Literature DB >> 30709587

Simplified risk prediction indices do not accurately predict 30-day death or readmission after discharge following colorectal surgery.

David G Brauer1, Sarah A Lyons1, Matthew R Keller2, Matthew G Mutch1, Graham A Colditz1, Sean C Glasgow3.   

Abstract

BACKGROUND: Risk-prediction indices are one category of the many tools implemented to guide efforts to decrease readmissions. However, using fied models to predict a complex process can prove challenging. In addition, no risk-prediction index has been developed for patients undergoing colorectal surgery. Therefore, we evaluated the performance of a widely utilized simplified index developed at the hospital level - LACE (length of stay, acute admission, Charlson comorbidity index score, and emergency department visits) and developed and evaluated a novel index in predicting readmissions in this patient population.
METHODS: Using a retrospective split-sample cohort, patients discharged after colorectal surgery were identified within the inpatient databases of the Healthcare Cost and Utilization Project for the states of New York, California, and Florida (2006-2014). The primary outcome was death or readmission within 30 days after discharge. Multivariable logistic regression models incorporated patient comorbidities, postoperative complications, and hospitalization details, and were evaluated using the C statistic.
RESULTS: A total of 440,742 patients met eligibility criteria. The rate of death or readmission within 30 days after discharge was 14.0% (n = 61,757). When applied to surgical patients, the LACE index demonstrated a poor model fit (C = 0.631). The model fit improved significantly-but remained poor (C = 0.654; P < .001)-with the addition of the following variables, which are known to be associated with readmission after colorectal surgery: age, indication for surgery, and creation of a new ostomy. A novel, simplified model also yielded a poor model fit (C = 0.660).
CONCLUSION: Postdischarge death or readmission after colorectal surgery is not accurately modeled using existing, modified, or novel simplified risk prediction models. Payers and providers must ensure that quality improvement efforts applying simplified models to complex processes, such as readmissions following colorectal surgery, may not be appropriate, and that models reflect the relevant patient population. Published by Elsevier Inc.

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Year:  2019        PMID: 30709587      PMCID: PMC6502644          DOI: 10.1016/j.surg.2018.12.007

Source DB:  PubMed          Journal:  Surgery        ISSN: 0039-6060            Impact factor:   3.982


  24 in total

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Authors:  Lisa M Sullivan; Joseph M Massaro; Ralph B D'Agostino
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Review 2.  Risk prediction models for hospital readmission: a systematic review.

Authors:  Devan Kansagara; Honora Englander; Amanda Salanitro; David Kagen; Cecelia Theobald; Michele Freeman; Sunil Kripalani
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3.  Readmission rates and cost following colorectal surgery.

Authors:  Elizabeth C Wick; Andrew D Shore; Kenzo Hirose; Andrew M Ibrahim; Susan L Gearhart; Jonathan Efron; Jonathan P Weiner; Martin A Makary
Journal:  Dis Colon Rectum       Date:  2011-12       Impact factor: 4.585

4.  Predicting the risk of unplanned readmission or death within 30 days of discharge after a heart failure hospitalization.

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Journal:  Am Heart J       Date:  2012-08-17       Impact factor: 4.749

5.  Evaluation of hospital readmissions in surgical patients: do administrative data tell the real story?

Authors:  Greg D Sacks; Aaron J Dawes; Marcia M Russell; Anne Y Lin; Melinda Maggard-Gibbons; Deborah Winograd; Hallie R Chung; James Tomlinson; Areti Tillou; Stephen B Shew; Darryl T Hiyama; H Gill Cryer; F Charles Brunicardi; Jonathan R Hiatt; Clifford Ko
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6.  Do hospital factors impact readmissions and mortality after colorectal resections at minority-serving hospitals?

Authors:  Elizabeth M Hechenbleikner; Chaoyi Zheng; Samuel Lawrence; Young Hong; Nawar M Shara; Lynt B Johnson; Waddah B Al-Refaie
Journal:  Surgery       Date:  2016-10-28       Impact factor: 3.982

7.  Racial Disparities in Readmissions for Patients with Inflammatory Bowel Disease (IBD) After Colorectal Surgery.

Authors:  Drew J Gunnells; Melanie S Morris; Aerin DeRussy; Allison A Gullick; Talha A Malik; Jamie A Cannon; Mary T Hawn; Daniel I Chu
Journal:  J Gastrointest Surg       Date:  2016-01-07       Impact factor: 3.452

Review 8.  Preventing 30-day hospital readmissions: a systematic review and meta-analysis of randomized trials.

Authors:  Aaron L Leppin; Michael R Gionfriddo; Maya Kessler; Juan Pablo Brito; Frances S Mair; Katie Gallacher; Zhen Wang; Patricia J Erwin; Tanya Sylvester; Kasey Boehmer; Henry H Ting; M Hassan Murad; Nathan D Shippee; Victor M Montori
Journal:  JAMA Intern Med       Date:  2014-07       Impact factor: 21.873

9.  Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study.

Authors:  Shu Yun Tan; Lian Leng Low; Yong Yang; Kheng Hock Lee
Journal:  BMC Health Serv Res       Date:  2013-09-29       Impact factor: 2.655

10.  Using the LACE index to predict hospital readmissions in congestive heart failure patients.

Authors:  Hao Wang; Richard D Robinson; Carlos Johnson; Nestor R Zenarosa; Rani D Jayswal; Joshua Keithley; Kathleen A Delaney
Journal:  BMC Cardiovasc Disord       Date:  2014-08-07       Impact factor: 2.298

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  1 in total

1.  Care Fragmentation and Mortality in Readmission after Surgery for Hepatopancreatobiliary and Gastric Cancer: A Patient-Level and Hospital-Level Analysis of the Healthcare Cost and Utilization Project Administrative Database.

Authors:  David G Brauer; Ningying Wu; Matthew R Keller; Sarah A Humble; Ryan C Fields; Chet W Hammill; William G Hawkins; Graham A Colditz; Dominic E Sanford
Journal:  J Am Coll Surg       Date:  2021-04-15       Impact factor: 6.532

  1 in total

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