Eric Johnson, MS

  • 4Articles
  • 19.2KReads
  • 2015–2022Active
  • 32Collaborators
  • 205Citations

About

Eric Johnson, MS, is affiliated with Kaiser Permanente Washington Health Research Institute in Seattle, Washington. His publications from 2015 to 2022 focus on suicide risk prediction, adherence to antidepressant medication, and trends in substances involved in deliberate self-poisoning. He has contributed to research on depression, addiction, and patient care within community practice settings. Johnson frequently collaborates with Gregory E. Simon, Karen J. Coleman, Susan M. Shortreed, Arne Beck, and Rebecca C. Rossom.

Publications

JCP
Machine Learning Prediction of Suicide Risk
Original Research

Machine Learning Prediction of Suicide Risk

August 31, 2022

Suicide assessment prompted by prediction models may be intrusive to patients with no history of suicidality. This study examined if machine learning models identify patients with high suicide risk...
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JCP
Original Research

Antidepressant Adherence in Psychiatry and Primary Care

October 24, 2017

Does rate of adherence to antidepressants vary much between physicians? This study of electronic health records and insurance claims data investigates the question, as well as whether adherence to...
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JCP
Article

Suicide Risk and PHQ-9 Responses

February 24, 2016

When your patients complete the Patient Health Questionnaire, they are asked about the frequency of suicidal thoughts. For patients who indicate suicidal ideation, how long does their suicide risk...
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JCP
Article

Population Trends in Substances Used in Deliberate Self-Poisoning Leading to Intensive Care Unit Admissions From 2000 to 2010

December 23, 2015

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Physicians Postgraduate Press, Inc. (PPP) makes no warranties about the accuracy or completeness of any information published in The Journal of Clinical Psychiatry or other PPP materials, and disclaims liability for any use or non-use of that information. Clinicians should not rely solely on these materials and should exercise their own professional judgment when making patient care decisions on an individualized basis.

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