Bias in team decision-making for advanced heart failure therapies: model application.
Megan HebdonNatalie PoolRyan YeeKathryn Herrera-TheutErika YeeLarry A AllenAyesha HasanJoAnn LindenfeldElizabeth CalhounNancy K SweitzerAnna WellingKhadijah BreathettPublished in: Journal of interprofessional care (2024)
Bias in advanced heart failure therapy allocation results in inequitable outcomes for minoritized populations. The purpose of this study was to examine how bias is introduced during group decision-making with an interprofessional team using Breathett's Model of Heart Failure Decision-Making. This was a secondary qualitative descriptive analysis from a study focused on bias in advanced heart failure therapy allocation. Team meetings were recorded and transcribed from four heart failure centers. Breathett's Model was applied both deductively and inductively to transcripts ( n = 12). Bias was identified during discussions about patient characteristics, clinical fragility, and prior clinical decision-making. Some patients were labeled as "good citizens" or as adherent/non-adherent while others benefited from strong advocacy from interprofessional team members. Social determinants of health also impacted therapy allocation. Interprofessional collaboration with advanced heart failure therapy allocation may be enhanced with the inclusion of patient advocates and limit of clinical decision-making using subjective data.
Keyphrases
- heart failure
- decision making
- left ventricular
- acute heart failure
- palliative care
- cardiac resynchronization therapy
- atrial fibrillation
- healthcare
- patient safety
- quality improvement
- end stage renal disease
- public health
- systematic review
- stem cells
- newly diagnosed
- case report
- mental health
- chronic kidney disease
- ejection fraction
- computed tomography
- machine learning
- adipose tissue
- cell therapy
- physical activity
- electronic health record
- mass spectrometry
- big data
- climate change
- pet ct
- positron emission tomography