Value-Based Care Has Not Resulted in Biased Patient Selection: Analysis of a Single Center’s Experience in the Care for Joint Replacement Bundle

Ryan, Sean P.; Plate, Johannes F.; Black, Collin S.; Howell, Claire B.; Jiranek, William A.; Bolognesi, Michael P.; Seyler, Thorsten M.

doi:10.1016/j.arth.2019.04.052

Cited by 21 publications

(20 citation statements)

References 28 publications

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“…Value-based care aims to lower healthcare costs associated with metastatic brain tumor management [ 4 ]. Important metrics used to gauge the effectiveness of value-based care approaches include minimizing hospital length of stay, optimizing discharge disposition, and reducing costs [ 5 , 6 ]. While statistical models that predict these value-based outcomes have been developed within various medical specialties, there is a lack of generalizability of these models for practical use in the metastatic brain tumor population [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

A novel online calculator predicting short-term postoperative outcomes in patients with metastatic brain tumors

et al. 2020

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Purpose Establishing predictors of hospital length of stay (LOS), discharge deposition, and total hospital charges is essential to providing high-quality, value-based care. Though previous research has investigated these outcomes for patients with metastatic brain tumors, there are currently no tools that synthesize such research findings and allow for prediction of these outcomes on a patient-by-patient basis. The present study sought to develop a prediction calculator that uses patient demographic and clinical information to predict extended hospital length of stay, non-routine discharge disposition, and high total hospital charges for patients with metastatic brain tumors. Methods Patients undergoing surgery for metastatic brain tumors at a single academic institution were analyzed (2017–2019). Multivariate logistic regression was used to identify independent predictors of extended LOS (> 7 days), non-routine discharge, and high total hospital charges (> $ 46,082.63). p < 0.05 was considered statistically significant. C-statistics and the Hosmer–Lemeshow test were used to assess model discrimination and calibration, respectively. Results A total of 235 patients were included in our analysis, with a mean age of 62.74 years. The majority of patients were female (52.3%) and Caucasian (76.6%). Our models predicting extended LOS, non-routine discharge, and high hospital charges had optimism-corrected c-statistics > 0.7, and all three models demonstrated adequate calibration (p > 0.05). The final models are available as an online calculator ( https://neurooncsurgery.shinyapps.io/brain_mets_calculator/ ). Conclusions Our models predicting postoperative outcomes allow for individualized risk-estimation for patients following surgery for metastatic brain tumors. Our results may be useful in helping clinicians to provide resource-conscious, high-value care.

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Section: Introductionmentioning

confidence: 99%

A novel online calculator predicting short-term postoperative outcomes in patients with metastatic brain tumors

et al. 2020

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“…Preoperative risk management programs were implemented to intervene in modifiable risk factors that can be addressed preoperatively to reduce the likelihood of complications like surgical site infections and prosthetic joint infections, readmissions, long LOS, and reoperation as well as reduced costs [7, 12, 19, 24, 25, 29, 41, 51, 54, 56-58]. These programs focus on managing modifiable risk factors such as obesity, malnutrition, diabetes, anemia, smoking, and substance use and make recommendations or referrals for managing these factors preoperatively.…”

Section: What We (Think) We Knowmentioning

confidence: 99%

“…For example, Ryan et al [56] found that only 34% of patients for whom a referral for preoperative treatment was recommended for weight loss, anemia, smoking cessation, pain management, hematology, endocrinology, or cardiology received a referral to the appropriate specialist. The remaining 11 studies we found related to preoperative risk management programs (Table 2) did not attempt to measure the success of their referrals to outside specialists [7,12,19,24,25,29,41,51,54,57,58]. Without well-established referral pathways and nurse navigation, preoperative risk management becomes a barrier to TJA, and fails to provide the necessary resources for patients from racial or ethnic minority backgrounds and patients with lower incomes to reach preoperative guideline thresholds.…”

Section: What We (Think) We Knowmentioning

confidence: 99%

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CORR Synthesis: How Might the Preoperative Management of Risk Factors Influence Healthcare Disparities in Total Joint Arthroplasty?

Dlott

Wiznia

2022

Clin Orthop Relat Res

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Both authors certify that there are no funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article related to the author or any immediate family members. All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research® editors and board members are on file with the publication and can be viewed on request. The opinions expressed are those of the writers, and do not reflect the opinion or policy of CORR® or The Association of Bone and Joint Surgeons®.

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“…BM patients face a high cost of care due to multi-modality treatments [1,3,4] with added prognostic uncertainties with signi cant morbidity and mortality [5]. Accurately predicting patients at high risk for a prolonged length of stay (LOS) and poor discharge dispositions after surgery may inform upfront surgical decision-making and optimize care centered around patient's preferences and healthcare resource utilization [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Validation of an Online Calculator to Predict Short-term Postoperative Outcomes in Patients with Metastatic Brain Tumors

Kang

Murphy

McCray

et al. 2021

Preprint

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Introduction: Estimating the risk of extended length of stay (LOS) or non-routine discharge disposition is helpful in surgical decision-making for patients with brain metastases (BM). In 2020, an online calculator was introduced by Khalafallah et al. that stratified the risk of patients with brain tumors based on poor surgical outcomes. We applied the calculator to our population of BM patients to determine its generalizability and validity. Methods: We included BM patients who underwent a cranial procedure between 2015 and 2018 at a single academic institution. Patient age, race, marital status, admission status, KPS score, and medical co-morbidities (5-point modified frailty index (mFI-5)) were included in the analysis. We calculated the areas under the Receiver Operating Characteristics (ROC) curves to determine the validity of the model proposed in predicting extended LOS (>7 days) and need for specialty care at discharge (non-routine discharge disposition). Results: We analyzed 244 patients (mean age 61.2 years (SD 11.1), 57.0% female, and 78.1% Caucasian). The areas under the ROC curves were 0.8427 and 0.8422 for extended LOS and non-routine discharge disposition, suggesting high accuracy of the models for these outcomes. However, the (mFI-5) was not a significant predictor of either outcome in our multivariate analyses. Conclusions: We validated Khalafallah et al.’s predictive models of extended LOS and non-routine discharge disposition in our patient population, which included a broader range of surgical procedures. Further investigation of this model could clarify how the type of neurosurgical procedure influences outcomes, the role of the mFI-5, and its overall generalizability.

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Value-Based Care Has Not Resulted in Biased Patient Selection: Analysis of a Single Center’s Experience in the Care for Joint Replacement Bundle

Cited by 21 publications

References 28 publications

A novel online calculator predicting short-term postoperative outcomes in patients with metastatic brain tumors

A novel online calculator predicting short-term postoperative outcomes in patients with metastatic brain tumors

CORR Synthesis: How Might the Preoperative Management of Risk Factors Influence Healthcare Disparities in Total Joint Arthroplasty?

Validation of an Online Calculator to Predict Short-term Postoperative Outcomes in Patients with Metastatic Brain Tumors

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