Predictors of 30-day hospital readmission after coronary artery bypass

Stewart, Robert D.; Campos, Christian T.; Jennings, B R; Lollis, S. Scott; Levitsky, Sidney; Lahey, Stephen J.

doi:10.1016/s0003-4975(00)01386-2

Cited by 80 publications

(70 citation statements)

References 5 publications

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“…18 Smaller studies have found much higher 30-day to 2-year all-cause readmission rates for females; however, this was attributed in part to a higher occurrence of surgical wound infections. 13,16,31,32 In contrast, in Sweden, a study with 1588 female patients found no gender difference in all-cause readmission rates with multivariable adjustment. 17 The pres- …”

Section: Discussionmentioning

confidence: 90%

“…15 This finding was also noted in a small study (nϭ158 women) in which gender was associated with an OR of 2.45 (95% CI 1.44 to 4.20) for 30-day readmission. 16 In contrast, a Swedish study involving 1588 women demonstrated no difference in readmission between men and women (OR 1.06, 95% CI 0.98 to 1.13) over a mean follow-up period of 2.1 years. 17 Follow-up of CABG patients in western Sweden revealed no gender differences in rates of myocardial infarction or stroke; however, at 5 years after surgery, women complained of angina more frequently than men.…”

Section: Clinical Perspective P 516mentioning

confidence: 91%

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Gender Differences in Outcomes After Hospital Discharge From Coronary Artery Bypass Grafting

et al. 2006

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Background-There are few comparative data regarding long-term nonfatal outcomes for women versus men after coronary artery bypass grafting (CABG). This study compares gender differences in cardiac events in a population of hospital survivors up to 11 years after isolated CABG surgery in Ontario, Canada. Methods and Results-A population-based cohort study (nϭ68 774 patients, 15 043 women) between September 1, 1991, and April 1, 2002, was assembled with linked clinical and administrative databases. Cox modeling and propensity score matching were used to compare death, cardiac readmission (angina, heart failure, myocardial infarction), repeat revascularization (angioplasty or CABG), and stroke readmission between men and women. Women were older (65Ϯ17 versus 62Ϯ13 years), more likely to present with urgent or emergent status (64% versus 56%), and less likely to receive arterial grafts (70% versus 78%). Women had a higher rate of cardiac readmission in the first year after surgery (hazard ratio [HR] of 1.5, 95% confidence interval [CI] 1.36 to 1.56), and this increased risk persisted after 1 year (HR 1.2, 95% CI 1.14 to 1.31). This was primarily due to readmissions for unstable angina (HR 1.3, 95% CI 1.24 to 1.38) and congestive heart failure (HR 1.1, 95% CI 1.06 to 1.21). Propensity-matched women had similar rates of death (HR 0.9, 95% CI 0.83 to 0.98) and repeat revascularization (HR 1.0, 95% CI 0.91 to 1.06). Conclusions-Women have a more complex clinical preoperative presentation and are more likely to be readmitted with unstable angina and congestive heart failure after CABG but experience survival similar to those seen in men. Gender differences in outcomes may be improved through durable revascularization strategies and close postoperative follow-up care targeted to women. (Circulation. 2006;113:507-516.)

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Section: Discussionmentioning

confidence: 90%

Section: Clinical Perspective P 516mentioning

confidence: 91%

Gender Differences in Outcomes After Hospital Discharge From Coronary Artery Bypass Grafting

et al. 2006

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“…The risk prediction models developed for clinical predictive purposes may not be used as risk adjustments, as the data on risk variables such as patient laboratory results or functional status are often not included in administrative data or insurance claims data. For example, Stewart et al (2000) in their study on predictors of 30-day hospital readmission after coronary artery bypass found patients' high level of creatinine or decreased left ventricular ejection fraction are associated with higher risks of readmission; however these variables are usually lacking in administrative or insurance claims data.…”

Section: Application Of Risk Prediction Modelsmentioning

confidence: 99%

Once A Cure; Second A Waste: Examining Hospital Readmission Rates of the Commercially Insured Under 65 Population

Fu¹

2016

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“…Among published studies, [18][19][20] including the current report, half of all CABG readmissions are to hospitals other than where surgery was performed. This is substantially >20% to 40% average for all Medicare readmissions 16 and emphasizes the need to link clinical data with claims sources to ensure complete case ascertainment.…”

Section: Many Cabg Readmissions Go To Other Hospitalsmentioning

confidence: 99%

“…Numerous studies 11,[18][19][20][21][22][24][25][26] have examined the causes and predictors of readmission after cardiac surgery, including CABG. Common reasons for readmission include wound infections; heart failure; arrhythmias; indeterminate chest pain, myocardial infarction, or angina; pneumonia or pleural effusions; stroke; sepsis; gastrointestinal complications; and renal failure.…”

Section: Improvement Opportunitiesmentioning

confidence: 99%

Development of a Clinical Registry-Based 30-Day Readmission Measure for Coronary Artery Bypass Grafting Surgery

Shahian

O’Brien

et al. 2014

Circulation

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Background— Reducing readmissions is a major healthcare reform goal, and reimbursement penalties are imposed for higher-than-expected readmission rates. Most readmission risk models and performance measures are based on administrative rather than clinical data. Methods and Results— We examined rates and predictors of 30-day all-cause readmission following coronary artery bypass grafting surgery by using nationally representative clinical data (2008–2010) from the Society of Thoracic Surgeons National Database linked to Medicare claims records. Among 265 434 eligible Medicare records, 226 960 (86%) were successfully linked to Society of Thoracic Surgeons records; 162 572 (61%) isolated coronary artery bypass grafting admissions constituted the study cohort. Logistic regression was used to identify readmission risk factors; hierarchical regression models were then estimated. Risk-standardized readmission rates ranged from 12.6% to 23.6% (median, 16.8%) among 846 US hospitals with ≥30 eligible cases and ≥90% of eligible Centers for Medicare and Medicaid Services records linked to the Society of Thoracic Surgeons database. Readmission predictors (odds ratios [95% confidence interval]) included dialysis (2.02 [1.87–2.19]), severe chronic lung disease (1.58 [1.49–1.68]), creatinine (2.5 versus 1.0 or lower:1.49 [1.41–1.57]; 2.0 versus 1.0 or lower: 1.37 [1.32–1.43]), insulin-dependent diabetes mellitus (1.45 [1.39–1.51]), obesity in women (body surface area 2.2 versus 1.8: 1.44 [1.35–1.53]), female sex (1.38 [1.33–1.43]), immunosuppression (1.38 [1.28–1.49]), preoperative atrial fibrillation (1.36 [1.30–1.42]), age per 10-year increase (1.36 [1.33–1.39]), recent myocardial infarction (1.24 [1.08–1.42]), and low body surface area in men (1.22 [1.14–1.30]). C-statistic was 0.648. Fifty-two hospitals (6.1%) had readmission rates statistically better or worse than expected. Conclusions— A coronary artery bypass grafting surgery readmission measure suitable for public reporting was developed by using the national Society of Thoracic Surgeons clinical data linked to Medicare readmission claims.

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Predictors of 30-day hospital readmission after coronary artery bypass

Cited by 80 publications

References 5 publications

Gender Differences in Outcomes After Hospital Discharge From Coronary Artery Bypass Grafting

Gender Differences in Outcomes After Hospital Discharge From Coronary Artery Bypass Grafting

Once A Cure; Second A Waste: Examining Hospital Readmission Rates of the Commercially Insured Under 65 Population

Development of a Clinical Registry-Based 30-Day Readmission Measure for Coronary Artery Bypass Grafting Surgery

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