MHRN III Supplemental Project: Effect of COVID-19 Pandemic on Mental Health Service Use

Grant Details

Title: Impact and Implications of Rapid Transition to Virtual Mental Health Care during COVID-19

Funder: NIMH

Grant Number: 3U19MH121738-02S1

Grant Period: 9/30/2020 – 6/30/2021

Narrative: The Mental Health Research Network conducts practice-based mental health research in large healthcare systems serving over 25 million patients in 16 states, with a focus on having large-scale data infrastructure available for rapid analyses. This study takes advantage of that infrastructure to study how changing from in-person to phone- or video visits during the COVID-19 crisis disrupts care of people with mental health conditions, including those in important and potentially disadvantaged subgroups. This work will help us understand who needs more support during crises as well as determine who benefits most from telehealth visits as the field of behavioral health care continues to transition to using more of these services.

  • Lead Site:
    • Overall PI: HPI (Project lead/site PI Rebecca Rossom)
  • Participating Sites/Subcontractors:
    • HFHS (project co-lead/site PI Brian Ahmedani)
    • KPWA (PI Greg Simon, co-I Rob Penfold)
  • Funder Contacts
    • Science Officer: Susan Azrin
    • Program Official: Michael Freed
    • Grants Management Official: Julie Bergerud
  • Awarded Budget (Total Cost)
    •  $344,930


Funding Announcement

Personnel Contact List

Current status

Data extraction is completed at all participating sites.  The first set of analyses examining changes in suicide death outcomes before and after onset of the COVID-19 pandemic were completed and the manuscript was published in Medical Care.  Preliminary analyses of counts and rates examining visit patterns, diagnoses, and treatment patterns before and after onset of the pandemic have been completed.  Additional primary analyses are ongoing for each of these metrics.  Final data analyses will be completed in late 2022.

Summary of findings

In participating health systems, overall suicide mortality declined slightly during the first months of the COVID-19 pandemic.

Among people receiving specialty mental health care, likelihood of interrupting treatment was slightly lower after the shift to telehealth delivery than before the pandemic.


Rossom RC, Penfold RB, Owen-Smith AA, Simon GE, Ahmedani BK. Suicide Deaths Before and During the Coronavirus Disease 2019 Pandemic: An Interrupted Time-series Study. Med Care. 2022 Mar 1. doi: 10.1097/MLR.0000000000001700. Online ahead of print. PMID: 35230276.

MHRN III Infrastructure: Administrative Core

Grant Details

Funder: NIMH

Grant Number: U19MH121738

Grant Period: 09/23/2019 – 06/30/2020

  • Narrative:​ Practice-based research has the potential to dramatically improve the speed, efficiency, relevance, and impact of mental health clinical and services research.  Mental Health Research Network (MHRN) III will include 14 research centers embedded in health systems serving a combined population of over 25 million patients in 16 states.  MHRN infrastructure will be enhanced to support a next-generation practice-based network, including:
    • Increased engagement of patients, health system leaders, and other stakeholders in network governance
    • An expanded public, open-source library of software tools and other technical resources
    • More formal processes for conducting feasibility pilot projects and rapid response to stakeholder queries
    • Expanded outreach to external stakeholders and research partners
  • Lead Site: KPWHRI
    • Overall PI: Greg Simon
  • Participating Sites/Subcontractors:
    • Baylor Scott & White – Site PI: Katherine Sanchez
    • Cornell University – Site PI: Jyotishman Pathak
    • Essentia Institute of Rural Health – Site PI: Stephen Waring
    • Georgia State University – Site PI: Ashli Owen-Smith
    • Harvard Pilgrim – Site PI: Christine Lu
    • HealthPartners – Site PI: Rebecca Rossom
    • Henry Ford Health System – Site PI Brian Ahmedani
    • KP Colorado – Site PI: Arne Beck
    • KP Georgia – Site PI Courtney McCracken
    • KP Hawaii – Site PI: Yihe Daida
    • KP Northern California – Site PI: Stacy Sterling
    • KP Northwest – Site PI: Frances Lynch
    • KP Southern California – Site PI: Karen Coleman
    • PalAlto Medical Foundation – Site PI: Ellis Dillon
  • Funder Contacts
    • Science Officer: Susan Azrin
    • Program Official: Michael Freed
    • Grants Management Official: Jackie Chia
  • Awarded Budget (Total Cost)
    • Year 1: $2,220,745
    • Year 2: $2,052,966
    • Year 3: $2,035,335
    • Year 4: $2,000,066
    • Year 5: $1,967,876

Documents & Reports

  • IRB Review
    • KPWA IRBnet file: [ 1475733 ]
    • KPWA IRB is single IRB reviewing for BSWH, HPHC, HPI, KPNC, KPNW, and KPSC.
    • EIRH, HFHS, KPCO, (KPGA?), KPHI, and PAMF IRB determination that work is exempt.
    • GSU and UW IRB determination that work is research not involving human subjects.

Personnel Contact List

Funded feasibility pilot projects


MRHN III Supplemental Project: Effect of Initiating Buprenorphine on Suicidal Behavior

Grant Details

Title: Buprenorphine Effect on Suicidal Behavior

Funder: NIMH

Grant Number: U19MH121738-02S2  (supplement to main MHRN cooperative agreement)

Grant Period: 9/17/2020 – 8/31/2022

Narrative: This large observational study will evaluate the effects of initiating buprenorphine treatment on subsequent suicidal behavior among people with opioid use disorder, including those with and without co-occurring mental health conditions or other known risk factors for suicidal behavior. We will use comprehensive health records data from four large health systems serving a combined member/patient population of approximately 11 million. Analyses will examine the overall effect of buprenorphine treatment on subsequent suicide attempts or death, heterogeneity of effects in patient subgroups, and specificity of effects to buprenorphine vs other medications.

We will be using previously developed suicide risk prediction tools to compare the outcomes of individuals who do and do not use buprenorphine with similar baseline suicide risk.

  • Lead Site: KPWA
    • Overall PI: Greg Simon
  • Participating Sites/Subcontractors:
    • KPNC – Site PI: Cynthia Campbell
    • KPSC – Site PI: Rulin Hechter
    • Henry Ford – Site PI: Brian Ahmedani
  • Funder Contacts:
    • Science Officer: Susan Azrin
    • Program Official: Michael Freed
    • Grants Management Official: Julie Bergerud
  • Awarded Budget (Total Cost):
    • Year 1: $514,616
    • Year 2: $274,321


Funding Announcement: PA-18-591

Notice of Award

Personnel Contact List

Human Subjects: YES

  • IRB Review:
    • KPWA is single IRB reviewing for KPWA, KPNC, and KPSC – Approved waiver of consent for use of records data
    • Henry Ford determined to be exempt
    • KPWA IRBnet File: [1649129]

Clinical Trial: NO

Current status

Exploratory analyses (in preparation for extraction of data at each site) have examined availability and quality of data regarding opioid medication use, availability and quality of data regarding injury and poisoning events, and types of visits occurring prior to initial buprenorphine prescriptions.  These analyses are informing refinements to research design and data specifications.  Final data extraction will occur during in October 2022 with analyses complete in early 2023.

Summary of findings

Not yet available



Effects of Medical Products on Suicidal Ideation and Behavior

Project Name:
Effects of Medical Products on Suicidal Ideation and Behavior
Principal Investigator:
Gregory Simon, MD, MPH
Principal Investigator Contact Information:
Principal Investigator Institution:
KP Washington Health Research Institute
Food and Drug Administration (FDA)
Funding Period:
9/30/2018 to 9/30/2021
We propose a comprehensive program of infrastructure development and methods development to support future generation of real-world evidence addressing these critical gaps.  The project team will include health systems and embedded research organizations with deep expertise in stakeholder engagement, medical informatics, data science, clinical epidemiology, biostatistics, pragmatic clinical trial methods, implementation science, and innovations in care delivery. Specific Tasks include: Augment the existing FDA Sentinel Initiative data infrastructure to support study of severe mental illness, suicidal ideation, and suicidal behavior. Evaluate and improve generalizability of models predicting suicidal behavior for use in future observational research and pragmatic trials. This program will be embedded in 4 integrated health systems serving a combined population of approximately 10 million members.  This work will be conducted in collaboration with health system and patient/family stakeholders, to assure that methods and evidence developed will actually address real-world questions. This infrastructure and methods development will enable a robust program of research regarding the effects of medical products on suicidal ideation and behavior, including: Scalable and re-usable methods to assess suicidal ideation and behavior as an adverse effect of existing products. Scalable and re-usable methods to assess therapeutic effects of existing products for reducing suicidal ideation and behaviorScalable and re-usable methods to rapidly evaluate possible therapeutic and adverse effects of new medical products on suicidal ideation and behavior. Large pragmatic trials to evaluate therapeutic effects of promising new product(s) on suicidal behavior
Grant Number:
Participating Sites:
Kaiser Permanente Washington
Harvard Pilgrim Healthcare
Kaiser Permanente Northern California
Kaiser Permanente Southern California
Henry Ford Health System                
Gregory Simon MD MPH
Susan Shortreed PhD
Yates Coley PhD
Richard Platt MD MS
Jeffrey Brown PhD
Darren Toh ScD
Jessica Young PhD
Stacy Sterling PhD
Karen Coleman PhD
Jean Lawrence ScD
Brian Ahmedani PhD
Major Goals Augment the existing FDA Sentinel Initiative data infrastructure to support study of severe mental illness, suicidal ideation, and suicidal behavior. Evaluate and improve generalizability of models predicting suicidal behavior for use in future observational research and pragmatic trials.
Description of study sample:
Various analyses are using data regarding approximately 4.5 million members of participating health systems.
Current Status:
Completed data infrastructure work includes:
– A toolkit to assess re-identification risk when sharing data derived from healthcare records:
– More timely updating of mortality data in health system research data warehouses.
– Regular reporting of availability and quality of patient-reported outcome data in health system research data warehouses.
Analyses are complete regarding:
– Value of more detailed data representation and more complex modeling methods for prediction of suicidal behavior.
– Accuracy of ICD-10-CM encounter diagnoses for identifying self-harm events.
– Value of data typically only available from electronic health records for prediction of suicidal behavior.
Study Registration:
Simon GE, Shortreed SM, Boggs JM, Clarke GN, Rossom RC, Richards JE, Beck A, Ahmedani BK, Coleman KJ, Bhakta B, Stewart CC, Sterling S, Schoenbaum M, Coley RY, Stone M, Mosholder AD, Yaseen ZS. Accuracy of ICD-10-CM encounter diagnoses from health records for identifying self-harm events. J Am Med Inform Assoc. 2022 Aug 26:ocac144. doi: 10.1093/jamia/ocac144.
Lessons Learned:
For prediction of suicidal behavior following outpatient mental health visits, more detailed temporal representation and more complex model development methods (random forest or neural networks vs. penalized logistic regression) do not meaningfully improve prediction accuracy.
When using prediction models to account for confounding by indication in observational studies of medication effects on suicidal behavior, random forest models may be slightly – but not meaningfully – superior to penalized logistic regression.
When using health records data to predict suicidal behavior, additional data available only from electronic health records (race, ethnicity, patient-reported outcome results) do not significantly improve prediction over data typically available from insurance claims.
What’s next?
Additional analyses will examine:
– Similarities and differences in prediction of opioid vs. other overdoses
– Similarities and differences in prediction of self-harm vs. accidental overdoses
– Changes in accuracy of suicide risk prediction models with health system implementation of Zero Suicide care improvement programs.

Pathways from Chronic Prescription Opioid Use to New Onset Mood Disorder

Grant Details

Funder: NIH, NIDA

Grant Number: R01ActDA043811

Grant Period: 4/1/2019 – 3/31/2023

Narrative: Research on the association between psychopathology and prescription opioid analgesic use (OAU) has established that mental illness influences risk of chronic OAU (i.e. >90-days), high dose OAU and misuse. We explored the reverse direction of association and found longer OAU and higher opioid doses are associated with increased risk of new onset depression (NOD), independent of pain. Using Veterans Health Affairs (VA) patient data revealed >90-day OAU was associated with a 35% (in VA patients) to 105% (in private sector patients) increased risk of NOD compared to patients with 1-30 day OAU. Our additional studies revealed that OAU is associated with depression recurrence and treatment resistant depression. If these results are confirmed in the present proposal, results have potential to greatly inform interventions to reduce chronic OAU (e.g. treating depression), elucidate pathways to OAU misuse, and generate a body of evidence that informs safe opioid prescribing. To reveal pathways from OAU to NOD and related depression phenotypes (i.e. dysthymia, bipolar, anhedonia, vital exhaustion) we must measure the patients’ pre-existing risk factors and post-OAU events. We will obtain diagnoses and symptom level data and covariates that are not available in the medical record data used in our R21 and strengthen the temporal relationships between OAU and NOD. The central hypothesis driving this research is that pre-OAU risk factors such as a history of depression and post-OAU events such as onset of opioid misuse contribute to NOD.
If NOD is explained by OAU alone and not by pre-existing risk factors, then the opioid epidemic is generating new cases of depression in a large population of middle-aged adults, otherwise not at risk for NOD. Findings will disentangle consequences or correlates of chronic pain per se from those of chronic, high dose OAU. We test whether the OAU-NOD association is moderated by pre-existing depression, substance use disorder (SUD), including opioid use disorder and trauma exposure. We next propose that post-OAU opioid misuse, SUD, poor functioning, low social support and poor sleep quality promote NOD. Using 12 monthly brief assessments, we will determine if change in OAU, independent of change in pain influences, depression trajectories and determine if there is a reciprocal relationship among these variables over time. We will determine if OAU is associated with different depression phenotypes and last determine which subtypes of depression contribute to incident opioid use disorder.

Lead Site: St. Louis University (PI Jeffrey Scherrer)

Participating Sites: HFHS (Site PI Brian Ahmedani)

Current Status:

Summary of Findings: