IMPORTANCE: Quantifying patient-physician cost conversations is challenging but important as out-of-pocket spending by US patients increases and patients are increasingly interested in discussing costs with their physicians.
BACKGROUND: Twitter is a potentially valuable tool for public health officials and state Medicaid programs in the United States, which provide public health insurance to 72 million Americans.
Health system data incompletely capture the social risk factors for drug overdose. This study aimed to improve the accuracy of a machine-learning algorithm to predict opioid overdose risk by integrating human services and criminal justice data with h...
The Journal of bone and joint surgery. American volume
33186002
BACKGROUND: Understanding the interactions between variables that predict prolonged hospital length of stay (LOS) following spine surgery can help uncover drivers of this risk in patients. This study utilized a novel game-theory-based approach to dev...
BACKGROUND: Robotic prostatectomy is a costly new technology, but the costs may be offset by changes in treatment patterns. The net effect of this technology on Medicaid spending has not been assessed.
Journal of managed care & specialty pharmacy
34032130
Medication therapy management (MTM) and comprehensive medication management (CMM) have been practiced by clinical pharmacists as a predominantly manual activity with interventions documented in a record-keeping system. Program evaluations, largely b...
BACKGROUND: People with intellectual and developmental disabilities (IDD) were disproportionately affected by the COVID-19 pandemic. Predicting COVID-19 infection has been difficult.
OBJECTIVES: To evaluate how different data sources affect the performance of machine learning algorithms that predict dental general anesthesia use among children with behavioral health conditions.
In 2008, Oregon expanded its Medicaid program using a lottery, creating a rare opportunity to study the effects of Medicaid coverage using a randomized controlled design (Oregon Health Insurance Experiment). Analysis showed that Medicaid coverage low...
OBJECTIVE: The objective of this study was to leverage machine learning techniques to analyze administrative claims and socioeconomic data, with the aim of identifying and interpreting the risk factors associated with high-dose opioid prescribing.