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A Cluster Analysis of Clinician Distress Trajectories when Caring for Seriously Ill Hospitalized Patients
Anessa M Foxwell1,2,3,4, Salimah H Meghani2,4, Katherine R Courtright1,4
1Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA.
Abstract:
Purpose:Inpatient clinicians may experience distress when providing complex care for the millions of Americans with serious illness hospitalized yearly. Understanding the types and clinical impact of clinician distress when caring for seriously ill inpatients can inform supportive interventions to minimize burnout symptoms. This study aims to identify distinct distress trajectories among clinicians caring for seriously ill inpatients over time using mobile ecological momentary assessments (mEMAs).Methods:We performed latent class cluster analysis of clinicians' prospective serial mEMAs to identify unique distress trajectories and estimated univariate ordinal logistic regression models using generated estimating equations methods to explore the relationship between distress type and patient and clinician characteristics.Results:We identified four distinct clinician distress trajectories from clinician responses (n = 142): low distress (23.2%), moderate distress (33.1%), high distress (23.9%), and variable distress (19.7%). The majority of patients had a primary malignancy (77.9%). Clinicians self-reported multiple symptoms: fatigue (59.3%), stress (57.4%), worry (47.2%), insomnia (33.3%), anger (13.9%), sadness (9.3%), and pain (4.6%). Clinicians' discipline (advanced practice provider [APP] vs. physician; χ2 = 9.11, p = 0.0025) and emotions (χ2 = 11.29, p = 0.0008) were significantly associated with the distress trajectory. Clinicians who had an increase in reported emotions were likely to be in a higher distress trajectory (odds ratio [OR] 1.90, p = 0.001), as were APPs compared with physicians (OR 6.16, p = 0.003).Conclusion:Clinicians experience distinct trajectories of distress while caring for seriously ill inpatients. While all groups experienced degrees of distress, identifying clinicians with high distress may enable health systems to target supportive interventions and resources in a timely manner to mitigate potential burnout and other emotional states.
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