Literature DB >> 27755392

The HOSPITAL Score Predicts Potentially Preventable 30-Day Readmissions in Conditions Targeted by the Hospital Readmissions Reduction Program.

Robert E Burke1, Jeffrey L Schnipper, Mark V Williams, Edmondo J Robinson, Eduard E Vasilevskis, Sunil Kripalani, Joshua P Metlay, Grant S Fletcher, Andrew D Auerbach, Jacques D Donzé.   

Abstract

BACKGROUND/
OBJECTIVES: New tools to accurately identify potentially preventable 30-day readmissions are needed. The HOSPITAL score has been internationally validated for medical inpatients, but its performance in select conditions targeted by the Hospital Readmission Reduction Program (HRRP) is unknown.
DESIGN: Retrospective cohort study.
SETTING: Six geographically diverse medical centers. PARTICIPANTS/EXPOSURES: All consecutive adult medical patients discharged alive in 2011 with 1 of the 4 medical conditions targeted by the HRRP (acute myocardial infarction, chronic obstructive pulmonary disease, pneumonia, and heart failure) were included. Potentially preventable 30-day readmissions were identified using the SQLape algorithm. The HOSPITAL score was calculated for all patients. MEASUREMENTS: A multivariable logistic regression model accounting for hospital effects was used to evaluate the accuracy (Brier score), discrimination (c-statistic), and calibration (Pearson goodness-of-fit) of the HOSPITAL score for each 4 medical conditions.
RESULTS: Among the 9181 patients included, the overall 30-day potentially preventable readmission rate was 13.6%. Across all 4 diagnoses, the HOSPITAL score had very good accuracy (Brier score of 0.11), good discrimination (c-statistic of 0.68), and excellent calibration (Hosmer-Lemeshow goodness-of-fit test, P=0.77). Within each diagnosis, performance was similar. In sensitivity analyses, performance was similar for all readmissions (not just potentially preventable) and when restricted to patients age 65 and above.
CONCLUSIONS: The HOSPITAL score identifies a high-risk cohort for potentially preventable readmissions in a variety of practice settings, including conditions targeted by the HRRP. It may be a valuable tool when included in interventions to reduce readmissions within or across these conditions.

Entities:  

Mesh:

Year:  2017        PMID: 27755392      PMCID: PMC5309170          DOI: 10.1097/MLR.0000000000000665

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  30 in total

1.  Medicare's readmissions-reduction program--a positive alternative.

Authors:  Robert A Berenson; Ronald A Paulus; Noah S Kalman
Journal:  N Engl J Med       Date:  2012-03-28       Impact factor: 91.245

Review 2.  Interventions to reduce 30-day rehospitalization: a systematic review.

Authors:  Luke O Hansen; Robert S Young; Keiki Hinami; Alicia Leung; Mark V Williams
Journal:  Ann Intern Med       Date:  2011-10-18       Impact factor: 25.391

3.  Interventions to decrease hospital readmissions: keys for cost-effectiveness.

Authors:  Robert E Burke; Eric A Coleman
Journal:  JAMA Intern Med       Date:  2013-04-22       Impact factor: 21.873

4.  Neighborhood socioeconomic disadvantage and 30-day rehospitalization: a retrospective cohort study.

Authors:  Amy J H Kind; Steve Jencks; Jane Brock; Menggang Yu; Christie Bartels; William Ehlenbach; Caprice Greenberg; Maureen Smith
Journal:  Ann Intern Med       Date:  2014-12-02       Impact factor: 25.391

5.  Comprehensive discharge planning and home follow-up of hospitalized elders: a randomized clinical trial.

Authors:  M D Naylor; D Brooten; R Campbell; B S Jacobsen; M D Mezey; M V Pauly; J S Schwartz
Journal:  JAMA       Date:  1999-02-17       Impact factor: 56.272

6.  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

7.  Assessing the performance of prediction models: a framework for traditional and novel measures.

Authors:  Ewout W Steyerberg; Andrew J Vickers; Nancy R Cook; Thomas Gerds; Mithat Gonen; Nancy Obuchowski; Michael J Pencina; Michael W Kattan
Journal:  Epidemiology       Date:  2010-01       Impact factor: 4.822

8.  Root Cause Analyses of Transfers of Skilled Nursing Facility Patients to Acute Hospitals: Lessons Learned for Reducing Unnecessary Hospitalizations.

Authors:  Joseph G Ouslander; Ilkin Naharci; Gabriella Engstrom; Jill Shutes; David G Wolf; Graig Alpert; Carolina Rojido; Ruth Tappen; David Newman
Journal:  J Am Med Dir Assoc       Date:  2016-01-14       Impact factor: 4.669

9.  Allocating scarce resources in real-time to reduce heart failure readmissions: a prospective, controlled study.

Authors:  Ruben Amarasingham; Parag C Patel; Kathleen Toto; Lauren L Nelson; Timothy S Swanson; Billy J Moore; Bin Xie; Song Zhang; Kristin S Alvarez; Ying Ma; Mark H Drazner; Usha Kollipara; Ethan A Halm
Journal:  BMJ Qual Saf       Date:  2013-07-31       Impact factor: 7.035

10.  Identifying potentially preventable readmissions.

Authors:  Norbert I Goldfield; Elizabeth C McCullough; John S Hughes; Ana M Tang; Beth Eastman; Lisa K Rawlins; Richard F Averill
Journal:  Health Care Financ Rev       Date:  2008
View more
  9 in total

1.  Acute Myocardial Infarction Readmission Risk Prediction Models: A Systematic Review of Model Performance.

Authors:  Lauren N Smith; Anil N Makam; Douglas Darden; Helen Mayo; Sandeep R Das; Ethan A Halm; Oanh Kieu Nguyen
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2018-01

2.  Thirty-Day Readmission Risk Model for Older Adults Hospitalized With Acute Myocardial Infarction.

Authors:  John A Dodson; Alexandra M Hajduk; Terrence E Murphy; Mary Geda; Harlan M Krumholz; Sui Tsang; Michael G Nanna; Mary E Tinetti; David Goldstein; Daniel E Forman; Karen P Alexander; Thomas M Gill; Sarwat I Chaudhry
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2019-05

Review 3.  Preventing COPD Readmissions Under the Hospital Readmissions Reduction Program: How Far Have We Come?

Authors:  Valerie G Press; Laura C Myers; Laura C Feemster
Journal:  Chest       Date:  2020-10-14       Impact factor: 9.410

4.  Assessing the impact of social determinants of health on predictive models for potentially avoidable 30-day readmission or death.

Authors:  Yongkang Zhang; Yiye Zhang; Evan Sholle; Sajjad Abedian; Marianne Sharko; Meghan Reading Turchioe; Yiyuan Wu; Jessica S Ancker
Journal:  PLoS One       Date:  2020-06-25       Impact factor: 3.240

5.  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

6.  180-day readmission risk model for older adults with acute myocardial infarction: the SILVER-AMI study.

Authors:  John A Dodson; Alexandra M Hajduk; Terrence E Murphy; Mary Geda; Harlan M Krumholz; Sui Tsang; Michael G Nanna; Mary E Tinetti; Gregory Ouellet; Deborah Sybrant; Thomas M Gill; Sarwat I Chaudhry
Journal:  Open Heart       Date:  2021-01

7.  Development of Electronic Health Record-Based Prediction Models for 30-Day Readmission Risk Among Patients Hospitalized for Acute Myocardial Infarction.

Authors:  Michael E Matheny; Iben Ricket; Christine A Goodrich; Rashmee U Shah; Meagan E Stabler; Amy M Perkins; Chad Dorn; Jason Denton; Bruce E Bray; Ram Gouripeddi; John Higgins; Wendy W Chapman; Todd A MacKenzie; Jeremiah R Brown
Journal:  JAMA Netw Open       Date:  2021-01-04

8.  Intervention by a clinical pharmacist carried out at discharge of elderly patients admitted to the internal medicine department: influence on readmissions and costs.

Authors:  Andrea Lázaro Cebas; José Manuel Caro Teller; Carmen García Muñoz; Carlos González Gómez; José Miguel Ferrari Piquero; Carlos Lumbreras Bermejo; José Antonio Romero Garrido; Juana Benedí González
Journal:  BMC Health Serv Res       Date:  2022-02-09       Impact factor: 2.655

9.  Personalized predictions of patient outcomes during and after hospitalization using artificial intelligence.

Authors:  C Beau Hilton; Alex Milinovich; Christina Felix; Nirav Vakharia; Timothy Crone; Chris Donovan; Andrew Proctor; Aziz Nazha
Journal:  NPJ Digit Med       Date:  2020-04-03
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.