Healthcare leadership development during a pandemic: do not stop, adapt

Research carried out in 2016 by two of the authors of this article investigated the role that leadership ‘theory’ plays within an individual's leadership development and identified other components of clinical leadership programmes that are key to enabling the development of future leaders. While early career doctors identified leadership theories and concepts as important within their development as clinical leaders, these must be closely tied to real-life practices and coupled with activities that aim to develop an increased self-awareness, understanding of others, clinical exposure and leadership tools that they can use in practice. During a healthcare crisis, such as a global pandemic, maintaining a focus on leadership development (particularly for more junior clinicians) might not be seen as important, but leadership is needed to help people and organisations ‘get through’ a crisis as well as help develop leadership capacity for the longer term. This article, drawing from contemporary literature, the authors' own research and reflections, discusses how leadership development needs to continually adapt to meet new demands and sets out tips for those involved with clinical leadership development.

HEALTHCARE LEADERSHIP: MOVING FROM CLINICAL SPECIALIST TO HEALTHCARE LEADER

Medical doctors may not have the necessary evidence-based knowledge of specific leadership styles to excel in a leadership role. This article explores the various leadership styles adopted by a clinical professional transitioning into a leadership role. The goal-path theory, developed by Robert House in 1971, was used as the theoretical lens for this study. Twenty peer-reviewed scientific articles, written in English and published between 2015 and 2020, were analyzed and synthesized to produce results. The results showed that employee retention was positively associated with transformational and authentic leadership styles; organizational commitment was positively related to transformational, transactional, and genuine leadership styles; and job satisfaction was positively related to transformational and authentic leadership styles. In particular, the transformational leadership style showed higher employee retention and job satisfaction rates than the transactional and non-interventional leadership styles. The original and transformative leadership styles increased job satisfaction and commitment, but the correlation between an authentic leadership style and these benefits was less clear. Clinical professionals must apply a transformational leadership style to become influential leaders.

Recruiting Resident Participants from Nursing Homes During the COVID Pandemic: Challenges and Solutions

Recruiting nursing home residents as participants in research is challenging. In early 2021, Covid-19 cases rose rapidly in nursing homes, prompting the rapid deployment of infectious disease protocols and ultimately, facility lockdowns to control the spread of the virus. By September, 2020, many research projects were delayed or cancelled, and future research was jeopardized. During this period, as well as prior to and after the administration of the COVID vaccine, we enrolled residents in a complex protocol involving administration of two Shingles vaccines (0- and 90 days) and three separate blood samples. Here, we present the strategies we used to recruit 216 residents, from 23 homes, over a 9-month period. We faced many challenges. Our research staff faced weekly COVID-19 antigen tests prior to entering the facility, adhering to strict protocols on travel, as well as packaging of materials that entered and left the facility. N95 masks and face shields further made it difficult to communicate with residents. For homes, COVID protocols required residents to be transported to specified areas to meet with research staff. Daily monitoring of COVID and Shingrix vaccine symptoms became part of daily care. To minimize resident harm and interruption of workflow in nursing homes, we utilized principles of stakeholder engagement, healthcare leadership, infectious disease/immunology, and staff (research and nursing homes) empowerment. In the face of crisis, like the COVID-19 pandemic, we have gained the trust and commitment of these facilities; thus, establishing a sustainable partnership that is prepared for what comes next.

Surgery Sequencing Coordination with Recovery Resource Constraints

Surgical practice administrators need to determine the sequence of surgeries and reserved operating room (OR) time for each surgery in the surgery scheduling process. Both decisions require coordination among multiple ORs and the recovery resource in the postanesthesia care unit (PACU) in a surgical suite. Although existing studies have addressed OR time reservation, surgery sequencing coordination is an open challenge in the stochastic surgical environment. In this paper, we propose an algorithmic solution to this problem based on stochastic optimization. The proposed methodology involves the development of a surrogate objective function that is highly correlated with the original one. The resulting surrogate model has network-structured subproblems after Lagrangian relaxation and decomposition, which makes it easier to solve than the impractically difficult original problem. We show that our proposed approach finds near-optimal solutions in small instances and outperforms benchmark methods by 13%–51% or equivalently an estimated saving of $760–$7,420 per day in surgical suites with 4–10 ORs. Our results illustrate a mechanism to alleviate congestion in the PACU. We also recommend that practice administrators prioritize sequencing coordination over the optimization of OR time reservation in an effort for performance improvement. Furthermore, we demonstrate how administrators should consider the impact of sequencing decisions when making strategic capacity adjustments for the PACU. Summary of Contribution: Our work provides an algorithmic solution to an open question in the field of healthcare operations management. This solution approach involves formulating a surrogate optimization model and exploiting its decomposability and network-structure. In computational experiments, we quantitatively benchmark its performance and assess its benefits. Our numerical results provide unique managerial insights for healthcare leadership.