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Mitchell J Barnett

Biographic Data

ID231284
NAMEMitchell J Barnett
GIVEN NAMESMitchell J
FAMILY NAMEBarnett
SIGNATUREBARNETT M J
AFFILIATIONSTouro University California
ORCID0000-0002-9645-9865
VERIFIEDYes
TOTAL WORKS7
TOTAL CITATIONS0
AUTHOR COUNT7
EDITOR COUNT0
FIRST PUBLICATION YEAR2001
LATEST PUBLICATION YEAR2023
H-INDEX0
  • Barber Motivation for Conducting Mental Health Screening and Receiving Mental Health Education in Barbershops That Primarily Serve African Americans: A Cross-sectional Study

    Open Access•Mohamed Jalloh, Jasmine Stompanato et al.•ARTICLE•Journal of Racial and Ethnic…•2023

  • The video gamer 500: Performance-enhancing drug use and Internet Gaming Disorder among adult video gamers

    Open Access•Eric J Ip, Emil Paul T Urbano et al.•ARTICLE•Computers in Human Behavior•2021

  • Men’s Health-Related Magazines: A Retrospective Study of What They Recommend and the Evidence Addressing Their Recommendations

    Open Access•Mohamed Jalloh, Mitchell J Barnett et al.•ARTICLE•American Journal of Men s Health•2020

    Magazines have traditionally been an effective medium for delivering health media messages to large populations or specific groups. In this retrospective cross-sectional study, we evaluated nine issues from 2016 publications of American men’s health-related magazines ( Men’s Health and Men’s Fitness) to evaluate their recommendations and determine their validity by examining corresponding evidence found in the peer-reviewed scientific literature.…

  • Predicting Resource Utilization in a Veterans Health Administration Primary Care Population: Comparison of Methods Based on Diagnoses and Medications

    Terry L Wahls, Mitchell J Barnett et al.•ARTICLE•Medical Care•2004•References: 23

    BACKGROUND: Valid methods of predicting resource utilization in primary care populations are needed. We compared the predictive validity of a method based on diagnoses from administrative data (Adjusted Clinical Groups [ACGs]) and a method using medication profiles (Chronic Disease Index [CDI]). METHODS: This retrospective cohort study included 31,212 primary care patients in a Veterans Health Administration (VA) network who received outpatient m…

  • Differences in Length of Stay in Veterans Health Administration and Other United States Hospitals: Is the Gap Closing

    Gary E Rosenthal, Peter J Kaboli et al.•ARTICLE•Medical Care•2003•References: 25

    OBJECTIVES: Compare risk-adjusted length of stay (LOS) in VA and other United States (non-VA) hospitals and determine if relative differences in LOS have changed in recent years. RESEARCH DESIGN: Retrospective cohort study. PATIENTS: Patients with ten common medical diagnoses admitted to all VA hospitals and to non-VA hospitals included in the National Hospital Discharge Survey (NHDS) during 1996 through 1999. DATA: Comparable data elements were …

  • Day of the Week of Intensive Care Admission and Patient Outcomes: A Multisite Regional Evaluation

    Mitchell J Barnett, Peter J Kaboli et al.•ARTICLE•Medical Care•2002•References: 29

    BACKGROUND: Relationships between day of the week of admission to hospitals and hospital outcomes have been poorly studied. Intensive care units (ICUs) appear to be uniquely suited to examine such a question given the unpredictability of ICU admissions and the clinical instability of their patient populations. METHODS: This retrospective cohort study included 156,136 patients admitted to 38 ICUs in 28 hospitals in a large Midwestern metropolitan …

  • Length of Stay as a Source of Bias in Comparing Performance in VA and Private Sector Facilities: Lessons Learned from a Regional Evaluation of Intensive Care Outcomes

    Peter J Kaboli, Mitchell J Barnett et al.•ARTICLE•Medical Care•2001•References: 30

    OBJECTIVES: Compare intensive care unit (ICU) mortality and length of stay (LOS) in a VA hospital and private sector hospitals and examine the impact of hospital utilization on mortality comparisons. RESEARCH DESIGN: Retrospective cohort study. SUBJECTS: Consecutive ICU admissions to a VA hospital (n = 1,142) and 27 private sector hospitals (n = 51,249) serving the same health care market in 1994 to 1995. MEASURES: Mortality and ICU LOS were adju…

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  • Length of Stay as a Source of Bias in Comparing Performance in VA and Private Sector Facilities: Lessons Learned from a Regional Evaluation of Intensive Care Outcomes

    Peter J Kaboli, Mitchell J Barnett et al.•ARTICLE•Medical Care•2001•References: 30

    OBJECTIVES: Compare intensive care unit (ICU) mortality and length of stay (LOS) in a VA hospital and private sector hospitals and examine the impact of hospital utilization on mortality comparisons. RESEARCH DESIGN: Retrospective cohort study. SUBJECTS: Consecutive ICU admissions to a VA hospital (n = 1,142) and 27 private sector hospitals (n = 51,249) serving the same health care market in 1994 to 1995. MEASURES: Mortality and ICU LOS were adju…

  • Day of the Week of Intensive Care Admission and Patient Outcomes: A Multisite Regional Evaluation

    Mitchell J Barnett, Peter J Kaboli et al.•ARTICLE•Medical Care•2002•References: 29

    BACKGROUND: Relationships between day of the week of admission to hospitals and hospital outcomes have been poorly studied. Intensive care units (ICUs) appear to be uniquely suited to examine such a question given the unpredictability of ICU admissions and the clinical instability of their patient populations. METHODS: This retrospective cohort study included 156,136 patients admitted to 38 ICUs in 28 hospitals in a large Midwestern metropolitan …

  • Differences in Length of Stay in Veterans Health Administration and Other United States Hospitals: Is the Gap Closing

    Gary E Rosenthal, Peter J Kaboli et al.•ARTICLE•Medical Care•2003•References: 25

    OBJECTIVES: Compare risk-adjusted length of stay (LOS) in VA and other United States (non-VA) hospitals and determine if relative differences in LOS have changed in recent years. RESEARCH DESIGN: Retrospective cohort study. PATIENTS: Patients with ten common medical diagnoses admitted to all VA hospitals and to non-VA hospitals included in the National Hospital Discharge Survey (NHDS) during 1996 through 1999. DATA: Comparable data elements were …

  • Predicting Resource Utilization in a Veterans Health Administration Primary Care Population: Comparison of Methods Based on Diagnoses and Medications

    Terry L Wahls, Mitchell J Barnett et al.•ARTICLE•Medical Care•2004•References: 23

    BACKGROUND: Valid methods of predicting resource utilization in primary care populations are needed. We compared the predictive validity of a method based on diagnoses from administrative data (Adjusted Clinical Groups [ACGs]) and a method using medication profiles (Chronic Disease Index [CDI]). METHODS: This retrospective cohort study included 31,212 primary care patients in a Veterans Health Administration (VA) network who received outpatient m…

  • Men’s Health-Related Magazines: A Retrospective Study of What They Recommend and the Evidence Addressing Their Recommendations

    Open Access•Mohamed Jalloh, Mitchell J Barnett et al.•ARTICLE•American Journal of Men s Health•2020

    Magazines have traditionally been an effective medium for delivering health media messages to large populations or specific groups. In this retrospective cross-sectional study, we evaluated nine issues from 2016 publications of American men’s health-related magazines ( Men’s Health and Men’s Fitness) to evaluate their recommendations and determine their validity by examining corresponding evidence found in the peer-reviewed scientific literature.…

  • The video gamer 500: Performance-enhancing drug use and Internet Gaming Disorder among adult video gamers

    Open Access•Eric J Ip, Emil Paul T Urbano et al.•ARTICLE•Computers in Human Behavior•2021

  • Barber Motivation for Conducting Mental Health Screening and Receiving Mental Health Education in Barbershops That Primarily Serve African Americans: A Cross-sectional Study

    Open Access•Mohamed Jalloh, Jasmine Stompanato et al.•ARTICLE•Journal of Racial and Ethnic…•2023

Medicine (7 works) · Emergency Medicine (4 works) · Emergency Medicine (4 works) · Internal Medicine (4 works) · Internal Medicine (4 works) · Emergency and Acute Care Studies (3 works) · Family medicine (3 works) · Gerontology (3 works) · Retrospective cohort study (3 works) · Clinical Psychology (2 works)

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