Reimbursement

Immunogenic cell death biomarkers for sepsis diagnosis and mechanism via integrated bioinformatics.

Immunogenic cell death (ICD) has been implicated in sepsis, a condition with high mortality, through mechanisms involving endoplasmic reticulum stress and other pathophysiological pathways. This study aimed to identify and validate ICD-related biomarkers for sepsis diagnosis and to elucidate their underlying mechanisms. Publicly available datasets (GSE65682, GSE95233 and GSE69528) and 57 ICD-relat...

Abolish Psychiatry, Abolish Neurology: Toward a Unified Discipline of Brain Medicine.

The longstanding division between psychiatry and neurology is a historical artifact, not a scientific necessity. Despite addressing the same organ, these fields operate as separate disciplines, fragmenting education, care, research, regulation, and reimbursement. This editorial argues for the abolition of that divide and the creation of a unified discipline of brain medicine. Drawing on advances i...

Advancing personalized, predictive, and preventive medicine in bladder cancer: a multi-omics and machine learning approach for novel prognostic modeling, immune profiling, and therapeutic target discovery.

OBJECTIVE: This study aimed to identify and analyze immunogenic cell death (ICD)-related multi-omics features in bladder cancer (BLCA) using single-ce...

Artificial intelligence in key pricing, reimbursement, and market access (PRMA) processes: better, faster, cheaper-can you really pick two?

The rapid evolution of large language models (LLMs) and machine learning (ML) presents both significant opportunities and challenges for market access...

Machine-Learned Codes from EHR Data Predict Hard Outcomes Better than Human-Assigned ICD Codes.

We used machine learning (ML) to characterize 894,154 medical records of outpatient visits from the Veterans Administration Central Data Warehouse (VA...

Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study.

BACKGROUND: Congestive heart failure (CHF) is a common cause of hospital admissions. Medical records contain valuable information about CHF, but manua...

Prospective Clinical Implementation of Paige Prostate Detect Artificial Intelligence Assistance in the Detection of Prostate Cancer in Prostate Biopsies: CONFIDENT P Trial Implementation of Artificial Intelligence Assistance in Prostate Cancer Detection.

PURPOSE: Pathologists diagnose prostate cancer (PCa) on hematoxylin and eosin (HE)-stained sections of prostate needle biopsies (PBx). Some laboratori...

Active learning and margin strategies for arrhythmia classification in implantable devices.

BACKGROUND AND OBJECTIVES: The massive storage of cardiac arrhythmic episodes from Implantable Cardioverter Defibrillators (ICD) and the advent of new...

Application of Clinical Department-Specific AI-Assisted Coding Using Taiwan Diagnosis-Related Groups: Retrospective Validation Study.

BACKGROUND: The accuracy of the ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) procedure coding system (P...

Enhanced Phenotype Identification of Common Ocular Diseases in Real-World Datasets.

OBJECTIVE: For studies using real-world data, accurately identifying patients with phenotypes of interest is challenging. To identify cohorts of inter...

Large language models vs human for classifying clinical documents.

BACKGROUND: Accurate classification of medical records is crucial for clinical documentation, particularly when using the 10th revision of the Interna...

Reimbursement and Regulatory Landscape for Artificial Intelligence in Medical Technology.

Integration of artificial intelligence (AI) into medical devices and services promises significant improvements in the diagnosis and treatment of dise...

A prospective study comparing highly qualified Molecular Tumor Boards with AI-powered software as a medical device.

BACKGROUND: The implementation of cancer precision medicine in Japan is deeply intertwined with insurance reimbursement policies and requires case-by-...

Cost-Effectiveness for Artificial Intelligence in Colonoscopy.

Artificial intelligence (AI) is set to transform the field of colonoscopy through the implementation of computer-assisted detection and diagnosis. Whi...

Extracting International Classification of Diseases Codes from Clinical Documentation Using Large Language Models.

BACKGROUND:  Large language models (LLMs) have shown promise in various professional fields, including medicine and law. However, their performance in...

R WE ready for reimbursement? A round up of developments in real-world evidence relating to health technology assessment: part 17.

In this update, we discuss a position statement from the National Institute of Health and Care Excellence (NICE) on the use of artificial intelligence...

Predictors for improvement in personality functioning during outpatient psychotherapy: A machine learning approach within a psychodynamic psychotherapy sample.

BACKGROUND: Since its introduction in the diagnostic manuals DSM-5 and ICD-11, the construct of personality functioning has gained increasing attentio...

Predicting Fear of Breast Cancer Recurrence in women five years after diagnosis using Machine Learning and healthcare reimbursement data from the French nationwide VICAN survey.

OBJECTIVE: A major concern for cancer survivors after treatment is the Fear of Cancer Recurrence (FCR), which is the fear that cancer will reappear or...

De Novo Natural Language Processing Algorithm Accurately Identifies Myxofibrosarcoma From Pathology Reports.

BACKGROUND: Available codes in the ICD-10 do not accurately reflect soft tissue sarcoma diagnoses, and this can result in an underrepresentation of so...

Evaluating a Natural Language Processing-Driven, AI-Assisted International Classification of Diseases, 10th Revision, Clinical Modification, Coding System for Diagnosis Related Groups in a Real Hospital Environment: Algorithm Development and Validation Study.

BACKGROUND: International Classification of Diseases codes are widely used to describe diagnosis information, but manual coding relies heavily on huma...