Literature DB >> 31660528

Predictors of 30-day hospital readmission: The direct comparison of number of discharge medications to the HOSPITAL score and LACE index.

Robert Robinson1, Mukul Bhattarai1, Tamer Hudali2, Carrie Vogler3.   

Abstract

Effective hospital readmission risk prediction tools exist, but do not identify actionable items that could be modified to reduce the risk of readmission. Polypharmacy has attracted attention as a potentially modifiable risk factor for readmission, showing promise in a retrospective study. Polypharmacy is a very complex issue, reflecting comorbidities and healthcare resource utilisation patterns. This investigation compares the predictive ability of polypharmacy alone to the validated HOSPITAL score and LACE index readmission risk assessment tools for all adult admissions to an academic hospitalist service at a moderate sized university-affiliated hospital in the American Midwest over a 2-year period. These results indicate that the number of discharge medications alone is not a useful tool in identifying patients at high risk of hospital readmission within 30 days of discharge. Further research is needed to explore the impact of polypharmacy as a risk predictor for hospital readmission. © Royal College of Physicians 2019. All rights reserved.

Entities:  

Keywords:  HOSPITAL score; LACE index; Readmission; discharge medications; polypharmacy

Year:  2019        PMID: 31660528      PMCID: PMC6798018          DOI: 10.7861/fhj.2018-0039

Source DB:  PubMed          Journal:  Future Healthc J        ISSN: 2514-6645


  28 in total

1.  Effect of polypharmacy, potentially inappropriate medications and anticholinergic burden on clinical outcomes: a retrospective cohort study.

Authors:  Wan-Hsuan Lu; Yu-Wen Wen; Liang-Kung Chen; Fei-Yuan Hsiao
Journal:  CMAJ       Date:  2015-02-02       Impact factor: 8.262

2.  Predicting non-elective hospital readmissions: a multi-site study. Department of Veterans Affairs Cooperative Study Group on Primary Care and Readmissions.

Authors:  D M Smith; A Giobbie-Hurder; M Weinberger; E Z Oddone; W G Henderson; D A Asch; C M Ashton; J R Feussner; P Ginier; J M Huey; D M Hynes; L Loo; C E Mengel
Journal:  J Clin Epidemiol       Date:  2000-11       Impact factor: 6.437

Review 3.  Clinical consequences of polypharmacy in elderly.

Authors:  Robert L Maher; Joseph Hanlon; Emily R Hajjar
Journal:  Expert Opin Drug Saf       Date:  2013-09-27       Impact factor: 4.250

4.  Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community.

Authors:  Carl van Walraven; Irfan A Dhalla; Chaim Bell; Edward Etchells; Ian G Stiell; Kelly Zarnke; Peter C Austin; Alan J Forster
Journal:  CMAJ       Date:  2010-03-01       Impact factor: 8.262

5.  International Validity of the HOSPITAL Score to Predict 30-Day Potentially Avoidable Hospital Readmissions.

Authors:  Jacques D Donzé; Mark V Williams; Edmondo J Robinson; Eyal Zimlichman; Drahomir Aujesky; Eduard E Vasilevskis; Sunil Kripalani; Joshua P Metlay; Tamara Wallington; Grant S Fletcher; Andrew D Auerbach; Jeffrey L Schnipper
Journal:  JAMA Intern Med       Date:  2016-04       Impact factor: 21.873

6.  Predictors of rehospitalization among elderly patients admitted to a rehabilitation hospital: the role of polypharmacy, functional status, and length of stay.

Authors:  Alessandro Morandi; Giuseppe Bellelli; Eduard E Vasilevskis; Renato Turco; Fabio Guerini; Tiziana Torpilliesi; Salvatore Speciale; Valeria Emiliani; Simona Gentile; John Schnelle; Marco Trabucchi
Journal:  J Am Med Dir Assoc       Date:  2013-05-07       Impact factor: 4.669

7.  Admission Data Predict High Hospital Readmission Risk.

Authors:  Everett Logue; William Smucker; Christine Regan
Journal:  J Am Board Fam Med       Date:  2016 Jan-Feb       Impact factor: 2.657

8.  The number of discharge medications predicts thirty-day hospital readmission: a cohort study.

Authors:  David Picker; Kevin Heard; Thomas C Bailey; Nathan R Martin; Gina N LaRossa; Marin H Kollef
Journal:  BMC Health Serv Res       Date:  2015-07-23       Impact factor: 2.655

9.  Comparison of predictive modeling approaches for 30-day all-cause non-elective readmission risk.

Authors:  Liping Tong; Cole Erdmann; Marina Daldalian; Jing Li; Tina Esposito
Journal:  BMC Med Res Methodol       Date:  2016-02-27       Impact factor: 4.615

10.  The HOSPITAL score and LACE index as predictors of 30 day readmission in a retrospective study at a university-affiliated community hospital.

Authors:  Robert Robinson; Tamer Hudali
Journal:  PeerJ       Date:  2017-03-29       Impact factor: 2.984

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  4 in total

1.  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.

Authors:  Mei-Chin Su; Yi-Jen Wang; Tzeng-Ji Chen; Shiao-Hui Chiu; Hsiao-Ting Chang; Mei-Shu Huang; Li-Hui Hu; Chu-Chuan Li; Su-Ju Yang; Jau-Ching Wu; Yu-Chun Chen
Journal:  Int J Environ Res Public Health       Date:  2020-02-02       Impact factor: 3.390

2.  Association of Sodium-Glucose Cotransporter 2 Inhibitors With Cardiovascular Outcomes in Patients With Type 2 Diabetes and Other Risk Factors for Cardiovascular Disease: A Meta-analysis.

Authors:  Mukul Bhattarai; Mohsin Salih; Manjari Regmi; Mohammad Al-Akchar; Radhika Deshpande; Zurain Niaz; Abhishek Kulkarni; Momin Siddique; Shruti Hegde
Journal:  JAMA Netw Open       Date:  2022-01-04

3.  Machine learning for predicting readmission risk among the frail: Explainable AI for healthcare.

Authors:  Somya D Mohanty; Deborah Lekan; Thomas P McCoy; Marjorie Jenkins; Prashanti Manda
Journal:  Patterns (N Y)       Date:  2021-12-03

4.  LACE Index to Predict the High Risk of 30-Day Readmission in Patients With Acute Myocardial Infarction at a University Affiliated Hospital.

Authors:  Vasuki Rajaguru; Tae Hyun Kim; Whiejong Han; Jaeyong Shin; Sang Gyu Lee
Journal:  Front Cardiovasc Med       Date:  2022-07-11
  4 in total

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