Medicaid

Artificial intelligence-assisted integrated care to promote colonoscopy uptake (AICC) in China: study protocol for a cluster randomized controlled trial.

BACKGROUND: Colorectal cancer (CRC) leads to heavy disease and economic burdens globally. Early screening such as colonoscopy has been demonstrated to reduce both CRC incidence and mortality. However, uptake of colonoscopy among high-risk individuals is low in China, limiting screening efficacy. To improve screening uptake, it is necessary to ensure the engagement of both specialist and general pr...

Spectral clustering identifies patterns of chiropractic care in a national longitudinal cohort.

OBJECTIVE: Characterise longitudinal patterns of chiropractic visits for neck pain or low back pain by using machine learning (ML) methods and explainable models. DATA AND METHODS: Using de-identified claims data from 2016 to 2023 for adults from the Optum Labs Data Warehouse, we applied spectral clustering (SC) to identify novel patient clusters. Then we used explainable boosting machines (EBM) f...

Randomized trial of electronic health record implemented AI risk prediction in kidney transplant care.

Artificial intelligence (AI)-based risk prediction is increasingly implemented in clinical care, but randomized evidence on communication and shared d...

The Actionable Innovation Day Approach: Participatory Model for Advancing Critical Care Innovation.

Health care innovation is essential for improving patient outcomes, enhancing system efficiency, and preparing for future challenges; however, meaning...

Machine Learning Prediction and Reducing Overdoses With Electronic Health Record Nudges (mPROVEN) in the Primary Care Setting: Protocol for a Cluster Randomized Controlled Trial.

BACKGROUND: Opioid overdose remains a leading cause of preventable death in the United States. Existing approaches to identify individuals at elevated...

Applicable Scenarios, Desired Features, and Risks of AI Psychotherapists in Depression Treatment From the Patient's Perspective: Exploratory Qualitative Study.

BACKGROUND: Depression is a pervasive global mental health issue, yet access to trained professionals remains severely limited. With the rapid advance...

Assessment of Pain Intensity Using Deep Learning Models in Non-Communicative Intensive Care Patients.

BACKGROUND: Pain is a multifaceted and subjective phenomenon frequently experienced by patients in intensive care units. In non-communicating populati...

Deep learning models to predict mammographic density jointly on standard dose and low dose images.

OBJECTIVES: Mammographic density is associated with increased risk of developing breast cancer. Automated estimation of density in women below normal ...

AI in Point-of-Care Imaging for Clinical Decision Support: Systematic Review of Diagnostic Accuracy, Task-Shifting, and Explainability.

BACKGROUND: Artificial intelligence (AI) integrated with point-of-care imaging is a promising approach to expand access in settings with limited speci...

Preliminary development of a child physical abuse algorithm using emergency department records.

BACKGROUND: Victims of child physical abuse (CPA) disproportionately use the emergency department, yet identifying CPA remains challenging in this set...

Detection of young-onset type 2 diabetes using deep learning across primary and secondary care: a nationwide, retrospective cohort study.

BACKGROUND: Once considered a disease observed in older adults, type 2 diabetes is now increasingly seen in youth and adolescence. Young-onset (<40 ye...

Using a large language model artificial intelligence agent to improve the efficiency of clinical quality measure evidence evaluation: a case study.

OBJECTIVES: To evaluate the feasibility and performance of a large language model (LLM)-based artificial intelligence (AI) agent, implemented within a...

Rapid Evaluation of Artificial Intelligence Technology Used for Ambient Dictation in Primary Care: Comparing the Quality of Documentation of Artificial Intelligence-Generated and Human-Produced Clinical Notes.

BACKGROUND: Ambient artificial intelligence (AI) scribes can reduce the burden of administrative documentation. Prior evaluations have been vendor spe...

Integrating AI-assisted image enhancement with physics-based synthesis of low-field MRI from high-field MRI.

OBJECTIVE: Low-field magnetic resonance imaging (MRI) offers distinct advantages in terms of affordability, portability, and accessibility. However, i...

Parental Perspectives on Oral Health Care for Autistic Children With Medicaid: A Qualitative Study.

Children with special health care needs and disabilities (CSHCND), particularly those with autism, experience disproportionately high rates of oral he...

Building a tactical medical chatbot for conflict and low-resource settings: A low-code platform approach.

BACKGROUND: Conflict zones severely disrupt healthcare access, with millions affected by armed conflicts. The lack of standardized medical guidance ex...

Identifying demographic predictors of increased non-fatal opioid overdose risk among New York State Medicaid enrollees following the COVID-19 pandemic: an analysis of heterogeneous treatment effects.

BACKGROUND: Overdose rates in the U.S. rose dramatically during the COVID-19 pandemic. Well-documented racial and sociodemographic inequities in the i...

Nurses' Evaluation of a Service Robot for Inpatient Care: Technology Acceptance Study.

BACKGROUND: The integration of robotic systems into nursing practice is increasingly discussed as a potential strategy to alleviate workload and suppo...

Ability of Deep Learning Image Reconstruction to Preserve Detail and Remove Noise in Coronary Computed Tomography Angiography: A Clinical Analysis.

PURPOSE: To analyze image quality over 3 levels (low, medium, and high) of deep learning image reconstruction (DLIR), evaluate whether edge detail is ...

Using Machine Learning to Improve Screening for Oropharyngeal Dysphagia in Hospitalized Versus Primary Care Adult Patients With COVID-19 Disease: Retrospective Observational Study.

BACKGROUND: Oropharyngeal dysphagia (OD) commonly occurs in patients with COVID-19 disease, posing diagnostic challenges due to isolation protocols. O...