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St. Louis, MO, United States

Otani K.,Indiana University - Purdue University Fort Wayne | Waterman B.,Thomson Reuters | Claiborne Dunagan W.,BJC Healthcare
Journal of Healthcare Management | Year: 2012

With increasing emphasis in healthcare on patient satisfaction, many patient satisfaction studies have been administered. Most assume that all patients combine their healthcare experiences (such as nursing care, physician care, etc.) in the same way to arrive at their satisfaction; however, no research has been conducted prior to the present study to investigate how patients' health conditions influence the way they combine their healthcare experiences. This study aims to determine how seriously ill patients differ from less seriously ill patients during their combining process. Data were collected from five large hospitals in the St. Louis area by administering a patient satisfaction questionnaire. Multiple linear regression analyses with a scatter term, a severity measure, and interaction effects of the severity measure were conducted while controlling for age, gender, and race. Two models (overall quality of care and willingness to recommend to others) were analyzed, and the severity of illness variable revealed interaction effects with physician care, staff care, food, and scatter term variables in the willingness to recommend model (six attributes were analyzed: admission process, nursing care, physician care, staff care, food, and room). With more seriously ill patients, physician care becomes more important and staff care becomes less important, and seriously ill patients are proportionately more likely to combine their attribute reactions only in the willingness to recommend model. All six attributes are not equally influential. Nursing care and staff care show consistent influence in both models. These findings show that if healthcare managers want to increase their patient satisfaction, they should enhance nursing care and staff care first to experience the most improvement. Source

Gase K.A.,BJC Healthcare | Babcock H.M.,University of Washington
American Journal of Infection Control | Year: 2015

There is still little known about how infection prevention (IP) staffing affects patient outcomes across the country. Current evaluations mainly focus on the ratio of IP resources to acute care beds (ACBs) and have not strongly correlated with patient outcomes. The scope of IP and the role of the infection preventionist in health care have expanded and changed dramatically since the Study on the Efficacy of Nosocomial Infection Control (SENIC Project) recommended a 1 IP resource to 250 ACB ration in the 1980s. Without a universally accepted model for accounting for additional IP responsibilities, it is difficult to truly assess IP staffing needs. A previously suggested alternative staffing model was applied to acute care hospitals in our organization to determine its utility. © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Source

Scharf D.P.,Saint Louis University | Mathews K.J.,Integration and Quality for the Southern Illinois Healthcare Foundation | Jackson P.,University of Washington | Hofsuemmer J.,BJC Healthcare | And 2 more authors.
Journal of Health Care for the Poor and Underserved | Year: 2010

Tis paper describes results of a qualitative study that explored barriers to research participation among African American adults. A purposive sampling strategy was used to identify African American adults with and without previous research experience. A total of 11 focus groups were conducted. Groups ranged in size from 4-10 participants (N=70). Mistrust of the health care system emerged as a primary barrier to participation in medical research among participants in our study. Mistrust stems from historical events including the Tuskegee syphilis study and is reinforced by health system issues and discriminatory events that continue to this day. Mistrust was an important barrier expressed across all groups regardless of prior research participation or socioeconomic status. Tis study illustrates the multifaceted nature of mistrust, and suggests that mistrust remains an important barrier to research participation. Researchers should incorporate strategies to reduce mistrust and thereby increase participation among African Americans. Source

Lin M.Y.,Rush University Medical Center | Hota B.,Rush University Medical Center | Khan Y.M.,Ohio State University | Woeltje K.F.,University of Washington | And 5 more authors.
JAMA - Journal of the American Medical Association | Year: 2010

Context: Central line-associated bloodstream infection (BSI) rates, determined by infection preventionists using the Centers for Disease Control and Prevention (CDC) surveillance definitions, are increasingly published to compare the quality of patient care delivered by hospitals. However, such comparisons are valid only if surveillance is performed consistently across institutions. Objective: To assess institutional variation in performance of traditional centralline-associated BSI surveillance. Design, Setting, and Participants: We performed a retrospective cohort study of 20 intensive care units among 4 medical centers (2004-2007). Unit-specific central line-associated BSI rates were calculated for 12-month periods. Infection preventionists, blinded to study participation, performed routine prospective surveillance using CDC definitions. A computer algorithm reference standard was applied retrospectively using criteria that adapted the same CDC surveillance definitions. Main Outcome Measures: Correlation of central line-associated BSI rates as determined by infection preventionist vs the computer algorithm reference standard. Variation in performance was assessed by testing for institution-dependent heterogeneity in a linear regression model. Results: Forty-one unit-periods among 20 intensive care units were analyzed, representing 241 518 patient-days and 165 963 central line-days. The median infection preventionist and computer algorithm central line-associated BSI rates were 3.3 (interquartile range [IQR], 2.0-4.5) and 9.0 (IQR, 6.3-11.3) infections per 1000 central line-days, respectively. Overall correlation between computer algorithm and infection preventionist rates was weak (ρ=0.34), and when stratified by medical center, point estimates for institution-specific correlations ranged widely: medical center A: 0.83; 95% confidence interval (CI), 0.05 to 0.98; P=.04; medical center B: 0.76; 95% CI, 0.32 to 0.93; P=.003; medical center C: 0.50, 95% CI, -0.11 to 0.83; P=.10; and medical center D: 0.10; 95% CI -0.53 to 0.66; P=.77. Regression modeling demonstrated significant heterogeneity among medical centers in the relationship between computer algorithm and expected infection preventionist rates (P<.001). The medical center that had the lowest rate by traditional surveillance (2.4 infections per 1000 central line-days) had the highest rate by computer algorithm (12.6 infections per 1000 central line-days). Conclusions: Institutional variability of infection preventionist rates relative to a computer algorithm reference standard suggests that there is significant variation in the application of standard central line-associated BSI surveillance definitions across medical centers. Variation in central line-associated BSI surveillance practice may complicate interinstitutional comparisons of publicly reported central line-associated BSI rates. ©2010 American Medical Association. All rights reserved. Source

Neuner E.A.,Cleveland Clinic | Casabar E.,Barnes Jewish Hospital | Reichley R.,BJC Healthcare | McKinnon P.S.,Cubist Pharmaceuticals Inc.
Diagnostic Microbiology and Infectious Disease | Year: 2010

Methicillin-resistant Staphylococcus aureus bacteremia (MRSAB) often persists despite full susceptibility to vancomycin; therefore, associated factors were assessed. A retrospective cohort analysis of 222 patients with MRSAB treated with vancomycin was conducted; patients with persistent MRSAB (pMRSAB) were compared to those with nonpersistent bacteremia (NPB). Incidence of pMRSAB was 9%. More patients with vancomycin MIC = 2 mg/L had pMRSAB (16%) compared to patients with vancomycin MIC <2 mg/L (5%), P = 0.012. SCC. mec type and Panton-Valentine leukocidin production were similar between patients with pMRSAB and NPB. There was no difference in vancomycin troughs, time to first dose, or area under the concentration-time curve/MIC between groups. More metastatic complications were observed in pMRSAB 63% versus NPB 32% (P = 0.005). Multivariate analysis found endocarditis (odds ratio [OR], 2.3; P = 0.021), complicated MRSAB (OR, 2.6; P = 0.009), vancomycin MIC = 2 (OR, 2.6; P = 0.009), and septic shock (OR 2.2 P = 0.031), which were independent predictors of pMRSAB. © 2010 Elsevier Inc. Source

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