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The value of the ambulatory care nurse remains undocumented from a quality and patient safety measurement perspective and the practice is at risk of being highly variable and of unknown quality. The American Academy of Ambulatory Care Nursing and the Collaborative Alliance for Nursing Outcomes propose nurse leaders create a tipping point to measure the value of nursing across the continuum of nursing care, moving from inpatient to ambulatory care. As care continues to shift into the ambulatory care environment, the quality imperative must also shift to assure highly reliable, safe, and effective health care.

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OBJECTIVE: Predictive models for falls, injury falls, and restraint prevalence were explored within nursing unit structures and processes of care. BACKGROUND: The patient care team is responsible for patient safety, and improving practice models may prevent injuries and improve patient safety. METHODS: Using unit-level self-reported data from 215 hospitals, falls, injury falls, and restraint prevalence were modeled with significant covariates as predictors. RESULTS: Fewer falls/injury falls were predicted by populations with fewer frail and at-risk patients, more unlicensed care hours, and prevention protocol implementation, but not staffing per se, restraint use, or RN expertise. Lower restraint use was predicted by fewer frail patients, shorter length of stay, more RN hours, more certified RNs, and implementation of fall prevention protocols. CONCLUSION: In the presence of risk, patient injuries and safety were improved by optimizing staffing skill mix and use of prevention protocols.

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OBJECTIVE: This study modeled the predictive power of unit/patient characteristics, nurse workload, nurse expertise, and hospital-acquired pressure ulcer (HAPU) preventive clinical processes of care on unit-level prevalence of HAPUs. DATA SOURCES: Seven hundred and eighty-nine medical-surgical units (215 hospitals) in 2009. STUDY DESIGN: Using unit-level data, HAPUs were modeled with Poisson regression with zero-inflation (due to low prevalence of HAPUs) with significant covariates as predictors. DATA COLLECTION/EXTRACTION METHODS: Hospitals submitted data on NQF endorsed ongoing performance measures to CALNOC registry. PRINCIPAL FINDINGS: Fewer HAPUs were predicted by a combination of unit/patient characteristics (shorter length of stay, fewer patients at-risk, fewer male patients), RN workload (more hours of care, greater patient [bed] turnover), RN expertise (more years of experience, fewer contract staff hours), and processes of care (more risk assessment completed). CONCLUSIONS: Unit/patient characteristics were potent HAPU predictors yet generally are not modifiable. RN workload, nurse expertise, and processes of care (risk assessment/interventions) are significant predictors that can be addressed to reduce HAPU. Support strategies may be needed for units where experienced full-time nurses are not available for HAPU prevention. Further research is warranted to test these finding in the context of higher HAPU prevalence.

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The Patient Protection and Affordable Care Act (PPACA, 2010) and the Institute of Medicine's (IOM, 2011) Future of Nursing report have prompted changes in the U.S. health care system. This has also stimulated a new direction of thinking for the profession of nursing. New payment and priority structures, where value is placed ahead of volume in care, will start to define our health system in new and unknown ways for years. One thing we all know for sure: we cannot afford the same inefficient models and systems of care of yesterday any longer. The Data-Driven Model for Excellence in Staffing was created as the organizing framework to lead the development of best practices for nurse staffing across the continuum through research and innovation. Regardless of the setting, nurses must integrate multiple concepts with the value of professional nursing to create new care and staffing models. Traditional models demonstrate that nurses are a commodity. If the profession is to make any significant changes in nurse staffing, it is through the articulation of the value of our professional practice within the overall health care environment. This position paper is organized around the concepts from the Data-Driven Model for Excellence in Staffing. The main concepts are: Core Concept 1: Users and Patients of Health Care, Core Concept 2: Providers of Health Care, Core Concept 3: Environment of Care, Core Concept 4: Delivery of Care, Core Concept 5: Quality, Safety, and Outcomes of Care. This position paper provides a comprehensive view of those concepts and components, why those concepts and components are important in this new era of nurse staffing, and a 3-year challenge that will push the nursing profession forward in all settings across the care continuum. There are decades of research supporting various changes to nurse staffing. Yet little has been done to move that research into practice and operations. While the primary goal of this position paper is to generate research and innovative thinking about nurse staffing across all health care settings, a second goal is to stimulate additional publications. This includes a goal of at least 20 articles in Nursing Economic$ on best practices in staffing and care models from across the continuum over the next 3 years.

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Public demand for safer care has catapulted the healthcare industry's efforts to understand relationships between patient safety and hospital performance. This study explored linkages between staff perceptions of safety culture (SC) and ongoing measures of hospital nursing unit-based structures, care processes, and adverse patient outcomes. Relationships between nursing-sensitive measures of hospital performance and SC were explored at the unit-level from 9 California hospitals and 37 nursing units. SC perceptions were measured 6 months prior to collection of nursing metrics and relationships between the two sets of data were explored using correlational and regression analyses. Significant relationships were found with reported falls and process measures for fall prevention. Multiple associations were identified with SC and the structure of care delivery: skill mix, staff turnover, and workload intensity demonstrated significant relationships with SC, explaining 22-45% of the variance. SC was an important factor to understand in the quest to advance safe patient care. These findings have affordability and care quality implications for hospital leadership. When senior leaders prioritized a safety culture, patient outcomes may have improved with less staff turnover and more productivity. A business case could be made for investing in patient safety systems to provide reliably safe care.

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Hospital-acquired pressure ulcers (HAPUs) are a serious nosocomial problem that has been viewed as a ubiquitous consequence of immobility. This article provides data from the Collaborative Alliance for Nursing Outcomes (CALNOC) that shows a significant reduction in HAPUs in adults from 78 acute care hospitals over 8 years (2003-2010).

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Benchmarking expedites the quest for best practices and is crucial to hospitals' effective, reliable, and superior performance. Comparative performance data are used by accrediting and regulatory bodies to evaluate performance and by consumers in making decisions on where to seek healthcare. Nursing-sensitive quality measures affirmed by the National Quality Forum are now used in public reporting and pay-for-performance in addition to traditional medical outcome metrics. This report provides hospital nursing-sensitive benchmarks from medical/surgical, critical care, and step-down units drawn from 196 hospitals during six quarters in 2007 and 2008. Outcome measures include pressure ulcer prevalence rates and fall/falls with injury rates. Additional indicators that describe nursing care (nurse staffing care hours, skill mix, nurse/patient ratios, workload intensity, voluntary turnover, and use of sitters) and patient descriptors (age, gender, and diagnosis description) were also included. Specific benchmarks are provided using the 10th and the 90th percentiles, as well as quartiles to allow hospitals an opportunity to understand comparative performance with specificity. The purpose of this article is to provide hospitals not currently participating in comparative benchmarking databases with nursing-sensitive data from the Collaborative Alliance for Nursing Outcomes for use in performance improvement processes.

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Benchmarking is an indispensable tool as hospital leaders face challenges to balance efficiency with safe and effective care. Selection of appropriate "like" hospitals is critical to the benchmarking aim of understanding comparative performance. Based on 10 years of observed outcome differences between small and large hospitals, the Collaborative Alliance for Nursing Outcomes (CALNOC) sought to empirically define small hospitals, and to determine if there were statistical differences between small and large hospitals for selected nursing sensitive outcome indicators. This article reports the examination of hospital size as a proxy characteristic to define "like" hospitals for the purpose of benchmarking outcomes. Findings suggest that optimal classifications into small and large hospital size based on the outcome indicators of falls, falls with injury, and hospital-acquired pressure ulcers stage 2 or worse (HAPU 2+) were not consistent with historical administrative categories based on average daily census and not consistent by outcome. Statistical differences were only found with HAPU 2+ in critical care units, with no differences in the fall outcomes. These data did not support the use of size-based categories to define like hospitals for benchmark comparisons.

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Quality professionals are the first to understand challenges of transforming data into meaningful information for frontline staff, operational managers, and governing bodies. To understand an individual facility, service, or patient care unit's comparative performance from within large data sets, prioritization and focused data presentation are needed. This article presents a methodology for translating data from large data sets into dashboards for setting performance improvement priorities, in a simple way that takes advantage of tools readily available and easily used by support staff. This methodology is illustrated with examples from a large nursing quality data set, the California Nursing Outcomes Coalition.

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This article examines the impact of mandated nursing ratios in California on key measures of nursing quality among adults in acute care hospitals. This study is a follow-up and extension of our first analysis exploring nurse staffing and nursing-sensitive outcomes comparing 2002 pre-ratios regulation data to 2004 postratios regulation data. For the current study we used postregulation ratios data from 2004 and 2006 to assess trends in staffing and outcomes. Findings for nurse staffing affirmed the trends noted in 2005 and indicated that changes in nurse staffing were consistent with expected increases in the proportion of licensed staff per patient. This report includes an exploratory examination of the relationship between staffing and nursing-sensitive patient outcomes. However anticipated improvements in nursing-sensitive patient outcomes were not observed. This report contributes to the growing understanding of the impacts of regulatory staffing mandates on hospital operations and patient outcomes.

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Using nursing quality benchmarks in operational dashboards and translating those data to drive performance excellence is a strategic imperative. Since access to unit-level, hospital-generated nurse-related benchmarks is an emerging arena, the authors provide an overview of aggregated trends and benchmarks gleaned from the California Nursing Outcome Coalition acute care database for 2 established nurse-related quality indicators-patient falls incidence and hospital-acquired pressure ulcer prevalence. Integrating these acute care benchmarks into clinical dashboards can be invaluable to clinicians, administrators, and policy makers who share a common commitment to expediting evidence-based improvement in patient care safety, outcomes, and excellence.

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PURPOSE: To explicate a replicable methodology for designing and analyzing a large ongoing reliable and valid quality database to examine nurse staffing and patient care outcomes in acute care hospitals. DESIGN: Prospective nurse staffing, process of care, and patient outcomes data based on the American Nurses Association's (ANA) nursing quality indicators collected from a voluntary convenience sample at acute care hospitals in California with rolling-site accrual. METHODS: The ongoing CalNOC database development and repository project, the largest statewide effort of its kind in the United States (US), currently includes data on hospital nurse staffing, patient days, patient falls, pressure ulcer and restraint prevalence, registered nurse (RN) education, and patients' perceptions of satisfaction with care. FINDINGS: As of May 2003, the CalNOC database contained staffing data from 842 units in 134 acute care hospitals over 20 quarters from April 1998 to March 2003. The repository also included clinical outcome information on 34,262 reported patient falls, pressure ulcer prevalence data on 41,982 patient observations, and service outcome data on patient satisfaction from 26,461 patients. Participating hospitals receive quarterly reports allowing them to benchmark their own performance against other participating hospitals. CalNOC methods have been adapted and replicated by both the Military Nursing Outcomes Database and VA Nursing Outcomes Database projects, and CalNOC nursing-sensitive measures have been endorsed by the National Quality Forum. CONCLUSIONS: This working model for collecting reliable and valid data was derived from multiple hospitals across California. The data are the basis for studies to contribute to the development of evidence-based public policy, and for ongoing study of the effects of nurse staffing on clinical and service outcomes.

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UNLABELLED: OBJECTIVE To examine the relationship between nurse staffing and patient perceptions of nursing care in a convenience sample of 40 California hospitals. BACKGROUND: Growing concern about the adequacy of nurse staffing has led to an increased emphasis on research exploring the relationships between nurse staffing and patient outcomes. Patient satisfaction with nursing care is one of the 21 indicators identified by the American Nurses Association as having a strong "theoretical link to the availability and quality of professional nursing services in hospital settings." This prospective study examined the relationship between nurse staffing and patient perceptions of nursing care in multiple hospitals using common definitions of both nurse staffing and patient perceptions of care. METHODS: Nurse staffing (structural variables) and patient perceptions of nursing care (outcome variables) from hospitals participating in both the ongoing California Nursing Outcomes Coalition statewide database project and the statewide Patients' Evaluation of Performance in California project, with data available on both measures for the same time periods, were examined. Analytic methods included both descriptive and inferential statistics. RESULTS: Hospitals with wide ranges of staffing levels showed similar results in patient perceptions of nursing care. Regression analysis revealed a statistically significant relationship between nursing hours per patient day, and 1 of the 6 dimensions of care measured ("respect for patient's values, preferences, and expressed needs"). CONCLUSIONS: Nurse staffing alone showed a significant but weak relationship to patient perceptions of their care, indicating that staffing is likely only one of several relevant variables influencing patient perceptions of their nursing care. This research contributes data to the body of knowledge regarding nurse staffing. It is essential that nurse executives integrate results from this and other studies in developing strategic and tactical staffing plans that yield positive patient care outcomes.

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The Kaiser Permanente North East Bay service area redesigned its quality program beginning in 1995, to better mirror how care was provided across the continuum. The old model had evolved over time, was based on departmental structure, and did not focus on all patient populations. The purpose of this article is to describe the redesign process, the quality model implemented, and future directions, with the hope that the lessons learned will provide other healthcare quality professionals some of the knowledge needed and, perhaps, the courage to "design" their quality programs.

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Healthcare quality professionals in the United States have opportunities to teach healthcare providers in other countries how to measure and monitor quality. Special preparation is required to effectively teach an international audience. This article offers tips for teaching basic quality concepts based upon the authors' experiences in the People's Republic of China. Working with health professionals in other countries is exciting and challenging for everyone involved. Approaching the opportunity with systematic preparation may be the key to success.

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