Trends in Medicare utilization and reimbursement for wound debridement procedures 2012-2017.

Wound care accounts for more than $6 billion of health expenditure in the United States annually. In addition, Medicare reimbursement per relative value unit has remained flat with respect to inflation over the past 20 years. Yet, physicians face increasing operating costs. The economic effects of declining inflation-adjusted Medicare physician reimbursement on the use of wound debridement procedures have yet to be elucidated. This study describes trends in Medicare reimbursement, utilization, and total Medicare expenditure for wound debridement procedures. Using Medicare claims data, we aggregated the volume of services and average Medicare reimbursement for wound debridement procedures over the calendar years 2012 to 2017. For each billing code, we estimated inflation-adjusted total Medicare expenditure by multiplying the average inflation-adjusted Medicare reimbursement by the aggregate volume of services. The average inflation-adjusted payment for wound debridement procedures decreased by 6% from 2012 to 2017. Over this time period, the utilization of wound care procedures increased 32%. Total inflation-adjusted annual Medicare expenditure on wound care increased 24% from 2012 to 2017. Therefore, despite declining physician reimbursement rates, total Medicare expenditure on wound debridement increased from 2012 to 2017. This increase in total Medicare expenditure was driven by higher utilization of wound debridement procedures.

Deep learning for dermatologists: Part II. Current applications.

Because of a convergence of the availability of large data sets, graphics-specific computer hardware, and important theoretical advancements, artificial intelligence has recently contributed to dramatic progress in medicine. One type of artificial intelligence known as deep learning has been particularly impactful for medical image analysis. Deep learning applications have shown promising results in dermatology and other specialties, including radiology, cardiology, and ophthalmology. The modern clinician will benefit from an understanding of the basic features of deep learning to effectively use new applications and to better gauge their utility and limitations. In this second article of a 2-part series, we review the existing and emerging clinical applications of deep learning in dermatology and discuss future opportunities and limitations. Part 1 of this series offered an introduction to the basic concepts of deep learning to facilitate effective communication between clinicians and technical experts.

Deep learning for dermatologists: Part I. Fundamental concepts.

Artificial intelligence is generating substantial interest in the field of medicine. One form of artificial intelligence, deep learning, has led to rapid advances in automated image analysis. In 2017, an algorithm demonstrated the ability to diagnose certain skin cancers from clinical photographs with the accuracy of an expert dermatologist. Subsequently, deep learning has been applied to a range of dermatology applications. Although experts will never be replaced by artificial intelligence, it will certainly affect the specialty of dermatology. In this first article of a 2-part series, the basic concepts of deep learning will be reviewed with the goal of laying the groundwork for effective communication between clinicians and technical colleagues. In part 2 of the series, the clinical applications of deep learning in dermatology will be reviewed and limitations and opportunities will be considered.

A time series analysis of immune checkpoint inhibitor use in the United States Medicare population: 2014-2019.

BACKGROUND: The adoption of immune checkpoint inhibitors (ICIs) has dramatically transformed the treatment of numerous cancers. Medicare is the largest payer in the US and pays for physician-administered drugs through its medical Part B benefit. The aim of this study was to describe trends in ICI utilization and corresponding government expenditures within the US Medicare population. METHODS: We analyzed Medicare data to describe trends in total number of claims, total annual expenditures, expenditures per patient, and expenditures per claim for ICIs from January 2014 to December 2019. RESULTS: From 2014 to 2019, utilization rates for each of the seven market approved ICIs in the US increased. Over this time period, total Medicare expenditure on ICIs increased 1916% from $285,506,498 to $5,755,319,571. Concurrently, overall Medicare Part B drug expenditure increased 57% from $23,679,547,748 to $37,271,080,631. Expenditures on ICIs accounted for 40% of the increase in total Medicare Part B drug spending over this time period. CONCLUSIONS: The rapid increase in utilization of ICIs has accounted for a disproportionate share of government drug spending growth in the United States. Policymakers can potentially curb spending growth by linking payments to patient outcomes.

How to Sequence Therapies in Mycosis Fungoides.

OPINION STATEMENT: Choice of therapy in mycosis fungoides is based on both patient- and lymphoma-specific factors, such as disease characteristics, comorbidities, symptoms and effect on quality of life, potential associated toxicities of therapy, response and tolerance to prior lines of therapy, and convenience and practicality. Generally, we sequence therapies from least toxic, targeted, nonimmunosuppressive to more toxic, immunosuppressive and from single agent to multiple agents, as necessary. If more toxic, immunosuppressive agents are required to alleviate disease burden or symptoms, we generally use them just long enough to control the disease, then transition to a maintenance regimen with less toxic, less immunosuppressive agents.

Quantifying the Financial Value of Clinical Specialty Choice and Its Association With Competitiveness of Admissions.

Background The factors influencing medical student clinical specialty choice have important implications for the future composition of the US physician workforce. The objective of this study was to determine the career net present values (NPVs) of US medical students' clinical specialty choices and identify any relationships between a specialty's NPV and competitiveness of admissions as measured by the US Medical Licensing Examination (USMLE) Step 1 scores. Methodology NPVs were calculated using the results of the 2019 Doximity Physician Compensation report, a survey of 90,000 physicians. Mean USMLE Step 1 scores for matched US allopathic seniors in the 2018 National Resident Matching Program were used as a measure of clinical specialties' competitiveness of admissions. We calculated a composite measure of NPV and annual work-hours by dividing each specialty's NPV by the reported average number of hours worked per year. Results In our analysis, orthopedic surgery had the highest NPV ($10,308,868), whereas family medicine had the lowest NPV ($5,274,546). Dermatology and plastic surgery had the highest mean USMLE Step 1 scores (249 for both), whereas family medicine had the lowest (220). Clinical specialties' NPVs were positively associated with mean USMLE Step 1 scores (Pearson's r = 0.82; p < 0.001). Conclusions In this study, we describe associations suggesting that medical students respond to financial incentives in choosing clinical specialties and that these decisions are mediated by USMLE Step 1 scores. This underscores the importance of titrating and aligning incentives to improve the allocation of medical students into clinical specialties.

The policy dimensions, regulatory landscape, and market characteristics of teledermatology in the United States.

The COVID-19 pandemic has spurred healthcare systems across the world to rapidly redesign their models of care delivery. As such, this pandemic has accelerated the adoption of teledermatology in the United States. However, it remains unknown whether this momentum will be maintained after the pandemic. The future of teledermatology in the United States will be significantly influenced by a complex set of policy, legal, and regulatory frameworks. An understanding of these frameworks will help dermatologists more effectively adopt and implement teledermatology platforms. In this article, we review the current state of teledermatology in the United States, including policy dimensions, the regulatory landscape, market characteristics, and future directions.

A microbial expression system for high-level production of scFv HIV-neutralizing antibody fragments in Escherichia coli.

Monoclonal antibodies (mABs) are of great biopharmaceutical importance for the diagnosis and treatment of diseases. However, their production in mammalian expression hosts usually requires extensive production times and is expensive. Escherichia coli has become a new platform for production of functional small antibody fragment variants. In this study, we have used a rhamnose-inducible expression system that allows precise control of protein expression levels. The system was first evaluated for the cytoplasmic production of super folder green fluorescence protein (sfGFP) in various production platforms and then for the periplasmic production of the anti-HIV single-chain variable antibody fragment (scFv) of PGT135. Anti-HIV broadly neutralizing antibodies, like PGT135, have potential for clinical use to prevent HIV transmission, to promote immune responses and to eradicate infected cells. Different concentrations of L-rhamnose resulted in the controlled production of both sfGFP and scFv PGT135 antibody. In addition, by optimizing the culture conditions, the amount of scFv PGT135 antibody that was expressed soluble or as inclusions bodies could be modulated. The proteins were produced in batch bioreactors, with yields of 4.9 g/L for sfGFP and 0.8 g/L for scFv. The functionality of the purified antibodies was demonstrated by their ability to neutralize a panel of different HIV variants in vitro. We expect that this expression system will prove very useful for the development of a more cost-effective production process for proteins and antibody fragments in microbial cells.

A general mechanism of ribosome dimerization revealed by single-particle cryo-electron microscopy.

Bacteria downregulate their ribosomal activity through dimerization of 70S ribosomes, yielding inactive 100S complexes. In Escherichia coli, dimerization is mediated by the hibernation promotion factor (HPF) and ribosome modulation factor. Here we report the cryo-electron microscopy study on 100S ribosomes from Lactococcus lactis and a dimerization mechanism involving a single protein: HPFlong. The N-terminal domain of HPFlong binds at the same site as HPF in Escherichia coli 100S ribosomes. Contrary to ribosome modulation factor, the C-terminal domain of HPFlong binds exactly at the dimer interface. Furthermore, ribosomes from Lactococcus lactis do not undergo conformational changes in the 30S head domains upon binding of HPFlong, and the Shine-Dalgarno sequence and mRNA entrance tunnel remain accessible. Ribosome activity is blocked by HPFlong due to the inhibition of mRNA recognition by the platform binding center. Phylogenetic analysis of HPF proteins suggests that HPFlong-mediated dimerization is a widespread mechanism of ribosome hibernation in bacteria.When bacteria enter the stationary growth phase, protein translation is suppressed via the dimerization of 70S ribosomes into inactive complexes. Here the authors provide a structural basis for how the dual domain hibernation promotion factor promotes ribosome dimerization and hibernation in bacteria.