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Patient length of stay (LOS) is an important indicator of emergency department (ED) performance. Investigating factors that influence LOS could thus improve healthcare delivery and patient safety. Previous studies have focused on patient-level factors to explain LOS variation, with little research into service-related factors. This study examined the association between LOS and multi-level factors including patient-, service- and organization-level factors.

This study uses a retrospective observational design to identify a cohort of patients from arrival to discharge from ED. A year-long data regarding patients flow trhoguh ED were analyzed using analytics techniques and multi-regression models. The response variable was patient LOS, and the independent variables were patient characteristics, service-related factors and organizational variables.

The findings of this study showed that older patients, middle triage and hospitalization were all associated with longer LOS. Service-related factors such as complexity of care provided, initial ward designation and ward transfer had a significant impact as well. Finally, prolonged LOS was associated with a higher ratio of patients per medical doctor and per nurse. In contrast, a higher number of residents in the ED were associated with longer patient LOS.

Previous studies on patient LOS have focused on patient-level factors, with little research on service-related factors. This study has addressed that gap by examining the association between LOS and multi-level factors including patient-, service- and organization-level factors. Patient-level factors included demographics, acuity, arrival shift, arrival mode and discharge type. Service-level factors consisted of first ward, ward transfer and complexity of care provided. Organizational factors consisted of three ratios: patients per MD, patients per nurse and patients per resident. The results add to the current understanding of factors that increase patient LOS in EDs and contribute to the body of knowledge on ED performance, operation management and quality of care. The study also provides practical and managerial insights that could be used to improve patient flow in EDs and reduce LOS.

The article is a description of the real-life experience based on the implementation of a financial forecasting model to inform budgeting and strategic planning. The organization is a charity-based health system that has hospitals and medical centers that provide care to the community. The health system performs a central budgeting process which is typically based on aggregation of individual budgets from the various hospitals and medical centers within the system. All financial data are reported to a central financial information system. Traditionally budgeting was done based on prior year's financial performance with a slight adjustment based on the hospital or medical center finance department's educated guess. This article describes the new forecasting method instituted to predict revenue and expenses, and to improve the budget planning process. Finally, the forecasts from the model are compared with real data to demonstrate accuracy of the financial forecasts. The model is since then being used in the budgeting process.

Health care organizations are facing the dual challenge of providing high-quality patient care at an affordable price. In this article, we argue that the role of people, or human resource management (HRM), and information, or health information technologies (HIT), is crucial in surmounting the above challenge. Specifically, we contend that HRM and HIT in health care are fundamental rather than support functions, and health care organizations need to build internal capabilities in both HRM and HIT to manage these resources effectively. Health care organizations vary in their levels of HRM and HIT capabilities. A few exceptional health care organizations have built both of these capabilities and have derived significant complementarities between HRM and HIT that, in turn, have allowed them to be leaders in value-based health care delivery. Several health care organizations have developed capabilities in either HRM or HIT but not in both, and still others have developed capabilities in neither function. Outsourcing of HRM and HIT by health care organizations is likely to hamper the integration and embedding of these functions in organizational operations. Although HIT has attracted significant attention from policy makers and health care organizations alike, it is not so with HRM. Most large-scale HIT initiatives that proceed without strong HRM capabilities are likely to result in disappointing outcomes. This occurs because the organizational change and development embodied in major HIT initiatives often cannot be sustained without strong HRM capabilities.

Hospitals provide care to several thousand patients hospitalized in various nursing units. This process involves admissions of patients entering the nursing units and discharges of patients leaving the nursing units. These admissions and discharges have been identified as hand-off points, and such transitional points have higher potential for errors. Furthermore, admissions and discharges also have several associated activities that need to be accomplished, thus causing an increase in the need for resources like nursing staff, etc., which impacts on efficiency. Hence, a better understanding of the trends and patterns in admissions and discharges is necessary to improve the safety and efficiency of healthcare processes. This healthcare-related forecasting case study uses admission and discharge data from more than 100 thousand patients from 38 nursing units like medicine, surgery, step-down, pediatric, etc., over a three-year period from October 2007 through October 2010 in a large academic health system in the United States. There are two primary goals for this study: (1) to perform pattern analysis on the admission and discharge data, for facility and workforce planning and determining shift structure purposes and (2) to perform forecasting for corrective allocation purposes. Similar methods can be used by other hospitals to improve safety and efficiency.

This research examines how social media helps increase the dynamic capabilities of health organizations. Using the concepts of “technical fitness” and “evolutionary fitness,” the research focuses on changes in: (1) the number of “likes”; (2) the amount of discussions in these pages; and (3) enabling factors for (1) and (2) over time.

Missouri Hospital Association (MHA) provides a sample of 164 hospitals. The Facebook pages of these hospitals are analyzed. Specifically, the number of “likes” and the amount of discussions are readily available for analysis. Data collection was conducted at two time points.

At time 1, 39% of the hospitals had an official Facebook page, increased to 47% at time 2. On average, there was a 22.2% increase in likes and a 4.0% increase in pages of discussions. Whether measured by staffs or patients’ capacity, size is a significant factor that contributes to the increase in likes and discussions. Yet, the location of a hospital — measured by urbanity — is statistically insignificant. Qualitative analyses suggest that certain patient groups particularly welcomed social media. Beside, pictures, videos, and “happy news” tended to increase usage of social media for hospital stakeholders.

Social media can help health organizations fulfill the social needs of their patients. This research applies several useful concepts. In further study, researchers may examine how hospitals optimize staffs’ and patients’ inputs. Besides, comparing how hospitals’ social media platforms operate differently in other states or countries may yield findings with practical implications.

The five articles in this section focus on topics such as pay-for-performance (P4P), high-commitment/high-involvement work practices, and safety culture. Interestingly, the link among all of these articles is in understanding and translating best practices in HRM from manufacturing organizations to health care organizations.