Evidence map›Paper›PMID 24160939›Full record

ReviewAnnual review of medicine2014

Reducing hospital readmission rates: current strategies and future directions.

Sunil Kripalani, Cecelia N Theobald, Beth Anctil, Eduard E Vasilevskis

2 registry-linked trialsAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Annual review of medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 243 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
243citing papers in PubMed, 9 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02763202 nacompletednot on this mapstarted 2016, after this paper: background citation

Aiming to Improve Readmissions Through InteGrated Hospital Transitions

TypeinterventionalSponsorWake Forest University Health SciencesRan2016 to 2017Enrolled1,876ConditionsHospital ReadmissionArmsCHS Transition Services
NCT02815462 nawithdrawnnot on this mapstarted 2016, after this paper: background citation

Impact of Implementing a Real Time Frequent Admitter Risk Score (FAM-FACE-SG) on Readmission Rates: a Pragmatic Cluster Randomised Controlled Trial (RCT).

TypeinterventionalSponsorSingapore General HospitalRan2016 to 2017Enrolled0ConditionsPatient ReadmissionArmsFAMFACESG, Control
3 · Its place in the literature

Who cites it

243 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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183 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sunil KripalaniDepartment of Medicine, Vanderbilt University, Nashville, Tennessee 37232; email: sunil.kripalani@vanderbilt.edu , cecelia.theobald@vanderbilt.edu , ed.vasilevskis@vanderbilt.edu , cecelia.theobald@vanderbilt.edu.
Cecelia N Theobald
Beth Anctil
Eduard E Vasilevskis

Funding

Health Literacy, Hospital Discharge, and Cardiovascular OutcomesR01HL109388 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KRIPALANI, SUNIL · 2011 to 2015
$3.3M
Predicting Acute Brain Dysfunction in Older Patients: A Quality Improvement ToolK23AG040157 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI VASILEVSKIS, EDUARD E · 2011 to 2015
$609k
NHLBI NIH HHS R01 HL109388NHLBI NIH HHS R01HL109388NIA NIH HHS K23 AG040157NIA NIH HHS K23AG040157
6 · The paper itself

Abstract

New financial penalties for institutions with high readmission rates have intensified efforts to reduce rehospitalization. Several interventions that involve multiple components (e.g., patient needs assessment, medication reconciliation, patient education, arranging timely outpatient appointments, and providing telephone follow-up) have successfully reduced readmission rates for patients discharged to home. The effect of interventions on readmission rates is related to the number of components implemented; single-component interventions are unlikely to reduce readmissions significantly. For patients discharged to postacute care facilities, multicomponent interventions have reduced readmissions through enhanced communication, medication safety, advanced care planning, and enhanced training to manage medical conditions that commonly precipitate readmission. To help hospitals direct resources and services to patients with greater likelihood of readmission, risk-stratification methods are available. Future work should better define the roles of home-based services, information technology, mental health care, caregiver support, community partnerships, and new transitional care personnel.

Indexed as

Patient DischargePatient HandoffAftercareAppointments and SchedulesCommunicationHumansMedicareMedication ReconciliationPatient Care PlanningPatient Care TeamPatient Education as TopicPatient ReadmissionReimbursement MechanismsRisk AssessmentUnited States

Identifiers

PMID24160939
PMCPMC4104507

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.