Literature DB >> 20890004

Measuring and preventing potentially avoidable hospital readmissions: a review of the literature.

Carrie H K Yam1, Eliza L Y Wong, Frank W K Chan, Fiona Y Y Wong, Michael C M Leung, E K Yeoh.   

Abstract

OBJECTIVE: To review literature identifying key components for measuring avoidable readmissions, their prevalence, risk factors, and interventions that can reduce potentially avoidable readmissions. DATA SOURCES AND EXTRACTION: Literature search using Medline, PubMed and the Cochrane Library up to June 2010, using the terms "avoidable", "preventable", "unplanned", "unnecessary", "readmission", and "rehospitalization". STUDY SELECTION: A total of 48 original papers and review articles were selected for inclusion in this review. DATA SYNTHESIS: Although hospital readmission seemed to be a term commonly used as an outcome indicator in many studies, it is difficult to make valid comparison of results from different studies. This is because the definitions of terms, methods of data collection, and approaches to data analysis differ greatly. The following criteria for studying hospital readmissions have been recommended: (a) identify hospital admissions and define relevant terms, (b) establish a clinical diagnosis for a readmission; (c) establish the purpose for a readmission, (d) set a discharge-to-readmission timeframe, and (e) identify the sources of information for assessing readmissions. Studies to identify avoidable readmissions usually involve medical records and chart reviews by clinicians using the classification scheme developed by the authors. The proportion of all readmissions assessed as preventable varies from 9 to 59% depending on the population of patients studied, duration of follow-up, type and methodology of the study and case-mix-related factors. A number of studies classified risk factors for readmission into four categories: patient, social, clinical, and system factors. Home-based interventions, intensive education/counselling, multidisciplinary care approaches, and telephone follow-up were the main types of interventions to address potentially avoidable readmissions.
CONCLUSIONS: A standard instrument to identify avoidable readmission is important in enabling valid comparisons within the system and at different timelines, so as to permit robust evaluation of interventions. The assessment of preventable risk factors for readmissions also provides a basis for designing and implementing intervention programmes.

Entities:  

Mesh:

Year:  2010        PMID: 20890004

Source DB:  PubMed          Journal:  Hong Kong Med J        ISSN: 1024-2708            Impact factor:   2.227


  25 in total

1.  NI2012 Classification of Reasons for Hospital Readmission.

Authors:  Kay R Jansen
Journal:  NI 2012 (2012)       Date:  2012-06-23

2.  Framework for Mining and Analysis of Standardized Nursing Care Plan Data.

Authors:  Ashfaq Khokhar; Muhammad Kamran Lodhi; Yingwei Yao; Rashid Ansari; Gail Keenan; Diana J Wilkie
Journal:  West J Nurs Res       Date:  2016-10-22       Impact factor: 1.967

3.  Assessing preventability in the quest to reduce hospital readmissions.

Authors:  Julia G Lavenberg; Brian Leas; Craig A Umscheid; Kendal Williams; David R Goldmann; Sunil Kripalani
Journal:  J Hosp Med       Date:  2014-06-25       Impact factor: 2.960

4.  Predicting Hospital Re-admissions from Nursing Care Data of Hospitalized Patients.

Authors:  Muhammad K Lodhi; Rashid Ansari; Yingwei Yao; Gail M Keenan; Diana Wilkie; Ashfaq A Khokhar
Journal:  Adv Data Min       Date:  2017-07-01

5.  Unplanned readmission rates, length of hospital stay, mortality, and medical costs of ten common medical conditions: a retrospective analysis of Hong Kong hospital data.

Authors:  Eliza L Y Wong; Annie W L Cheung; Michael C M Leung; Carrie H K Yam; Frank W K Chan; Fiona Y Y Wong; Eng-Kiong Yeoh
Journal:  BMC Health Serv Res       Date:  2011-06-17       Impact factor: 2.655

6.  The influence of an intermediate care hospital on health care utilization among elderly patients--a retrospective comparative cohort study.

Authors:  Unni Dahl; Roar Johnsen; Rune Sætre; Aslak Steinsbekk
Journal:  BMC Health Serv Res       Date:  2015-02-01       Impact factor: 2.655

7.  Effectiveness of an intermediate care hospital on readmissions, mortality, activities of daily living and use of health care services among hospitalized adults aged 60 years and older--a controlled observational study.

Authors:  Unni Dahl; Aslak Steinsbekk; Roar Johnsen
Journal:  BMC Health Serv Res       Date:  2015-08-28       Impact factor: 2.655

Review 8.  Effects, barriers and facilitators in predischarge home assessments to improve the transition of care from the inpatient care to home in adult patients: an integrative review.

Authors:  Uta Kirchner-Heklau; Kai Krause; Susanne Saal
Journal:  BMC Health Serv Res       Date:  2021-06-02       Impact factor: 2.655

9.  The impact of EHR and HIE on reducing avoidable admissions: controlling main differential diagnoses.

Authors:  Ofir Ben-Assuli; Itamar Shabtai; Moshe Leshno
Journal:  BMC Med Inform Decis Mak       Date:  2013-04-17       Impact factor: 2.796

10.  Framework and components for effective discharge planning system: a Delphi methodology.

Authors:  Carrie H K Yam; Eliza L Y Wong; Annie W L Cheung; Frank W K Chan; Fiona Y Y Wong; Eng-kiong Yeoh
Journal:  BMC Health Serv Res       Date:  2012-11-14       Impact factor: 2.655

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