Improving Suicide Risk Prediction with Social Determinants Data

Grant Details

Funder: NIMH

Grant Number: R56MH125794-01A1

Grant Period: 1/1/2022 – 12/31/2022

Brief Narrative: Suicide accounted for 47,511 deaths in the United States in 2019 and the suicide rate has increased by 39% since 1999. Suicide prevention is an NIMH research priority. Recent research in estimating machine learning algorithms to predict suicide risk has been tremendously successful. The models have been implemented as part of routine prevention programs in health systems such as Kaiser Permanente Washington, HealthPartners, and the Veterans Health Administration. Despite these successes, existing models have important shortcomings. A significant proportion of suicides followed healthcare visits where the predicted risk was low (and where an intervention might have taken place otherwise). The models do not currently include any information about social determinants of suicide (e.g., living alone, financial stress) or negative life events (NLE), such as divorce, bankruptcy, and criminal arrest. Adding social determinants data and NLE data to models may improve predictive accuracy. The specific aims of this study are: (1) expand and enhance the risk prediction dataset with over 1500 date-stamped variables describing social determinants of suicide risk and NLE; (2) construct and evaluate suicide risk prediction models using social determinants and NLE data alone; (3) construct and evaluate suicide risk prediction models using social determinants, NLE and healthcare data together and estimate interaction terms between social determinants, NLE, and healthcare predictors. An example would be “depression diagnosis” interacted with “divorce filing in last 30 days”. This will be the first large scale study to incorporate individual-level, date-stamped measures of social determinants and NLE into machine learning suicide risk prediction models. Upon successful completion of this study we expect to know how much incorporating these new data contributes to the accuracy of suicide risk prediction models. This will be an important next step towards implementing better suicide prevention programs and reducing overall suicide rates.

Lead Site: KPWA (PI Rob Penfold)

Participating Sites: N/A

Current Status

We fielded the discrete choice experiment in mid-October 2022. Planned recruitment is 720.

Summary of Findings

Publications

Trans-America Consortium of the Health Care Systems Research Network for the All of Us Research Program

Grant Details

Funder: NIH Office of the Director

Grant Number: OT2OD026550

Grant Period: 1/4/2018 – 3/31/2023

Narrative:

Lead Site: HFHS (co-PIs Christine Johnson and Brian Ahmedani)

Participating Sites:

Current Status:

Ongoing recruitment, enrollment and retention of 100,000 participants and members.

Summary of Findings:

Publications:

Cronin, R.M., Jerome, R.N., Mapes, B.M., Andrade, R., Johnston, R., Ayala, J., Schlundt, D., Bonnet, K.R., Kripalani, S., Goggins, K., Wallston, K.A., Couper, M.P., Elliott, M.R., Harris, P.A., Begale, M.A., Munoz, F.A., Lopez-Class, M., Cella, D., Condon, D.M., AuYoung, M., Mazor, K.M., Mikita, S., Manganiello, M., Borselli, N., Fowler, S.L., Rutter, J.L., Denny, J.C., Karlson, E.W., Ahmedani, B.K., O’Donnell, C.J. Vanderbilt University Medical Center Pilot Team, and the Participant Provided Information Committee. (2019). Development of the Initial Surveys for the All of Us Research Program. Epidemiology, 30(4), 597-608.. doi: 10.1097/EDE.0000000000001028. PMID: 31045611. 

Ramirez AH, Sulieman L, Schlueter DJ, Halvorson A, Qian J, Ratsimbazafy F, Loperena R, Mayo K, Basford M, Deflaux N, Muthuraman KN, Natarajan K, Kho A, Xu H, Wilkins C, Anton-Culver H, Boerwinkle E, Cicek M, Clark CR, Cohn E, Ohno-Machado L, Schully SD, Ahmedani BK, Argos M, Cronin RM, O’Donnell C, Fouad M, Goldstein DB, Greenland P, Hebbring SJ, Karlson EW, Khatri P, Korf B, Smoller JW, Sodeke S, Wilbanks J, Hentges J, Mockrin S, Lunt C, Devaney SA, Gebo K, Denny JC, Carroll RJ, Glazer D, Harris PA, Hripcsak G, Philippakis A, Roden DM; All of Us Research Program. (2022). The All of Us Research Program: Data quality, utility, and diversity. Patterns (N Y); 3(8), 100570. doi: 10.1016/j.patter.2022.100570. PMID: 36033590.

Cronin, R.M., Halvorson, A.E., Springer, C., Feng, X., Sulieman, L., Loperena-Cortes, R., Mayo, K., Carroll, R.J., Chen, Q., Ahmedani, B.K., Karnes, J., Korf, B., O’Donnell, C.J., Qian, J., Ramirez, A.H., All of Us Research Program Investigators.  (2021). Comparison of Family Health History in Surveys versus Electronic Health Records in the All of Us Research Program. Journal of the American Medical Informatics Association, 28(4):695-703. doi: 10.1093/jamia/ocaa315. PMID: 33404595. 

Using NLP to Increase Identification of Child Maltreatment in EHR

Grant Details

Funder: NIMH (MHRN III Feasibility Pilot Program)

Grant Number: U19MH121738

Project Period: 7/1/2020 – 6/30/2021

Narrative:

Background: Child maltreatment is a critical public health issue and health care systems play an important role in identifying and treating children who experience maltreatment. To date, few studies of child maltreatment have used data from large health systems to try and understand how these systems identify and manage youth who experience maltreatment. Preliminary analyses of the number of children identified as having experienced child maltreatment in the most recent MHRN quarterly descriptive analyses (2018) indicate that there is likely a significant under-reporting of child maltreatment in the MHRN health systems. Epidemiologic studies suggest that many more youth would have been identified with child maltreatment. One reason for this potential under reporting is that providers may not use the ICD codes to document child maltreatment consistently. Some maltreatment may be discussed in chart notes but not documented using ICD codes. Better identification of maltreatment could aid both research and practice within health care systems. Natural Language Processing may help to identify additional youth with maltreatment. If NLP identifies cases that are not documented through ICD codes, this could indicate the need for health system efforts to develop new ways of consistently document child maltreatment. NLP might also help to identify any groups (e.g., age, gender, race/ethnicity) that may be particularly likely to have insufficient documentation of child maltreatment. 

This work aligns with NIMH’s strategies to increase research and improve outcomes of mental health services in diverse and vulnerable populations, and to conduct research that helps health systems to base care decisions on the best possible data.   

Research Question: The overarching question is does NLP allow us to obtain estimates the number of children who experience maltreatment more comparable to national epidemiologic data? Does NLP of chart notes identify new cases of child maltreatment that are not already documented with ICD codes? What is the overlap between the two methods? Are there differences by age group or race-ethnicity? Does NLP allow us to differentiate between new/current maltreatment versus history of maltreatment?

Methods: We propose to use simple NLP queries at 1 MHRN site (e.g., terms such as physical abuse, maltreatment) to search chart notes and to compare the number of cases identified through NLP and compare those to cases identified through ICD codes. We will also conduct analyses to see if there is variation in identification by age group, gender, and race/ethnicity.  

Planned Product: We plan to write a paper documenting our findings. We also plan to write a grant related to child maltreatment using this data.

  • Lead Site: KPWA (PI Rob Penfold)
  • Participating Sites:
  • KPSC (Co-I Sonya Negriff)
  • KPNW (Co-I Frances Lynch)

Current Status

  • NLP pipeline created
  • Manual adjudication of NLP “hits” complete
  • Descriptive statistics complete

Summary of Findings

The prevalence of child maltreatment as measured by adjudicated occurrences of terms and phrases discovered by NLP is much higher than when measured via discrete data elements.

Publications

None yet

PHQ9 Differential Item Functioning

Grant Details

Funder: NIMH (MHRN III Feasibility Pilot Program)

Grant Number: U19MH121738

Project Period: 7/1/2020 – 6/30/2021

Narrative:

Background: Depression and suicide screeners like the Patient Health Questionnaire 9 (PHQ-9) are widely employed within healthcare systems in the U.S. as part of measurement-based care. Some research suggests the full or partial cross-cultural equivalence of the PHQ-9 among different racial and ethnic groups, including the standard one-factor model (Harry & Waring, 2019; Keum, Miller, & Kurotsuchi Inkelas, 2018; Merz et al., 2011; Patel et al., 2019), although in some cases two-factor models have presented the best fit (Granillo, 2012; Harry & Waring, 2019; Harry, Coley, Waring, & Simon, under review; Keum et al., 2018). Findings of cross-cultural equivalence allows for meaningful comparisons to be made in scale mean scores between different cultural groups. However, research has also shown the differential item functioning for some PHQ-9 items based on race (Huang et al., 2006). Furthermore, little cross-cultural research is available on the PHQ-9 that includes American Indian/Alaska Native people (AI/AN) (Harry & Waring, 2019; Harry et al., under review). This is even though AI/AN people have a higher rate of suicide than the general population (Curtin & Hedegaard, 2019) and few studies have researched depression prevalence among this group (Garrett et al., 2015). While available evidence suggests elevated depression rates amongst AI/AN people, most research has focused on individual tribal groups, and the little research that has included national samples has primarily only included those who identify solely as AI/AN and not additional racial or ethnic groups (Asdigian et al., 2018). Depression prevalence may differ between sub-populations of AI/AN people (Asdigian et al., 2018). Mental and behavioral health scales may also function differently between separate tribal or cultural AI/AN groups (Walls et al., 2018).

Recent studies have begun to fill the gap on the cross-cultural equivalence of the PHQ-9 with AI/AN people. Current findings have been mixed, including the study by Harry and Waring (2019) with a general patient population and another study by Harry et al. (under review) that included only those with mental health or substance abuse disorder diagnoses, suggesting that more research is needed. It is unknown if any individual PHQ-9 items function differently between AI/AN people and other racial and ethnic groups (Harry et al., under review). Both researchers and clinicians would benefit from understanding how individual PHQ-9 items function for different groups of AI/AN people and in comparison to other diverse racial and ethnic groups. This is a timely opportunity to extend our work by leveraging the findings from our prior research in this area, focus more closely on the functioning of item 9 between racial and ethnic groups, as well as develop additional preliminary results for a future R01 grant application.

This project supports the NIMH strategic goal of striving for prevention and cures. It does so by focusing on the cultural context component of developing strategies for tailoring existing interventions to optimize outcomes.

Research Question: In a patient population with mental health or substance abuse disorder diagnoses, how do individual PHQ-9 items function for AI/AN adults and other diverse racial and ethnic groups?

Methods: The differential item functioning of PHQ-9 items would be assessed using item response theory, or how different groups with differing levels of depression endorse PHQ-9 items. We would compare two geographically and culturally distinct groups of AI/AN adults (ages 18 to 64), as well as groups of Hispanic, non-Hispanic Native Hawaiian/Pacific Islander, non-Hispanic White, non-Hispanic Black, and non-Hispanic Asian adults. This study would be conducted using existing data from prior research and therefore would not require additional analyst support. The project has already been approved by the Essentia Health Institutional Review Board.

Planned Product: The primary product would be a paper presenting our results. Those results would also provide additional preliminary data for a series of broader, multi-MHRN site NIH grant applications on the cross-cultural assessment of depression and suicide risk and culturally competent interventions for AI/AN people and other indigenous groups, like Native Hawaiians. Collaboration with local tribal communities and researchers would be emphasized.

Lead Site: Essential Rural Health Institute (PI Melissa Harry)

Participating Sites: N/A

Current Status

Paper is under review with Psychological Assessment as of 10/12/2022.

Summary of Findings

Publications

Reduce Racial/Ethnic Disparities in Suicide Risk Prediction (RED)

Grant Details

Title: Innovative methods to reduce racial and ethnic disparities in suicide risk prediction

Funder: NIMH

Grant number: 1R01MH125821

Grant period: 1/1/2022 – 12/31/2025

Brief Narrative: Suicide risk prediction models are being used by health care systems to guide delivery of suicide prevention interventions, but these prediction models may not accurately identify high-risk patients in racial and ethnic subgroups that are less prevalent or have lower rates of suicide attempt and death. This project will reduce racial and ethnic disparities in suicide risk models by developing methods for prediction model estimation that optimize performance within subgroups, rather than across the whole population, and adjust for misclassification of suicide outcomes. We will also design sample size calculations that evaluate the ability of a prediction study to accurately identify high-risk individuals within racial and ethnic subgroups.

  • Lead site:
    • KPWA (PI Yates Coley)
  • Participating sites:
    • University of Washington (Co-I Noah Simon)
    • KPSC (Co-I Karen Coleman)

Awarded budget (total cost): $1,622,626

Human Subjects: Reviewed by KPWA IRB, IRBNet# 1870253

Current status

Statistical methods research is underway. IRB and data use approvals are in place for all planned analyses. Current activities are focused on methods for accounting for outcome misclassification; evaluating variable importance in suicide prediction models; and designing estimation methods to optimize performance in racial/ethnic subgroups.

Summary of findings

Publications

MHRN III Pilot Project 2: Outreach to Reduce Depression Treatment Disparities

Funder: NIMH

Grant Number: U19MH121738

Project Period: 07/01/2021 – 06/30/2024

Brief Narrative:

Failure to initiate treatment is a major gap in care for depression – A recent Mental Health Research Network (MHRN) study involving more than 240,000 patients in 5 health systems with a new diagnosis of depression in primary care found that only about a third (36%) had completed a psychotherapy visit or filled a prescription for antidepressant medication within 90 days of a new depression diagnosis.
Large racial and ethnic disparities in depression treatment initiation exist – In that MHRN study the odds of Asians, Blacks and Hispanics initiating treatment were 30% lower than for Non-Hispanic Whites.
Previous research has focused on care after treatment initiation – Collaborative care and care management programs can reduce disparities, improving outcomes among traditionally under-served racial and ethnic groups. This work, however, has usually focused on those who have already initiated treatment.
Interventions to improve treatment initiation must accommodate diversity of patient experience and preferences –Underserved racial and ethnic groups may prefer psychotherapy over medication and may also prefer alternative treatments or alternative care providers. One size of depression treatment does not fit all.
eHealth technologies have the potential to address failures in treatment initiation – Previous research by MHRN investigators and others demonstrates that online messaging and other telehealth technologies can effectively and efficiently improve depression treatment adherence. These interventions, however, have focused on adherence after treatment initiation and have been tested primarily in non-Hispanic white patients.
Proposed trial: This pilot study will refine, adapt and test an outreach intervention to improve depression treatment initiation among patients recently receiving a new diagnosis of depression in primary care. Focusing on African American, Asian, Native Hawaiian/Pacific Islander and Hispanic patients, the study will leverage existing MHRN work to implement an automated outreach program with follow-up care facilitation by mental health clinicians. The intervention will utilize analytic and technological expertise developed by the MHRN to rapidly identify patients, send outreach messages, conduct assessments and facilitate care for patients with depression who fail to initiate treatment in a timely manner. The intervention will be developed with the input of patients in the target racial and ethnic minority populations and providers. Approximately 400 eligible patients in two MHRN health systems will be randomized to the intervention group or usual care. Outcomes (treatment initiation and rates recorded depression remission and response) will be ascertained from health system records. Analyses will examine intervention participation and compare the primary outcome (treatment initiation) and secondary outcomes (recorded depression remission and response) between groups. Results will inform a subsequent full-scale pragmatic trial to assess reduction in population-level disparities.

  • Lead Site:
    • KPHI (PI Vanessa Simiola)
  • Participating Sites:
    • HFHS (Site PI Lisa Matero)
    • KPWA (Co-I Greg Simon)
  • Awarded Budget (total costs):
    • Year 1: $112,382

Current Status

Over the reporting period Institutional Board Approval has been granted and focus group materials have been finalized as part of the formative research. Eligible participants were identified within the health care systems via distributed SAS code. Participant recruitment is currently underway within one (KPHI) of the two health care systems, with online focus groups scheduled in the beginning of May. The second health care system (HFHS) is awaiting local IRB approval and will begin recruitment immediately following. Provider surveys are scheduled for the end of the reporting period.

Summary of findings

Not yet available

Publications

None

Documents

Funding Announcement

Notice of Award

Personnel Contact List

Human Subjects: YES

IRB Review: KPSC is single IRB reviewing for KPHI, HFHS, and KPWA. File #12874.

Clinical Trial: YES

Evaluating Zero Suicide Care Improvement Programs in MHRN Health Systems

Grant Details

Title: An Evaluation of the National Zero Suicide Model Across Learning Healthcare Systems

Funder: NIMH

Grant Number: 1U01MH114087

Grant Period: 08/03/2017 – 05/31/2022

Narrative: Health systems at six participating sites have all committed to developing and implementing various components of a National Zero Suicide Model (NZSM), originally developed at the lead site for this study, Henry Ford Health System (HFHS).  Each health system will decide which components to implement at their respective site.  This study will develop metrics to measure fidelity and outcomes for the NZSM components implemented in each system using EHR and insurance claims data.  The project will then use these metrics to conduct fidelity and outcome evaluation of the various NZSM approaches in each system using an Interrupted Time Series Design.

Short-term project objectives:

We seek to accomplish three specific aims:

  1. Collaborate with health system leaders across sites to develop EHR metrics to measure specific quality improvement targets and care processes tailored to local NZSM implementation.
  2. Examine the fidelity of the specific NZSM care processes implemented in each system.
  3. Investigate suicide attempt and mortality outcomes within and across NZSM system models.

Long-term project objectives:

Learnings from this study will be immediately available on the Zero Suicide and MHRN websites, shared directly with SAMHSA and NIMH (thru the MHRN), and disseminated broadly to health systems via Zero Suicide Training Academies well before published data are available. As such, our goal is rapid dissemination and translation to practice, as opposed to the standard research-to-practice model – which the NIH and others estimate can take 17 years.

  • Lead Site:
    • Overall PI: HFHS Brian Ahmedani
  • Participating Sites/Subcontractors:
    • KPWA (site PI Greg Simon)
    • KPCO (site PI Jennifer Boggs)
    • KPNW (site PI Greg Clarke)
  • Funder Contacts
    • Science Officer: Susan Azrin
    • Program Official: Michael Freed
    • Grants Management Official: Julie Bergerud

Documents & Reports

Funding Announcement

Personnel Contact List

Publications

Manuscripts in process

ZS manuscript tracker: https://airtable.com/shr7wfbafq5c1rwTY

MHRN manuscript proposal form: https://airtable.com/shrD81CbLqaRrF8ga

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

Documents

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.

Publications

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.

Comparative Risks and Benefits of Gender Reassignment Therapies

Project Name:
Comparative Risks and Benefits of Gender Reassignment Therapies
Principal Investigator:
Michael Goodman, MD MPH
Principal Investigator Contact Information:
mgoodm2@emory.edu
Principal Investigator institution:
Emory University
Funder
PCORI
Funding Period:
05/2013 – 04/2016
Abstract:
The goal of this study is to understand the short- and long-term health issues among transgender persons who had or are planning to have a sex change treatment. Members of the transgender community and their doctors express concerns about mental and physical health problems in this group of people; however, large studies of transgender persons in the United States have not been conducted. This project is an electronic medical record-based study evaluating a group of 6,500 transgender individuals, whose care is covered by the Veterans Administration (nationally) or by Kaiser Permanente (in Georgia and in Northern and Southern California). In this study, we will compare frequencies of various diseases and deaths from various causes in transgender persons and separately in those who request female-to-male and male-to-female sex change to similar measures in a sample of men and women who are not transgender and are of the same age and race. We will also compare health problems by treatment categories (e.g., no medical treatment, versus treatment with hormones only, versus hormones plus surgery). The proposed project will be carried out by a team that includes experts in chronic and infectious diseases, mental disorders, and sexual minority health issues. All of the project activities will be implemented in consultation with the study advisors who will serve as advocates for the transgender community. This will likely be the largest study of transgender persons available to date, and the first study of its kind conducted in the United States.
Grant Number:
N/A
Participating Sites:               
Emory University
Kaiser Permanente Georgia
Kaiser Permanente Northern California
Kaiser Permanente Southern California
The Veterans Health Administration
Investigators:
Michael Goodman
Ashli Owen-Smith
Dennis Tolsma
Enid Hunkeler
Virginia Quinn
Douglas Roblin
Theresa Gillespie
Major Goals:
The goal of this study is to understand the short- and long-term health issues among transgender persons who had or are planning to have a sex change treatment.
Description of study sample:
6,500 transgender individuals, whose care is covered by the Veterans Administration (nationally) or by Kaiser Permanente (in Georgia and in Northern and Southern California).
Current Status:  
Project completed
Study Registration:
HSRP20143115
Publications:
Collin L, Reisner SL, Tangpricha V, Goodman M. Prevalence of Transgender Depends on the “Case” Definition: A Systematic Review. J Sex Med. 2016 Apr;13(4):613-26. doi: 10.1016/j.jsxm.2016.02.001. Epub 2016 Mar 25.Holz LE, Goodman M. Epidemiology of advanced prostate cancer: overview of known and less explored disparities in prostate cancer prognosis. Curr Probl Cancer. 2015 Jan-Feb;39(1):11-6. doi: 10.1016/j.currproblcancer.2014.11.003. Epub 2014 Nov 26.Reisner SL, Deutsch MB, Bhasin S, Bockting W, Brown GR, Feldman J, Garofalo R, Kreukels B, Radix A, Safer JD, Tangpricha V, T?Sjoen G, Goodman M. Advancing methods for US transgender health research. Curr Opin Endocrinol Diabetes Obes. 2016 Apr;23(2):198-207. doi: 10.1097/MED.0000000000000229.Roblin D, Barzilay J, Tolsma D, Robinson B, Schild L, Cromwell L, Braun H, Nash R, Gerth J, Hunkeler E, Quinn VP, Tangpricha V, Goodman M.  A novel method for estimating transgender status using electronic medical recordsAnn Epidemiol. 2016 Mar;26(3):198-203. doi: 10.1016/j.annepidem.2016.01.004. Epub 2016 Feb 4.Goodman M, Adams N, Corneil T, Kreukels B, Motmans J, Coleman E. Size and distribution of transgender and gender non-conforming populations: A narrative review. Endocrinology and Metabolism Clinics of North America 2019 8(2):303-321Gerth J, Becerra-Culqui T, Bradlyn A, Getahun D, Hunkeler E, Lash T, Millman A, Nash R, Quinn V, Robinson B, Roblin D, Silverberg M, Tangpricha V, Vupputuri S, Goodman M. Agreement between medical records and self-reports: Implications for transgender health research.  Reviews in Endocrine and Metabolic Disorders 2018 19(3):263-269Getahun D, Nash R, Flanders D, Baird T, Becerra-Culqui T, Cromwell L, Hunkeler E, Lash T, Millman A, Quinn V, Robinson B, Roblin D, Silverberg M, Safer J, Slovis J, Tangpricha V, Goodman M. Cross-sex hormones and acute cardiovascular events in transgender persons:  A cohort study.  Annals of Internal Medicine 2018 169(4):205-213Nash R, Ward K, Jemal A, Sandberg D, Tangpricha V, Goodman M. Frequency and distribution of cancers among gender minority patients: an analysis of U.S. national surveillance data.  Cancer Epidemiology 2018 54(6):1-6Becerra-Culqui T, Liu Y, Nash R, Cromwell L, Flanders W, Getahun D, Giammattei S, Hunkeler E, Lash T, Millman A, Quinn V, Robinson B, Roblin D, Sandberg D, Silverberg M, Tangpricha V, Goodman M.  Mental health of transgender and gender non-conforming youth compared with their peers.  Pediatrics 2018 141(5): e20173845Owen-Smith A, Gerth J, Sineath C, Barzilay J, Becerra-Culqui T, Getahun D, Giammattei S, Hunkeler E, Lash T, Millman A, Nash R, Quinn V, Robinson B, Roblin D, Sanchez T, Silverberg M, Tangpricha V, Valentine C, Winter S, Woodyatt C, Goodman M.  Association between gender confirmation treatments and perceived gender congruence, body satisfaction and mental health in a cohort of transgender individuals.  Journal of Sexual Medicine 2018 15(4):591-600Quinn V, Nash R, Hunkeler E, Contreras R, Cromwell L, Becerra-Culqui T, Getahun D, Giammattei S, Lash T, Millman A, Robinson B, Roblin D, Silverberg M, Slovis J, Tangpricha V, Tolsma D, Valentine C, Ward K, Winter S, Goodman M.  Cohort profile:  study of transition, outcomes & gender (STRONG) to assess health status of transgender people.  BMJ Open 2017 7(12):e018121Silverberg M, Nash R, Becerra-Culqui T, Cromwell L, Getahun D, Hunkeler E, Lash T, Millman A, Quinn V, Robinson B, Roblin D, Slovis J, Tangpricha V, Goodman M. Cohort study of cancer risk among insured transgender people. Annals of Epidemiology 2017 27(8):499-501Braun H, Nash R, Tangpricha V, Brockman J, Ward K, Goodman M. Cancer in transgender people: Evidence and methodological considerations. Epidemiologic Reviews 2017 39(1):93-107Owen-Smith A, Sineath C, Sanchez T, Dea R, Giammattei S, Gillespie T, Helms M, Hunkeler E, Quinn V, Roblin D, Slovis J, Stephenson R, Sullivan P, Tangpricha V, Woodyatt C, Goodman M. Perception of community tolerance and prevalence of depression among transgender persons  Journal of Gay & Lesbian Mental Health 2017 21(1) 64-76Owen-Smith A, Woodyatt C, Sineath C, Hunkeler E, Barnwell L, Graham A, Goodman M. Perceptions of barriers to and facilitators of participation in health research among transgender people  Transgender Health 2016 1(1): 187-196.Sineath C, Woodyatt C, Sanchez Y, Giammattei S, Gillespie T, Hunkeler E, Owen-Smith A, Quinn V, Roblin D, Stephenson R, Sullivan P, Tangpricha V, Goodman M.  Determinants of and barriers to hormonal and surgical treatment receipt among transgender people.  Transgender Health 2016 1(1):129-136
Resources:
N/A
Lessons Learned:
To date-the study supported 15 publications.  Many additional analyses are on-going
What’s next?
We seeking additional funding to expand the cohort and extend follow up through 2025.

Diversity Supplement – Understanding factors that lead to disparities in depression treatment

Project Name:
Diversity Supplement – Understanding factors that lead to disparities in depression treatment
Principal Investigator:
Karen J Coleman, PhD
Principal Investigator Contact Information:
Karen.J.Coleman@kp.org
Principal Investigator institution:
Kaiser Permanente Southern California
Funder
NIMH
Funding Period:  
09/2014 – 06/2016 (no-cost extension through 06/2017)
Abstract:
Depression and other mental illnesses lead to more disability than the most prevalent physical chronic illnesses such as heart disease, diabetes, and cancer, and may cost the U.S. healthcare system as much as 300 billion dollars annually. There are clear racial and ethnic differences in depression treatment, however, it is unknown if these are patient, provider, or healthcare system driven. The diversity supplement was designed to build on previous work funded within the Mental Health Research Network (MHRN) on practice variation in the treatment of depression. The original aims of the diversity supplement were as follows: Aim 1: To understand the healthcare system-, provider-, and patient-level factors that predict taking the initial antidepressant medication prescribed and/or attendance at the initial psychotherapy visit (primary adherence) within 30 days of an initial depression diagnosis.
Aim 2: To identify the healthcare system-, provider-, and patient-level factors that predict continuation of depression-related treatment once started (secondary adherence).
AIM 3: To characterize racial/ethnic disparities in the achievement of depression improvement or remission with treatment as assessed with the patient health questionnaire (PHQ9), and to understand the role of adherence in this response to treatment.
Grant Number:  
U19MH092201 (Supplement under MHRN II)
Participating Sites Contributing Data:
Kaiser Permanente Southern California, Pasadena, CA
Group Health Cooperative, Seattle, Washington
HealthPartners Institute, Minneapolis, Minnesota
Kaiser Permanente Colorado, Denver, Colorado
Kaiser Permanente Hawaii, Honolulu, Hawaii
Henry Ford Healthcare Systems, Detroit, Michigan
Additional Sites Participating in the Study:
Baylor Scott & White, Temple, Texas
University of Utah, Salt Lake City, Utah
Investigators:
Karen J. Coleman, PhD
Gregory Simon, MD MPH
Rebecca Rossom, MD
Arne Beck, PhD
Beth Waitzfelder, PhD
John Zieber, PhD
Brian Ahmedani, PhD
Zach Imel, PhD
Major Goals: To provide a high-level understanding of how race/ethnicity contributes independently to the variation for initiation and continuation of depression treatment. To provide a dataset and documentation associated with this dataset and its analyses that can be used by other researchers interested in the treatment of depression in large healthcare systems. To provide a basis for testing culturally tailored or appropriate interventions that improve the adherence to depression treatment in a variety of patient populations.
Major Limitations: Questions about depression treatment outcomes cannot be addressed with this dataset because PHQ9 data collection in the five healthcare systems during the study period was not widespread. Questions about healthcare system variation in policies and guidelines for depression treatment cannot be addressed with this dataset as these variables were not available for study. Questions about provider-level variation in the treatment of depression can only be addressed for two sites in the study due to the lack of data collected for providers in the other sites. Thus, conclusions about provider-level variation and its contribution to depression treatment modalities and adherence cannot generalize to other healthcare settings.
Description of study sample:
There are two study samples included in this study. One is for initiation of treatment for patients newly diagnosed with depression and one is for adherence to a new episode of antidepressant medication and/or formal psychotherapy treatment in patients diagnosed with depression. Treatment in the Newly Diagnosed Patients 18 and older who had a new depression diagnosis in primary care clinics between 1/1/2009 and 12/31/2013 were included. Patients were excluded if they had a diagnosis of bipolar disorder, schizophrenia spectrum disorder, or other psychosis in the prior two years to the diagnosis date. To ensure the availability of data needed to create the patient sample for all analyses, the sample was limited to those who were continuously enrolled in the healthcare systems for at least 360 days prior to the diagnosis date, allowing a 60-day gap. New episodes of depression were defined as an ICD-9 code for depression made in a primary care setting, with no diagnosis or treatment for depression (either psychotherapy or antidepressant medication) during the 360 days prior to the diagnosis. These patients were followed for 90 days after the diagnosis date to look for the initiation of treatment (see definitions below for treatment). Patients who disenrolled from the healthcare systems in less than 90 days after diagnosis were excluded. Adherence in the Newly Treated
Patients 18 and older who had a new episode of formal psychotherapy treatment (PT) between 1/1/2010 and 12/31/2013 or a new antidepressant treatment (AD) between 1/1/2010 and 12/31/2013 were included. Patients were excluded if they had a diagnosis of bipolar disorder, schizophrenia spectrum disorder, or other psychosis in the prior two years to index date. The sample was also limited to those who were continuously enrolled in the healthcare systems for at least 270 days prior to the index AD/PT episode, allowing a 60-day gap. A new episode of AD/PT treatment was defined as not having any evidence of the same type of treatment (AD or PT) during the previous 270 days before the date of the new episode.  AD episodes with a prescription for trazodone were excluded because this drug is primarily prescribed for sleep disturbance and not depression. We did not consider appointments that were less than 30 minutes and/or clearly designated as only medication management to be formal psychotherapy.
Current Status:
The analytic dataset and its documentation have been compiled.  Further analyses funded by the project are limited to the following manuscripts which are currently in process: The Mental Health Provider as a Source of Racial and Ethnic Disparities in Adherence to Antidepressant Medication and Psychotherapy (Imel et al.)
Study Registration:
N/A
Publications: Coleman KJ, Stewart C, Waitzfelder BE, Zeber JE, Morales LS, Ahmed AT, Ahmedani BK, Beck A, Copeland LA, Cummings JR, Hunkeler EM, Lindberg NM, Lynch F, Lu CY, Owen-Smith AA, Trinacty CM, Whitebird RR, Simon GE. Racial-Ethnic Differences in Psychiatric Diagnoses and Treatment Across 11 Health Care Systems in the Mental Health Research Network. Psychiatr Serv. 2016 Jul 1;67(7):749-57. doi: 10.1176/appi.ps.201500217. Epub 2016 Apr 15.Rossom RC, Shortreed S, Coleman KJ, Beck A, Waitzfelder BE, Stewart C, Ahmedani BK, Zeber JE, Simon GE. Antidepressant adherence across diverse populations and healthcare settings. Depress Anxiety. 2016 Aug;33(8):765-74. doi: 10.1002/da.22532. Epub 2016 Jun 20.Simon GE, Coleman KJ, Waitzfelder BE, Beck A, Rossom RC, Stewart C, Penfold RB. Adjusting Antidepressant Quality Measures for Race and Ethnicity. JAMA Psychiatry. 2015 Oct;72(10):1055-6. doi: 10.1001/jamapsychiatry.2015.1437.Simon GE, Rossom RC, Beck A, Waitzfelder BE, Coleman KJ, Stewart C, Operskalski B, Penfold RB, Shortreed SM. Antidepressants are not overprescribed for mild depression. J Clin Psychiatry. 2015 Dec;76(12):1627-32. doi: 10.4088/JCP.14m09162.Zeber JE, Coleman KJ, Fischer H, Yoon TK, Ahmedani BK, Beck A, Hubley S, Imel ZE, Rossom RC, Shortreed SM, Stewart C, Waitzfelder BE, Simon GE. The impact of race and ethnicity on rates of return to psychotherapy for depression. Depress Anxiety. 2017 Dec;34(12):1157-1163. doi: 10.1002/da.22696. Epub 2017 Nov 2. PubMed PMID: 29095538; PubMed Central PMCID: PMC5718939.Waitzfelder B, Stewart C, Coleman KJ, Rossom R, Ahmedani BK, Beck A, Zeber JE, Daida YG, Trinacty C, Hubley S, Simon GE. Treatment Initiation for New Episodes of Depression in Primary Care Settings. J Gen Intern Med. 2018 Aug;33(8):1283-1291. doi: 10.1007/s11606-017-4297-2. Epub 2018 Feb 8. PubMed PMID: 29423624.
Resources:
A data dictionary and descriptive tables for the data file associated with this project will be available soon. Some research questions cannot be addressed by this dataset and require an initial review and possible discussion to make this determination. For immediate questions, contact Greg Simon at simon.g@ghc.org.
Lessons Learned:
For all systems contributing data to this project, electronic medical records, insurance claims, and other data systems were organized in a Virtual Data Warehouse (VDW) to facilitate population-based research. The VDW is a collection of common data definitions and formats to ensure equivalent de-identified data for analysis. Because the VDW relies on data availability from a diverse set of healthcare settings in the Health Care Systems Research Network customizing data abstraction such as healthcare system policy variables or provider-level descriptive information is difficult and in some cases impossible. This needs to be considered when studies are proposed that examine the interplay of healthcare system-, provider-, and patient-level factors in mental health-related treatment choices and outcomes.
What’s next?
Possible harvest of new PHQ9 data as implementation of screening and treatment follow-up have increased exponentially since 2013. Pursue an R01 to characterize heterogeneity of achievement of depression improvement or remission and incorporate more healthcare sites (only 6 of 13 MHRN sites were included) and use additional provider variation analytic methods. Other possible grant ideas that have been discussed: Culturally-tailored intervention to assist with the decisions around depression treatment (shared decision-making and motivational interviewing models)