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October 18, 2009Journal of the American College of Surgeons

Risk Adjustment in the American College of Surgeons National Surgical Quality Improvement Program: A Comparison of Logistic Versus Hierarchical Modeling

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Why the study?

Does hierarchical modeling yield important differences in quality assessments compared with logistic models when applied to ACS-NSQIP data?

Population

ACS-NSQIP patients who underwent colorectal operations in 2008 at hospitals that reported at least 100…

Comparison

Hierarchical modeling for risk adjustment vs Logistic regression modeling

Design

Other

Follow-up

30-day

Authors

MCMark E. CohenNorthwestern UniversityJDJustin B. DimickDartmouth CollegeKBKarl Y. BilimoriaNorthwestern University

Discussion

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Implication

Logistic regression identifies nearly identical ACS-NSQIP outliers as hierarchical modeling; supports its continued use but leaves open generalizability to other datasets.

Structured PICO

Does hierarchical modeling yield important differences in quality assessments compared with logistic models when applied to ACS-NSQIP data?

P
Population
ACS-NSQIP patients who underwent colorectal operations in 2008 at hospitals that reported at least 100 operations
I
Intervention
Hierarchical modeling for risk adjustment
C
Comparator
Logistic regression modeling
O
Outcome
Identification of hospitals with outlying outcomes for 30-day morbidity and mortality

Logistic regression provides nearly identical results to hierarchical modeling for identifying hospital outliers in ACS-NSQIP data, remaining an accurate and efficient method for risk adjustment.

Cite This Study

Cohen et al. (2009) studied this question.

synapsesocial.com/papers/6a71640e75498292b70adf27https://doi.org/10.1016/j.jamcollsurg.2009.08.020
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