA outcomes for patients under treatment in ED. The designed algorithms are trained and tested using four data groups which are created using feature selection. The model with the best predictive performance is then interpreted using the SHaply Additive exPlanations (SHAP) method. The results show that best model has an area under the curve (AUC) and sensitivity of 76% and 82%, respectively. The best model was explained using SHAP method.

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Profile of Patients Hospitalized for Heart Failure Who Leave Against Medical Advice

Cited by 5 publications

References 20 publications

Harms and Contributors of Leaving Against Medical Advice in Patients With Infective Endocarditis

Harms and Contributors of Leaving Against Medical Advice in Patients With Infective Endocarditis

Ethical considerations when patients initiate their own discharge

A study of “left against medical advice” emergency department patients: an optimized explainable artificial intelligence framework

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