Importance of variables from different time frames for predicting self-harm using health system data.

Objective: Self-harm risk prediction models developed using health system data (electronic health records and insurance claims information) often use patient information from up to several years prior to the index visit when the prediction is made. Measurements from some time periods may not be available for all patients. Using the framework of algorithm-agnostic variable importance, we study the predictive potential of variables corresponding to different time horizons prior to the index visit and demonstrate the application of variable importance techniques in the biomedical informatics setting. Materials and Methods: We use variable importance to quantify the potential of recent (up to three months before the index visit) and distant (more than one year before the index visit) patient mental health information for predicting self-harm risk using data from seven health systems. We quantify importance as the decrease in predictiveness when the variable set of interest is excluded from the prediction task. We define predictiveness using discriminative metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and positive predictive value. Results: Mental health predictors corresponding to the three months prior to the index visit show strong signal of importance; in one setting, excluding these variables decreased AUC from 0.85 to 0.77. Predictors corresponding to more distant information were less important. Discussion: Predictors from the months immediately preceding the index visit are highly important. Implementation of self-harm prediction models may be challenging in settings where recent data are not completely available (e.g., due to lags in insurance claims processing) at the time a prediction is made. Conclusion: Clinically derived variables from different time frames exhibit varying levels of importance for predicting self-harm. Variable importance analyses can inform whether and how to implement risk prediction models into clinical practice given real-world data limitations. These analyses be applied more broadly in biomedical informatics research to provide insight into general clinical risk prediction tasks.

Influenza and COVID-19 Vaccine Uptake Among Individuals With Versus Without Diagnosed Psychiatric Disorders.

OBJECTIVE: The authors sought to examine influenza and COVID-19 vaccine uptake among individuals diagnosed as having psychiatric disorders compared with those without such diagnoses and to examine variations in vaccine uptake by sociodemographic and clinical characteristics. METHODS: The study was conducted in the Kaiser Permanente Georgia, Washington, and Southern California health care systems. Individuals with psychiatric conditions had at least one diagnosis of any psychiatric disorder during a 12-month study period; individuals in the control group had no psychiatric disorder diagnoses during this period, and the two groups were matched on age and sex. Bivariate analyses were conducted with Pearson chi-square tests; multivariate analyses were used to calculate the odds of receiving an influenza vaccine (N=1,307,202 individuals) or COVID-19 vaccine (N=1,380,894 individuals) and were controlled for selected covariates. RESULTS: After controlling for relevant confounders, the authors found that having a diagnosis of any psychiatric illness was associated with significantly increased odds of receiving an influenza vaccine (OR=1.18; 95% CI=1.17-1.19, p<0.001), compared with no diagnosis of a psychiatric disorder. Having any psychiatric illness was associated with decreased odds of receiving a COVID-19 vaccine (OR=0.97; 95% CI=0.96-0.98, p<0.001), after the analysis was controlled for the same covariates. CONCLUSIONS: The findings provide evidence that people with mental health conditions were more likely to receive an influenza vaccine but were less likely to receive a COVID-19 vaccine, compared with individuals without such conditions. However, the vaccination rates observed for individuals with and without diagnosed psychiatric conditions were below national benchmarks, suggesting room for improving vaccine uptake in both patient populations.

Development and Validation of Electronic Health Record Measures of Safety Planning Practices as Part of Zero Suicide Implementation.

OBJECTIVE: Safety planning for suicide prevention is an important quality metric for Zero Suicide implementation. We describe the development, validation, and application of electronic health record (EHR) programs to measure uptake of safety planning practices across six integrated healthcare systems as part of a Zero Suicide evaluation study. METHODS: Safety planning was documented in narrative notes and structured EHR templates using the Stanley Brown Safety Planning Intervention (SBSPI) in response to a high-risk cutoff score on the Columbia Suicide Severity Rating Scale (CSSRS). Natural Language Processing (NLP) metrics were developed and validated using chart review to characterize practices documented in narrative notes. We applied NLP to measure frequency of documentation in the narrative text and standard programming methods to examine structured SBSPI templates from 2010-2022. RESULTS: Chart reviews found three safety planning practices documented in narrative notes that were delivered to at least half of patients at risk: professional contacts, lethal means counseling for firearms, and lethal means counseling for medication access/storage. NLP methods were developed to identify these practices in clinical text with high levels of accuracy (Sensitivity, Specificity, & PPV ≥ 82%). Among visits with a high-risk CSSRS, 40% (Range 2-73% by health system) had an SBSPI template within 1 year of implementation. CONCLUSIONS: This is one of the first reports describing development of measures that leverage electronic health records to track use of suicide prevention safety plans. There are opportunities to use the methods developed here in future evaluations of safety planning.

Measuring safety planning delivery in real-world systems to understand quality of suicide prevention care is challenging.Natural Language Processing (NLP) methods effectively identified some safety planning practices in electronic health records (EHR) from all notes ensuring a comprehensive measurement, but NLP will require updates/testing for local documentation practices.Structured safety planning templates in the EHR using the Stanley Brown Safety Planning Intervention improve ease and accuracy of measurement but may be less comprehensive than NLP for capturing all instances of safety planning documentation.

Clozapine Use Among People With Psychotic Disorders Who Experience Specific Indications for Clozapine.

Objective: To examine rates of clozapine use among people with psychotic disorders who experience specific indications for clozapine.Methods: Records data from 11 integrated health systems identified patients aged 18 years or older with recorded International Classification of Diseases, Tenth Revision, Clinical Modification, diagnoses of schizophrenia, schizoaffective disorder, or other psychotic disorder who experienced any of the 3 events between January 1, 2019, and December 31, 2019, suggesting indications for clozapine: a diagnosis of self-harm injury or poisoning, suicidal ideation diagnosed or in response to standardized assessments, and hospitalization or emergency department (ED) care for psychotic disorder despite treatment with 2 or more antipsychotic medications. Prescription dispensing data identified all clozapine use prior to or in the 12 months following each indication event. Analyses were conducted with aggregate data from each health system; no individual data were shared.Results: A total of 7,648 patients with psychotic disorder diagnoses experienced at least 1 indication event. Among 1,097 experiencing a self-harm event, 32 (2.9%) had any prior clozapine use, and 10 (0.9%) initiated clozapine during the following 12 months. Among 6,396 with significant suicidal ideation, 238 (3.7%) had any prior clozapine use, and 70 (1.1%) initiated clozapine over 12 months. Among 881 with hospitalization or ED visit despite pharmacotherapy, 77 (8.7%) had any prior clozapine treatment, and 41 (4.7%) initiated clozapine over 12 months. Among those with significant suicidal ideation, rates of both prior clozapine treatment and subsequent initiation varied significantly by race and ethnicity, with rates among Hispanic and non-Hispanic Black patients lower than among non Hispanic White patients.Conclusions: Initiating clozapine treatment is uncommon among people with psychotic disorders who experience events suggesting clozapine is indicated, with even lower rates among Black and Hispanic patients.

Health Expenditures After Bariatric Surgery: A Retrospective Cohort Study.

OBJECTIVE: Bariatric surgery leads to substantial improvements in weight and weight-related conditions, but prior literature on post-surgical health expenditures is equivocal. In a retrospective cohort study, we compared expenditures between surgical and matched non-surgical patients. SUMMARY BACKGROUND DATA AND METHODS: In a retrospective study, total, outpatient, inpatient and medication expenditures 3 years before and 5.5 years after surgery were compared between 22,698 bariatric surgery (n=7,127 RYGB, 15,571 sleeve gastrectomy) patients from 2012-2019 and 66,769 matched non-surgical patients, using generalized estimating equations. We also compared expenditures between patients receiving the two leading surgical procedures in weighted analyses. RESULTS: Surgical and non-surgical cohorts were well matched, 80-81% female, with mean body mass index (BMI) of 44, and mean age of 47 (RYGB) and 44 (SG) years. Estimated total expenditures were similar between surgical and non-surgical groups 3 years before surgery ($27 difference, 95% confidence interval (CI): -42, 102)), increased 6 months prior to surgery for surgical patients, and decreased below pre-period levels for both groups after 3-5.5 years to become similar (difference at 5.5 y=-$61, 95% CI: -166, 52). Long-term outpatient expenditures were similar between groups. Surgical patients' lower long-term medication expenditures ($314 lower at 5.5 y, 95% CI: -419, -208) were offset by a higher risk of hospitalization. Total expenditures were similar between RYGB and SG patients 3.5 to 5.5 years after surgery. CONCLUSIONS: Bariatric surgery translated into lower medication expenditures than matched controls, but not lower overall long-term expenditures. Expenditure trends appear similar for the two leading bariatric operations.

Adolescents Who Do Not Endorse Risk via the Patient Health Questionnaire Before Self-Harm or Suicide.

Importance: Given that the Patient Health Questionnaire (PHQ) item 9 is commonly used to screen for risk of self-harm and suicide, it is important that clinicians recognize circumstances when at-risk adolescents may go undetected. Objective: To understand characteristics of adolescents with a history of depression who do not endorse the PHQ item 9 before a near-term intentional self-harm event or suicide. Design, Setting, and Participants: This was a retrospective cohort study design using electronic health record and claims data from January 2009 through September 2017. Settings included primary care and mental health specialty clinics across 7 integrated US health care systems. Included in the study were adolescents aged 13 to 17 years with history of depression who completed the PHQ item 9 within 30 or 90 days before self-harm or suicide. Study data were analyzed September 2022 to April 2023. Exposures: Demographic, diagnostic, treatment, and health care utilization characteristics. Main Outcome(s) and Measure(s): Responded "not at all" (score = 0) to PHQ item 9 regarding thoughts of death or self-harm within 30 or 90 days before self-harm or suicide. Results: The study included 691 adolescents (mean [SD] age, 15.3 [1.3] years; 541 female [78.3%]) in the 30-day cohort and 1024 adolescents (mean [SD] age, 15.3 [1.3] years; 791 female [77.2%]) in the 90-day cohort. A total of 197 of 691 adolescents (29%) and 330 of 1024 adolescents (32%), respectively, scored 0 before self-harm or suicide on the PHQ item 9 in the 30- and 90-day cohorts. Adolescents seen in primary care (odds ratio [OR], 1.5; 95% CI, 1.0-2.1; P = .03) and older adolescents (OR, 1.2; 95% CI, 1.0-1.3; P = .02) had increased odds of scoring 0 within 90 days of a self-harm event or suicide, and adolescents with a history of inpatient hospitalization and a mental health diagnosis had twice the odds (OR, 2.0; 95% CI, 1.3-3.0; P = .001) of scoring 0 within 30 days. Conversely, adolescents with diagnoses of eating disorders were significantly less likely to score 0 on item 9 (OR, 0.4; 95% CI, 0.2-0.8; P = .007) within 90 days. Conclusions and Relevance: Study results suggest that older age, history of an inpatient mental health encounter, or being screened in primary care were associated with at-risk adolescents being less likely to endorse having thoughts of death and self-harm on the PHQ item 9 before a self-harm event or suicide death. As use of the PHQ becomes more widespread in practice, additional research is needed for understanding reasons why many at-risk adolescents do not endorse thoughts of death and self-harm.

Bariatric Surgery and the Long-Term Risk of Venous Thromboembolism: A Population-Based Cohort Study.

PURPOSE: Bariatric surgery is associated with a greater venous thromboembolism (VTE) risk in the weeks following surgery, but the long-term risk of VTE is incompletely characterized. We evaluated bariatric surgery in relation to long-term VTE risk. MATERIALS AND METHODS: This population-based retrospective matched cohort study within three United States-based integrated health care systems included adults with body mass index (BMI) ≥ 35 kg/m2 who underwent bariatric surgery between January 2005 and September 2015 (n = 30,171), matched to nonsurgical patients on site, age, sex, BMI, diabetes, insulin use, race/ethnicity, comorbidity score, and health care utilization (n = 218,961). Follow-up for incident VTE ended September 2015 (median 9.3, max 10.7 years). RESULTS: Our population included 30,171 bariatric surgery patients and 218,961 controls; we identified 4068 VTE events. At 30 days post-index date, bariatric surgery was associated with a fivefold greater VTE risk (HRadj = 5.01; 95% CI = 4.14, 6.05) and a nearly fourfold greater PE risk (HRadj = 3.93; 95% CI = 2.87, 5.38) than no bariatric surgery. At 1 year post-index date, bariatric surgery was associated with a 48% lower VTE risk and a 70% lower PE risk (HRadj = 0.52; 95% CI = 0.41, 0.66 and HRadj = 0.30; 95% CI = 0.21, 0.44, respectively). At 5 years post-index date, lower VTE risks persisted, with bariatric surgery associated with a 41% lower VTE risk and a 55% lower PE risk (HRadj = 0.59; 95% CI = 0.48, 0.73 and HRadj = 0.45; 95% CI = 0.32, 0.64, respectively). CONCLUSION: Although in the short-term bariatric surgery is associated with a greater VTE risk, in the long-term, it is associated with a substantially lower risk.

Suicide Screening, Risk Assessment, and Lethal Means Counseling During Zero Suicide Implementation.

OBJECTIVE: The authors measured implementation of Zero Suicide (ZS) clinical practices that support identification of suicide risk and risk mitigation, including screening, risk assessment, and lethal means counseling, across mental health specialty and primary care settings. METHODS: Six health care systems in California, Colorado, Michigan, Oregon, and Washington participated. The sample included members ages ≥13 years from 2010 to 2019 (N=7,820,524 patients). The proportions of patients with suicidal ideation screening, suicide risk assessment, and lethal means counseling were estimated. RESULTS: In 2019, patients were screened for suicidal ideation in 27.1% (range 5.0%-85.0%) of mental health visits and 2.5% (range 0.1%-35.0%) of primary care visits among a racially and ethnically diverse sample (44.9% White, 27.2% Hispanic, 13.4% Asian, and 7.7% Black). More patients screened positive for suicidal ideation in the mental health setting (10.2%) than in the primary care setting (3.8%). Of the patients screening positive for suicidal ideation in the mental health setting, 76.8% received a risk assessment, and 82.4% of those identified as being at high risk received lethal means counseling, compared with 43.2% and 82.4%, respectively, in primary care. CONCLUSIONS: Six health systems that implemented ZS showed a high level of variation in the proportions of patients receiving suicide screening and risk assessment and lethal means counseling. Two opportunities emerged for further study to increase frequency of these practices: expanding screening beyond patients with regular health care visits and implementing risk assessment with lethal means counseling in the primary care setting directly after a positive suicidal ideation screening.

Pre-surgical factors related to latent trajectories of 5-year weight loss for a diverse bariatric surgery population.

BACKGROUND: Analyzing trajectories of weight loss may address how particular groups of patients respond to metabolic and bariatric surgery. OBJECTIVES: The Bariatric Experience Long Term (BELONG) study was designed to use a theoretical model to examine determinants of weight loss and recurrence. SETTING: Large integrated health system in Southern California with 11 surgical practices and 23 surgeons. METHODS: A total of n = 1338 patients who had metabolic and bariatric surgery were surveyed before surgery to measure factors related to median percent total weight loss (%TWL) over 5 years. Longitudinal weight data were available for n = 1024 (76.5% of the sample). Data were analyzed using latent growth mixture models (GMM) to estimate trajectories of weight change separately for gastric sleeve and bypass operations. These trajectories were then described using relevant variables from the baseline survey. RESULTS: For both gastric sleeve (n = 733) and bypass (n = 291) operations, 3 latent trajectories of median %TWL were found corresponding to most, moderate, and least %TWL. Sleeve trajectories were distinguished by body mass index at surgery and geocoded environmental factors. Bypass trajectories varied by self-reported and geocoded environmental factors, comorbidity burden, race, experiential avoidance, and weight control strategies. CONCLUSIONS: Future research should examine the role of the built and perceived environment in surgical weight loss. Bariatric practices should focus less on the presurgical period for predictors of long-term weight loss and begin efforts to monitor real-time patient-reported outcomes to help tailor intervention strategies for patients who either do not lose an expected amount of weight or who begin to experience weight recurrence.

Predicting suicide death after emergency department visits with mental health or self-harm diagnoses.

OBJECTIVE: Use health records data to predict suicide death following emergency department visits. METHODS: Electronic health records and insurance claims from seven health systems were used to: identify emergency department visits with mental health or self-harm diagnoses by members aged 11 or older; extract approximately 2500 potential predictors including demographic, historical, and baseline clinical characteristics; and ascertain subsequent deaths by self-harm. Logistic regression with lasso and random forest models predicted self-harm death over 90 days after each visit. RESULTS: Records identified 2,069,170 eligible visits, 899 followed by suicide death within 90 days. The best-fitting logistic regression with lasso model yielded an area under the receiver operating curve of 0.823 (95% CI 0.810-0.836). Visits above the 95th percentile of predicted risk included 34.8% (95% CI 31.1-38.7) of subsequent suicide deaths and had a 0.303% (95% CI 0.261-0.346) suicide death rate over the following 90 days. Model performance was similar across subgroups defined by age, sex, race, and ethnicity. CONCLUSIONS: Machine learning models using coded data from health records have moderate performance in predicting suicide death following emergency department visits for mental health or self-harm diagnosis and could be used to identify patients needing more systematic follow-up.

Short report: Transition to International Classification of Diseases, 10th Revision and the prevalence of autism in a cohort of healthcare systems.

LAY ABSTRACT: Currently, the prevalence of autism spectrum disorder (henceforth "autism") is 1 in 36, an increasing trend from previous estimates. In 2015, the United States adopted a new version (International Classification of Diseases, 10th Revision) of the World Health Organization coding system, a standard for classifying medical conditions. Our goal was to examine how the transition to this new coding system impacted autism diagnoses in 10 healthcare systems. We obtained information from electronic medical records and insurance claims data from July 2014 through December 2016 for each healthcare system. We used member enrollment data for 30 consecutive months to observe changes 15 months before and after adoption of the new coding system. Overall, the rates of autism per 1000 enrolled members was increasing for 0- to 5-year-olds before transition to International Classification of Diseases, 10th Revision and did not substantively change after the new coding was in place. There was variation observed in autism diagnoses before and after transition to International Classification of Diseases, 10th Revision for other age groups. The change to the new coding system did not meaningfully affect autism rates at the participating healthcare systems. The increase observed among 0- to 5-year-olds is likely indicative of an ongoing trend related to increases in screening for autism rather than a shift associated with the new coding.

Stability of Suicide Risk Prediction Models During Changes in Health Care Delivery.

OBJECTIVE: The authors aimed to use health records data to examine how the accuracy of statistical models predicting self-harm or suicide changed between 2015 and 2019, as health systems implemented suicide prevention programs. METHODS: Data from four large health systems were used to identify specialty mental health visits by patients ages ≥11 years, assess 311 potential predictors of self-harm (including demographic characteristics, historical risk factors, and index visit characteristics), and ascertain fatal or nonfatal self-harm events over 90 days after each visit. New prediction models were developed with logistic regression with LASSO (least absolute shrinkage and selection operator) in random samples of visits (65%) from each calendar year and were validated in the remaining portion of the sample (35%). RESULTS: A model developed for visits from 2009 to mid-2015 showed similar classification performance and calibration accuracy in a new sample of about 13.1 million visits from late 2015 to 2019. Area under the receiver operating characteristic curve (AUC) ranged from 0.840 to 0.849 in the new sample, compared with 0.851 in the original sample. New models developed for each year for 2015-2019 had classification performance (AUC range 0.790-0.853), sensitivity, and positive predictive value similar to those of the previously developed model. Models selected similar predictors from 2015 to 2019, except for more frequent selection of depression questionnaire data in later years, when questionnaires were more frequently recorded. CONCLUSIONS: A self-harm prediction model developed with 2009-2015 visit data performed similarly when applied to 2015-2019 visits. New models did not yield superior performance or identify different predictors.

Predicting risk of suicidal behavior from insurance claims data vs. linked data from insurance claims and electronic health records.

PURPOSE: Observational studies assessing effects of medical products on suicidal behavior often rely on health record data to account for pre-existing risk. We assess whether high-dimensional models predicting suicide risk using data derived from insurance claims and electronic health records (EHRs) are superior to models using data from insurance claims alone. METHODS: Data were from seven large health systems identified outpatient mental health visits by patients aged 11 or older between 1/1/2009 and 9/30/2017. Data for the 5 years prior to each visit identified potential predictors of suicidal behavior typically available from insurance claims (e.g., mental health diagnoses, procedure codes, medication dispensings) and additional potential predictors available from EHRs (self-reported race and ethnicity, responses to Patient Health Questionnaire or PHQ-9 depression questionnaires). Nonfatal self-harm events following each visit were identified from insurance claims data and fatal self-harm events were identified by linkage to state mortality records. Random forest models predicting nonfatal or fatal self-harm over 90 days following each visit were developed in a 70% random sample of visits and validated in a held-out sample of 30%. Performance of models using linked claims and EHR data was compared to models using claims data only. RESULTS: Among 15 845 047 encounters by 1 574 612 patients, 99 098 (0.6%) were followed by a self-harm event within 90 days. Overall classification performance did not differ between the best-fitting model using all data (area under the receiver operating curve or AUC = 0.846, 95% CI 0.839-0.854) and the best-fitting model limited to data available from insurance claims (AUC = 0.846, 95% CI 0.838-0.853). Competing models showed similar classification performance across a range of cut-points and similar calibration performance across a range of risk strata. Results were similar when the sample was limited to health systems and time periods where PHQ-9 depression questionnaires were recorded more frequently. CONCLUSION: Investigators using health record data to account for pre-existing risk in observational studies of suicidal behavior need not limit that research to databases including linked EHR data.

Beyond clinical outcomes: Case control study of the role of race in disruptive life events for people with serious mental illness.

OBJECTIVE: To understand how race and serious mental illness (SMI) interact for disruptive life events defined as financial (bankruptcy and judgement filings), and non-financial (arrests). METHODS: Patients were adults with schizophrenia (SCZ; N = 16,159) or bipolar I disorder (BPI; N = 30,008) matched 1:1 to patients without SMI (non-SMI) from health systems in Michigan and Southern California during 1/1/2007 through 12/31/2018. The main exposure was self-reported race, and the outcome was disruptive life events aggregated by Transunion. We hypothesized that Black patients with SCZ or BPI would be the most likely to experience a disruptive life event when compared to Black patients without SMI, and all White or Asian patients regardless of mental illness. RESULTS: Black patients with SCZ had the least likelihood (37% lower) and Asian patients with BPI had the greatest likelihood (2.25 times higher) of experiencing a financial disruptive life event among all patients in the study. There was no interaction of race with either SCZ or BPI for experiencing an arrest. The findings did not support our hypotheses for patients with SCZ and partially supported them for patients with BPI. CONCLUSIONS: Clinical initiatives to assess social determinants of health should consider a focus on Asian patients with BPI.

Racial Differences in Psychiatric Symptoms, Maladaptive Eating, and Lifestyle Behaviors After Bariatric Surgery.

There are several psychological and behavioral factors associated with poorer outcomes following bariatric surgery, yet it is unknown whether and how these factors may differ by race. In this cross-sectional study, individuals who underwent bariatric surgery from 2018 to 2021 and up to 4 years post-surgery were invited to complete an online survey. Psychiatric symptoms, maladaptive eating patterns, self-monitoring behaviors, and exercise frequency were examined. Participants (N = 733) were 87% women, 63% White, with a mean age of 44 years. Analyses of covariance demonstrated that White individuals endorsed greater anxiety symptoms (p =.01) and emotional eating due to depression (p = .01), whereas Black individuals endorsed greater depression severity (p = .02). Logistic regression analyses demonstrated that White individuals were more likely to experience loss of control eating (OR= 1.7, p = .002), grazing (OR= 2.53, p <.001), and regular self-weighing (OR= 1.41, p <.001) than Black individuals, and were less likely to skip meals (OR= .61, p = .04), or partake in nighttime eating (OR= .40, p <.001). There were no racial differences in binge eating, emotional eating due to anxiety or frustration, use of a food diary, or exercise. Thus, depressive symptoms, skipping meals, and nighttime eating may be important, modifiable intervention targets to optimize the benefits of bariatric surgery and promote equitable outcomes.

Suicide attempts after bariatric surgery: comparison to a nonsurgical cohort of individuals with severe obesity.

BACKGROUND: The rate of suicide is higher among individuals following bariatric surgery compared with the general population; however, it is not clear whether risk is associated with bariatric surgery beyond having severe obesity. OBJECTIVE: To compare the risk of a suicide attempt among those who had bariatric surgery versus a nonsurgical cohort with severe obesity. SETTING: Aggregate count data were collected from 5 healthcare systems. METHODS: Individuals were identified in the surgical cohort if they underwent bariatric surgery between 2009 and 2017 (n = 35,522) and then were compared with a cohort of individuals with severe obesity who never had bariatric surgery (n = 691,752). Suicide attempts were identified after study enrollment date using International Classification of Diseases, Ninth and Tenth Editions (ICD-9 and ICD-10) diagnosis codes from 2009 to 2021. RESULTS: The relative risk of a suicide attempt was 64% higher in the cohort with bariatric surgery than that of the nonsurgical cohort (2.2% versus 1.3%; relative risk = 1.64; 95% CI, 1.53-1.76). Within the cohort with bariatric surgery, suicide attempts were more common among the 18- to 39-year age group (P < .001), women (P = .002), Hawaiian-Pacific Islanders (P < .001), those with Medicaid insurance (P < .001), and those with a documented mental health condition at baseline (in the previous 2 years; P < .001). CONCLUSIONS: The relative risk of suicide attempts was higher among those who underwent bariatric surgery compared with a nonsurgical cohort, though absolute risk remained low. Providers should be aware of this increased risk. Screening for suicide risk after bariatric surgery may be useful to identify high-risk individuals.

Suicide-related care among patients who have experienced an opioid-involved overdose.

OBJECTIVE: Our objective was to describe suicide prevention care for individuals prescribed opioids or with opioid use disorder (OUD) and identify opportunities for improving this care. METHODS: Adult patients (n = 65) from four health systems with an opioid-involved overdose and clinicians (n = 21) who had contact with similar patients completed 30-60-min semi-structured interviews. A community advisory board contributed to development of all procedures, and interpretation and summary of findings. RESULTS: Patients were mostly female (59%), White (63%) and non-Hispanic (77%); 52 were prescribed opioids, 49% had diagnosed OUD, and 42% experienced an intentional opioid-involved overdose. Findings included: 1) when prescribed an opioid or treated for OUD, suicide risks were typically not discussed; 2) 35% of those with an intentional opioid-involved overdose and over 80% with an unintentional overdose reported no discussion of suicidal ideation when treated for the overdose; and 3) suicide-related follow-up care was uncommon among those with unintentional overdoses despite suicidal ideation being reported by >20%. Clinicians reported that when prescribing opioids or treating OUD, post-overdose suicide-related screening or counseling was not done routinely. CONCLUSIONS: There were several opportunities to tailor suicide prevention care for patients who were treated for opioid-involved overdoses within health systems.

Baseline Psychosocial, Environmental, Health, and Behavioral Correlates of 1- and 3-Year Weight Loss After Bariatric Surgery.

PURPOSE: Weight loss surgery is an effective, long-term treatment for severe obesity but individual response to surgery varies widely. The purpose of this study was to test a comprehensive theoretical model of factors that may be correlated with the greatest surgical weight loss at 1-3 years following surgery. Such a model would help determine what predictive factors to measure when patients are preparing for surgery that may ensure the best weight outcomes. MATERIALS AND METHODS: The Bariatric Experience Long Term (BELONG) study collected self-reported and medical record-based baseline information as correlates of 1- and 3-year % total weight loss (TWL) in n = 1341 patients. Multiple linear regression was used to determine the associations between 120 baseline variables and %TWL. RESULTS: Participants were 43.4 ± 11.3 years old, Hispanic or Black (52%; n = 699), women (86%; n = 1149), and partnered (72%; n = 965) and had annual incomes of ≥ $51,000 (60%; n = 803). A total of 1006 (75%) had 3-year follow-up weight. Regression models accounted for 10.1% of the variance in %TWL at 1-year and 13.6% at 3 years. Only bariatric operation accounted for a clinically meaningful difference (~ 5%) in %TWL at 1-year. At 3 years after surgery, only bariatric operation, Black race, and BMI ≥ 50 kg/m2 were associated with clinically meaningful differences in %TWL. CONCLUSIONS: Our findings combined with many others support a move away from extensive screening and selection of patients at the time of surgery to a focus on improving access to this treatment.

Research data warehouse: using electronic health records to conduct population-based observational studies.

Background: Electronic health records and many legacy systems contain rich longitudinal data that can be used for research; however, they typically are not readily available. Materials and methods: At Kaiser Permanente Southern California (KPSC), a research data warehouse (RDW) has been developed and maintained since the late 1990s and widely extended in 2006, aggregating and standardizing data collected from internal and a few external sources. This article provides a high-level overview of the RDW and discusses challenges common to data warehouses or repositories for research use. To demonstrate the application of the data, we report the volume, patient characteristics, and age-adjusted prevalence of selected medical conditions and utilization rates of selected medical procedures. Results: A total of 105 million person-years of health plan enrollment was recorded in the RDW between 1981 and 2018, with most healthcare utilization data available since early or middle 1990s. Among active enrollees on December 31, 2018, 15% were ≥65 years of age, 33.9% were non-Hispanic white, 43.3% Hispanic, 11.0% Asian, and 8.4% African American, and 34.4% of children (2-17 years old) and 72.1% of adults (≥18 years old) were overweight or obese. The age-adjusted prevalence of asthma, atrial fibrillation, diabetes mellitus, hypercholesteremia, and hypertension increased between 2001 and 2018. Hospitalization and Emergency Department (ED) visit rates appeared lower, and office visit rates seemed higher at KPSC compared to the reported US averages. Discussion and conclusion: Although the RDW is unique to KPSC, its methodologies and experience may provide useful insights for researchers of other healthcare systems worldwide in the era of big data analysis.

Assessing the differential item functioning of PHQ-9 items for diverse racial and ethnic adults with mental health and/or substance use disorder diagnoses: A retrospective cohort study.

BACKGROUND: Improving health equity in depression care and suicide screening requires that measures like the Patient Health Questionnaire 9 (PHQ-9) function similarly for diverse racial and ethnic groups. We evaluated PHQ-9 differential item functioning (DIF) between racial/ethnic groups in a retrospective cohort study of secondary electronic health record (EHR) data from eight healthcare systems. METHODS: The population (n = 755,156) included patients aged 18-64 with mental health and/or substance use disorder (SUD) diagnoses who had a PHQ-9 with no missing item data in the EHR for primary care or mental health visits between 1/1/2009-9/30/2017. We drew two random samples of 1000 from the following racial/ethnic groups originally recorded in EHRs (n = 14,000): Hispanic, and non-Hispanic White, Black, Asian, American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander, multiracial. We assessed DIF using iterative hybrid ordinal logistic regression and item response theory with p < 0.01 and 1000 Monte Carlo simulations, where change in model R2 > 0.01 represented non-negligible (e.g., clinically meaningful) DIF. RESULTS: All PHQ-9 items displayed statistically significant, but negligible (e.g., clinically unmeaningful) DIF between compared groups. The negligible DIF varied between random samples, although six items showed negligible DIF between the same comparison groups in both random samples. LIMITATIONS: Our findings may not generalize to disaggregated racial/ethnic groups or persons without mental health and/or SUD diagnoses. CONCLUSIONS: We found the PHQ-9 had clinically unmeaningful cross-cultural DIF for adult patients with mental health and/or SUD diagnoses. Future research could disaggregate race/ethnicity to discern if within-group identification impacts PHQ-9 DIF.