CE: Nursing Orientation to Data Science and Machine Learning.

ABSTRACT: Nurses collect, use, and produce data every day in countless ways, such as when assessing and treating patients, performing administrative functions, and engaging in strategic planning in their organizations and communities. These data are aggregated into large data sets in health care systems, public and private databases, and academic research settings. In recent years the machines used in this work (computer hardware) have become increasingly able to analyze large data sets, or "big data," at high speed. Data scientists use machine learning tools to aid in analyzing this big data, such as data amassed from large numbers of electronic health records. In health care, predictions for patient outcomes has become a focus of research using machine learning. It's important for nurses and nurse administrators to understand how machine learning has changed our ways of thinking about data and turning data into knowledge that can improve patient care. This article provides an orientation to machine learning and data science, offers an understanding of current challenges and opportunities, and describes the nursing implications for nurses in various roles.

Decreasing Central Line-Associated Bloodstream Infections Acquired in the Home Setting Among Pediatric Oncology Patients [Formula: see text].

Most children receiving cancer treatment require a central venous catheter (CVC), putting them at risk for central line-associated bloodstream infections (CLABSI). As patients are discharged home with a CVC in place, caregivers are expected to maintain the CVC following an in-hospital education session before their first discharge home. Following a review of the literature, the education process was modified to improve the quality of education for caregivers. While the existing step-by-step handbook was reviewed and deemed aligned with best practices, other materials were added for this project: a caregiver skills competency checklist, a handout reviewing oral care and hygiene in the home, and a guide for nurses on what materials to provide families at the time of diagnosis. Additionally, caregivers were required to receive two additional CVC care reinforcement sessions during subsequent admissions to the inpatient units, which involved redemonstrations of skills using the competency checklist. Home-acquired CLABSI in pre- and postintervention groups were compared, and compliance of reinforcement education was measured. Though no statistical significance was found, the odds of experiencing a CLABSI were found to be higher in the preintervention group for mucosal-barrier injury (odds ratio = 2.23; 95% confidence interval [0.43, 22.10]) and laboratory-confirmed bloodstream infections (odds ratio = 4.53; 95% confidence interval [0.59, 203.71]). The clinical significance of reducing home-acquired CLABSI has a positive impact on patient outcomes by decreasing morbidity and mortality, inpatient lengths of stay, and overall health care costs.

Evidence-Based Quality Improvement Training Programs: Building Staff Capability and Organizational Capacity.

BACKGROUND: Patient harm from medical errors is frequently the result of poorly designed systems. Quality improvement (QI) training programs should build staff capability and organizational capacity for improving systems. PROBLEM: Lack of internal expertise in QI and financial impact of hiring consultants deter organizations from developing QI training. APPROACH: One safety net hospital, with minimal resources, used evidence-based elements to create a Quality Academy Program. OUTCOMES: Significant outcomes demonstrated individual capability in undertaking QI initiatives. Staff who continued QI posttraining and the number of initiatives launched demonstrated organizational capacity. Feedback showed an increase in confidence with projects intended to improve care processes and patient outcomes. CONCLUSIONS: The elements shown to be essential in QI programs to build capability and capacity for organizational improvement can improve patient outcomes and organizational work processes as well as impact staff engagement and morale.

Transformational quality in Kaiser Permanente Northern California.

The evolving nature of health care related to optimizing the quality of patient care while increasing efficiencies presents an opportunity to redesign roles within hospital quality departments to meet these upcoming challenges. Specifically, passage of the Patient Protection and Affordable Care Act and creation of Accountable Care Organizations will require hospitals to carefully monitor patient care outcomes as well as continually seek to improve their processes. An approach used by the Kaiser Permanente Northern California Regional Quality and Regulatory Services Department assisted the 21 hospitals of Kaiser Permanente Northern California to improve quality-of-care outcomes, establish effective assessment teams, and create infrastructure for sustainability. Leadership by a centralized internal consulting group used a model that weighs risk and opportunity against cost and outcomes to support strategic planning as projects and initiatives developed, rather than after they were initiated. This model can assist other organizations in maximizing cost-efficient and -effective performance improvement approaches to clinical and operational excellence.

AHRQ's hospital survey on patient safety culture: psychometric analyses.

OBJECTIVE: This project analyzed the psychometric properties of the Agency for Healthcare Research and Quality Hospital Survey on Patient Safety Culture (HSOPSC) including factor structure, interitem reliability and intraclass correlations, usefulness for assessment, predictive validity, and sensitivity. METHODS: The survey was administered to 454 health care staff in 3 hospitals before and after a series of multidisciplinary interventions designed to improve safety culture. Respondents (before, 434; after, 368) included nurses, physicians, pharmacists, and other hospital staff members. RESULTS: Factor analysis partially confirmed the validity of the HSOPSC subscales. Interitem consistency reliability was above 0.7 for 5 subscales; the staffing subscale had the lowest reliability coefficients. The intraclass correlation coefficients, agreement among the members of each unit, were within recommended ranges. The pattern of high and low scores across the subscales of the HSOPSC in the study hospitals were similar to the sample of Pacific region hospitals reported by the Agency for Healthcare Research and Quality and corresponded to the proportion of items in each subscale that are worded negatively (reverse scored). Most of the unit and hospital dimensions were correlated with the Safety Grade outcome measure in the tool. CONCLUSION: Overall, the tool was shown to have moderate-to-strong validity and reliability, with the exception of the staffing subscale. The usefulness in assessing areas of strength and weakness for hospitals or units among the culture subscales is questionable. The culture subscales were shown to correlate with the perceived outcomes, but further study is needed to determine true predictive validity.