当前位置： SCI文献检索 > JAMA Surgery期刊下所有文献 > Nomogram to Predict Postoperative Readmission in Patients Who Undergo General Surgery.

Nomogram to Predict Postoperative Readmission in Patients Who Undergo General Surgery.

Abstract：

IMPORTANCE:The Centers for Medicare and Medicaid Services have implemented penalties for hospitals with above-average readmission rates under the Hospital Readmissions Reductions Program. These changes will likely be extended to affect postoperative readmissions in the future. OBJECTIVES:To identify variables that place patients at risk for readmission, develop a predictive nomogram, and validate this nomogram. DESIGN, SETTING, AND PARTICIPANTS:Retrospective review and prospective validation of a predictive nomogram. A predictive nomogram was developed with the linear predictor method using the American College of Surgeons National Surgical Quality Improvement Program database paired with institutional billing data for patients who underwent nonemergent inpatient general surgery procedures. The nomogram was developed from August 1, 2006, through December 31, 2011, in 2799 patients and prospectively validated from November 1, 2013, through December 19, 2013, in 255 patients at a single academic institution. Area under the curve and positive and negative predictive values were calculated. MAIN OUTCOMES AND MEASURES:The outcome of interest was readmission within 30 days of discharge following an index hospitalization for a surgical procedure. RESULTS:Bleeding disorder (odds ratio, 2.549; 95% CI, 1.464-4.440), long operative time (odds ratio, 1.601; 95% CI, 1.186-2.160), in-hospital complications (odds ratio, 16.273; 95% CI, 12.028-22.016), dependent functional status, and the need for a higher level of care at discharge (odds ratio, 1.937; 95% CI, 1.176-3.190) were independently associated with readmission. The nomogram accurately predicted readmission (C statistic = 0.756) in a prospective evaluation. The negative predictive value was 97.9% in the prospective validation, while the positive predictive value was 11.1%. CONCLUSIONS AND RELEVANCE:Development of an online calculator using this predictive model will allow us to identify patients who are at high risk for readmission at the time of discharge. Patients with increased risk may benefit from more intensive postoperative follow-up in the outpatient setting.

journal_name

JAMA Surg

journal_title

JAMA surgery

authors

Tevis SE,Weber SM,Kent KC,Kennedy GD

doi

10.1001/jamasurg.2014.4043

subject

Has Abstract

pub_date

2015-06-01 00:00:00

pages

505-10

issue

eissn

2168-6254

issn

2168-6262

pii

2276482

journal_volume

150

pub_type

杂志文章

在线工具

Nomogram to Predict Postoperative Readmission in Patients Who Undergo General Surgery.