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Diffusion of innovations, defined as the adoption and implementation of new ideas, processes, products, or services in health care, is both particularly important and especially challenging. One known problem with adoption and implementation of new technologies is that, while organizations often make innovations immediately available, organizational actors are more wary about adopting new technologies because these may impact not only patients and practices but also reimbursement. As a result, innovations may remain underutilized, and organizations may miss opportunities to improve and advance. As innovation adoption is vital to achieving success and remaining competitive, it is important to measure and understand factors that impact innovation diffusion. Building on a survey of a national sample of 654 clinicians, our study measures the extent of diffusion of value-enhancing care delivery innovations (i.e., technologies that not only improve quality of care but has potential to reduce care cost by diminishing waste, Faems et al., 2010) for 13 clinical specialties and identifies healthcare-specific individual characteristics such as: professional purview, supervisory responsibility, financial incentive, and clinical tenure associated with innovation diffusion. We also examine the association of innovation diffusion with perceived value of one type of care delivery innovation – artificial intelligence (AI) – for assisting clinicians in their clinical work. Responses indicate that less than two-thirds of clinicians were knowledgeable about and aware of relevant value-enhancing care delivery innovations. Clinicians with broader professional purview, more supervisory responsibility, and stronger financial incentives had higher innovation diffusion scores, indicating greater knowledge and awareness of value-enhancing, care delivery innovations. Higher levels of knowledge of the innovations and awareness of their implementation were associated with higher perceptions of the value of AI-based technology. Our study contributes to our knowledge of diffusion of innovation in healthcare delivery and highlights potential mechanisms for speeding innovation diffusion.

High-quality nursing home (NH) care has long been a challenge within the United States. For decades, policymakers at the state and federal levels have adopted and implemented regulations to target critical components of NH care outcomes. Simultaneously, our delivery system continues to change the role of NHs in patient care. For example, more acute patients are cared for in NHs, and the Center for Medicare and Medicaid Services (CMS) has implemented value payment programs targeting NH settings. As a part of these growing pressures from the broader healthcare delivery system, the culture-change movement has emerged among NHs over the past two decades, prompting NHs to embody more person-centered care as well as promote settings which resemble someone's home, as opposed to institutionalized healthcare settings.

Researchers have linked culture change to high-quality outcomes and the ability to adapt and respond to the ever-changing pressures brought on by changes in our regulatory and delivery system. Making enduring culture change within organizations has long been a challenge and focus in NHs. Despite research suggesting that culture-change initiatives that promote greater resident-centered care are associated with several desirable patient outcomes, their adoption and implementation by NHs are resource intensive, and research has shown that NHs with high percentages of low-income residents are especially challenged to adopt these initiatives.

This chapter takes a novel approach to examine factors that impact the adoption of culture-change initiatives by assessing knowledge management and the role of knowledge management activities in promoting the adoption of innovative care delivery models among under-resourced NHs throughout the United States. Using primary data from a survey of NH administrators, we conducted logistic regression models to assess the relationship between knowledge management and the adoption of a culture-change initiative as well as whether these relationships were moderated by leadership and staffing stability. Our study found that NHs were more likely to adopt a culture-change initiative when they had more robust knowledge management activities. Moreover, knowledge management activities were particularly effective at promoting adoption in NHs that struggle with leadership and nursing staff instability. Our findings support the notion that knowledge management activities can help NHs acquire and mobilize informational resources to support the adoption of care delivery innovations, thus highlighting opportunities to more effectively target efforts to stimulate the adoption and spread of these initiatives.

At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.

This chapter demonstrates the ways in which digital inclusion functions as a super social determinant of health, particularly within the arena of family carework and healthcare for vulnerable disabled US communities. The focus on vulnerable populations, including the elderly, chronically ill, young disabled, neurodivergent, and/or medically complex children and the families that care for them, is a useful case to present a compelling argument for the need to take seriously digital inclusion to maximize health, safety, and well-being for growing populations of Americans today. The authors argue that digital inclusion is an increasingly influential social determinant of health and a key dimension of health equity that offers important benefits and potentials, especially for vulnerable patient populations, for whom in-home and family-centered care are necessary parts of health maintenance, prevention, and well-being. The chapter ends with a discussion of ways that the US government can mitigate digital barriers and facilitate equitable access to broadband internet and e-health resources that address the intersections of digital, health, and care inequalities, with significant impacts in all three dimensions.

While uncertainty has always been a feature of the healthcare environment, its pace and scope are rapidly increasing, fueled by myriad factors such as technological advancements, the threat and frequency of disruptive events, global economic developments, and increasing complexity. Contemporary healthcare organizations thus persistently face what is known as “deep uncertainty,” which obscures their ability to predict outcomes of strategic action and decision-making, presenting them with novel challenges and threatening their survival. Persistent, deep uncertainty challenges us to revisit and reconsider how we think about uncertainty and the strategic actions needed by organizations to thrive under these circumstances. Simply put, how can healthcare organizations thrive in the face of deeply uncertain environments? We argue that healthcare organizations need to employ both adaptive and creative strategic approaches in order to effectively meet patients' needs and capture value in the long-term future. The chapter concludes by offering two ways organizations can build the dynamic capabilities needed to employ such approaches.