What Are the Cost Drivers for the Major Bowel Bundled Payment Care Improvement Initiative?

2020 ◽  
Vol 64 (1) ◽  
pp. 112-118
Author(s):  
Rocco Ricciardi ◽  
Marilyn A. Moucharite ◽  
Caitlin Stafford ◽  
Guy Orangio ◽  
Patricia L. Roberts
Keyword(s):  
Cost Drivers ◽  
Bundled Payment ◽  
Care Improvement ◽  
The Cost

scholarly journals Simulating Costs for Episode-Based Bundled Payments for Cranial Neurosurgical Procedures

Neurosurgery ◽  
2019 ◽  
Vol 66 (Supplement_1) ◽  
Author(s):  
Zachary A Medress ◽  
Beatrice Ugiliweneza ◽  
Jonathon J Parker ◽  
Dengzhi Wang ◽  
Eric Burton ◽  
...  
Keyword(s):  
Malignant Glioma ◽  
Administrative Database ◽  
Orthopedic Procedures ◽  
Neurosurgical Procedures ◽  
Bundled Payment ◽  
Bundled Payments ◽  
Significant Variability ◽  
Cost Variability ◽  
Care Improvement ◽  
The Cost

Abstract INTRODUCTION Episode-based bundled payments were introduced by Medicare in 2013 as the Bundled Care Improvement Initiative (BPCI) in order to improve care coordination and cost efficiency. BPCI has been implemented for orthopedic, cardiac, and spine procedures, but has not yet been applied to cranial neurosurgical procedures. We project the cost of episode-based bundled payments for cranial neurosurgical procedures. METHODS We performed a large retrospective observational study using the MarketScan administrative database to project bundled payment costs for common cranial neurosurgical procedures. Operations were classified into 4 groups: craniotomy for unruptured aneurysm, craniotomy for meningioma, craniotomy for malignant glioma, and craniotomy for metastasis. We project 30-, 60-, and 90-d bundle payments for each category, and analyze the contributions of postdischarge costs to total bundle payments at each time point. RESULTS We identified 15 276 procedures that met our inclusion criteria. We observed significant variability between groups, with 90-d bundle projected costs ranging from $58,200 for craniotomy for meningioma to $102,073 for craniotomy for malignant glioma. We also found significant variability in projected bundled payments within each class of operation. On average, payment for the index hospitalization accounted for 85% of projected costs for a 30-d bundle and 70.5% of projected costs for a 90-d bundle. Multivariate analysis showed that medical comorbidities, adjuvant therapies, and payer status significantly contributed to projected cranial bundle costs. CONCLUSION For the first time in our knowledge, we report projected costs of 30-, 60-, and 90-d episode-based bundled payments for common elective vascular and tumor cranial operations. As previously identified in the orthopedic literature, there is significant cost variability in total bundle payments within each cranial procedure. Compared to spine and orthopedic procedures, postdischarge costs significantly impact total bundle payments in cranial neurosurgery.

scholarly journals Real-Time Identification of Patients Included in the CMS Bundled Payment Care Improvement (BPCI) Program

2020 ◽  
Vol 41 (S1) ◽  
pp. s367-s368
Author(s):  
Michael Korvink ◽  
John Martin ◽  
Michael Long
Keyword(s):  
Performance Evaluation ◽  
Real Time ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Care Providers ◽  
Meta Model ◽  
Bundled Payment ◽  
Clinical Cohort ◽  
Real Time Identification ◽  
Care Improvement

Background: The Bundled Payment Care Improvement Program is a CMS initiative designed to encourage greater collaboration across settings of care, especially as it relates to an initial set of targeted clinical episodes, which include sepsis and pneumonia. As with many CMS incentive programs, performance evaluation is retrospective in nature, resulting in after-the-fact changes in operational processes to improve both efficiency and quality. Although retrospective performance evaluation is informative, care providers would ideally identify a patient’s potential clinical cohort during the index stay and implement care management procedures as necessary to prevent or reduce the severity of the condition. The primary challenges for real-time identification of a patient’s clinical cohort are CMS-targeted cohorts are based on either MS-DRG (grouping of ICD-10 codes) or HCPCS coding—coding that occurs after discharge by clinical abstractors. Additionally, many informative data elements in the EHR lack standardization and no simple and reliable heuristic rules can be employed to meaningfully identify those cohorts without human review. Objective: To share the results of an ensemble statistical model to predict patient risks of sepsis and pneumonia during their hospital (ie, index) stay. Methods: The predictive model uses a combination of Bernoulli Naïve Bayes natural language processing (NLP) classifiers, to reduce text dimensionality into a single probability value, and an eXtreme Gradient Boosting (XGBoost) algorithm as a meta-model to collectively evaluate both standardized clinical elements alongside the NLP-based text probabilities. Results: Bernoulli Naïve Bayes classifiers have proven to perform well on short text strings and allow for highly explanatory unstructured or semistructured text fields (eg, reason for visit, culture results), to be used in a both comparative and generalizable way within the larger XGBoost model. Conclusions: The choice of XGBoost as the meta-model has the benefits of mitigating concerns of nonlinearity among clinical features, reducing potential of overfitting, while allowing missing values to exist within the data. Both the Bayesian classifier and meta-model were trained using a patient-level integrated dataset extracted from both a patient-billing and EHR data warehouse maintained by Premier. The data set, joined by patient admission-date, medical record number, date of birth, and hospital entity code, allows the presence of both the coded clinical cohort (derived from the MS-DRG) and the explanatory features in the EHR to exist within a single patient encounter record. The resulting model produced F1 performance scores of .65 for the sepsis population and .61 for the pneumonia population.Funding: NoneDisclosures: None

scholarly journals Early Effects of Medicareʼs Bundled Payment for Care Improvement Program for Lumbar Fusion

Spine ◽  
2018 ◽  
Vol 43 (10) ◽  
pp. 705-711 ◽  
Author(s):  
Brook I. Martin ◽  
Jon D. Lurie ◽  
Farrokh R. Farrokhi ◽  
Kevin J. McGuire ◽  
Sohail K. Mirza
Keyword(s):  
Lumbar Fusion ◽  
Improvement Program ◽  
Bundled Payment ◽  
Early Effects ◽  
Care Improvement

Medicare bundles for arthroplasty

2021 ◽  
Vol 103-B (6 Supple A) ◽  
pp. 119-125
Author(s):  
Bryan D. Springer ◽  
Jordan McInerney
Keyword(s):  
Acute Care ◽  
Acute Care Hospitals ◽  
Drop Out ◽  
Retention Rates ◽  
Fee For Service ◽  
Target Price ◽  
High Performing ◽  
Bundled Payment ◽  
Bundled Payments ◽  
Care Improvement

Aims There is concern that aggressive target pricing in the new Bundled Payment for Care Improvement Advanced (BPCI-A) penalizes high-performing groups that had achieved low costs through prior experience in bundled payments. We hypothesize that this methodology incorporates unsustainable downward trends on Target Prices and will lead to groups opting out of BPCI Advanced in favour of a traditional fee for service. Methods Using the Centers for Medicare and Medicaid Services (CMS) data, we compared the Target Price factors for hospitals and physician groups that participated in both BPCI Classic and BPCI Advanced (legacy groups), with groups that only participated in BPCI Advanced (non-legacy). With rebasing of Target Prices in 2020 and opportunity for participants to drop out, we compared retention rates of hospitals and physician groups enrolled at the onset of BPCI Advanced with current enrolment in 2020. Results At its peak in July 2015, 342 acute care hospitals and physician groups participated in Lower Extremity Joint Replacement (LEJR) in BPCI Classic. At its peak in March 2019, 534 acute care hospitals and physician groups participated in LEJR in BPCI Advanced. In January 2020, only 14.5% of legacy hospitals and physician groups opted to stay in BPCI Advanced for LEJR. Analysis of Target Price factors by legacy hospitals during both programmes demonstrates that participants in BPCI Classic received larger negative adjustments on the Target Price than non-legacy hospitals. Conclusion BPCI Advanced provides little opportunity for a reduction in cost to offset a reduced Target Price for efficient providers, as made evident by the 85.5% withdrawal rate for BPCI Advanced. Efficient providers in BPCI Advanced are challenged by the programme’s application of trend and efficiency factors that presumes their cost reduction can continue to decline at the same rate as non-efficient providers. It remains to be seen if reverting back to Medicare fee for service will support the same level of care and quality achieved in historical bundled payment programmes. Cite this article: Bone Joint J 2021;103-B(6 Supple A):119–125.

Impact of Bundled Payment Care Improvement Initiative on Healthcare Expenditure in Major Bowel Procedures

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Robert N. Goldstone ◽  
Jianying Zhang ◽  
Caitlin Stafford ◽  
Liliana Bordeianou ◽  
Hiroko Kunitake ◽  
...  
Keyword(s):  
Healthcare Expenditure ◽  
Bundled Payment ◽  
Care Improvement

Cloud Build Methodology

2021 ◽  
pp. 108-132
Author(s):  
Richard Ehrhardt
Keyword(s):  
Hybrid Cloud ◽  
Design Decisions ◽  
Cost Drivers ◽  
Hybrid Clouds ◽  
Different Types ◽  
The Cost

The cloud build methodology chapter provides an introduction to the build methods for hybrid clouds. It does this by first introducing the concept of a hybrid cloud and the different types of services provides by clouds. It then overviews the components of hybrid clouds and how these components get incorporated into the design. It takes a brief look at the cost drivers with building a cloud to provide background with design decisions to be made. With the background on the design, it takes the reader through the build of a hybrid cloud and how automation can be used to reduce the cost. Lastly, it takes a brief look at a possible direction of cloud builds.

Cost Drivers for 2.5D and 3D Applications

2013 ◽  
Vol 2013 (DPC) ◽  
pp. 000334-000346
Author(s):  
Chet Palesko ◽  
E. Jan Vardaman ◽  
Alan Palesko
Keyword(s):  
High Performance ◽  
Specific Activity ◽  
Cost Effective ◽  
Cost Models ◽  
Network Systems ◽  
Cost Drivers ◽  
Technology Applications ◽  
Silicon Vias ◽  
The Cost ◽  
3D Applications

2.5D and 3D applications using through silicon vias (TSVs) are increasingly being considered as a packaging alternative. Miniaturization and high performance product requirements are driving this move – even though in many cases the cost of both 2.5D and 3D is still high. The primary applications for 2.5D interposers with TSVs are GPUs/CPUs, high-end ASICs, and FPGAs. Adoption for FPGAs has already started. The key to the performance gains in recently introduced FPGAs is the partitioning of an FPGA die into four “slices” that are mounted on a silicon interposer or what Xilinx calls its Stacked Silicon Interconnect technology. Applications for interposers include tablets, gaming, and high-end computing and network systems. The drivers are mainly partitioning large die, integrating single chips into a module, reducing die size where substrate density is the constraint, and using the interposer to minimize the stress on large die that are fabricated with extra-low-k (ELK) dielectrics. The primary applications for 3D solutions are stacked memory cubes and memory plus logic. The true 3D nature of stacking all active silicon allows better miniaturization, but yield issues can quickly drive the cost unacceptably high. This analysis examines the cost drivers for 2.5D and 3D applications. Activity based cost models will be used to analyze the complete cost of fabricating and assembling active die on a silicon interposer and active die stacking on other active die. Total product cost impact - not just the cost of a specific activity - is the focus of this analysis. Since yields play a major role in cost, a sensitivity analysis of the different yields including die yield before wafer probe, die yield after wafer probe, TSV yield, interposer yield, assembly yield, substrate yield, etc. will be presented. The critical yield points in the manufacturing flow and dominant activity cost drivers (equipment, material, and /or labor) will be presented as well as suggested minimum thresholds for 2.5D and 3D technology to be a cost effective technology.

Cost Comparison of 2.5D/3D Packaging to other Packaging Technologies

2013 ◽  
Vol 2013 (1) ◽  
pp. 000429-000433
Author(s):  
Chet Palesko ◽  
Amy Palesko ◽  
E. Jan Vardaman
Keyword(s):  
Cost Reduction ◽  
High Performance ◽  
Cost Comparison ◽  
Through Silicon Vias ◽  
Cost Drivers ◽  
3D Packaging ◽  
Silicon Vias ◽  
The Cost ◽  
3D Applications

2.5D and 3D applications using through silicon vias (TSVs) are increasingly being considered as an alternative to conventional packaging. Miniaturization and high performance product requirements are driving this move, although in many cases the cost of both 2.5D and 3D is still high. In this paper we will identify the major cost drivers for 2.5D and 3D packaging and assess cost reduction progress, including current costs versus expected future costs. We will also compare these costs to alternative packaging.

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