Risk stratification in primary total joint arthroplasty: the current state of knowledge

Christian Gronbeck, Mark P Cote, Jay R Lieberman, Mohamad J Halawi, Christian Gronbeck, Mark P Cote, Jay R Lieberman, Mohamad J Halawi

Abstract

Background: As we transition to value-based care delivery models, risk stratification in total joint arthroplasty is more important than ever. The purpose of this study was to identify patients who would likely require higher level of care and may not be suitable for inclusion in bundled payment models.

Methods: The American College of Surgeons National Surgical Quality Improvement Program database was queried for all patients who underwent primary total joint arthroplasty between 2011 and 2012. Five types of adverse events were assessed: medical complications, surgical complications, readmission, reoperation, and mortality. Univariate and multivariate logistic regression analyses were performed using a large number of demographic and morbidity variables.

Results: A total of 14,185 patients were identified. The 30-day medical complication, surgical complication, readmission, reoperation, and mortality rates were 2.0%, 3.2%, 4.0%, 1.5%, and 0.2%, respectively. Among the different variables assessed, only the American Society of Anesthesiologists (ASA) physical classification system was a significant risk factor for most outcomes assessed. Peripheral vascular disease was the most significant risk factor for medical complications and reoperation (odds ratio, 2.73 and 3.23, respectively). Bleeding disorders were the most significant risk factor for readmission and mortality (odds ratio, 2.03 and 5.86, respectively).

Conclusions: ASA score is a more reliable risk stratification tool than Charlson Comorbidity Index, but it is not sufficient by itself. Patients with higher ASA scores combined with peripheral vascular disease and/or bleeding disorders are at especially high risk of developing postsurgical adverse events and may not be suitable for inclusion in bundled payment models. These data can be used to develop better risk stratification models that are critically needed.

Keywords: ASA physical classification system; Arthroplasty; Charlson Comorbidity Index; Hip; Knee; Risk stratification.

Figures

Figure 1
Figure 1
Multimodal logistic regression analysis showing adjusted odds ratio scatter chart for the associations between development of a medically related adverse event and Charlson Comorbidity Index (CCI), American Society of Anesthesiologists (ASA) physical classification system, or demographic and comorbidity variables shown to be significant. ∗Indicates of significance the risk factor in the multimodal model at the P = .05 level. BMI, body mass index; COPD, chronic obstructive pulmonary disease.
Figure 2
Figure 2
Multimodal logistic regression analysis showing adjusted odds ratio scatter chart for the associations between development of a surgically related adverse event and CCI, ASA physical classification system, or demographic and comorbidity variables shown to be significant. ∗Indicates of significance the risk factor in the multimodal model at the P = .05 level.
Figure 3
Figure 3
Multimodal logistic regression analysis showing adjusted odds ratio scatter chart for the associations between development of readmission and CCI, ASA physical classification system, or demographic and comorbidity variables shown to be significant. ∗Indicates of significance the risk factor in the multimodal model at the P = .05 level.
Figure 4
Figure 4
Multimodal logistic regression analysis showing adjusted odds ratio scatter chart for the associations between development of reoperation and CCI, ASA physical classification system, or demographic and comorbidity variables shown to be significant. ∗Indicates of significance the risk factor in the multimodal model at the P = .05 level.
Figure 5
Figure 5
Multimodal logistic regression analysis showing adjusted odds ratio scatter chart for the associations between mortality and CCI, ASA physical classification system, or demographic and comorbidity variables shown to be significant. ∗Indicates of significance the risk factor in the multimodal model at the P = .05 level.

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