Data-Driven Approaches to Health Care Provider Resilience and Burnout During COVID-19

Background: The United States is battling dual pandemics, heath care provider (HCP) exhaustion and COVID-19. HCP exhaustion, or burnout, preceded the COVID-19 pandemic with its devastating consequences. Indeed, almost 50% of military, civilian, and Veterans Administration health system HCPs report symptoms of depersonalization, emotional exhaustion, or lack of personal accomplishment. Thus, as our nation prepares for the second surge of COVID-19, it is of paramount importance that we build our HCP resilience emergently. There is a pressing, critical need to quantitatively and rigorously identify predictors of HCP stress and burnout, and to integrate existing qualitative tools with novel biometric, physiologic and neuro-imaging ones, in order to measure and quantify the efficacy of non-pharmacologic interventions that reduce burnout and build resilience in HCPs. Relevance to Focus Area: COVID-19 has affected military HCPs, Veterans' health and their families. The well-being and emotional resilience of health care workers are key components of maintaining essential health care services during the COVID-19 pandemic. Therefore, this proposal conducts the crucial research that informs us of evidence-based interventions to put in place for health care workers as well as early predictors to aid monitoring and assessment of mental health and well-being of health care personnel. Military and Veteran families are affected with COVID-19 in an unimaginable way with worsening of medical and mental health problems, such as depression, post-traumatic stress disorder (PTSD), and suicidal ideation due to isolation of troops from colleagues and families resulting from lockdowns, with an enormous need for health care support. Unfortunately, mental health clinicians in the military and Department of Veterans Affairs (VA) are an especially vulnerable population for burnout, limiting their ability to care for our troops and Veterans. To address this issue, we aim to recruit a diverse group of HCPs - from academic centers, community centers, VA and mental health providers in the community. Our proposal aims to improve understanding of physiological and biological resilience and burnout in HCPs that would impact health care of civilian as well as military patients. We aim to test potential behavioral countermeasures to mitigate negative impacts and maximize Service Member and family resilience to stressors related to pandemics and disasters by building resilience in their HCPs. Overall Objective: Our objective is to apply Artificial Intelligence-Machine Learning approaches to define and measure qualitative, physiologic, and biologic markers of burnout and resilience in HCPs, before and after instituting systematic, protocolized Mind-Body interventions. We will engage multiple sites that include both inpatient and outpatient HCPs, leveraging the interdisciplinary expertise of the assembled team. We propose two distinct, non-pharmacologic interventions that have shown significant promise in promoting resilience, reducing fatigue and preventing burnout: (1) Experience Resolution Methodology (ERM) coaching and (2) Transcendental Meditation (TM). Physician coaching, a commonly offered intervention by health care centers, has been shown to reduce HCP burnout in pilot studies. Our collaborators developed ERM coaching, a cognitive-based stress reduction modality, as a methodology that instilled a sense of resolution and new perspective in more than 70% of their clientele (N>560, 5%-10% HCP) after 8 hours of coaching. These outcomes persist in almost 50% of clients at the 6-month mark. The second intervention, TM, is a mind-body intervention designed to increase parasympathetic tone and alpha wave coherence throughout the brain in order to promote a state of relaxation. TM has demonstrated efficacy in several high-stress cohorts, including physician and nursing cohorts and, importantly, in military cadets and Veterans suffering from PTSD. TM serves as a potential complementary intervention to enhance the effects of ERM coaching. This efficacy data in high stress environments supports ERM coaching and TM as two interventions to promote resilience in HCPs in the midst of the COVID-19 pandemic. We propose a 4-year, multi-site, four-arm parallel-group randomized clinical trial (RCT) compare treatment as usual (TAU) to TM alone, ERM alone, and TM+ERM. Specific Aims: Aim 1: Assess the efficacy of (1) TM versus TAU, (2) a form of coaching termed ERM versus TAU, and (3) TM plus ERM versus TAU in increasing resilience and reducing burnout syndrome in HCPs. Hypothesis 1: TM, ERM, and TM + ERM will significantly improve resilience and burnout compared to TAU over a 3-month period. HCPs will be randomized to one of four groups: TAU control (n=70), TM (n=70), ERM coaching (n=70), and TM+ERM (n=70). Participant data will be collected on Burnout (MBI), Resilience (CD-RISC-25), Psychosocial distress/Anxiety (BSI General Severity Index, PTSD symptoms (PCL-5), Depression (PHQ-9), Quality of Life (Q-LES-Q-short form) and Insomnia (ISI). Primary outcome measures will include resilience scores pre- and post-intervention (baseline vs. 3 months). Secondary outcome measures will include change in Burnout, Depression, Anxiety, Quality of Life, PTSD Symptoms and Insomnia. Aim 2: To characterize the biometric, immunologic, and neuro-functional characteristics of HCPs' resilience and burnout. Hypothesis 2: Physiologic, immunologic, and neuro-functional measures can complement rating scale-based tools in identifying changes in resilience and early burnout in HCPs. We will measure (1) physiologic markers: heart rate variability (HRV), GSR, EEG, and voice biomarkers, (2) biological markers of stress - stress proteins in plasma, peripheral blood mononuclear cell (PBMC) flow cytometry, and (3) neuroimaging (fMRI). An Apple Watch will assess changes in resting HRV. Participants will undergo plasma stress protein testing, PBMC flow cytometry and EEG at baseline and at the end of 12 months. Participant data on HRV, GSR, voice recordings and fMRI will be collected at baseline and at the end of 3 months. Aim 3: To develop a medical predictive model and develop a composite resilience and burnout index. Hypothesis 3: The data generated in Aims 1 and 2 will allow us to establish rigorous predictive models and a composite resilience-burnout index (RBI), that can be used to quantify and determine efficacy of TM and/or ERM in HCPs. Data collected from survey and psychometric scales, baseline demographics, physiological markers (HRV, EEG, Voice Biomarker, Galvanic Skin Response), and biological markers (CRP, immune signatures) will be analyzed with artificial intelligence/machine learning in order to quantify the degree of burnout and resilience in the ERM coaching, TM, and combined TM+ERM coaching group. We then hypothesize that our multi-parameter Resilience and Burnout Index (RBI) will accurately predict outcomes in our randomized controlled trial. Study Design: HCPs will be enrolled after screening for inclusion and exclusion criteria and informed consent from a cohort of physicians, trainees, physician assistants, nurse practitioners, respiratory therapists at Duke Health System and its affiliated VA hospital (first site) and Mindpath Centers (second site). HCPs will be randomized in one of four groups (1) TAU (Treatment as usual with waitlist control), (2) Transcendental Meditation (TM), (3) ERM, and (4) TM+ ERM. Primary outcome measured will be change in Resilience (CD-RISC-10) at 3 months of study participation while secondary outcomes include change in Burnout (Maslach Burnout Inventory), Depression (PHQ-9), Anxiety (Basic Symptom Index), Trauma symptoms (PCL-5), Quality of Life (QLES), and Insomnia (Insomnia Severity Index). Physiological markers (HRV-heart rate variability, Galvanic Skin Response-GSR, Voice modulation to stress) and Neuroimaging targeted at neurovascular blood flow in selective patients (fMRI) would be obtained at baseline and at end of 3 months. Immunological markers (stress proteins in plasma, Peripheral Blood Mononuclear Cell-PBMC-Flow Cytometry) and Neuro-electrical activity markers (EEG) would be obtained at baseline and at the end of 12 months. Data will be analyzed periodically with artificial intelligence to develop predictive markers of Resilience and Burnout. 50% of participants in TAU arm will be offered either TM or Coaching as intervention after 3 months of participation. Clinical Impact: Upon completion, this proposal will identify quantitative and multidimensional measures and predictors of resilience and burnout in HCPs, test the efficacy of two non-pharmacologic interventions and provide evidence-based rationale for offering specific impactful interventions to the broader community, including VA-associated patients, their families and civilians. Less