Applied health services researchers often use methods that address observed confounding in attempts to estimate causal treatment effects. In prior work, vector-based kernel weighting (VBKW) was shown to minimize bias and maximize efficiency …

A joint modeling approach on survival and longitudinal data has proven to be valuable in end of life applications, especially when there is a strong relationship between the longitudinal measurements and survival outcomes in the presence of high …

Self-reports or professional interviews have typically been used to diagnose depression, although these methods often miss significant behavioral signals. Sometimes, people with depression may not express their feelings accurately, which can make …

Mediation analysis is a statistical approach that can provide insights regarding the intermediary processes by which an intervention or exposure affects a given outcome. Mediation analyses rose to prominence, particularly in social science …

Machine learning (ML) has the potential to revolutionize healthcare, allowing healthcare providers to improve patient-care planning, resource planning and utilization. Furthermore, identifying key-risk-factors and interaction-effects can help …

Statistical methods for provider profiling are designed to measure healthcare quality and create incentives for low-quality providers to improve. While most existing healthcare quality metrics assess the overall treatment delivered to providers’ …

Real-world data have become increasingly important in medical science and healthcare. A new, effective, and practically feasible statistical design is needed to unlock the potential of real-world data that decision-makers and practitioners can use …

Public procurement, a critical facet in acquiring goods and services, has garnered scholarly attention in e-procurement. However, its application in healthcare remains underexplored. This paper addresses this gap by proposing a decentralized …

Adoption and use of real-world data (RWD) for decision-making has been complicated by concerns regarding whether RWD was fit-for-purpose or was of sufficient validity to support the creation of credible RWE. This has greater urgency as regulatory …

Researchers often use survey methods to elicit patient perspectives on their healthcare. Survey results are often subject to response bias and missing data. As part of an observational study of Veterans’ healthcare preferences, we conducted a …

Propensity score methods have been widely adopted in observational studies, however research on propensity score-based weighting (PSW) methods in complex survey data settings is lacking, particularly for binary outcomes. We conducted a simulation …

This article addresses the problem of one-sided hypothesis testing on the means of two populations when there is uncertainty as to which population a datum is drawn. Such situations arise, for example, in the use of Bayesian imputation methods to …

Parkinson’s disease is related to nervous system disorders in human beings. In this paper, the status of Parkinson’s disease has been predicted based on the analysis of features of two Parkinson’s disease symptoms: Dysphonia and Dysarthria. The …

During the past 14 years, a clinical audit has been used in the Netherlands to provide hospitals with data on their performance in colorectal cancer care. Continuous feedback on the quality of care provided at each hospital is essential to improve …

Laboratory tests have an important role in informing diagnosis and aiding in the determination of appropriate courses of management and/or treatment in the Emergency Department setting. Over-ordering of laboratory tests can lead to increased costs …

Interoperability plays a crucial role in facilitating seamless data sharing across system boundaries, necessitating collaborative efforts among multiple systems. To achieve this, the presence of a common reference model for data exchange and …