Healthcare services for the aging population in the United States are a complex configuration of acute healthcare organizations, and post acute nursing facilities, home healthcare, and community based services. The system encompasses all services that imply the need for clinical, medical, or professional judgment (Baldrige National Quality Program, 2006). Most Americans believe the system exists to provide preventive services, management for chronic conditions, and health care services to meet the needs of the people (National Committee for Quality Assurance (NCQA), 2004). However, the healthcare delivery system is fragmented across a broad array of settings (Coleman, Smith, Frank, Min, Parry, & Kramer, 2004), plagued by gaps in quality of care, and does not provide optimal care to the majority of American citizens (NCQA, 2004). As a result, national efforts are focused on the identification of quality indicators, performance measures, and the driving need for consensus standards across a multiplicity of providers, payers, and stakeholders. The overarching focus of this effort is to bridge the gaps in health care quality, and reduce documented disparities for vulnerable populations (National Quality Forum (2004). Healthcare transitions occur as patients receive a broad range of services across a multiplicity of providers, payers, and settings. Aging patients > 65 are most vulnerable during these transitions. A poorly executed transition can result in complications for the patient, duplication of tests and services, discharge delays, increased lengths of stay, early readmissions to the acute care setting, frustration for families and care givers, and dissatisfaction with overall services. Management of care and accountability across settings is limited and patients are falling through the cracks in the foundation of the healthcare system (Covinsky, 2003). The intent of this research was to examine healthcare transitions for patients > 65 admitted to a large acute healthcare system, and to identify measurable quality indicators for an innovative delivery model designed to optimize early discharge from the hospital through rapid rehabilitation. This was a quasi-experimental, cross-sectional design measured at the patient level. The research included a total sample of 250 patients representing both the intervention and the control group. The intervention group consisted of 100 patients who were rapidly discharged to a transitional care facility in the community, and 150 patients randomly selected to a control group that did not transition to rapid rehabilitation. The groups were matched as closely as possible by age, gender, race, primary diagnoses, and the complexity of case. Inefficiency was measured by 3 indicators (1) length of stay, (2) total expenses before contractual allowances, and (3) discharge delays from the hospital. Ineffectiveness was measured by 3 indicators: (1) readmission within 30 days, (2) patient safety with falls serving as the proxy, and (3) overall patient satisfaction. Descriptive analysis was performed utilizing SPSS 15.0. Path analysis was method of choice for data analysis and AMOS 7.0 was utilized for the measurement model. Descriptive analysis found a broad range of diagnosis related groups across 183 women and 67 men with a mean age of 80 for both groups. Initial analysis found the intervention group had a mean length of stay of 9.17 days, and experienced 20 readmissions. The control group had a mean length of stay of 6.77 days, and 30 readmissions. The statistical analysis suggested length of stay and cost of healthcare services are statistically significant indicators at the 0.05 or lower level and that patient safety has the potential to be developed as an indicator for effective outcomes. The identification of quality indicators, measurement of efficiency and effectiveness, and establishing predictors for successful healthcare transitions is dependent on the quality and integrity of data abstracted from hospital information systems, accuracy of information in patient records, and the consensus of standards and definitions across a multiplicity of stakeholders. Further research and collaboration is necessary to ensure that patient transition to innovative care programs such as rapid rehabilitation is based on well-defined patient selection criteria. The intent of the methodologies and quality indicators explored in this research supports the increasing need to ensure that inferences and quality measurements drawn from healthcare information is based on valid, reliable, and well defined data sources (Pan, Fergusson, Schweitzer, & Hebert, 2005). This research suggests hospitals are making steady progress to overcome challenges to safe, quality health services as outlined by the Institute of Medicine (2001) for system redesign, but finds specific implications for hospital leadership. There is a need to thread evidence based practice initiatives into hospital and clinical structures to accommodate new delivery models, processes, and case management. Health services information needs to be housed in a central repository or data warehouse to increase transparency of reportable information across systems and to ensure that valid and reliable information is utilized to draw inferences about performance of hospital systems (Selden & Sowa, 2004) and that quality measurements are established to ensure a scientific foundation for the management of healthcare services (Wan, 2002).

Each year in the United States, thousands of people are readmitted within 30 days of being discharged from a hospital. Current research indicates that at least one-third of these rehospitalizations are preventable. The purpose of this project was to examine patient and environmental characteristics of those who were readmitted within 30 days of discharge for commonalities that may explain the gap in practice for a specific health care organization. The project was undertaken in response to the organization's need to improve a 50th-percentile ranking with the goal of reaching the top 10th percentile. A plan-do study-act framework was used as a guide to ensure no steps in the process were missed and the logical progression of the project was clear. Three fiscal quarters of data, including 515 readmissions, were examined. A data analytics cube on hospital-wide readmissions provided patient and environmental characteristics that were charted using common language for sorting purposes. Data analysis revealed that 77% of patients were admitted within 30 days of discharge with a diagnosis that differed significantly from the index admission. Potential gaps in practice identified were a need for more patient and family engagement and education by nursing during the inpatient stay in regard to the primary admitting condition, the management of comorbidities, and potential posthospital complications. Need exists for more intense whole-patient monitoring, communication, and education following the transition from hospital to home. A reduction in 30-day readmissions can reduce the psychological and physical burden on patients and families, on health care resources that could be used for other purposes, and on society in the form of financial costs that continue to rise.