scholarly journals LACE Score-Based Risk Management Tool for Long-Term Home Care Patients: A Proof-of-Concept Study in Taiwan

2021 ◽  
Vol 18 (3) ◽  
pp. 1135
Author(s):  
Mei-Chin Su ◽  
Yu-Chun Chen ◽  
Mei-Shu Huang ◽  
Yen-Hsi Lin ◽  
Li-Hwa Lin ◽  
...  
Keyword(s):  
Risk Management ◽  
Home Care ◽  
Readmission Rate ◽  
Management Tool ◽  
Predictive Score ◽  
Care Providers ◽  
Real World Evidence ◽  
Before And After ◽  
Reduction Effect

Background: Effectively predicting and reducing readmission in long-term home care (LTHC) is challenging. We proposed, validated, and evaluated a risk management tool that stratifies LTHC patients by LACE predictive score for readmission risk, which can further help home care providers intervene with individualized preventive plans. Method: A before-and-after study was conducted by a LTHC unit in Taiwan. Patients with acute hospitalization within 30 days after discharge in the unit were enrolled as two cohorts (Pre-Implement cohort in 2017 and Post-Implement cohort in 2019). LACE score performance was evaluated by calibration and discrimination (AUC, area under receiver operator characteristic (ROC) curve). The clinical utility was evaluated by negative predictive value (NPV). Results: There were 48 patients with 87 acute hospitalizations in Pre-Implement cohort, and 132 patients with 179 hospitalizations in Post-Implement cohort. These LTHC patients were of older age, mostly intubated, and had more comorbidities. There was a significant reduction in readmission rate by 44.7% (readmission rate 25.3% vs. 14.0% in both cohorts). Although LACE score predictive model still has room for improvement (AUC = 0.598), it showed the potential as a useful screening tool (NPV, 87.9%; 95% C.I., 74.2–94.8). The reduction effect is more pronounced in infection-related readmission. Conclusion: As real-world evidence, LACE score-based risk management tool significantly reduced readmission by 44.7% in this LTHC unit. Larger scale studies involving multiple homecare units are needed to assess the generalizability of this study.

scholarly journals Assess the Performance and Cost-Effectiveness of LACE and HOSPITAL Re-Admission Prediction Models as a Risk Management Tool for Home Care Patients: An Evaluation Study of a Medical Center Affiliated Home Care Unit in Taiwan

2020 ◽  
Vol 17 (3) ◽  
pp. 927
Author(s):  
Mei-Chin Su ◽  
Yi-Jen Wang ◽  
Tzeng-Ji Chen ◽  
Shiao-Hui Chiu ◽  
Hsiao-Ting Chang ◽  
...  
Keyword(s):  
Risk Management ◽  
Cost Effectiveness ◽  
Home Care ◽  
Readmission Rate ◽  
Prediction Models ◽  
Medical Center ◽  
Management Tool ◽  
Receiver Operating Curve ◽  
Limited Information ◽  
Net Reclassification Improvement

The LACE index and HOSPITAL score models are the two most commonly used prediction models identifying patients at high risk of readmission with limited information for home care patients. This study compares the effectiveness of these two models in predicting 30-day readmission following acute hospitalization of such patients in Taiwan. A cohort of 57 home care patients were enrolled and followed-up for one year. We compared calibration, discrimination (area under the receiver operating curve, AUC), and net reclassification improvement (NRI) to identify patients at risk of 30-day readmission for both models. Moreover, the cost-effectiveness of the models was evaluated using microsimulation analysis. A total of 22 readmissions occurred after 87 acute hospitalizations during the study period (readmission rate = 25.2%). While the LACE score had poor discrimination (AUC = 0.598, 95% confidence interval (CI) = 0.488–0.702), the HOSPITAL score achieved helpful discrimination (AUC = 0.691, 95% CI = 0.582–0.785). Moreover, the HOSPITAL score had improved the risk prediction in 38.3% of the patients, compared with the LACE index (NRI = 0.383, 95% CI = 0.068–0.697, p = 0.017). Both prediction models effectively reduced readmission rates compared to an attending physician’s model (readmission rate reduction: LACE, 39.2%; HOSPITAL, 43.4%; physician, 10.1%; p < 0.001). The HOSPITAL score provides a better prediction of readmission and has potential as a risk management tool for home care patients.

Coupling wildfire spread and erosion models to quantify post-fire erosion before and after fuel treatments

2019 ◽  
Vol 28 (9) ◽  
pp. 687 ◽  
Author(s):  
Michele Salis ◽  
Liliana Del Giudice ◽  
Peter R. Robichaud ◽  
Alan A. Ager ◽  
Annalisa Canu ◽  
...  
Keyword(s):  
Risk Management ◽  
Vegetation Type ◽  
Fire Severity ◽  
Management Tool ◽  
Exceedance Probability ◽  
Fuel Treatments ◽  
Sediment Delivery ◽  
Efficient Treatment ◽  
Before And After ◽  
Wildfire Spread

Wildfires are known to change post-fire watershed conditions such that hillslopes can become prone to increased erosion and sediment delivery. In this work, we coupled wildfire spread and erosion prediction modelling to assess the benefits of fuel reduction treatments in preventing soil runoff. The study was conducted in a 68000-ha forest area located in Sardinia, Italy. We compared no-treatment conditions v. alternative strategic fuel treatments performed in 15% of the area. Fire behaviour before and after treatments was estimated by simulating 25000 wildfires for each condition using the minimum travel time fire-spread algorithm. The fire simulations replicated historic conditions associated with severe wildfires in the study area. Sediment delivery was then estimated using the Erosion Risk Management Tool (ERMiT). Our results showed how post-fire sediment delivery varied among and within fuel treatment scenarios. The most efficient treatment alternative was that implemented near the road network. We also evaluated other factors such as exceedance probability, time since fire, slope, fire severity and vegetation type on post-fire sediment delivery. This work provides a quantitative assessment approach to inform and optimise proactive risk management activities intended to reduce post-fire erosion.

scholarly journals A long-term risk management tool for electricity markets using swarm intelligence

2010 ◽  
Vol 80 (4) ◽  
pp. 380-389 ◽  
Author(s):  
F. Azevedo ◽  
Z.A. Vale ◽  
P.B. Moura Oliveira ◽  
H.M. Khodr
Keyword(s):  
Risk Management ◽  
Swarm Intelligence ◽  
Electricity Markets ◽  
Management Tool

Health Care Use Before and After Entering Long-Term Services and Supports

2016 ◽  
Vol 37 (1) ◽  
pp. 26-40 ◽  
Author(s):  
Robert Newcomer ◽  
Charlene Harrington ◽  
Denis Hulett ◽  
Taewoon Kang ◽  
Michelle Ko ◽  
...  
Keyword(s):  
Health Care ◽  
Acute Care ◽  
Long Term Care ◽  
Health Care Use ◽  
Care Providers ◽  
Term Care ◽  
Before And After ◽  
Ed Visits ◽  
Post Acute Care

Objective: We examined the health care utilization patterns of Medicare and Medicaid enrollees (MMEs) before and after initiating long-term care in the community or after admission to a nursing facility (NF). Method: We used administrative data to compare hospitalizations, emergency department (ED) visits, and post-acute care use of MMEs receiving long-term care in California in 2006-2007. Results: MMEs admitted to a NF for long-term care had much greater use of hospitalizations, ED visits, and post-acute care before initiating long-term care than those entering long-term care in the community. Post-entry, community service users had less than half the average monthly hospital and ED use compared with the NF cohort. Conclusion: Hospital and ED use prior to and following NF and personal care program entry suggest a need for reassessing the monitoring of these high-risk populations and the communication between health and community care providers.

scholarly journals Care Situation and Caregiver Burden of Home-care Stroke Patients Before and After the Introduction of Long-term Care Insurance

2013 ◽  
Vol 28 (4) ◽  
pp. 511-516 ◽  
Author(s):  
Aki WATANABE ◽  
Hirofumi NAGAYAMA ◽  
Takayuki KAWAGUCHI ◽  
Michinari FUKUDA ◽  
Tsugio AKUTSU ◽  
...  
Keyword(s):  
Home Care ◽  
Caregiver Burden ◽  
Long Term Care ◽  
Stroke Patients ◽  
Term Care ◽  
Before And After ◽  
Long Term Care Insurance ◽  
Care Situation

Home Care of Patients with Head Injury: Are We Neglecting the Caregivers?

2017 ◽  
Vol 14 (02/03) ◽  
pp. 083-085
Author(s):  
Yawar Shoaib ◽  
Amit Dagar ◽  
Abraq Reyaz
Keyword(s):  
Health Care ◽  
Head Injury ◽  
Home Care ◽  
Health Care Providers ◽  
Negative Impact ◽  
Relevant Literature ◽  
Mental Illnesses ◽  
Care Providers ◽  
Term Care

AbstractIn the absence of professional long-term care facilities in India, home care to patients with head injury is usually provided by family members. In this scenario, the mental health of the caregivers remains an important issue. This factor is constantly neglected by the health care providers and the society alike. With the result, the caregivers are prone to depression, anxiety, and other forms of mental illnesses. This also has a negative impact on the recovery and rehabilitation of the head injury survivor. In this article, the authors have reviewed relevant literature to find out the extent and prevalence of this problem among home caregivers of patients with head injury. The authors have also highlighted the possible measures that the treating neurosurgeon and the society can take for effective management of these issues. Their aim is to make the neurosurgeon and other health care providers aware of this issue and its various ramifications.

scholarly journals Implementing electronic health records (EHRs): health care provider perceptions before and after transition from a local basic EHR to a commercial comprehensive EHR

2017 ◽  
Vol 25 (6) ◽  
pp. 618-626 ◽  
Author(s):  
Marie Krousel-Wood ◽  
Allison B McCoy ◽  
Chad Ahia ◽  
Elizabeth W Holt ◽  
Donnalee N Trapani ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Providers ◽  
Preventive Care ◽  
Care Delivery ◽  
Primary Care Providers ◽  
Easy Access ◽  
Care Providers ◽  
Before And After ◽  
Electronic Health

Abstract Objective We assessed changes in the percentage of providers with positive perceptions of electronic health record (EHR) benefit before and after transition from a local basic to a commercial comprehensive EHR. Methods Changes in the percentage of providers with positive perceptions of EHR benefit were captured via a survey of academic health care providers before (baseline) and at 6–12 months (short term) and 12–24 months (long term) after the transition. We analyzed 32 items for the overall group and by practice setting, provider age, and specialty using separate multivariable-adjusted random effects logistic regression models. Results A total of 223 providers completed all 3 surveys (30% response rate): 85.6% had outpatient practices, 56.5% were &gt;45 years old, and 23.8% were primary care providers. The percentage of providers with positive perceptions significantly increased from baseline to long-term follow-up for patient communication, hospital transitions – access to clinical information, preventive care delivery, preventive care prompt, preventive lab prompt, satisfaction with system reliability, and sharing medical information (P &lt; .05 for each). The percentage of providers with positive perceptions significantly decreased over time for overall satisfaction, productivity, better patient care, clinical decision quality, easy access to patient information, monitoring patients, more time for patients, coordination of care, computer access, adequate resources, and satisfaction with ease of use (P &lt; 0.05 for each). Results varied by subgroup. Conclusion After a transition to a commercial comprehensive EHR, items with significant increases and significant decreases in the percentage of providers with positive perceptions of EHR benefit were identified, overall and by subgroup.

Sign in / Sign up

Export Citation Format

Share Document