Variability in Catheter-Associated Asymptomatic Bacteriuria Rates Among Individual Nurses in Intensive Care Units: An Observational Cross-Sectional Study

Catheter-associated asymptomatic bacteriuria (CAABU) is frequent in intensive care units (ICUs) and contributes to the routine use of antibiotics and to antibiotic-resistant infections. While nurses are responsible for the implementation of CAABU-prevention guidelines, variability in how individual nurses contribute to CAABU-free rates in ICUs has not been previously explored. This study’s objective was to examine the variability in CAABU-free outcomes of individual ICU nurses. This observational cross-sectional study used shift-level nurse-patient data from the electronic health records from two ICUs in a tertiary medical center in the US between July 2015 and June 2016. We included all adult (18+) catheterized patients with no prior CAABU during the hospital encounter and nurses who provided their care. The CAABU-free outcome was defined as a 0/1 indicator identifying shifts where a previously CAABU-free patient remained CAABU-free (absence of a confirmed urine sample) 24–48 hours following end of shift. The analytical approach used Value-Added Modeling and a split-sample design to estimate and validate nurse-level CAABU-free rates while adjusting for patient characteristics, shift, and ICU type. The sample included 94 nurses, 2,150 patients with 256 confirmed CAABU cases, and 21,729 patient shifts. Patients were 55% male, average age was 60 years. CAABU-free rates of individual nurses varied between 94 and 100 per 100 shifts (Wald test: 227.88, P\u3c0.001) and were robust in cross-validation analyses (correlation coefficient: 0.66, P\u3c0.001). Learning and disseminating effective CAABU-avoidance strategies from top-performers throughout the nursing teams could improve quality of care in ICUs

An approach for estimating measurement uncertainty in medical laboratories using data from long-term quality control and external quality assessment schemes

The present study was prompted by the ISO 15189 requirements that medical laboratories should estimate measurement uncertainty (MU)

Quality and Cost Analysis of Nurse Staffing, Discharge Preparation, and Postdischarge Utilization

Objectives. To determine the impact of unit-level nurse staffing on quality of discharge teaching, patient perception of discharge readiness, and postdischarge readmission and emergency department (ED) visits, and cost-benefit of adjustments to unit nurse staffing. Data Sources. Patient questionnaires, electronic medical records, and administrative data for 1,892 medical–surgical patients from 16 nursing units within four acute care hospitals between January and July 2008. Design. Nested panel data with hospital and unit-level fixed effects and patient and unit-level control variables. Data Collection/Extraction. Registered nurse (RN) staffing was recorded monthly in hours-per-patient-day. Patient questionnaires were completed before discharge. Thirty-day readmission and ED use with reimbursement data were obtained by cross-hospital electronic searches. Principal Findings. Higher RN nonovertime staffing decreased odds of readmission (OR=0.56); higher RN overtime staffing increased odds of ED visit (OR=1.70). RN nonovertime staffing reduced ED visits indirectly, via a sequential path through discharge teaching quality and discharge readiness. Cost analysis projected total savings from 1 SD increase in RN nonovertime staffing and decrease in RN overtime of U.S.$11.64 million and U.S.$544,000 annually for the 16 study units. Conclusions. Postdischarge utilization costs could potentially be reduced by investment in nursing care hours to better prepare patients before hospital discharge

A semiparametric bivariate probit model for joint modeling of outcomes in STEMI patients

In this work we analyse the relationship among in-hospital mortality and a treatment effectiveness outcome in patients affected by ST-Elevation myocardial infarction. The main idea is to carry out a joint modeling of the two outcomes applying a Semiparametric Bivariate Probit Model to data arising from a clinical registry called STEMI Archive. A realistic quantification of the relationship between outcomes can be problematic for several reasons. First, latent factors associated with hospitals organization can affect the treatment efficacy and/or interact with patient’s condition at admission time. Moreover, they can also directly influence the mortality outcome. Such factors can be hardly measurable. Thus, the use of classical estimation methods will clearly result in inconsistent or biased parameter estimates. Secondly, covariate-outcomes relationships can exhibit nonlinear patterns. Provided that proper statistical methods for model fitting in such framework are available, it is possible to employ a simultaneous estimation approach to account for unobservable confounders. Such a framework can also provide flexible covariate structures and model the whole conditional distribution of the response

Patient Satisfaction in the Spanish National Health Service: Partial Least Squares Structural Equation Modeling

The aim of this article was to determine which key indicators influence patient satisfaction with the Spanish NHS to provide useful information for policy decision-making. A total of 33 variables for each of the 17 Spanish autonomous communities were collected from the statistical portal of the Spanish Ministry of Health, Social Services, and Equality between 2005 and 2016. A cross-sectional study was applied using Partial Least Squares to a Structural Equation Model (PLS-SEM). The influence of expenditures, resource allocation, and safety were hypothesized about patient satisfaction. Gross Domestic Product (GDP) and life expectancy were used as control variables. Moreover, the influence of resource allocation on use was tested. The model explained 57.1% of patient satisfaction with the Spanish NHS. It was positively influenced mainly by resource allocation and expenditures, followed by safety and life expectancy. Additionally, resources directly influenced the level of use. The number of hospital beds, hemodialysis equipment, rate of adverse drug reactions, and expenditure positively influenced patient satisfaction. In contrast, the number of posts in day hospitals, the hospital infection rate, and the percentage of pharmacy spending negatively influenced patient satisfaction

An Exploratory Study of Patient Falls

Debate continues between the contribution of education level and clinical expertise in the nursing practice environment. Research suggests a link between Baccalaureate of Science in Nursing (BSN) nurses and positive patient outcomes such as lower mortality, decreased falls, and fewer medication errors. Purpose: To examine if there a negative correlation between patient falls and the level of nurse education at an urban hospital located in Midwest Illinois during the years 2010-2014? Methods: A retrospective crosssectional cohort analysis was conducted using data from the National Database of Nursing Quality Indicators (NDNQI) from the years 2010-2014. Sample: Inpatients aged ≥ 18 years who experienced a unintentional sudden descent, with or without injury that resulted in the patient striking the floor or object and occurred on inpatient nursing units. Results: The regression model was constructed with annual patient falls as the dependent variable and formal education and a log transformed variable for percentage of certified nurses as the independent variables. The model overall is a good fit, F (2,22) = 9.014, p = .001, adj. R2 = .40. Conclusion: Annual patient falls will decrease by increasing the number of nurses with baccalaureate degrees and/or certifications from a professional nursing board-governing body

How to improve drug dosing for patients with renal impairment in primary care - a cluster-randomized controlled trial

Background: Patients with chronic kidney disease (CKD) are at increased risk for inappropriate or potentially harmful prescribing. The aim of this study was to examine whether a multifaceted intervention including the use of a software programme for the estimation of creatinine clearance and recommendation of individual dosage requirements may improve correct dosage adjustment of relevant medications for patients with CKD in primary care. Methods: A cluster-randomized controlled trial was conducted between January and December 2007 in small primary care practices in Germany. Practices were randomly allocated to intervention or control groups. In each practice, we included patients with known CKD and elderly patients (>=70 years) suffering from hypertension. The practices in the intervention group received interactive training and were provided a software programme to assist with individual dose adjustment. The control group performed usual care. Data were collected at baseline and at 6 months. The outcome measures, analyzed across individual patients, included prescriptions exceeding recommended maximum daily doses, with the primary outcome being prescriptions exceeding recommended standard daily doses by 30% or more. Results: Data from 44 general practitioners and 404 patients are included. The intervention was effective in reducing prescriptions exceeding the maximum daily dose per patients, with a trend in reducing prescriptions exceeding the standard daily dose by more than 30%. Conclusions: A multifaceted intervention including the use of a software program effectively reduced inappropriately high doses of renally excreted medications in patients with CKD in the setting of small primary care practices