| 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) |
Tag: Health equity and diversity
Practice Variation in High- and Low-value Care for Mood Disorders
| Project Name: Practice Variation in High- and Low-Value Care for Mood Disorders |
| Principal Investigator: Gregory Simon MD MPH |
| Principal Investigator Contact Information: simon.g@ghc.org |
| Principal Investigator institution: Group Health Research Institute |
| Funder NIMH |
| Funding Period: 09/2010 – 06/2015 |
| Abstract: This multi-site observational study examined patient, provider, and health system influences on process of depression care in primary care and mental health specialty settings. Comprehensive records data from five MHRN sites (Group Health Cooperative, HealthPartners, Kaiser Permanente Colorado, Kaiser Permanente Hawaii, and Kaiser Permanente Southern California) were used to identify three patient cohorts: Primary care patients receiving a new diagnosis of depression with no recent history of depression treatment. Primary care and mental health specialty patients initiating a new episode of antidepressant treatment with a diagnosis of depression. Mental health specialty patients initiating a new episode of psychotherapy with a diagnosis of depression |
| Grant Number: U19 MH092201 (Mental Health Research Network Cooperative Agreement) |
| Participating Sites: Group Health Cooperative HealthPartners Institute Kaiser Permanente Colorado Kaiser Permanente Hawaii Kaiser Permanente Southern California |
| Investigators: Gregory Simon MD MPH Robert Penfold PhD Susan Shortreed, PhD Rebecca Rossom MD Arne Beck PhD Beth Waitzfelder PhD Karen Coleman PhD |
| Major Goals: To examine patient and provider contributions to variation in care (medication and psychotherapy) for depression. |
| Description of study sample: The sample includes new diagnoses and new treatment episodes between 1/1/2010 and 12/31/2012. These data are being used to address the following specific questions: Among primary care patients receiving a new diagnosis of depression, how do specific patient characteristics (age, sex, race/ethnicity, severity of depression) influence both the likelihood of initiating any treatment for depression and the choice between treatments (medication or psychotherapy)Among patients initiating medication treatment for depression, how are medication selection, early medication adherence, and acute-phase treatment response related to specific patient characteristics (age, sex, race/ethnicity, severity of depression)? How do these treatment processes vary among providers? Among patients initiating psychotherapy for depression, how are early treatment adherence and acute-phase treatment response related to specific patient characteristics (age, sex, race/ethnicity, severity of depression)? How do these treatment processes vary among providers? |
| Current Status: All analyses are complete. |
| Study Registration: N/A |
| Publications: 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. No abstract available. PMID:26352783Simon GE, Rossom RC, Beck A, Waitzfelder BE, Coleman KJ, Stewart C, Operskalski B, Penfold RB, Shortreed SM.J. Antidepressants are not overprescribed for mild depression. Clin Psychiatry. 2015 Dec;76(12):1627-32. doi: 10.4088/JCP.14m09162.PMID:26580702Simon GE, Johnson E, Stewart C, Rossom RC, Beck A, Coleman KJ, Waitzfelder B, Penfold R, Operskalski BH, Shortreed SM. Does patient adherence to antidepressant medication actually vary between physicians? J Clin Psychiatry. 2017 Oct 24 (epub ahead of print) |
| Resources: None |
| Lessons Learned: In MHRN health systems, we see little evidence for over-prescribing of antidepressants for mild depression. Likelihood of prematurely discontinuing antidepressant medication is much higher in minority racial and ethnic groups than in non-Hispanic Whites, and these racial and ethnic differences are far larger than differences related to other demographic or clinical characteristics. Likelihood of prematurely discontinuing psychotherapy for depression is modestly higher in minority racial and ethnic groups – but racial/ethnic disparities in psychotherapy adherence are smaller than disparities in antidepressant medication adherence. Among primary care patients receiving a new diagnosis of depression, likelihood of initiating any specific treatment (medication or psychotherapy) is lower among minority racial or ethnic groups. Patients from minority racial and ethnic groups are more likely to start psychotherapy than medication. Failure to adjust antidepressant treatment quality measures for race and ethnicity will significantly disadvantage health systems serving members from traditionally under-served racial and ethnic groups. After accounting for random variation, likelihood of prematurely discontinuing antidepressant medication varies only minimally across physicians. |
| What’s next? A follow-up study (funded during the second cycle of MHRN funding) will further explore racial and ethnic disparities in care identified in this project. |
Precursors of first-episode psychosis in a population-based sample
| Project Name: Precursors of first-episode psychosis in a population-based sample |
| Principal Investigator: Gregory Simon, MD MPH |
| Principal Investigator Contact Information: simon.g@ghc.org |
| Principal Investigator institution: Kaiser Permanente Washington |
| Funding Period: 07/2013 – 06/2018 |
| Abstract: Schizophrenia is estimated to be the 8th-ranked cause of life years lost to disability and premature death among people aged 15 to 44. Reducing this disease burden is a public health priority. Among people experiencing first onset of psychotic symptoms, delay in receipt of effective treatment contributes significantly to poor long-term outcomes. Furthermore, warning signs or prodromal symptoms may be identifiable prior to onset of actual psychotic symptoms. Accumulating evidence suggests that preventive interventions (prior to onset of actual psychotic symptoms) or early clinical interventions (to reduce the interval between onset of symptoms and receipt of effective care) can both improve long-term prognosis. Existing models for early detection and early intervention – either for research or care delivery – have limited reach and scalability. Our preliminary studies suggest that a generalizable algorithm retrospectively applied to electronic medical records data can accurately identify first episodes of psychosis with a positive predictive value of 80 to 90% and a sensitivity of over 80% – when compared to structured chart review. If electronic records in large health systems could be used to efficiently identify large and representative samples of people experiencing first-episode psychosis, this method could dramatically accelerate research and transform care delivery. We propose a population-based research program to address immediate questions regarding early intervention programs and to develop methods to support the next generation of early intervention research. This research will draw from five large health systems serving a diverse and representative population of over 7.5 million people. Specific aims of this program include: Use electronic records data from large integrated health care systems to validate and refine a generalizable algorithm for identifying first presentations of psychosis. Examine patterns of health care contact prior to first diagnosis of psychosis to identify the optimal care settings and target populations for early detection programs and preventive interventions. Examine patterns of treatment following first diagnosis of psychosis in order to identify the gaps in care leading to prolonged duration of untreated psychosis. Examine sources of health insurance coverage at first diagnosis of psychotic disorder and subsequent lapses in coverage in order to inform the design of future intervention programs. Explore the use of text mining methods to identify potential indicators of prodromal symptoms in notes of outpatient visits prior to first diagnosis of psychosis in order to develop innovative strategies for accurate real-time identification of prodromal symptoms. Understand patient, family, and clinician perspectives regarding population-based research outreach following a new diagnosis of psychosis to inform future research and care delivery. Examine rate and causes of mortality after first diagnosis of psychotic disorder |
| Grant Number: 5R01MH099666 |
| Funder: NIMH |
| Participating Sites: Group Health Cooperative Kaiser Permanente Colorado Kaiser Permanente Northern California Kaiser Permanente Northwest Kaiser Permanente Southern California |
| Investigators: Gregory Simon, MD MPH David Carrell, PhD Frances Lynch, PhD Bobbi Jo Yarborough, PhD Carla Green, PhD Arne Beck, PhD Enid Hunkeler, MA Stacy Sterling, PhD Karen Coleman, PhD |
| Major Goals: Goals include Aim 1: Describe initial presentation with psychotic symptoms in a population-based sample. Aim 2: Examine patterns of care prior to diagnosis. Aim 3: Examine treatment adherence/continuity after diagnosis. Aim 4: Examine impact of health insurance coverage. Aim 5: Mine clinical text to identify possible prodromal “signals”. Aim 6: Explore acceptability of outreach interventions. Aim 7: Examine mortality after first diagnosis of psychotic disorder |
| Description of study sample: Cases: First diagnosis of schizophrenia spectrum psychosis, mood disorder with psychosis or other psychotic disorder between 1/1/2007 and 12/31/2012. Continuously enrolled in the health plan for >=12 months prior to the initial diagnosis. Age 15 and above. Controls: No prior record of psychosis or mood disorder. Continuously enrolled in the health plan for >=24 months. Age 15 and above. Meet one of these criteria for one of three control groups. First diagnosis of depression (matched to cases by age, sex, and year)First diagnosis of inflammatory bowel disease (matched to cases by age, sex, and year)Any outpatient visit (matched to cases by age, sex, and year). |
| Current Status: Analyses for all aims are complete |
| Study Registration: N/A |
| Publications: Simon GE, Coleman KJ, Yarborough BJ, Operskalski B, Stewart C, Hunkeler EM, Lynch F, Carrell D, Beck A. First presentation with psychotic symptoms in a population-based sample. Psychiatr Serv. 2017; 68: 457-461.Simon GE, Stewart C, Yarborough BJ, Lynch F, Coleman KJ, Beck A, Operskalski BH, Penfold RS, Hunkeler EM. Mortality after first diagnosis of psychotic disorder in adolescents and young adults. JAMA Psychiatry 2018; 75: 254-260.Simon GE, Stewart C, Hunkeler EM, Yarborough BJ, Lynch F, Coleman KJ, Beck A, Operskalski BH, Penfold RS, Carrell DS. Care pathways prior to first diagnosis of psychotic disorder in adolescents and young adults. Am J Psychiatry 2018 (Jan 24 epub ahead of print). |
| Resources: None available yet |
| Lessons Learned: DetectionIncidence rate suggests reasonable capture of all new casesHalf have some prior mental health contact. Patterns of utilization prior to first diagnosis differ by race/ethnicityInitiation>90% without patient specialty MH follow-up within 1 month>60% with filled prescription for antipsychotic medication within 1 month. Engagement/ContinuationOnly 50% still engaged in outpatient specialty MH care by 1 yea. rOf those who disengage: outcome is poor in 1/3 and unknown in 1/3 MortalityMortality is markedly increased soon after first diagnosis of psychotic disorderExcess mortality is largely due to injuries and poisonings, especially self-inflicted injuries and poisonings |
| What’s next? Submit manuscripts for Aims 3 to 7 |
Treatment Utilization Before Suicide
| Project Name: Treatment Utilization Before Suicide |
| Principal Investigator: Brian Ahmedani, PhD |
| Principal Investigator Contact Information: BAHMEDA1@HFHS.ORG |
| Principal Investigator institution: Henry Ford Health System Research Centers |
| Funder: NIMH |
| Funding Period: 03/2015 – 02/2020 |
| Adult suicide rates in the United States rose by almost 30 percent between 1999 and 2010. These rates have not markedly improved in decades. To date, previous suicide attempts and psychiatric diagnoses are largely the only known clinical risk factors for suicide death. Recent research shows that most individuals who die by suicide make a health care visit in the weeks and months prior to their death. Most of these visits occur in primary care or outpatient medical specialty settings. However, over half of these visits do not include a psychiatric diagnosis. Thus, there is limited evidence available from health care users in the US general population to inform targeted suicide screening and risk identification efforts in general medical settings. New research is needed to investigate the general medical clinical factors associated with suicide risk among individuals without a known risk factor. This research project uses data on more than 4000 individuals who died by suicide and made health care visits to one of eight health care systems across the United States in the year prior to their death. These health systems are members of the Mental Health Research Network and have affiliated health plans. They are able to capture nearly all health care for their patients via the Virtual Data Warehouse (VDW). The VDW consists of electronic medical record and insurance claims data organized using standardized data structures and definitions across sites. These data are matched with official regional mortality data. This project includes the following Specific Aims: 1) Identify the types and timing of clinical factors prior to suicide, 2a) Compare clinical factors before suicide to a matched sample of health care users, 2b) Detect associations between additional clinical factors and suicide, and 3) Develop a prediction model of clinical factors prior to suicide. We employ a case-control study approach to test specific hypotheses, while also using novel environment-wide association study methods and latent class analysis to detect new risk factors. We develop a prediction model of clinical factors and suicide. Clinical factors to be studied include medical diagnoses, medications, health care procedures, and types of health care visits. These results will inform decisions about how to focus suicide prevention in medical settings and provide information in response to the 2012 National Action Alliance for Suicide Prevention and US Surgeon General report. |
| Grant Number: R01MH103539 |
| Participating Sites: Henry Ford Health System Harvard Pilgrim Healthcare HealthPartners Kaiser Permanente Hawaii Kaiser Permanente Northwest Kaiser Permanente Colorado Kaiser Permanente Georgia Kaiser Permanente Washington |
| Investigators: Brian K. Ahmedani, PhD Gregory E. Simon, MD, MPH Rebecca Rossom, MD, MSCR Arne Beck, PhD Frances Lynch, PhD Beth Waitzfelder, PhD Christine Lu, PhD Ashli Owen-Smith, PhD Deepak Prabhakar, MD, MPH L. Keoki Williams, MD, MPH Edward Peterson, PhD Cathrine Frank, MD |
| Major Goals: The main goal of this project is to investigate general medical and other healthcare factors and risk of suicide to develop a comprehensive healthcare algorithm to predict suicide, with particular focus on general medical settings. |
| Description of study sample: This large case-control study includes >3,000 individuals who died by suicide between 2000-2015 and >300,000 matched general population members of 8 large health systems across the United States. |
| Current Status: June 26, 2019: Aims 1-2 have been completed. The work in Aim 3 is currently underway, including developing a series of predictive models for the full sample and a series of subgroups.. We will complete data analysis and draft the manuscript in Winter 2019-2020. |
| Study Registration: N/A |
| Publications:Ahmedani BK, Simon GE, Stewart C, Beck A, Waitzfelder BE, Rossom R, Lynch F, Owen-Smith A, Hunkeler EM, Whiteside U, Operskalski BH, Coffey MJ, Solberg LI. Health care contacts in the year before suicide death. J Gen Intern Med. 2014 Jun;29(6):870-7. doi: 10.1007/s11606-014-2767-3. PMID: 24567199Ahmedani BK, Stewart C, Simon GE, Lynch F, Lu CY, Waitzfelder BE, Solberg LI, Owen-Smith AA, Beck A, Copeland LA, Hunkeler EM, Rossom RC, Williams K. Racial/Ethnic differences in health care visits made before suicide attempt across the United States. Med Care. 2015 May;53(5):430-5. doi: 10.1097/MLR.0000000000000335. PMID: 25872151.Ahmedani BK, Peterson EL, Hu Y, Rossom RC, Lynch F, Lu CY, Waitzfelder BE, Owen-Smith AA, Hubley S, Prabhakar D, Williams LK, Zeld N, Mutter E, Beck A, Tolsma D, Simon GE. Major Physical Health Conditions and Risk of Suicide. Am J Prev Med. 2017 Sep;53(3):308-315. doi: 10.1016/j.amepre.2017.04.001. PMID: 28619532.Boggs JM, Simon GE, Ahmedani BK, Peterson E, Hubley S, Beck A. The Association of Firearm Suicide With Mental Illness, Substance Use Conditions, and Previous Suicide Attempts. Ann Intern Med. 2017 Aug 15;167(4):287-288. doi: 10.7326/L17-0111. PMID: 28672343.Prabhakar D, Peterson EL, Hu Y, Rossom RC, Lynch FL, Lu CY, Waitzfelder BE, Owen-Smith AA, Williams LK, Beck A, Simon GE, Ahmedani BK. Dermatologic Conditions and Risk of Suicide: A Case-Control Study. Psychosomatics. 2018; 59(1): 58-61. doi: 10.1016/j.psym.2017.08.001. PMID: 28890116.Boggs JM, Beck A, Hubley S, Peterson EL, Hu Y, Williams LK, Prabhakar D, Rossom RC, Lynch FL, Lu CY, Waitzfelder BE, Owen-Smith AA, Simon GE, Ahmedani BK.General Medical, Mental Health, and Demographic Risk Factors Associated With Suicide by Firearm Compared With Other Means. Psychiatric Services. 2018; 69(6):677-684. doi: 10.1176/appi.ps.201700237. PMID: 29446332.Owen-Smith AA, Ahmedani BK, Peterson E, Simon GE, Rossom RC, Lynch FL, Lu CY, Waitzfelder BE, Beck A, DeBar LL, Sanon V, Maaz Y, Khan S, Miller-Matero LR, Prabhakar D, Frank C, Drake CL, Braciszewski JM. The Mediating Effect of Sleep Disturbance on the Relationship Between Nonmalignant Chronic Pain and Suicide Death. Pain Pract. 2019 Apr;19(4):382-389. doi: 10.1111/papr.12750. Epub 2019 Jan 18. PMID: 30462885Yeh HH, Westphal J, Hu Y, Peterson EL, Williams LK, Prabhakar D, Frank C, Autio K, Elsiss F, Simon GE, Beck A, Lynch FL, Rossom RC, Lu CY, Owen-Smith AA, Waitzfelder BE, Ahmedani BK. Diagnosed Mental Health Conditions and Risk of Suicide Mortality. Psychiatr Serv. 2019 Jun 12:appips201800346. doi: 10.1176/appi.ps.201800346. [Epub ahead of print]. PMID: 31185853 |
| Resources: None |
| Lessons Learned: Most individuals make healthcare visits before suicide. Most visits occur in primary care or general medical specialty settings. Approximately half of individuals do not have a mental health condition diagnosed during their health care visits before suicide. Among 19 physical health conditions under study, 17 were associated with increased risk for suicide after adjustment for age and sex, and 9 associations persisted after additional adjustment for mental health and substance use conditions. |
| What’s next? The final predictive modeling analyses are underway for the final study aim. A series of papers are currently under review or in development based on data from Aims 1-2. |