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Background – Reliable and valid hospital nurse staffing measures are a major requirement for health services research. As the use of these measures increases, discussion is growing as to whether current nurse staffing measures adequately meet the needs of health services researchers.

Objective – This study assesses whether the measures, sampling frameworks, and data sources meet the needs of health services research in areas such as staffing assessment; patient, nurse, and financial outcomes; and prediction of staffing.

Methods – We performed a systematic review of articles from 1990 through 2007, which use hospital nurse staffing measures in original research, or which address the validity, reliability, and availability of the measures. Taxonomies of measures, sampling frameworks, and sources were developed. Articles were analyzed to assess what measures, sampling strategies, and sources of data were used and to ascertain whether the measures, samples, and sources meet the needs of researchers.

Results – The review identified 107 articles that use hospital nurse staffing measures for original research. Multiple types of measures, some of which are used more often than others and some of which are more valid than others, exist in each of the following categories: staffing counts, staffing/patient load ratios, and skill mix. Sampling frameworks range from hospital units to all hospitals nationally, with all hospitals in a state being the most common. Data sources range from small-scale surveys to national databases. The American Hospital Association Annual Survey is the most frequently used data source, but there are limitations with its nurse staffing measures. Arguably, the multiplicity of measures and differences in sampling and data sources are due, in part, to data availability. The limitations noted by other researchers and by this review indicate that staffing measures need improvements in conceptualization, content, scope, and availability.

Discussion – Recommendations are made for improvements to research and administrative practice and to data.

A system of care is a function-specific, rather than agency-specific approach defined as a “comprehensive spectrum of mental health and other necessary services which are organized into a coordinated network to meet the multiple and changing needs of children and adolescents with severe emotional disturbances and their families” (Stroul & Friedman, 1986). A system of care provides a mental health delivery system for children with SED with a wide array of accessible, community-based services that focus on children's individual needs, include the family in treatment planning, and provide culturally competent services. System of care services are provided by multiple child serving agencies and are collaborative and coordinated (Stroul & Friedman, 1986).

Workplace voice is well-established and encompasses behaviors such as prosocial voice, informal complaints, grievance filing, and whistleblowing, and it focuses on interactions between the employee and supervisor or the employee and the organizational collective. In contrast, our chapter focuses on employee prosocial advocacy voice (PAV), which the authors define as prosocial voice behaviors aimed at preventing harm or promoting constructive changes by advocating on behalf of others. In the context of a healthcare organization, low quality and unsafe patient care are salient and objectionable states in which voice can motivate actions on behalf of the patient to improve information exchanges, governance, and outreach activities for safer outcomes. The authors draw from the theory and research on responsibility to intersect with theories on information processing, accountability, and stakeholders that operate through voice between the employee-patient, employee-coworker, and employee-profession, respectively, to propose a model of PAV in patient-centered healthcare. The authors complete the model by suggesting intervening influences and barriers to PAV that may affect patient-centered outcomes.

This chapter investigates whether signing more hospital contracts with Health Maintenance Organizations (HMOs) and Preferred Provider Organizations (PPOs), hospital affiliation in a system, having more system hospital members located in the same area, and increased competition from area hospitals, contributes to improvements in the cost efficiency of U.S. Midwestern hospitals. Hospitals may offer HMOs and PPOs discounts on contracts to provide health care services to firm employees enrolled in HMOs and PPOs (discounts would lead to smaller price mark-ups over costs for hospital services). Enacting policies to enhance cost efficiency may help hospitals maintain a specified level of profits.

Research suggests that improving hospital work environments and solving the nursing shortage are critical to improving patient care. The Houston–Galveston region created an aggressive approach to this issue by forming an unusual coalition of business, university, and hospital leaders and using a quality improvement approach. Four years later, the project has achieved over 40% participation among hospitals in the 13-county region and includes 50 hospitals employing approximately 15,000 registered nurses. The data that have been collected by this collaborative to date suggests that hospitals are taking action to improve outcomes by modifying their key initiatives to address the attributed causes of poor work environments. From 2004 to 2005, executives of top performing hospitals increasingly attributed successful work environment outcomes to an emphasis on management development and executive-driven initiatives, de-emphasizing specific employee behavior, process, and outcome-based initiatives.

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.