Hierarchical Condition Category

IMPORTANCE: Models predicting health care spending and other outcomes from administrative records are widely used to manage and pay for health care, despite well-documented deficiencies. New methods are needed that can incorporate more than 70 000 diagnoses without creating undesirable coding incentives. OBJECTIVE: To develop a machine learning (ML) algorithm, building on Diagnostic Item (DXI) categories and Diagnostic Cost Group (DCG) methods, that automates development of clinically credible and transparent predictive models for policymakers and clinicians...

INTRODUCTION: Current data regarding reimbursement trends in Medicare services and the complexity of patients treated as physicians' progress in their academic career are conflicting. In otolaryngology, there are no data examining these metrics. METHODS: Medicare services, reimbursement, and patient complexity risk scores (based on hierarchical condition category coding) of US rhinology fellowship-trained faculty were stratified and compared by rank and years in practice...

OBJECTIVE: The objective was to measure specialty provider networks in Medicare Advantage (MA) and examine associations with market factors. DATA SOURCES AND STUDY SETTING: We relied on traditional Medicare (TM) and MA prescription drug event data from 2011 to 2017 for all Medicare beneficiaries in the United States as well as data from the Area Health Resources File. STUDY DESIGN: Relying on a recently developed and validated prediction model, we calculated the provider network restrictiveness of MA contracts for nine high-prescribing specialties...

Medicare beneficiaries' healthcare spending varies across geographical regions, influenced by availability of medical resources and institutional efficiency. We aimed to evaluate whether social vulnerability influences healthcare costs among Medicare beneficiaries. Multivariable regression analyses were conducted to determine whether the social vulnerability index (SVI), released by the CDC, was associated with average submitted covered charges, total payment amounts, or total covered days upon hospital discharge among Medicare beneficiaries...

The clinical burden of mental illness, in particular schizophrenia and bipolar disorder, are driven by frequent chronic courses and increased mortality, as well as the risk for comorbid conditions such as cardiovascular disease and type 2 diabetes. Evidence suggests an overlap of molecular pathways between psychotic disorders and somatic comorbidities. In this study, we developed a computational framework to perform comorbidity modeling via an improved integrative unsupervised machine learning approach based on multi-rank non-negative matrix factorization (mrNMF)...

This paper develops a Bayesian method to detect heterogeneity in the relationship between covariates and the outcome in models with ordered responses. To this end, we construct an efficient Markov chain Monte Carlo algorithm for a hierarchical Bayesian model that selects random coefficients in ordered models. This method extends an approach for selecting random coefficients in linear mixed models into the ordered setting by adding two enhancements that are relevant to the latter category of models. First, we construct steps to efficiently estimate cut-points by addressing identification and ordering constraints...

INTRODUCTION: Total joint arthroplasties (TJAs) have recently been shifting toward outpatient arthroplasty. This study aims to explore recent trends in outpatient total joint arthroplasty (TJA) procedures and examine whether patients with a higher comorbidity burden are undergoing outpatient arthroplasty. METHODS: Medicare fee-for-service claims were screened for patients who underwent total hip, knee, or shoulder arthroplasty procedures between January 2019 and December 2022...

Successfully promoting drought tolerance in wheat genotypes will require several procedures, such as field experimentations, measuring relevant traits, using analysis tools of high precision and efficiency, and taking a complementary approach that combines analyses of phenotyping and genotyping at once. The aim of this study is to assess the genetic diversity of 60 genotypes using SSR (simple sequence repeat) markers collected from several regions of the world and select 13 of them as more genetically diverse to be re-evaluated under field conditions to study drought stress by estimating 30 agro-physio-biochemical traits...

Heterogeneity of pyrolytic parameters in municipal solid waste (MSW) significantly hinders its waste-to-energy efficiency. So far, hardly any light has been shed on current pyrolytic heterogeneity conditions or feasible pyrolytic homogeneity enhancement approaches of MSW. Accordingly, pyrolytic properties (Ea and logA) of 130 MSW samples in 6 categories were collected from literature. A kinetic parameters clustering-based sorting strategy for MSW was proposed. A so-called C index was established to compare their sorting performance for Ea and logA against two traditional sorting strategies (substance categorization and density clustering)...

Robust visual place recognition (VPR) enables mobile robots to identify previously visited locations. For this purpose, the extracted visual information and place matching method plays a significant role. In this paper, we critically review the existing VPR methods and group them into three major categories based on visual information used, i.e., handcrafted features, deep features, and semantics. Focusing the benefits of convolutional neural networks (CNNs) and semantics, and limitations of existing research, we propose a robust appearance-based place recognition method, termed SVS-VPR, which is implemented as a hierarchical model consisting of two major components: global scene-based and local feature-based matching...

PURPOSE: This study aimed to identify the infant-rearing experiences of parents during the coronavirus disease 2019 (COVID-19) pandemic and provide foundational data for the development of infant-rearing support programs during pandemic situations. METHODS: Convergent mixed methods were used to better understand the research outcomes by converging both quantitative and qualitative data. A total of 149 parents with infant-rearing experiences during the pandemic responded to a self-report survey, and 10 parents participated in the interviews...

OBJECTIVE: To study diagnosis coding intensity across Medicare programs, and to examine the impacts of changes in the risk model adopted by the Centers for Medicare and Medicaid Services (CMS) for 2024. DATA SOURCES AND STUDY SETTING: Claims and encounter data from the CMS data warehouse for Traditional Medicare (TM) beneficiaries and Medicare Advantage (MA) enrollees. STUDY DESIGN: We created cohorts of MA enrollees, TM beneficiaries attributed to Accountable Care Organizations (ACOs), and TM non-ACO beneficiaries...

This review describes the Hierarchical Taxonomy of Psychopathology (HiTOP) model of psychosis-related psychopathology, the psychosis superspectrum. The HiTOP psychosis superspectrum was developed to address shortcomings of traditional diagnoses for psychotic disorders and related conditions including low reliability, arbitrary boundaries between psychopathology and normality, high symptom co-occurrence, and heterogeneity within diagnostic categories. The psychosis superspectrum is a transdiagnostic dimensional model comprising two spectra-psychoticism and detachment-which are in turn broken down into fourteen narrow components, and two auxiliary domains-cognition and functional impairment...

BACKGROUND AND OBJECTIVES: Under the Merit-Based Incentive Payment System (MIPS), Medicare evaluates provider performance to determine payment adjustments. Studies examining the first year of MIPS (2017) showed that safety-net providers had lower MIPS scores, but the performance of safety-net physicians over time has not been studied. This study aimed to examine the performance of safety-net vs non-safety-net neurosurgeons in MIPS from 2017 to 2020. METHODS: Safety-net neurosurgeons were defined as being in the top quartile according to proportion of dual-eligible beneficiaries and non-safety-net in the bottom quartile...

Stock price data often exhibit nonlinear patterns and dynamics in nature. The parameter selection in generalized autoregressive conditional heteroskedasticity (GARCH) and autoregressive integrated moving average (ARIMA) models is challenging due to stock price volatility. Most studies examined the manual method for parameter selection in GARCH and ARIMA models. These procedures are time-consuming and based on trial and error. To overcome this, we considered a GWO method for finding the optimal parameters in GARCH and ARIMA models...

INTRODUCTION: Quisqualis indica L. (QIL) has a long history as a traditional Chinese herb in China, but the study of volatile components in QIL from different geographical sources has been relatively rare. OBJECTIVES: To establish an optimal headspace gas chromatography-mass spectrometry (HS-GC-MS) method to comprehensively analyse the volatile component profile and screen quality markers of QIL from different origins. METHODS: Response surface methodology (RSM) was used to optimise the conditions for headspace analysis...

BACKGROUND: Elder mistreatment (EM) is associated with adverse health outcomes and healthcare utilization patterns that differ from other older adults. However, the association of EM with healthcare costs has not been examined. Our goal was to compare healthcare costs between legally adjudicated EM victims and controls. METHODS: We used Medicare insurance claims to examine healthcare costs of EM victims in the 2 years surrounding initial mistreatment identification in comparison to matched controls...

The ramifications of anthropogenic activities on the environment and the welfare of aquatic life in lakes worldwide are becoming increasingly alarming. There is a lack of research in the Indian Himalayas on fish biomarker responses to stressful aquatic conditions and the use of environmetric modelling in GIS. Our research evaluates the environmental health of urban lakes in multiple basins using multi-biomarker endpoints (13 features) in Schizothorax niger and hydrochemical characterization (9 features) of water...

BACKGROUND: The recent rising health spending intrigued efficiency and cost-based performance measures. However, mortality risk adjustment methods are still under consideration in cost estimation, though methods specific to cost estimate have been developed. Therefore, we aimed to compare the performance of diagnosis-based risk adjustment methods based on the episode-based cost to utilize in efficiency measurement. METHODS: We used the Health Insurance Review and Assessment Service-National Patient Sample as the data source...

The utilization of multiscale entropy methods to characterize vibration signals has proven to be promising in intelligent diagnosis of mechanical equipment. However, in the current multiscale entropy methods, only the information in the low-frequency range is utilized and the information in the high-frequency range is discarded. In order to take full advantage of the information, in this paper, a fault feature extraction method utilizing the bidirectional composite coarse-graining process with fuzzy dispersion entropy is proposed...