Large language models and synthetic health data: progress and prospects.

Objectives: Given substantial obstacles surrounding health data acquisition, high-quality synthetic health data are needed to meet a growing demand for the application of advanced analytics for clinical discovery, prediction, and operational excellence. We highlight how recent advances in large language models (LLMs) present new opportunities for progress, as well as new risks, in synthetic health data generation (SHDG).

Materials And Methods: We synthesized systematic scoping reviews in the SHDG domain, recent LLM methods for SHDG, and papers investigating the capabilities and limits of LLMs.

As good as it gets? A new approach to estimating possible prediction performance.

How much information does a dataset contain about an outcome of interest? To answer this question, estimates are generated for a given dataset, representing the minimum possible absolute prediction error for an outcome variable that any model could achieve. The estimate is produced using a constrained omniscient model that mandates only that identical observations receive identical predictions, and that observations which are very similar to each other receive predictions that are alike. It is demonstrated that the resulting prediction accuracy bounds function effectively on both simulated data and real-world datasets.

Health Care Usage During the COVID-19 Pandemic and the Adoption of Telemedicine: Retrospective Study of Chronic Disease Cohorts.

Background: The COVID-19 pandemic accelerated telehealth adoption across disease cohorts of patients. For many patients, routine medical care was no longer an option, and others chose not to visit medical offices in order to minimize COVID-19 exposure. In this study, we take a comprehensive multidisease approach in studying the impact of the COVID-19 pandemic on health care usage and the adoption of telemedicine through the first 12 months of the COVID-19 pandemic.

Eleven Years of Gender Data Visualization: A Step Towards More Inclusive Gender Representation.

We present an analysis of the representation of gender as a data dimension in data visualizations and propose a set of considerations around visual variables and annotations for gender-related data. Gender is a common demographic dimension of data collected from study or survey participants, passengers, or customers, as well as across academic studies, especially in certain disciplines like sociology. Our work contributes to multiple ongoing discussions on the ethical implications of data visualizations.

Predicting Heterogeneity in Patient Response to Morphine Treatment for Neonatal Opioid Withdrawal Syndrome.

Infants with neonatal opioid withdrawal syndrome commonly receive morphine treatment to manage their withdrawal signs. However, the effectiveness of this pharmacotherapy in managing the infants' withdrawal signs vary widely. We sought to understand how information available early in infant monitoring can anticipate this treatment response, focusing on early modified Finnegan Neonatal Abstinence Scoring System (FNASS) scores, polygenic risk for opioid dependence (polygenic risk score (PRS)), and drug exposure.

Rationing scarce healthcare capacity: A study of the ventilator allocation guidelines during the COVID-19 pandemic.

In the United States, even though national guidelines for allocating scarce healthcare resources are lacking, 26 states have specific ventilator allocation guidelines to be invoked in case of a shortage. While several states developed their guidelines in response to the recent COVID-19 pandemic, New York State developed these guidelines in 2015 as "pandemic influenza is a foreseeable threat, one that we cannot ignore." The primary objective of this study is to assess the existing procedures and priority rules in place for allocating/rationing scarce ventilator capacity and propose alternative (and improved) priority schemes.

Understanding Gender Biases and Differences in Web-Based Reviews of Sanctioned Physicians Through a Machine Learning Approach: Mixed Methods Study.

Background: Previous studies have highlighted gender differences in web-based physician reviews; however, so far, no study has linked web-based ratings with quality of care.

Objective: We compared a consumer-generated measure of physician quality (web-based ratings) with a clinical quality outcome (sanctions for malpractice or improper behavior) to understand how patients' perceptions and evaluations of physicians differ based on the physician's gender.

Methods: We used data from a large web-based physician review website and the Federation of State Medical Boards.

Aiding the prescriber: developing a machine learning approach to personalized risk modeling for chronic opioid therapy amongst US Army soldiers.

The opioid epidemic is a major policy concern. The widespread availability of opioids, which is fueled by physician prescribing patterns, medication diversion, and the interaction with potential illicit opioid use, has been implicated as proximal cause for subsequent opioid dependence and mortality. Risk indicators related to chronic opioid therapy (COT) at the point of care may influence physicians' prescribing decisions, potentially reducing rates of dependency and abuse.

Prediction of treatment nonadherence among older adults with chronic obstructive pulmonary disease using Medicare real-world data.

Suboptimal maintenance medication (MM) adherence remains a clinical problem among Medicare beneficiaries with chronic obstructive pulmonary disease (COPD). To inform risk-based personalized decision-making, this study sought to develop and validate prediction models of nonadherence to COPD MMs for Medicare beneficiaries. This was a retrospective cohort study of beneficiaries aged 65 years and older with COPD and inhaled MMs.

Voice activated remote monitoring technology for heart failure patients: Study design, feasibility and observations from a pilot randomized control trial.

Background: Heart failure (HF) is a serious health condition, associated with high health care costs, and poor outcomes. Patient empowerment and self-care are a key component of successful HF management. The emergence of telehealth may enable providers to remotely monitor patients' statuses, support adherence to medical guidelines, improve patient wellbeing, and promote daily awareness of overall patients' health.

Prevalence and Newly Diagnosed Rates of Multimorbidity in Older Medicare Beneficiaries with COPD.

Few studies have quantified the multimorbidity burden in older adults with chronic obstructive pulmonary disease (COPD) using large and generalizable data. Such evidence is essential to inform evidence-based research, clinical care, and resource allocation. This retrospective cohort study used a nationally representative sample of Medicare beneficiaries aged 65 years or older with COPD and 1:1 matched (on age, sex, and race) non-COPD beneficiaries to: (1) quantify the prevalence of multimorbidity at COPD onset and one-year later; (2) quantify the rates [per 100 person-years (PY)] of newly diagnosed multimorbidity during in the year prior to and in the year following COPD onset; and (3) compare multimorbidity prevalence in beneficiaries with and without COPD.

Voice Interface Technology Adoption by Patients With Heart Failure: Pilot Comparison Study.

Background: Heart failure (HF) is associated with high mortality rates and high costs, and self-care is crucial in the management of the condition. Telehealth can promote patients' self-care while providing frequent feedback to their health care providers about the patient's compliance and symptoms. A number of technologies have been considered in the literature to facilitate telehealth in patients with HF.

The bird's-eye view: A data-driven approach to understanding patient journeys from claims data.

Objective: In preference-sensitive conditions such as back pain, there can be high levels of variability in the trajectory of patient care. We sought to develop a methodology that extracts a realistic and comprehensive understanding of the patient journey using medical and pharmaceutical insurance claims data.

Materials And Methods: We processed a sample of 10 000 patient episodes (comprised of 113 215 back pain-related claims) into strings of characters, where each letter corresponds to a distinct encounter with the healthcare system.

Direct membrane filtration for wastewater treatment and resource recovery: A review.

Direct membrane filtration has shown great potential in wastewater treatment and resource recovery in terms of its superior treated water quality, efficient nutrient recovery, and sustainable operation, especially under some scenarios where biological treatment is not feasible. This paper aims to give a comprehensive review of the state-of-the-art of direct membrane filtration processes (including pressure-driven, osmotic-driven, thermal-driven, and electrical-driven) in treating different types of wastewater for water reclamation and resource recovery. The factors influencing membrane performance and treatment efficiency in these direct membrane filtration processes are well illustrated, in which membrane fouling was identified as the main challenge.

Impact of Global Budget Revenue Policy on Emergency Department Efficiency in the State of Maryland.

Introduction: On January 1, 2014, the State of Maryland implemented the Global Budget Revenue (GBR) program. We investigate the impact of GBR on length of stay (LOS) for inpatients in emergency departments (ED) in Maryland.

Methods: We used the Hospital Compare data reports from the Centers for Medicare and Medicaid Services (CMS) and CMS Cost Reports Hospital Form 2552-10 from January 1, 2012-March 31, 2016, with GBR hospitals from Maryland and hospitals from West Virginia (WV), Delaware (DE), and Rhode Island (RI).

The Value of Shorter Initial Opioid Prescriptions: A Simulation Evaluation.

Background: During the period from 1999 to 2016, more than 350,000 Americans died from overdoses related to the use of prescription opioids. To the extent that supply is directly related to overprescribing, policy interventions aimed at changing prescriber behavior, such as the recent Centers for Disease Control and Prevention guideline, are clearly warranted. Although these could plausibly reduce the prevalence of opioid overuse and dependency, little is known about their economic and health-related impacts.

Stated Pain Levels, Opioid Prescription Volume, and Chronic Opioid Use Among United States Army Soldiers.

Introduction: The use of opioids has increased drastically over the past few years and decades. As a result, concerns have mounted over serious outcomes associated with chronic opioid use (COU), including dependency and death. A greater understanding of the factors that are associated with COU will be critical if prescribers are to navigate potentially competing objectives to provide compassionate care, while reducing the overall opioid use problem.

Sensitivity of the Medication Possession Ratio to Modelling Decisions in Large Claims Databases.

Objectives: When preparing administrative medical and pharmacy claims data for analysis, decisions about data clean up and analytical approach need to be made. However, information about the effects of various modelling decisions on adherence measures such as the medication possession ratio (MPR) is limited. We address this gap with this study.

Understanding Adherence and Prescription Patterns Using Large-Scale Claims Data.

Background: Advanced computing capabilities and novel visual analytics tools now allow us to move beyond the traditional cross-sectional summaries to analyze longitudinal prescription patterns and the impact of study design decisions. For example, design decisions regarding gaps and overlaps in prescription fill data are necessary for measuring adherence using prescription claims data. However, little is known regarding the impact of these decisions on measures of medication possession (e.