31 research outputs found
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Mandated health insurance increases rates of elective knee surgery
The recent federal ruling to against Affordable Care Act (ACA), specifically the mandate requiring people to buy insurance, has once again brought the healthcare reform debate to the spotlight. The ACA increased the number of insured Americans through the development of subsidized healthcare plans and health insurance exchanges. Insurance-based differences in the rate of upper extremity elective orthopaedic surgery have been described before and after healthcare reform in Massachusetts, where a similar mandate was put into place years before the ACA was passed. However, no comprehensive study has evaluated insurance-based differences of knee elective surgery before and after reform.
To investigate how an individual mandate to purchase health insurance affects rates of knee surgery.
A retrospective review was performed within an orthopaedic surgery department at a tertiary-care, academic medical center in Massachusetts. The rate of elective knee surgery performed before and after the healthcare reform (2005-2006 and 2007-2010, respectively) was calculated. The patients were categorized by insurance type (Commonwealth Care, Medicare, Medicaid, private insurance, Workers' Compensation, TriCare, and Uninsured). Using
testing, differences in rates of surgery between the pre-reform and post-reform period and among insurance subgroups were calculated.
Rate of surgery increased in the post-reform period (pre-reform 8.07% (95%CI: 7.03%-9.11%), post-reform 9.38% (95%CI: 8.74%-10.03%) (
= 0.04) and was statistically significant. When the insurance groups and insurance types were compared, the rates of surgery are not significantly different before or after reform.
The increase in the rate of elective knee surgery in the post-reform period suggests that health care reform in Massachusetts has been successful in decreasing the uninsured population and may increase health care expenditures. This is a hypothesis generating study that suggests further avenues of study on how mandated coverage may change healthcare utilization and cost
Impact of Clinical Decision Support on Radiography for Acute Ankle Injuries: A Randomized Trial
Introduction: While only 15–20% of patients with foot and ankle injuries presenting to urgent care centers have clinically significant fractures, most undergo radiography. We examined the impact of electronic point-of-care clinical decision support (CDS) on adherence to the Ottawa Ankle Rules (OAR), as well as use and yield of foot and ankle radiographs in patients with acute ankle injury. Methods: We obtained institutional review board approval for this randomized controlled study performed April 18, 2012—December 15, 2013. All ordering providers credentialed at an urgent care affiliated with a quaternary care academic hospital were randomized to either receive or not receive CDS, based on the OAR and integrated into the physician order-entry system, with feedback at the time of imaging order. If the patient met OAR low-risk criteria, providers were advised against imaging and could either cancel the order or ignore the alert. We identified patients with foot and ankle complaints via ICD-9 billing codes and electronic health records and radiology reports reviewed for those who were eligible. Chi-square was used to compare adherence to the OAR (primary outcome), radiography utilization rate and radiography yield of foot and ankle imaging (secondary outcomes) between the intervention and control groups. Results: Of 14,642 patients seen at urgent care during the study period, 613 (4.2%, representing 632 visits) presented with acute ankle injury and were eligible for application of the OAR; 374 (59.2%) of these were seen by control-group providers. In the intervention group, CDS adherence was higher for both ankle (239/258=92.6% vs. 231/374=61.8%, p=0.02) and foot radiography (209/258=81.0% vs. 238/374=63.6%; p<0.01). However, ankle radiography use was higher in the intervention group (166/258=64.3% vs. 183/374=48.9%; p<0.01), while foot radiography use (141/258=54.6% vs. 202/374=54.0%; p=0.95) was not. Radiography yield was also higher in the intervention group (26/307=8.5% vs. 18/385=4.7%; p=0.04). Conclusion: Clinical decision support, previously demonstrated to improve guideline adherence for high-cost imaging, can also improve guideline adherence for radiography – as demonstrated by increased OAR adherence and increased imaging yield
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Fully Automated Deep Learning System for Bone Age Assessment
Skeletal maturity progresses through discrete phases, a fact that is used routinely in pediatrics where bone age assessments (BAAs) are compared to chronological age in the evaluation of endocrine and metabolic disorders. While central to many disease evaluations, little has changed to improve the tedious process since its introduction in 1950. In this study, we propose a fully automated deep learning pipeline to segment a region of interest, standardize and preprocess input radiographs, and perform BAA. Our models use an ImageNet pretrained, fine-tuned convolutional neural network (CNN) to achieve 57.32 and 61.40% accuracies for the female and male cohorts on our held-out test images. Female test radiographs were assigned a BAA within 1 year 90.39% and within 2 years 98.11% of the time. Male test radiographs were assigned 94.18% within 1 year and 99.00% within 2 years. Using the input occlusion method, attention maps were created which reveal what features the trained model uses to perform BAA. These correspond to what human experts look at when manually performing BAA. Finally, the fully automated BAA system was deployed in the clinical environment as a decision supporting system for more accurate and efficient BAAs at much faster interpretation time (<2 s) than the conventional method
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Discovery and Clinical Proof-of-Concept of RLY-2608, a First-in-Class Mutant-Selective Allosteric PI3Kα Inhibitor That Decouples Antitumor Activity from Hyperinsulinemia.
UNLABELLED: PIK3CA (PI3Kα) is a lipid kinase commonly mutated in cancer, including ∼40% of hormone receptor-positive breast cancer. The most frequently observed mutants occur in the kinase and helical domains. Orthosteric PI3Kα inhibitors suffer from poor selectivity leading to undesirable side effects, most prominently hyperglycemia due to inhibition of wild-type (WT) PI3Kα. Here, we used molecular dynamics simulations and cryo-electron microscopy to identify an allosteric network that provides an explanation for how mutations favor PI3Kα activation. A DNA-encoded library screen leveraging electron microscopy-optimized constructs, differential enrichment, and an orthosteric-blocking compound led to the identification of RLY-2608, a first-in-class allosteric mutant-selective inhibitor of PI3Kα. RLY-2608 inhibited tumor growth in PIK3CA-mutant xenograft models with minimal impact on insulin, a marker of dysregulated glucose homeostasis. RLY-2608 elicited objective tumor responses in two patients diagnosed with advanced hormone receptor-positive breast cancer with kinase or helical domain PIK3CA mutations, with no observed WT PI3Kα-related toxicities. SIGNIFICANCE: Treatments for PIK3CA-mutant cancers are limited by toxicities associated with the inhibition of WT PI3Kα. Molecular dynamics, cryo-electron microscopy, and DNA-encoded libraries were used to develop RLY-2608, a first-in-class inhibitor that demonstrates mutant selectivity in patients. This marks the advance of clinical mutant-selective inhibition that overcomes limitations of orthosteric PI3Kα inhibitors. See related commentary by Gong and Vanhaesebroeck, p. 204 . See related article by Varkaris et al., p. 227 . This article is featured in Selected Articles from This Issue, p. 201
Figure S6 from Discovery and Clinical Proof-of-Concept of RLY-2608, a First-in-Class Mutant-Selective Allosteric PI3Kα Inhibitor That Decouples Antitumor Activity from Hyperinsulinemia
Varied levels of PI3Kα-dependency across cell lines</p