The ESRD Prospective Payment System introduced two incentives to increase home dialysis use: bundling injectable medications into a single payment for treatment and paying for home dialysis training. We evaluated the effects of the ESRD Prospective Payment System on home dialysis use by patients starting dialysis in the United States from January 1, 2006 to August 31, 2013. We analyzed data on dialysis modality, insurance type, and comorbidities from the United States Renal Data System. We estimated the effect of the policy on home dialysis use with multivariable logistic regression and compared the effect on Medicare Parts A/B beneficiaries with the effect on patients with other types of insurance. The ESRD Prospective Payment System associated with a 5.0% (95% confidence interval [95% CI], 4.0% to 6.0%) increase in home dialysis use by the end of the study period. Home dialysis use increased by 5.8% (95% CI, 4.3% to 6.9%) among Medicare beneficiaries and 4.1% (95% CI, 2.3% to 5.4%) among patients covered by other forms of health insurance. The difference between these groups was not statistically significant (1.8%; 95% CI, -0.2% to 3.8%). Conversely, in both populations, the training add-on did not associate with increases in home dialysis use beyond the effect of the policy. The ESRD Prospective Payment System bundling, but not the training add-on, associated with substantial increases in home dialysis, which were identical for both Medicare and non-Medicare patients. These spill-over effects suggest that major payment changes in Medicare can affect all patients with ESRD.
Identifying disparities in uveal melanoma (UM) treatment patterns and survival across racial, ethnic, and socioeconomic (SES) groups reveals possible inequities in ophthalmologic health care.OBJECTIVE To examine the association of race, ethnicity, and SES with UM treatment and survival. DESIGN, SETTING, AND PARTICIPANTSA retrospective cohort analysis of 28% of the US population using the Surveillance, Epidemiology, and End Results (SEER) 18 registries from January 1, 2004, to December 31, 2014, was conducted. Data analysis was performed from April to July 2018. SEER identified 4475 individuals using International Classification of Diseases for Oncology, Third Edition site and morphology codes.EXPOSURES Race, ethnicity, and SES estimated by tertile using Yost Index composite scores.MAIN OUTCOMES AND MEASURES Treatment odds ratios (ORs), 1-year and 5-year survival estimates, mortality hazard ratios (HRs), and Kaplan-Meier survival curves. Hypothesis was formulated before data collection.RESULTS Multivariate analyses of 4475 individuals (2315 [51.7%] men; non-Hispanic white, 4130 [92.3%]; nonwhite, 345 [7.7%]) showed that patients who were nonwhite (OR, 1.45; 95% CI, 1.12-1.88) and socioeconomically disadvantaged (lower SES: OR, 2.21; 95% CI, 1.82-2.68; middle SES: OR, 1.86; 95% CI, 1.56-2.21) were more likely to receive primary enucleation. No interactions were observed between race/ethnicity, SES, and stage at diagnosis. From 2004 to 2014, rates of primary enucleation decreased across all racial/ethnic and SES groups, but disparities persisted. Socioeconomically disadvantaged patients had lower 5-year all-cause survival rates (lower SES: 69.2%; middle SES: 68.1%; and upper SES: 73.8%), although disease-specific survival did not vary significantly by racial/ethnic or SES strata. Mortality risk was associated with older age at diagnosis
BackgroundRepetitive laboratory testing in stable patients is low-value care. Electronic health record (EHR)-based interventions are easy to disseminate but can be restrictive.ObjectiveTo evaluate the effect of a minimally restrictive EHR-based intervention on utilisation.SettingOne year before and after intervention at a 600-bed tertiary care hospital. 18 000 patients admitted to General Medicine, General Surgery and the Intensive Care Unit (ICU).InterventionProviders were required to specify the number of times each test should occur instead of being able to order them indefinitely.MeasurementsFor eight tests, utilisation (number of labs performed per patient day) and number of associated orders were measured.ResultsUtilisation decreased for some tests on all services. Notably, complete blood count with differential decreased 9% (p<0.001) on General Medicine and 21% (p<0.001) in the ICU.ConclusionsRequiring providers to specify the number of occurrences of labs changes significantly reduces utilisation in some cases.
Differences between target and implanted intraocular lens (IOL) power in Ethiopian cataract outreach campaigns were evaluated, and machine learning (ML) was applied to optimize the IOL inventory and minimize avoidable refractive error. Patients from Ethiopian cataract campaigns with available target and implanted IOL records were identified, and the diopter difference between the two was measured. Gradient descent (an ML algorithm) was used to generate an optimal IOL inventory, and we measured the models performance across varying surplus levels. Only 45.6% of patients received their target IOL power and 23.6% received underpowered IOLs with current inventory (50% surplus). The ML-generated IOL inventory ensured that more than 99.5% of patients received their target IOL when using only 39% IOL surplus. In Ethiopian cataract campaigns, most patients have avoidable postoperative refractive error secondary to suboptimal IOL inventory. Optimizing the IOL inventory using this ML model might eliminate refractive error from insufficient inventory and reduce costs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.