Reimagining how we develop leaders for healthcare’s evolving digital/data ecosystem: Implications for graduate programs in health administration

We began by comparing two competency models: NCHL and AMIA, with a focus on how informatics relates to each NCHL competency. This was done because our own experience in environments with both a CAHME and a CAHIIM accredited program led to a more nuanced, integrative view than often seen in traditional programs and in the industry.

As background, the NCHL Health Leadership Competency Model 3.0TM and the AMIA Health Informatics Core Competencies both outline key areas of competency development for healthcare professionals but with distinct focuses and applications. The NCHL Competency Model emphasizes leadership development within healthcare organizations. It is organized into seven domains, four of which are “action” domains (Execution, Relations, Transformation, and Boundary Spanning) that focus on practical leadership skills, and three “enabling” domains (Health System Awareness, Self-Awareness, and Values) that address personal and professional growth. This model supports leadership in various areas such as organizational transformation, collaboration, project management, and strategic orientation, specifically tailored to enhance healthcare leadership across organizational structures.

On the other hand, the AMIA Health Informatics Core Competencies are more focused on health informatics as an interdisciplinary field that combines health, information science, and technology to solve biomedical and healthcare problems. This model stresses foundational knowledge in areas such as clinical informatics, consumer health informatics, and population informatics. AMIA’s core competencies are structured around using data, technology, and informatics to drive decision-making, problem-solving, and health outcomes, focusing on equipping professionals with technical expertise and an understanding of socio-technical systems and human behavior. While both models aim to enhance healthcare, the NCHL is leadership-focused, promoting high-level organizational and managerial competencies, whereas AMIA targets technical proficiency in health informatics, emphasizing the application of data and technology in healthcare delivery and decision-making.

These models were selected as examples only, as we recognize that programs in health administration and health informatics will often use different competency models. Table 1 provides a comprehensive overview of the intersection between health informatics and AI, demonstrating how both fields can be integrated to strengthen leadership competencies in healthcare. In general, the AMIA Core Competencies related to health informatics support the NCHL Leadership Competencies by providing the technological and data-driven tools needed to achieve the leadership goals set in the NCHL framework. Our analysis is presented in Table 1, column 2.

We next considered how AI could be included in both types of programs (HA and HI). Rather than considering a new, additional competency statement, we considered if and how AI might integrate in every competency. Our analysis is located in Table 1, column 3. For example, in the “Project Management” competency, health informatics is utilized by leveraging project management software specifically for health informatics projects, applying data analytics to monitor project progress, and using informatics solutions for resource management and risk mitigation. AI, on the other hand, enhances project management by optimizing resource allocation and scheduling, using real-time monitoring for project risks, and employing AI-driven tools to improve planning, execution, and evaluation processes. This pattern is repeated across all competencies, with health informatics typically focusing on data management, analysis, and communication tools, while AI is used to enhance predictive analytics, decision-making, and optimization across various aspects of healthcare leadership, such as organizational awareness, team leadership, and change management.

This analysis focused on the competencies and perspectives that are viewed to be required in a digitally transforming healthcare environment. Eight first-order codes coalesced into four second-order themes. In this paper, we present our results stemmed from four main themes that emerged from our iterative analysis along with exemplary quotes from the health system leaders’ interviews. The four main themes state that to effectively leverage technology and accelerate transformation, leaders must demonstrate these four traits:

1. Digitally/Tech Savvy Leaders. Leaders must have a strong knowledge of information technology, use data/analytics in decision making, and digital tools that can improve organizational performance.

2. Knowledgeable of the Regulatory Environment. CIOs and CEOs must understand regulations in general and the way it may impact IT investments, as well as how IT can be used to improve organizational reporting and effectiveness.

3. Financial Acumen in Health Information and Cyber Security. Executives described how CIOs and other technical leaders must be fluent in two areas related to financial acumen: Fiscal Management/Resource Allocation and Service Reimbursement. In addition, they stated CEOs need to be able to consider the financial implications of information technology investments and cyber security risks.

4. Change Management. Leaders described how their executives are engaged in complex, multi-faceted change management and all leaders must excel in the specific areas of Leading/Team Leadership and Visioning/Strategic Planning.

Representative quotes from each of the identified subthemes are presented in Table 2 to illustrate the key findings and provide deeper insights into necessary traits and skillsets future healthcare leaders need to possess in a digitally transforming ecosystem.

Based on the study’s findings, both traditional and executive health administration programs should evolve to better equip future healthcare leaders with the competencies needed to thrive in a digital healthcare ecosystem. These programs should integrate more informatics-related courses and technical skills into their curriculum, such as training in data analytics tools like Tableau and understanding how to leverage big data for decision-making. Additionally, in-depth training on healthcare compliance, risk management, and policy interpretation will help students navigate the increasingly complex regulatory environment. Enhancing fiscal management, resource allocation, and service reimbursement education is also crucial, emphasizing strategic resource management to maximize patient care quality and organizational financial health.

For executive programs, advanced courses on health informatics, big data analytics, and digital health technologies should ensure executives are proficient in leveraging data for strategic decision-making. The curriculum should offer comprehensive modules on healthcare compliance, risk management, and the latest federal and state regulations, particularly focusing on telehealth and reimbursement policies. Advanced fiscal management, resource allocation, and understanding of healthcare reimbursement mechanisms will be crucial for strategic financial planning and resource optimization. Leadership and change management training should be enhanced, focusing on strategic planning, visioning, and managing complex change initiatives. To support continuous professional development, executive health administration programs should introduce micro-credentials in emerging areas such as digital health and advanced data analytics, along with ongoing learning opportunities through short courses, workshops, and certifications. By incorporating these changes, health administration programs can ensure their graduates are well-prepared to meet the demands of a digitally transforming healthcare landscape.

Both traditional and executive health informatics programs should also adapt to meet the evolving demands of the healthcare landscape, as indicated by the study’s findings. To prepare informatics professionals for leadership roles, these programs should broaden their curriculum to include business strategy, organizational behavior, and leadership courses, ensuring that graduates possess both technical proficiency and essential business acumen. Training on healthcare finance and regulatory compliance is crucial, emphasizing the understanding of reimbursement mechanisms and the financial implications of IT decisions. Additionally, the curriculum should integrate advanced change management skills, focusing on leading digital transformation initiatives, managing resistance, and fostering a culture of innovation.

For executive programs, specialized training should further support continuous professional development. Executive health informatics programs should offer micro-credentials in areas such as cybersecurity in healthcare, health IT project management, and advanced data governance. Tailored leadership development programs, including executive coaching, mentorship, and peer learning opportunities, should also be provided to address the unique challenges faced by senior informatics professionals. By incorporating these elements, both traditional and executive health informatics programs can equip students with the comprehensive skill sets needed to navigate the complexities of modern healthcare environments and drive technological advancements in their organizations.

Incumbent health are leaders must recognize that the integration of advanced technologies such as AI and data analytics is not merely a technical upgrade but a strategic shift that redefines organizational dynamics and decision-making processes. This means moving beyond traditional leadership competencies to develop a nuanced understanding of how these technologies can drive value across clinical, operational, and financial dimensions. Leaders should be prepared to engage with these technologies at a strategic level, ensuring that their organizations are not only adopting new tools but are also leveraging them to enhance patient outcomes, optimize resource allocation, and maintain regulatory compliance.

Moreover, as digital tools become increasingly embedded in healthcare operations, incumbent leaders must foster a culture of continuous learning and innovation within their organizations. This involves creating an environment where teams are encouraged to experiment with new approaches, learn from failures, and iterate on success. Leadership in this context extends beyond managing day-to-day operations; it requires a vision of how technology can be harnessed to meet future challenges and opportunities in healthcare. Leaders must also be vigilant about the ethical implications of emerging technologies, particularly in areas like data privacy and AI-driven decision-making ensuring that their organizations uphold the highest standards of patient care and trust. By prioritizing these strategic and cultural shifts, incumbent healthcare leaders can position their organizations to thrive in an increasingly complex and data-driven healthcare landscape.

As AI and digital technologies rapidly evolve in healthcare, ethical considerations must remain a priority. The accelerated pace of innovation means that patients will increasingly question the ethical foundations of their medical care. Issues such as patient privacy, data security, algorithmic bias, and transparency in AI-driven decision-making must be carefully managed to maintain public trust. Healthcare leaders must ensure that AI applications align with ethical principles by upholding patient autonomy, ensuring informed consent, and promoting equitable access to care. Establishing clear ethical guidelines and governance structures will be essential to addressing these concerns as technology continues to advance.

• Graduate healthcare administration programs must integrate informatics and AI competencies into their curricula to equip future leaders for a digitally transforming healthcare ecosystem.
• Effective healthcare leaders will need to combine traditional management skills with proficiency in data analytics, regulatory compliance, and AI-driven tools to optimize organizational outcomes.
• Continuous adaptation and innovation in leadership training are essential for addressing the increasing complexity of healthcare driven by technology and regulatory changes.