Implementation of a Medical Intensive Care Unit Acute-Care Nurse Practitioner Service

2011 ◽  
Vol 39 (2) ◽  
pp. 32-39 ◽  
Author(s):  
Janna S. Landsperger ◽  
Kristina Jill Williams ◽  
Susan M. Hellervik ◽  
Cherry B. Chassan ◽  
Lisa N. Flemmons ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Acute Care ◽  
Nurse Practitioner ◽  
Medical Intensive Care Unit ◽  
Care Nurse ◽  
Medical Intensive Care ◽  
Acute Care Nurse Practitioner

Outcomes of Care Managed by an Acute Care Nurse Practitioner/Attending Physician Team in a Subacute Medical Intensive Care Unit

2005 ◽  
Vol 14 (2) ◽  
pp. 121-130 ◽  
Author(s):  
Leslie A. Hoffman ◽  
Frederick J. Tasota ◽  
Thomas G. Zullo ◽  
Carmella Scharfenberg ◽  
Michael P. Donahoe
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Acute Care ◽  
Nurse Practitioners ◽  
Nurse Practitioner ◽  
Medical Intensive Care Unit ◽  
Care Nurse ◽  
Medical Intensive Care ◽  
Acute Care Nurse Practitioner ◽  
Attending Physician

• Background Many academic medical centers employ nurse practitioners as substitutes to provide care normally supplied by house staff.• Objective To compare outcomes in a subacute medical intensive care unit of patients managed by a team consisting of either an acute care nurse practitioner and an attending physician or an attending physician and critical care/pulmonary fellows.• Methods During a 31-month period, in 7-month blocks of time, 526 consecutive patients admitted to the unit for more than 24 hours were managed by one or the other of the teams. Patients managed by the 2 teams were compared for a variety of outcomes.• Results Patients managed by the 2 teams did not differ significantly for any workload, demographic, or medical condition variable. The patients also did not differ in readmission to the high acuity unit (P = .25) or subacute unit (P = .44) within 72 hours of discharge or in mortality with (P = .25) or without (P = .89) treatment limitations. Among patients who had multiple weaning trials, patients managed by the 2 teams did not differ in length of stay in the subacute unit (P = .42), duration of mechanical ventilation (P = .18), weaning status at time of discharge from the unit (P = .80), or disposition (P = .28). Acute Physiology Scores were significantly different over time (P = .046). Patients managed by the fellows had more reintubations (P=.02).• Conclusions In a subacute intensive care unit, management by the 2 teams produced equivalent outcomes.

Management of Patients in the Intensive Care Unit: Comparison Via Work Sampling Analysis of an Acute Care Nurse Practitioner and Physicians in Training

2003 ◽  
Vol 12 (5) ◽  
pp. 436-443 ◽  
Author(s):  
Leslie A. Hoffman ◽  
Frederick J. Tasota ◽  
Carmella Scharfenberg ◽  
Thomas G. Zullo ◽  
Michael P. Donahoe
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Acute Care ◽  
Nurse Practitioner ◽  
Similar Proportion ◽  
Coordination Of Care ◽  
Care Nurse ◽  
Training Requirements ◽  
Work Sampling ◽  
Acute Care Nurse Practitioner

• Background Little is known about aspects of practice that differ between acute care nurse practitioners and physicians that might affect patients’ outcomes.• Objective To determine if time spent in work activities differs between an acute care nurse practitioner and physicians in training (pulmonary/critical care fellows) managing patients’ care in a step-down medical intensive care unit.• Methods Work sampling techniques were used to collect data when the nurse practitioner had 6 months’ or less experience in the role (T1), after the nurse practitioner had 12 months’ experience in the role (T2), and when physicians in training provided care on a rotational schedule (nurse practitioner not present, T3). These data were used to estimate the time spent in direct management of patients, coordination of care, and nonunit activities.• Results Results for T1 and T2 were similar. When T2 and T3 were compared, the nurse practitioner and the physicians in training spent approximately half their time in activities directly related to management of patients (40% vs 44%, not significantly different). The nurse practitioner spent more time in activities related to coordination of care (45% vs 18%; P < .001) and less time in nonunit activities (15% vs 37%; P < .001).• Conclusion The nurse practitioner and the physicians in training spent a similar proportion of time performing required tasks. Because of training requirements, physicians spent more time than the nurse practitioner in nonunit activities. Conversely, the nurse practitioner spent more time interacting with patients and patients’ families and collaborating with health team members.

Abstract 142: Which Hospitals Fail to Improve Readmission Rates?

2012 ◽  
Vol 5 (suppl_1) ◽  
Author(s):  
Karen E Joynt ◽  
Sidney T Le ◽  
Matthew Inada-Kim ◽  
Ashish K Jha
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Acute Care ◽  
Odds Ratio ◽  
Readmission Rate ◽  
Medical Intensive Care Unit ◽  
Acute Care Hospitals ◽  
Teaching Hospitals ◽  
Readmission Rates ◽  
Medical Intensive Care

Objective: The 30-day readmission rate in the Medicare population is near 18%, with an associated cost of $16 billion dollars annually. Policy makers have become focused on trying to identify successful strategies to reduce both the clinical and economic burden of rehospitalizations, and to this end, the Affordable Care Act sets up penalties for hospitals with high readmission rates. Despite the national attention to readmissions, there are many hospitals that have failed to improve their readmission rates. Understanding who these persistently poor-performing hospitals are is key to helping them improve. Methods: We used national Medicare data from 2007 through 2009 to calculate mean readmission rates across six common conditions (heart failure, acute myocardial infarction, chronic obstructive pulmonary disease, pneumonia, stroke and gastrointestinal bleeding) for all acute-care hospitals in the U.S. We identified poor baseline performers as those hospitals with performance in the worst quartile of readmission rates in 2007. We then categorized these hospitals into two groups: those who improved by 2009 and those who did not. We compared the characteristics of hospitals and markets in each of these groups. Results: Our sample was comprised of 869 poor-performing acute-care hospitals. Baseline median composite readmission rates were 27.8% (IQR 25.8%-32.5%). Of these, 214 (24.6%) hospitals failed to improve their readmission rates by 2009; the median 2009 readmission rate for persistently poor performers was 32.0% (IQR 27.1%-38.0%) while the rate fo hospitals that improved was 20.9% (IQR 18.5%-23.6%). Persistently poor performers were more likely to be small hospitals (71% versus 32%, p<0.001), publicly owned (32% versus 21%, p=0.003), rural (43% versus 18%, p=0.02), non-teaching hospitals (86% versus 74%, p<0.001). They were less likely to have a medical intensive care unit (20% versus 52%, p=0.001). Persistently poor performers were located in areas with fewer specialist physicians (7 per 100,000 population versus 9 per 100,000 population, p<0.001) and lower median income ($33,299 versus $34,523, p<0.001). In multivariate logistic regression analyses, the strongest predictors of being a persistently poor performer were being a small hospital (odds ratio 13.3, p<0.001) and lacking a medical intensive care unit (odds ratio 2.9, p<0.001). Conclusions and Implications: Between 2007 and 2009, small, public, non-teaching hospitals were far less likely to improve their readmission rates than others; in general, persistently poor performers were hospitals with lower resource levels and more socioeconomically disadvantaged populations. As hospitals face looming penalties for high readmission rates, our findings raise concern about the ability of the small, worst-performing hospitals and those with poor resource bases to improve their outcomes, and thus raise concerns about the potential of readmissions penalties to widen disparities in care. Policymakers may need to consider coupling readmission penalties with programs and resources to help these vulnerable hospitals improve in order to avoid unintended consequences of this policy initiative.

scholarly journals Passive Ceiling Light Disinfection System to Reduce Bioburden in an Intensive Care Unit

2018 ◽  
Vol 08 (03) ◽  
pp. 138-143
Author(s):  
Annie Rohan ◽  
Imraan Khan ◽  
Donglei Yin ◽  
Jie Yang
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Acute Care ◽  
Care Setting ◽  
Medical Intensive Care Unit ◽  
Low Cost ◽  
Acute Care Setting ◽  
Automated Technology ◽  
Medical Intensive Care ◽  
Ceiling Light

AbstractA ceiling-installed narrow spectrum (402–420 nm) bactericidal blue light disinfection system was installed in a large suburban medical intensive care unit (ICU) and evaluated for implementation feasibility and effectiveness in reducing environmental bioburden. Installation of 54 ceiling devices was accomplished at low cost and with minimal ICU process disruption. Postinstallation high-touch surface colony counts were significantly lower than preinstallation. Linear mixed modeling demonstrated a 21% average overall decrease in colony count after installation, with consistent reduction in colony counts starting from week 4 postinstallation. Automated technology is potentially more efficient in reducing environmental bioburden in the acute care setting compared with other bioburden reducing methods or can provide a robust compliment to manual cleaning.

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