Mohsen Soltanifar

CMHSU: An R Statistical Software Package to Detect Mental Health Status Substance Use Status and Their Concurrent Status in the North American Healthcare Administrative Databases

Lighting Talk, 2:30 - 2:55 PM

The concept of concurrent mental health and substance use (MHSU) and its detection in patients has garnered growing interest among psychiatrists and healthcare policymakers over the past two decades. Researchers have proposed various diagnostic methods, including the Data-Driven Diagnostic Method (DDDM), for the identification of MHSU. However, the absence of a standalone statistical software package to facilitate DDDM for large healthcare administrative databases has remained a significant gap. This paper introduces the R statistical software package CMHSU, available on the Comprehensive R Archive Network (CRAN), for the diagnosis of mental health (MH), substance use (SU), and their concurrent status (MHSU). The package implements DDDM using hospital and medical service physician visit counts along with maximum time span parameters for MH, SU, and MHSU diagnoses. A working example with a simulated real-world dataset is presented to explore three critical dimensions of MHSU detection based on the DDDM. Additionally, the limitations of the CMHSU package and potential directions for its future extension are discussed.

Pronouns: he/him Vancouver, BC, Canada Dr. Mohsen Soltanifar is a mathematical statistician with over three years of experience in contract research organizations (CROs) and the pharmaceutical industry, more than five years in healthcare industry, and over four years of part-time teaching in North American academia. His primary research interests encompass clinical trials and real-world evidence, with a focus on leveraging R software for study design, data analysis, and results presentation. Dr. Soltanifar has published in several therapeutic areas, including psychiatry, psychology, pulmonology, and pediatrics. He earned his PhD in Biostatistics from the University of Toronto, Canada, in 2020 and is accredited as a Professional Statistician (P.Stat) by the Statistical Society of Canada, effective 2024.