RESUMO
Objective: To characterize the development and performance of a cataract surgery episode-based cost measure for the Medicare Quality Payment Program. Design: Claims-based analysis. Participants: Medicare clinicians with cataract surgery claims between June 1, 2016, and May 31, 2017. Methods: We limited the analysis to claims with procedure code 66984 (routine cataract surgery), excluding cases with relevant ocular comorbidities. We divided episodes into subgroups by surgery location (Ambulatory Surgery Center [ASC] or Hospital Outpatient Department [HOPD]) and laterality (bilateral when surgeries were within 30 days apart). For the episode-based cost measure, we calculated costs occurring between 60 days before surgery and 90 days after surgery, limited to services identified by an expert committee as related to cataract surgery and under the influence of the cataract surgeon. We attributed costs to the clinician submitting the cataract surgery claim, categorized costs into clinical themes, and calculated episode cost distribution, reliability in detecting clinician-dependent cost variation, and costs with versus without complications. We compared episode-based cost scores with hypothetical "nonselective" cost scores (total Medicare beneficiary costs between 60 days before surgery and 90 days after surgery). Main Outcome Measures: Episode costs with and without complications, clinician-dependent variation (proportion of total cost variance), and proportion of costs from cataract surgery-related clinical themes. Results: We identified 583 356 cataract surgery episodes attributed to 10 790 clinicians and 8189 with ≥ 10 episodes during the measurement period. Most surgeries were performed in an ASC (71%) and unilateral (66%). The mean episode cost was $2876. The HOPD surgeries had higher costs; geography and episodes per clinician did not substantially affect costs. The proportion of cost variation from clinician-dependent factors was higher in episode-based compared with nonselective cost measures (94% vs. 39%), and cataract surgery-related clinical themes represented a higher proportion of total costs for episode-based measures. Episodes with complications had higher costs than episodes without complications ($3738 vs. $2276). Conclusions: The cataract surgery episode-based cost measure performs better than a comparable nonselective measure based on cost distribution, clinician-dependent variance, association with cataract surgery-related clinical themes, and quality alignment (higher costs in episodes with complications). Cost measure maintenance and refinement will be important to maintain clinical validity and reliability. Financial Disclosures: Proprietary or commercial disclosure may be found after the references.
RESUMO
Clustering is a widely used machine learning technique for unlabelled data. One of the recently proposed techniques is the twin support vector clustering (TWSVC) algorithm. The idea of TWSVC is to generate hyperplanes for each cluster. TWSVC utilizes the hinge loss function to penalize the misclassification. However, the hinge loss relies on shortest distance between different clusters, and is unstable for noise-corrupted datasets, and for re-sampling. In this paper, we propose a novel Sparse Pinball loss Twin Support Vector Clustering (SPTSVC). The proposed SPTSVC involves the ϵ-insensitive pinball loss function to formulate a sparse solution. Pinball loss function provides noise-insensitivity and re-sampling stability. The ϵ-insensitive zone provides sparsity to the model and improves testing time. Numerical experiments on synthetic as well as real world benchmark datasets are performed to show the efficacy of the proposed model. An analysis on the sparsity of various clustering algorithms is presented in this work. In order to show the feasibility and applicability of the proposed SPTSVC on biomedical data, experiments have been performed on epilepsy and breast cancer datasets.
