2.50
Hdl Handle:
http://hdl.handle.net/10755/622084
Category:
Full-text
Format:
Text-based Document
Type:
Presentation
Level of Evidence:
N/A
Research Approach:
N/A
Title:
Preventing Heart Failure Readmissions By Using a Risk-Stratification Tool
Other Titles:
Cardiac Disease Health Promotion
Author(s):
Dermenchyan, Anna
Lead Author STTI Affiliation:
Gamma Tau-at-Large
Author Details:
Anna Dermenchyan, BSN, RN, CCRN-K, Professional Experience: Numerous presentations on clinical topics, professional development, networking, evidence-based practice, leadership, and healthy work environments at local, regional and national conferences. Past presenter and attendee at the Biennial Convention and Nursing Research Congress. Author Summary: Anna Dermenchyan is a PhD student at the UCLA School of Nursing and Senior Clinical Quality Specialist in the Department of Medicine at UCLA Health, Los Angles, CA. She serves as the President for the Gamma Tau-at-Large Chapter in Los Angeles and past Chair of the regional Odyssey Conference.
Abstract:

Purpose: To implement strategies to improve care and patients’ experience and reduce readmissions for heart failure (HF) patients, Ronald Reagan UCLA Medical Center accepted an invitation from the American College of Cardiology (ACC) to join the Patient Navigator Program (PNP). The goal for the program is for hospitals to establish a patient-centered focus that involves making hospitalization less stressful for patients by providing evidence-based quality improvement strategies. At the initiation of the program (Spring 2014), UCLA utilized a validated risk model, LACE index, to identify patients who are at high risk of readmissions before discharge. This tool has been used to predict the risk of unplanned readmissions as well as mortality within 30 days of hospital discharge in both medical and surgical patients.

Methods:  The LACE Index tool is used to identify patients who would benefit from specific interventions. The score is calculated in the electronic health record (EHR) for each patient from 0 to 19 on the basis of all the following parameters: length of stay (L), acuity of admission (A), comorbidity (C), and emergency department visits in the preceding 6 months (E). Based on the LACE criteria, a low (0–6), medium (7–10) or high (≥11), each score has an identified bundled intervention for each level of risk (Table 1). For example, a HF patient with a low risk score of 6 would receive medication reconciliation from the pharmacist, an updated medication list from the nurse, and a standardized discharge summary from the discharging physician, as well as a follow-up appointment within 5 days. In contrast, a HF patient with a high risk score of 14 would receive the same interventions plus consultations by a physical therapist, a social worker, a case manager, and a dietician; one-to-one medication teaching by the pharmacist; and a follow-up appointment within 3 days.

Results:  The LACE Index score is now calculated in the EHR for all patients. Currently, HF patients receive bundled interventions 80% of the time on the cardiac wards. Since the initiation of the risk score, 30-day unadjusted readmission rates for HF patients at UCLA have decreased from 19% (baseline) to 16.7% (2016, Q2) as compared to the Navigator hospitals 19.2% (baseline) to 17.9% (2016, Q2). In the area of patient experience related to patients’ understanding of medications, UCLA is consistently higher than other Navigator hospitals (100% vs. 72.2%) and has identified and shared best practices during the monthly webinars. In addition, UCLA has increased the number of HF patients consistently receiving a follow-up appointment within 7 days after discharge: baseline of 76.6% to 87.5% (2016, Q2). 

Conclusion: There are numerous factors that cause hospital readmissions. By using a risk model, UCLA is able to identify patients who would benefit from specific evidence-based interventions. This has improved outcomes in 30-day unadjusted readmission rates and patient experience.

Keywords:
Bundled Interventions; Hospital Readmissions; Risk Score
Repository Posting Date:
24-Jul-2017
Date of Publication:
24-Jul-2017
Other Identifiers:
INRC17D14
Conference Date:
2017
Conference Name:
28th International Nursing Research Congress
Conference Host:
Sigma Theta Tau International
Conference Location:
Dublin, Ireland
Description:
Event Theme: Influencing Global Health Through the Advancement of Nursing Scholarship

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.type.categoryFull-texten
dc.formatText-based Documenten
dc.typePresentationen
dc.evidence.levelN/Aen
dc.research.approachN/Aen
dc.titlePreventing Heart Failure Readmissions By Using a Risk-Stratification Toolen_US
dc.title.alternativeCardiac Disease Health Promotionen
dc.contributor.authorDermenchyan, Annaen
dc.contributor.departmentGamma Tau-at-Largeen
dc.author.detailsAnna Dermenchyan, BSN, RN, CCRN-K, Professional Experience: Numerous presentations on clinical topics, professional development, networking, evidence-based practice, leadership, and healthy work environments at local, regional and national conferences. Past presenter and attendee at the Biennial Convention and Nursing Research Congress. Author Summary: Anna Dermenchyan is a PhD student at the UCLA School of Nursing and Senior Clinical Quality Specialist in the Department of Medicine at UCLA Health, Los Angles, CA. She serves as the President for the Gamma Tau-at-Large Chapter in Los Angeles and past Chair of the regional Odyssey Conference.en
dc.identifier.urihttp://hdl.handle.net/10755/622084-
dc.description.abstract<p><strong><strong>Purpose: </strong></strong><span>To implement strategies to improve care and patients’ experience and reduce readmissions for heart failure (HF) patients, Ronald Reagan UCLA Medical Center accepted an invitation from the American College of Cardiology (ACC) to join the Patient Navigator Program (PNP). The goal for the program is for hospitals to establish a patient-centered focus that involves making hospitalization less stressful for patients by providing evidence-based quality improvement strategies. At the initiation of the program (Spring 2014), UCLA utilized a validated risk model, LACE index, to identify patients who are at high risk of readmissions before discharge. This tool has been used to predict the risk of unplanned readmissions as well as mortality within 30 days of hospital discharge in both medical and surgical patients.</span></p> <p><strong><strong>Methods: </strong> </strong>The LACE Index tool is used to identify patients who would benefit from specific interventions. The score is calculated in the electronic health record (EHR) for each patient from 0 to 19 on the basis of all the following parameters: length of stay (L), acuity of admission (A), comorbidity (C), and emergency department visits in the preceding 6 months (E). Based on the LACE criteria, a low (0–6), medium (7–10) or high (≥11), each score has an identified bundled intervention for each level of risk (Table 1). For example, a HF patient with a low risk score of 6 would receive medication reconciliation from the pharmacist, an updated medication list from the nurse, and a standardized discharge summary from the discharging physician, as well as a follow-up appointment within 5 days. In contrast, a HF patient with a high risk score of 14 would receive the same interventions plus consultations by a physical therapist, a social worker, a case manager, and a dietician; one-to-one medication teaching by the pharmacist; and a follow-up appointment within 3 days.<strong></strong></p> <p><strong><strong>Results: </strong> </strong>The LACE Index score is now calculated in the EHR for all patients. Currently, HF patients receive bundled interventions 80% of the time on the cardiac wards. Since the initiation of the risk score, 30-day unadjusted readmission rates for HF patients at UCLA have decreased from 19% (baseline) to 16.7% (2016, Q2) as compared to the Navigator hospitals 19.2% (baseline) to 17.9% (2016, Q2). In the area of patient experience related to patients’ understanding of medications, UCLA is consistently higher than other Navigator hospitals (100% vs. 72.2%) and has identified and shared best practices during the monthly webinars. In addition, UCLA has increased the number of HF patients consistently receiving a follow-up appointment within 7 days after discharge: baseline of 76.6% to 87.5% (2016, Q2).<strong> </strong></p> <p><strong>Conclusion: </strong>There are numerous factors that cause hospital readmissions. By using a risk model, UCLA is able to identify patients who would benefit from specific evidence-based interventions. This has improved outcomes in 30-day unadjusted readmission rates and patient experience.</p>en
dc.subjectBundled Interventionsen
dc.subjectHospital Readmissionsen
dc.subjectRisk Scoreen
dc.date.available2017-07-24T19:37:25Z-
dc.date.issued2017-07-24-
dc.date.accessioned2017-07-24T19:37:25Z-
dc.conference.date2017en
dc.conference.name28th International Nursing Research Congressen
dc.conference.hostSigma Theta Tau Internationalen
dc.conference.locationDublin, Irelanden
dc.descriptionEvent Theme: Influencing Global Health Through the Advancement of Nursing Scholarshipen
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