Explanipedia

Telemedicine and Depression Screening After the Start of the COVID-19 Pandemic Open

Maria E. Garcia, John Neuhaus, Jennifer Livaudais‐Toman, Mitchell D. Feldman, Lisa Ochoa‐Frongia , et al. · 2024

This cohort study investigates the probability of depression screening by visit type and by patient demographic characteristics in a large health system during the early COVID-19 pandemic.

Does Sponsorship Promote Equity in Career Advancement in Academic Medicine? A Scoping Review Open

Rachel Schwartz, Mia Williams, Mitchell D. Feldman · 2023

Sponsorship describes a set of actions wherein an influential champion ( sponsor ) uses their position to actively support a colleague’s career by helping them gain visibility, recognition, and/or positions. There is growing awareness of t…

Faculty knowledge, actions, and perceptions of sponsorship: an institutional survey study Open

Mia Williams, Veronica Yank, Patricia O’Sullivan, Brian K. Alldredge, Mitchell D. Feldman · 2023

A majority of respondents at a large academic health center reported sponsorship familiarity, receipt, and satisfaction. Yet many perceived persistent institutional biases and the need for systematic change to improve sponsorship transpare…

Equitability of Depression Screening After Implementation of General Adult Screening in Primary Care Open

Maria E. Garcia, Ladson Hinton, John Neuhaus, Mitchell D. Feldman, Jennifer Livaudais‐Toman , et al. · 2022

Importance Depression is a debilitating and costly medical condition that is often undertreated. Men, racial and ethnic minority individuals, older adults, and those with language barriers are at increased risk for undertreatment of depres…

Responding to the Great Resignation: Detoxify and Rebuild the Culture Open

Mark Linzer, Elizabeth P. Griffiths, Mitchell D. Feldman · 2022

On the Results of Medical Examination of the Population in Sverdlovsk Oblast in 2018-2021 Open

Mitchell D. Feldman, V Tokareva · 2022

Based on the analysis of annual reports «The main results of the medical examination of certain groups of the adult population in Sverdlovsk oblast» for 2018-2021, the article considers the medical examination in the region as one of the m…

Primary Care Physician Recognition and Documentation of Depressive Symptoms Among Chinese and Latinx Patients During Routine Visits: A Cross-Sectional Study Open

Maria E. Garcia, Ladson Hinton, Steven E. Gregorich, Jennifer Livaudais‐Toman, Celia P. Kaplan , et al. · 2021

Purpose: Asian and Latinx individuals have a high burden of untreated depression. Under-recognition of depressive symptoms may contribute to existing disparities in depression treatment. The objective of this cross-sectional study w…

Utilizing Lean Leadership Principles to Build an Academic Primary Care Practice of the Future Open

Sasha Morduchowicz, Jonathan S. Lee, Lei Choi, Coleen Kivlahan, Dan Null , et al. · 2020

A new Mentor Evaluation Tool: Evidence of validity Open

Michi Yukawa, Stuart A. Gansky, Patricia O’Sullivan, Arianne Teherani, Mitchell D. Feldman · 2020

The Mentor Evaluation Tool demonstrates evidence of validity for research, clinical, educational or career mentors in academic health science careers. However, MET did not distinguish individuals nominated as outstanding mentors from other…

FRI0611-HPR EUROPEAN PRESCRIBERS' PERSPECTIVES ON BIOSIMILARS Open

Michael S Reilly, Mitchell D. Feldman · 2020

Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality prediction Open

Hamid Mohamadlou, Saarang Panchavati, J.R. Calvert, Anna Lynn-Palevsky, Sidney Le , et al. · 2019

In order to evaluate mortality predictions based on boosted trees, this retrospective study uses electronic medical record data from three academic health centers for inpatients 18 years or older with at least one observation of each vital…

Change in Faculty Perceptions of Burnout and Work Life in an Academic General Medicine Clinic: a Pre-Post Study Open

Jonathan S. Lee, Leah Karliner, Katherine A. Julian, Mark Linzer, Mitchell D. Feldman · 2019

Dietary habits, body image, and health service access related to cardiovascular diseases in rural Zambia: A qualitative study Open

Yukiko Tateyama, Patou Masika Musumari, Teeranee Techasrivichien, S. Pilar Suguimoto, Richard Zulu , et al. · 2019

This study revealed that participants are relatively well aware of cardiovascular diseases and their risk factors. However, they engage in high-risk health behaviors, due to ingrained taste preferences, limited knowledge, and unavoidable s…

WIDOWHOOD AND MORTALITY RISK OF OLDER PEOPLE IN RURAL CHINA: DO GENDER AND LIVING ARRANGEMENT MAKE A DIFFERENCE? Open

Huiying Liu, Qian Jiang, Mitchell D. Feldman · 2018

Objectives: Increased mortality after spousal bereavement has been observed in many populations. Few studies have investigated the widowhood effect in a traditional culture where the economy is underdeveloped. In this study, we assessed wh…

Multicenter validation of a machine learning algorithm for 48 hour all-cause mortality prediction Open

Hamid Mohamadlou, Saarang Panchavati, Jacob Calvert, Anna Lynn-Palevsky, Christopher Barton , et al. · 2018

Purpose This study evaluates a machine-learning-based mortality prediction tool. Materials and Methods We conducted a retrospective study with data drawn from three academic health centers. Inpatients of at least 18 years of age and with a…

Correction: Socio-behavioral risk factors among older adults living with HIV in Thailand Open

Patou Masika Musumari, Arunrat Tangmunkongvorakul, Kriengkrai Srithanaviboonchai, Mitchell D. Feldman, Wathee Sitthi , et al. · 2018

[This corrects the article DOI: 10.1371/journal.pone.0188088.].

Socio-behavioral risk factors among older adults living with HIV in Thailand Open

Patou Masika Musumari, Arunrat Tangmunkongvorakul, Kriengkrai Srithanavibooncha, Mitchell D. Feldman, Wathee Sitthi , et al. · 2017

Smoking and alcohol use is common among OALHIV, with a substantial proportion not engaging in physical exercises. Interventions for OALHIV should particularly target males and those of lower socio-economic status to deter smoking and alcoh…

Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial Open

David Shimabukuro, Christopher W. Barton, Mitchell D. Feldman, Samson Mataraso, Ritankar Das · 2017

Introduction Several methods have been developed to electronically monitor patients for severe sepsis, but few provide predictive capabilities to enable early intervention; furthermore, no severe sepsis prediction systems have been previou…

Eight Years at the Helm Open

Mitchell D. Feldman, Richard L. Kravitz · 2017

Richard Kravitz: I suppose that depends on what your definition of Bit^is.MF: I mean that this issue of JGIM is the very last one we'll publish together.RK: If I were the sentimental sort, I might pause to reflect on that.But I thought I w…

Medical Education Then and Now Open

Mitchell D. Feldman, Jonathan Kramer‐Feldman · 2017

Psychiatric Consultation at Your Fingertips: Descriptive Analysis of Electronic Consultation From Primary Care to Psychiatry Open

Margaret Lowenstein, Olusinmi Bamgbose, Nathaniel Gleason, Mitchell D. Feldman · 2017

For the majority of patients, psychiatrists provided strategies for ongoing management in primary care without an in-person evaluation, and PCPs implemented most psychiatrist recommendations. eConsults show promise as one means of supporti…

What’s in a Name? Open

Mitchell D. Feldman · 2017

Altruism and Medical Practice Open

Mitchell D. Feldman · 2017

Reinventing Primary Care: Embracing Change, Preserving Relationships Open

Richard L. Kravitz, Mitchell D. Feldman · 2017

International Perspectives on General Internal Medicine Open

Jessica Greene, Mitchell D. Feldman · 2017

Peer Review at JGIM Open

Mitchell D. Feldman, Richard L. Kravitz · 2016

Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach Open

Thomas Desautels, Jacob Calvert, Jana Hoffman, Melissa Jay, Yaniv Kerem , et al. · 2016

Despite using little more than vitals, InSight is an effective tool for predicting sepsis onset and performs well even with randomly missing data.

Guns, Doctors and Public Health Open

Mitchell D. Feldman · 2016

Getting to the ‘Why’ of Behavior Change Open

Mitchell D. Feldman · 2016

Chronic Pain and Prescription Drug Use and Abuse: Emerging Research in General Internal Medicine Open

Mitchell D. Feldman · 2016

Mitchell D. Feldman YOU? Author Swipe