Changes in Postpartum Opioid Prescribing After Implementation of State Opioid Prescribing Limits.

Importance: In response to the growing opioid crisis, states implemented opioid prescribing limits to reduce exposure to opioid analgesics. Research in other clinical contexts has found that these limits are relatively ineffective at changing opioid analgesic prescribing.

Objective: To examine the association of state-level opioid prescribing limits with opioid prescribing within the 30-day postpartum period, as disaggregated by type of delivery (vaginal vs cesarean) and opioid naivete.

Antidepressant prescribing inequalities in people with comorbid depression and type 2 diabetes: A UK primary care electronic health record study.

Aims: To compare the likelihood of being prescribed an antidepressant in depressed individuals with and without type 2 diabetes.

Methods: We performed a matched cohort study using primary care record data from the UK Clinical Practice Research Datalink. We used multivariable logistic regression to compare antidepressant prescribing during the first five years of starting oral antidiabetic medication to a comparison group without type 2 diabetes, matched based on GP practice, age and sex.

Impact of chronic pelvic pain on quality of life in diverse young adults.

Purpose: To examine the relationship between quality of life (QoL) and chronic pelvic pain (CPP), including an evaluation of whether differences exist between reported races and coping mechanisms used.

Methods: We used a cross-sectional survey design and analyzed data using descriptive and inferential statistics. We administered two surveys: the World Health Organization Quality of Life-BREF (26 items) and the Impact of Female Chronic Pelvic Pain Questionnaire (8 items).

Teaching Data Science through an Interactive, Hands-On Workshop with Clinically Relevant Case Studies.

Background:  In this case report, we describe the development of an innovative workshop to bridge the gap in data science education for practicing clinicians (and particularly nurses). In the workshop, we emphasize the core concepts of machine learning and predictive modeling to increase understanding among clinicians.

Objectives:  Addressing the limited exposure of health care providers to leverage and critique data science methods, this interactive workshop aims to provide clinicians with foundational knowledge in data science, enabling them to contribute effectively to teams focused on improving care quality.

Integrating Diversity, Equity, Inclusion, and Accessibility into a Data Storytelling Model for Health Informatics Education.

Background:  Health informatics education is pivotal in integrating diversity, equity, inclusion, and accessibility (DEIA) principles into curricula and leveraging data with equity considerations. Integrating clinically driven data with other datasets is crucial to comprehensive understanding of patient care demographics, experiences, and outcomes to create equity-minded data storytelling. Publicly available Healthy People 2030 (HP2030) resources complement academic electronic health records, supporting tailored learning activities in informatics education to enhance educational utility through a DEIA lens.