1. How do you define strategic leadership in the context of advancing population health, and what differentiates it from traditional healthcare leadership approaches?
Strategic leadership in population health focuses on aligning innovation, data, and partnerships to address health inequities at scale. It differs from traditional healthcare leadership by moving beyond direct care delivery to designing systems-level solutions rooted in evidence and community context. This approach emphasizes prevention, resilience, and cross-sector coordination. Through this lens, I’ve led initiatives that improved outcomes in underserved communities—proving that strategic leadership is about anticipating challenges, aligning with national priorities, and building sustainable, equitable health systems.
2. Can you elaborate on the theoretical and practical foundations that informed the development of the Emotional Resilience and Motivation Quotient (ERQM) tool, and how its application has influenced chronic disease outcomes?
The ERMQ tool was built on interdisciplinary theory—combining behavioral psychology, emotional intelligence, and systems design—applied through advanced analytics and validated psychometric frameworks. Practically, it quantifies emotional resilience and motivation in high-pressure healthcare settings, addressing a critical gap in public health preparedness. Its implementation has reduced burnout by 30%, enhanced team cohesion, and led to improved patient engagement. This emotional readiness translated into better chronic disease outcomes, including improved adherence, fewer missed visits, and measurable gains in recovery times within vulnerable populations.
One of the greatest system-level challenges to achieving health equity is fragmentation—across care delivery, data systems, and community resources. I’ve addressed this through integrated models that blend predictive analytics, community partnerships, and culturally responsive engagement. By aligning health services with local needs and social realities—especially in under-resourced areas—we’ve increased preventive care uptake and reduced avoidable hospitalizations. These initiatives are rooted in trust-building, actionable data, and systems-thinking, allowing us to navigate entrenched inequities with measurable, community-centered outcomes.
Interdisciplinary collaboration ensures that population health interventions are not siloed but informed by diverse expertise—clinical, behavioral, technological, and community-based. This breadth enables nuanced, effective solutions. Under my leadership, shared governance models that prioritize stakeholder co-design and cross-sector accountability have proven most successful. These models foster aligned goals, rapid problem-solving, and scalable innovation. By integrating insights across disciplines, we’ve delivered measurable outcomes in chronic disease prevention and health equity, particularly in high-need communities, where collaboration drives both relevance and sustainability.
In implementing the Expanded Access to Care grant, I applied a robust evaluation framework to measure long-term impact on underserved populations. Metrics included improvements in COVID-19 vaccination rates, pre-diabetes risk assessments, blood pressure screenings, and patient education on the importance of routine immunizations. The program demonstrated measurable outcomes such as increased vaccine uptake, improved chronic disease monitoring, enhanced care continuity, and reduced preventable hospitalizations—collectively advancing health equity and strengthening population health infrastructure in high-need communities.
I ensure federally aligned chronic disease prevention strategies remain adaptable to hyperlocal needs by integrating national frameworks—such as the CDC’s DSMES program and the U.S. Health Equity Strategy—with community-specific data and cross-sector collaboration. Using predictive analytics and stakeholder engagement, I tailor interventions to reflect local health profiles while aligning with federal benchmarks. This dual-focus approach has allowed my programs to remain scalable, evidence-based, and deeply responsive to the unique needs of medically underserved populations, without compromising on national priorities.
One high-impact case from my portfolio is the Expanded Access to Care and Continued Access to Vaccination initiative, funded by a $2.75 million New York City DOHMH grant. We implemented a hybrid model that combined mobile clinics with traditional clinic infrastructure to expand reach in low-uptake ZIP codes. This approach increased COVID-19 vaccination rates, enabled continued access to care, and integrated screenings for chronic diseases. Real-time data guided deployment, and outcomes directly influenced state-level funding and policy decisions supporting sustained investment in equitable, community-centered public health models.
Community engagement is central to my program design. In my Monkeypox prevention initiative, I operationalized involvement by training community ambassadors from high-risk neighborhoods to lead targeted outreach, education, and vaccine navigation. These ambassadors co-developed materials, shared real-time feedback, and built trust with underserved groups, enabling culturally relevant interventions. Their deep local ties helped identify barriers, increase vaccine uptake, and shape ongoing strategies. This model ensured that community voices directly informed program delivery, making it more responsive, equitable, and sustainable.
In my experience, integrating behavioral health into chronic disease prevention has significantly reshaped both patient outcomes and system performance. We incorporated behavioral health screenings and referrals within chronic disease programs, addressing the underlying stress, trauma, and emotional factors that often impact disease progression and treatment adherence. This approach resulted in higher engagement, reduced emergency care utilization, and improved self-management among patients. It also fostered a more cohesive care model, where physical and mental health were addressed together, leading to more sustainable health improvements
I reconcile short-term outcome pressures with long-term transformation by embedding sustainability into every stage of program design. For example, in our CDC-funded Expanded Access to Care initiative, we launched immediate services like mobile units and health education to drive measurable improvements in screening and vaccination rates. At the same time, we integrated community ambassadors, local data systems, and emotional resilience tools to build lasting engagement and system adaptability. This dual-track model ensures both impact today and structural change over time.
My framework integrates public health emergency preparedness and chronic disease prevention by addressing both immediate crises and long-term vulnerabilities. During the Monkeypox response, we deployed rapid community outreach, testing, and vaccination while simultaneously identifying individuals at risk for unmanaged chronic conditions. We used this touchpoint to connect them to hypertension and diabetes services. By embedding resilience tools and care navigation into emergency protocols, we not only mitigate outbreaks but also strengthen chronic disease systems—ensuring preparedness leads to sustainable population health improvement.
One often overlooked dimension of workforce resiliency in population health is emotional exhaustion stemming from prolonged exposure to community trauma and systemic barriers. Traditional models focus on productivity and burnout mitigation, but few address the deeper psychological toll on frontline staff. Through my Emotional Resilience and Motivation Quotient (ERMQ) tool, I’ve shown how data-driven assessments of staff well-being can guide interventions. Leadership must evolve from transactional management to emotionally intelligent, trauma-informed guidance that fosters psychological safety, meaning, and long-term motivation.
Artificial intelligence and advanced analytics hold transformative potential for equitable chronic disease prevention by enabling hyperlocal, real-time insights into population health needs. I’ve used predictive modeling to identify disparities in screening and intervention uptake, allowing us to target underserved populations more precisely. AI can personalize outreach, optimize resource allocation, and detect emerging trends before they escalate. However, its power lies in equitable design—ensuring datasets reflect diverse populations and outputs are interpreted through a health equity lens to avoid algorithmic bias.
Three core leadership principles have consistently shaped my success: equity-centered design, systems thinking, and participatory leadership. I prioritize listening to community voices early, ensuring interventions address root causes, not just symptoms. Systems thinking allows me to design scalable models that align with both hyperlocal needs and national priorities. Lastly, I foster cross-sector collaboration and shared ownership—mobilizing stakeholders, community ambassadors, and frontline teams to co-create and implement sustainable solutions rooted in data, empathy, and measurable impact.
Preet Kukreja is a nationally recognized expert in population health, health equity, and public health innovation. She has led impactful initiatives addressing chronic disease prevention, social determinants of health, and emergency preparedness in underserved communities. Her work integrates federal frameworks with local implementation, producing measurable outcomes in health access, resilience, and system transformation. She is the pioneer of the Emotional Resilience and Motivation Quotient tool, adopted to reduce burnout and improve patient outcomes. Ms. Kukreja is a Fellow of the New York Academy of Medicine and the Association for Project Management. She serves on the Action Board of the American Public Health Association and the Community Advisory Board of the Johns Hopkins Center for Health Equity.
