A Predictive Model to Identify Patients at Risk of Unplanned 30-Day Acute Care Hospital Readmission

2013 ◽  
Author(s):  
Klaus Lemke
Keyword(s):  
At Risk ◽  
Predictive Model ◽  
Acute Care ◽  
Hospital Readmission ◽  
Acute Care Hospital ◽  
Care Hospital ◽  
Patients At Risk

scholarly journals Estimated annual numbers of US acute-care hospital patients at risk for venous thromboembolism

2007 ◽  
Vol 82 (9) ◽  
pp. 777-782 ◽  
Author(s):  
Frederick A. Anderson ◽  
Maxim Zayaruzny ◽  
John A. Heit ◽  
Dogan Fidan ◽  
Alexander T. Cohen
Keyword(s):  
At Risk ◽  
Venous Thromboembolism ◽  
Acute Care ◽  
Acute Care Hospital ◽  
Care Hospital ◽  
Hospital Patients ◽  
Patients At Risk

scholarly journals Implementing an Evidence-Based Practice Change for Alcohol Withdrawal in an Acute Care Hospital

2021 ◽  
Author(s):  
◽  
Theresa Carroll
Keyword(s):  
At Risk ◽  
Acute Care ◽  
Alcohol Withdrawal ◽  
Acute Care Hospital ◽  
The United States ◽  
Withdrawal Symptoms ◽  
Evidence Based ◽  
Care Hospital ◽  
Standard Facility ◽  
Patients At Risk

Practice Problem: Alcohol Use Disorders (AUD) affects a significant portion of the population in the United States. When AUD is either unrecognized or inadequately treated in the acute care setting it can lead to medical complications, increased length or stay (LOS), increased healthcare expense, and increased patient mortality. PICOT: In a population of adult patients admitted to an acute care hospital progressive care unit (P), how does applying an initial evidence-based screening tool to detect risk for moderate to severe alcohol withdrawal, the PAWSS (I), compare to no standard screening or assessment for potential alcohol withdrawal symptoms (C) affect the occurrence of patient deterioration for acute alcohol withdrawal symptoms (O) within an eight week timeframe (T)? Intervention: The PAWSS tool was utilized to screen all patients admitted to the progressive care unit. Patients identified at moderate to severe risk by a score of ≥4 were treated according to the standard facility practice with included CIWA-Ar monitoring and medication management with benzodiazepine medication. Outcome: The project was able to demonstrate a significant decrease in the mean LOS for those patients identified at risk and treated for AWS, with an average decrease of 50 hours in length of stay for those patients treated during the project implementation. Conclusion: Early recognition of patients at risk for AWS is an important component of effective management and treatment. Further study is needed into best practices for treatment of patients at risk, and internal compliance measures within the organization.

Comparative Evaluation of Malnutrition Screening in Oncology Patients in an Acute Care Hospital: A Pilot Study

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Sinha Chandni Sen ◽  
LaSalle Colette ◽  
Argabright Debra ◽  
Hollenbeck Clarie B
Keyword(s):  
Pilot Study ◽  
Acute Care ◽  
Comparative Evaluation ◽  
Acute Care Hospital ◽  
Care Hospital ◽  
Oncology Patients

A Taxonomy for Psycho-Oncological Intervention Techniques in an Acute Care Hospital in Germany

2021 ◽  
pp. 1-7
Author(s):  
Martina Madl ◽  
Marietta Lieb ◽  
Katharina Schieber ◽  
Tobias Hepp ◽  
Yesim Erim
Keyword(s):  
Acute Care ◽  
Interrater Reliability ◽  
Acute Care Hospital ◽  
Future Research ◽  
Systematic Research ◽  
Care Hospital ◽  
Certification System ◽  
Stepwise Procedure ◽  
Further Development

<b><i>Background:</i></b> Due to the establishment of a nationwide certification system for cancer centers in Germany, the availability of psycho-oncological services for cancer patients has increased substantially. However, little is known about the specific intervention techniques that are applied during sessions in an acute care hospital, since a standardized taxonomy is lacking. With this study, we aimed at the investigation of psycho-oncological intervention techniques and the development of a comprehensive and structured taxonomy thereof. <b><i>Methods:</i></b> In a stepwise procedure, a team of psycho-oncologists generated a data pool of interventions and definitions that were tested in clinical practice during a pilot phase. After an adaptation of intervention techniques, interrater reliability (IRR) was attained by rating 10 previously recorded psycho-oncological sessions. A classification of interventions into superordinate categories was performed, supported by cluster analysis. <b><i>Results:</i></b> Between April and June 2017, 980 psycho-oncological sessions took place. The experts agreed on a total number of 22 intervention techniques. An IRR of 89% for 2 independent psycho-oncological raters was reached. The 22 techniques were classified into 5 superordinate categories. <b><i>Discussion/Conclusion:</i></b> We developed a comprehensive and structured taxonomy of psycho-oncological intervention techniques in an acute care hospital that provides a standardized basis for systematic research and applied care. We expect our work to be continuously subjected to further development: future research should evaluate and expand our taxonomy to other contexts and care settings.

Performance of a Predictive Model versus Prescription-Based Thresholds in Identifying Patients at Risk of Fatal Opioid Overdose

2021 ◽  
Vol 56 (3) ◽  
pp. 396-403
Author(s):  
Lindsey M. Ferris ◽  
Brendan Saloner ◽  
Kate Jackson ◽  
B. Casey Lyons ◽  
Vijay Murthy ◽  
...  
Keyword(s):  
At Risk ◽  
Predictive Model ◽  
Opioid Overdose ◽  
Patients At Risk ◽  
Model Versus
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