Quality Measurement in Adult Cardiac Surgery: Part 2—Statistical Considerations in Composite Measure Scoring and Provider Rating

O’Brien, Sean M.; Shahian, David M.; DeLong, Elizabeth R.; Normand, Sharon‐Lise T.; Edwards, Fred H.; Ferraris, Victor A.; Haan, Constance K.; Rich, Jeffrey B.; Shewan, Cynthia M.; Dokholyan, Rachel S.; Anderson, Richard P.; Peterson, Eric D.

doi:10.1016/j.athoracsur.2007.01.055

Cited by 208 publications

(159 citation statements)

References 13 publications

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“…July 29,2014 likely that the conditions requiring readmission, often surgical complications, were major contributors to increased mortality.…”

Section: Circulationmentioning

confidence: 99%

“…Furthermore, mortality is only 1 aspect of quality, which led the STS to implement and publicly report a composite CABG performance measure consisting of 11 individual measures of performance in 4 domains. [28][29][30][31] Readmission may be another important candidate metric for multidimensional performance assessment. For CABG, as with several medical conditions, 32 risk-adjusted mortality and readmission rates measure overlapping but different aspects of quality.…”

Section: Readmission and Mortality Rates Are Complementary Performancmentioning

confidence: 99%

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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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“…July 29,2014 likely that the conditions requiring readmission, often surgical complications, were major contributors to increased mortality.…”

Section: Circulationmentioning

confidence: 99%

Section: Readmission and Mortality Rates Are Complementary Performancmentioning

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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“…This high level of agreement is consistent with previously reported results from the same STS data set. 18 Although the method of combining process measures made little difference for performance rankings, other small variations had a large impact. Merely reversing the outcome assessment from survival to mortality ratios resulted in some providers switching from best to worst performers.…”

Section: O'brien Et Al Behavior Of Composite Measures 2973mentioning

confidence: 99%

“…Neither the HQID method nor the variations we explored involve sophisticated statistical modeling, such as the type recommended by O'Brien et al 18 In these more complex analyses, hierarchical models are used to produce "shrunken" estimates that more reliably reflect each provider's long-run performance. These shrunken estimates can be combined with a simple weighting scheme that is "balanced" in its weighting of process and outcome measures.…”

Section: O'brien Et Al Behavior Of Composite Measures 2973mentioning

confidence: 99%

Exploring the Behavior of Hospital Composite Performance Measures

et al. 2007

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Background-Composite scores that combine several performance measures into a single ranking are becoming the accepted metric for assessing hospital performance. In particular, the Centers for Medicare & Medicaid Services Hospital Quality Incentive Demonstration (HQID) project bases financial rewards and penalties on these scores. Although the HQID composite calculation is straightforward and easily understood, its method of combining process and outcome measures has not been validated. Methods and Results-Using data on 530 hospitals from the Society of Thoracic Surgeons National Cardiac Database, we replicated the HQID methodology with 6 nationally endorsed performance measures (5 process measures plus survival) for coronary artery bypass surgery. Composite scores were essentially determined by process measure performance alone; the survival component explained only 4% of the composite score's total variance. This result persisted even when the survival component was allowed a 5-fold greater weighting in the composite summary. The popular "all-or-none" measurement approach was also dominated by the process component. Substantial disagreement was found among hospital rankings when several alternative methods were used; up to 60% of hospitals eligible for the top financial reward under HQID would change designation depending on the composite methodology used. The application of a simple statistical adjustment (standardization) to each method would provide more consistent results and a more balanced assessment of performance based on both process and outcomes. Conclusions-Existing methods used to create composite performance measures have remarkably different weighting of process versus outcomes metrics and lead to highly divergent provider rankings. Simple alternative methods can create more balanced process-outcome performance assessments.

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“…The four domains of STS quality measures are 1) perioperative medical care of preoperative beta blockade, discharge aspirin, discharge beta blockade, and discharge antilipid therapy; 2) operative care of the use of at least one IMA; 3) risk-adjusted operative mortality; and 4) absence of postoperative morbidity, specifically renal insufficiency, deep sternal wound infection, re-exploration for any cause, stroke, and prolonged ventilation/intubation [72]. The STS QMTF has developed and tested a composite measure of cardiac surgery quality that encompasses multiple domains of care, uses Bayesian random-effects analyses, uses all-or-none scoring where appropriate, and avoids subjective weighting of individual measures, to provide validated quality measures useful to various types of users [73]. With the STS composite quality score in use, Shahian and colleagues looked at the association of hospital CABG volume to the STS composite quality score, and found only 1% of composite score variation was explained by volume [70].…”

Section: Application Of Performance Measures For Reporting Qualitymentioning

confidence: 99%

Risk Prediction and Outcome Analysis

Haan¹

2012

Current Concepts in General Thoracic Surgery

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Quality Measurement in Adult Cardiac Surgery: Part 2—Statistical Considerations in Composite Measure Scoring and Provider Rating

Cited by 208 publications

References 13 publications

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

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

Exploring the Behavior of Hospital Composite Performance Measures

Risk Prediction and Outcome Analysis

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