Access the full text.
Sign up today, get DeepDyve free for 14 days.
EA Coleman, C Parry, S Chalmers, SJ Min (2006)
The care transitions intervention: results of a randomized controlled trial., 166
N Allaudeen, A Vidyarthi, J Maselli, A Auerbach (2011)
Redefining readmission risk factors for general medicine patients., 6
C Boult, B Dowd, D McCaffrey, L Boult, R Hernandez, H Krulewitch (1993)
Screening elders for risk of hospital admission., 41
KG Moons, FE Harrell, EW Steyerberg (2002)
Should scoring rules be based on odds ratios or regression coefficients?, 55
J Billings, J Dixon, T Mijanovich, D Wennberg (2006)
Case finding for patients at risk of readmission to hospital: development of algorithm to identify high risk patients., 333
J Donzé, J Labarère, M Méan, D Jiménez, D Aujesky (2011)
Prognostic importance of anaemia in patients with acute pulmonary embolism., 106
JA Hanley, BJ McNeil (1982)
The meaning and use of the area under a receiver operating characteristic (ROC) curve., 143
DM Smith, JA Norton, CJ McDonald (1985)
Nonelective readmissions of medical patients., 38
C van Walraven, IA Dhalla, C Bell (2010)
Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community., 182
BW Jack, VK Chetty, D Anthony (2009)
A reengineered hospital discharge program to decrease rehospitalization: a randomized trial., 150
RL Kane, G Keckhafer, S Flood, B Bershadsky, MS Siadaty (2003)
The effect of Evercare on hospital use., 51
HF Groenveld, JL Januzzi, K Damman (2008)
Anemia and mortality in heart failure patients: a systematic review and meta-analysis., 52
EA Coleman, SJ Min, A Chomiak, AM Kramer (2004)
Posthospital care transitions: patterns, complications, and risk identification., 39
GW Waterer, LA Kessler, RG Wunderink (2004)
Medium-term survival after hospitalization with community-acquired pneumonia., 169
P Halfon, Y Eggli, I Prêtre-Rohrbach, D Meylan, A Marazzi, B Burnand (2006)
Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care., 44
MD Silverstein, H Qin, SQ Mercer, J Fong, Z Haydar (2008)
Risk factors for 30-day hospital readmission in patients ?65 years of age., 21
JL Schnipper, CL Roumie, C Cawthon (2010)
Rationale and design of the Pharmacist Intervention for Low Literacy in Cardiovascular Disease (PILL-CVD) study., 3
D Kansagara, H Englander, A Salanitro (2011)
Risk prediction models for hospital readmission: a systematic review., 306
MD Naylor, D Brooten, R Campbell (1999)
Comprehensive discharge planning and home follow-up of hospitalized elders: a randomized clinical trial., 281
MD Naylor, DA Brooten, RL Campbell, G Maislin, KM McCauley, JS Schwartz (2004)
Transitional care of older adults hospitalized with heart failure: a randomized, controlled trial., 52
SF Jencks, MV Williams, EA Coleman (2009)
Rehospitalizations among patients in the Medicare fee-for-service program., 360
C van Walraven, C Bennett, A Jennings, PC Austin, AJ Forster (2011)
Proportion of hospital readmissions deemed avoidable: a systematic review., 183
O Hasan, DO Meltzer, SA Shaykevich (2010)
Hospital readmission in general medicine patients: a prediction model., 25
P Halfon, Y Eggli, G van Melle, J Chevalier, JB Wasserfallen, B Burnand (2002)
Measuring potentially avoidable hospital readmissions., 55
S Kripalani, CL Roumie, AK Dalal (2012)
Effect of a pharmacist intervention on clinically important medication errors after hospital discharge: a randomized trial., 157
ORIGINAL INVESTIGATION HEALTH CARE REFORM Potentially Avoidable 30-Day Hospital Readmissions in Medical Patients Derivation and Validation of a Prediction Model Jacques Donze ´, MD, MSc; Drahomir Aujesky, MD, MSc; Deborah Williams, MHA; Jeffrey L. Schnipper, MD, MPH Importance: Because effective interventions to reduce Results: Among 10 731 eligible discharges, 2398 dis- hospital readmissions are often expensive to imple- charges (22.3%) were followed by a 30-day readmis- ment, a score to predict potentially avoidable readmis- sion, of which 879 (8.5% of all discharges) were identi- sions may help target the patients most likely to benefit. fied as potentially avoidable. The prediction score identified 7 independent factors, referred to as the Objective: To derive and internally validate a predic- HOSPITAL score: hemoglobin at discharge, discharge from tion model for potentially avoidable 30-day hospital re- an oncology service, sodium level at discharge, proce- admissions in medical patients using administrative and dure during the index admission, index type of admis- clinical data readily available prior to discharge. sion, number of admissions during the last 12 months, and length of stay. In the validation set, 26.7% of the pa- Design: Retrospective cohort study. tients were classified as high risk, with an estimated po- tentially
JAMA Internal Medicine – American Medical Association
Published: Apr 22, 2013
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.