Sexual and Gender Minority Status and Suicide Mortality: An Explainable Artificial Intelligence Analysis

Objectives: Suicide risk is elevated in lesbian, gay, bisexual, and transgender (LGBT) individuals. Limited data on LGBT status in healthcare systems hinder our understanding of this risk. This study used natural language processing to extract LGBT status and a deep neural network (DNN) to examine suicidal death risk factors among US Veterans. Methods: Data on 8.8 million veterans with visits between 2010 and 2017 was used. A case-control study was performed, and suicide death risk was analyzed by a DNN. Feature impacts and interactions on the outcome were evaluated. Results: The crude suicide mortality rate was higher in LGBT patients. However, after adjusting for over 200 risk and protective factors, known LGBT status was associated with reduced risk compared to LGBT-Unknown status. Among LGBT patients, black, female, married, and older Veterans have a higher risk, while Veterans of various religions have a lower risk. Conclusion: Our results suggest that disclosed LGBT status is not directly associated with an increase suicide death risk, however, other factors (e.g., depression and anxiety caused by stigma) are associated with suicide death risks.

Non-affirmation minority stress, internalized transphobia, and subjective cognitive decline among transgender and gender diverse veterans aged 45 years and older

OBJECTIVES

To examine the associations of two measures of minority stress, non-affirmation minority stress and internalized transphobia, with subjective cognitive decline (SCD) among transgender and gender diverse (TGD) veterans.

METHOD

We administered a cross-sectional survey from September 2022 to July 2023 to TGD veterans. The final analytic sample included 3,152 TGD veterans aged ≥45 years. We used a generalized linear model with quasi-Poisson distribution to calculate prevalence ratios (PR) and 95% confidence intervals (CIs) measuring the relationship between non-affirmation minority stress and internalized transphobia and past-year SCD.

RESULTS

The mean age was 61.3 years (SD = 9.7) and the majority (70%) identified as trans women or women. Overall, 27.2% (n = 857) reported SCD. Adjusted models revealed that TGD veterans who reported experiencing non-affirmation minority stress or internalized transphobia had greater risk of past-year SCD compared to those who did not report either stressor (aPR: 1.09, 95% CI: 1.04-1.15; aPR: 1.19, 95% CI: 1.12-1.27).

CONCLUSION

Our findings demonstrate that proximal and distal processes of stigma are associated with SCD among TGD veterans and underscore the need for addressing multiple types of discrimination. Above all, these results indicate the lasting sequelae of transphobia and need for systemic changes to prioritize the safety and welfare of TGD people.

Metformin prescription for U.S. veterans with prediabetes, 2010-2019

Affecting an estimated 88 million Americans, prediabetes increases the risk for developing type 2 diabetes mellitus (T2DM), and independently, cardiovascular disease, retinopathy, nephropathy, and neuropathy. Nevertheless, little is known about the use of metformin for diabetes prevention among patients in the Veterans Health Administration, the largest integrated healthcare system in the U.S. This is a retrospective observational cohort study of the proportion of Veterans with incident prediabetes who were prescribed metformin at the Veterans Health Administration from October 2010 to September 2019. Among 1,059,605 Veterans with incident prediabetes, 12,009 (1.1%) were prescribed metformin during an average 3.4 years of observation after diagnosis. Metformin prescribing was marginally higher (1.6%) among those with body mass index (BMI) ≥35 kg/m2, age <60 years, HbA1c≥6.0%, or those with a history of gestational diabetes, all subgroups at a higher risk for progression to T2DM. In a multivariable model, metformin was more likely to be prescribed for those with BMI ≥35 kg/m2 incidence rate ratio [IRR] 2.6 [95% confidence intervals (CI): 2.1-3.3], female sex IRR, 2.4 [95% CI: 1.8-3.3], HbA1c≥6% IRR, 1.93 [95% CI: 1.5-2.4], age <60 years IRR, 1.7 [95% CI: 1.3-2.3], hypertriglyceridemia IRR, 1.5 [95% CI: 1.2-1.9], hypertension IRR, 1.5 [95% CI: 1.1-2.1], Major Depressive Disorder IRR, 1.5 [95% CI: 1.1-2.0], or schizophrenia IRR, 2.1 [95% CI: 1.2-3.8]. Over 20% of Veterans with prediabetes attended a comprehensive structured lifestyle modification clinic or program. Among Veterans with prediabetes, metformin was prescribed to 1.1% overall, a proportion that marginally increased to 1.6% in the subset of individuals at highest risk for progression to T2DM.

Risk factors for suicide among veterans living with and without HIV: a nested case-control study

The rate of suicide among people with HIV (PWH) remains elevated compared to the general population. The aim of the study was to examine the association between a broad range of risk factors, HIV-specific risk factors, and suicide. We conducted a nested case-control study using data from the Veterans Aging Cohort Study (VACS) between 2006 and 2015. The risk of suicide was estimated using conditional logistic regression and models were stratified by HIV status. Most risk factors associated with suicide were similar between PWH and people without HIV; these included affective disorders, use of benzodiazepines, and mental health treatment. Among PWH, HIV-specific risk factors were not associated with suicide. A multiplicative interaction was observed between a diagnosis of HIV and a previous suicide attempt. Among PWH, a high prevalence of psychiatric, substance use disorders and multimorbidity contribute to the risk of suicide.

Relationship Between Pain and LGBT Status Among Veterans in Care in a Retrospective Cross-Sectional Cohort

Background

Pain assessment is performed in many healthcare systems, such as the Veterans Health Administration, but prior studies have not assessed whether pain screening varies in sexual and gender minority populations that include individuals who identify as lesbian, gay, bisexual, and/or transgender (LGBT).

Objective

The purpose of this study was to evaluate pain screening and reported pain of LGBT Veterans compared to non-LGBT Veterans.

Methods

Using a retrospective cross-sectional cohort, data from the Corporate Data Warehouse, a national repository with clinical/administrative data, were analyzed. Veterans were classified as LGBT using natural language processing. We used a robust Poisson model to examine the association between LGBT status and binary outcomes of pain screening, any pain, and persistent pain within one year of entry in the cohort. All models were adjusted for demographics, mental health, substance use, musculoskeletal disorder(s), and number of clinic visits.

Results

There were 1,149,486 Veterans (218,154 (19%) classified as LGBT) in our study. Among LGBT Veterans, 94% were screened for pain compared to 89% among those not classified as LGBT (non-LGBT) Veterans. In adjusted models, LGBT Veterans' probability of being screened for pain compared to non-LGBT Veterans was 2.5% higher (95% CI 2.3%, 2.6%); risk of any pain was 2.1% lower (95% CI 1.6%, 2.6%); and there was no significant difference between LGBT and non-LGBT Veterans in persistent pain (RR = 1.00, 95% CI (0.99, 1.01), p = 0.88).

Conclusions

In a nationwide sample, LGBT Veterans were more likely to be screened for pain but had lower self-reported pain scores, though adjusted differences were small. It was notable that transgender and Black Veterans reported the greatest pain. Reasons for these findings require further investigation.

Identifying suicide documentation in clinical notes through zero-shot learning

Background and Aims

In deep learning, a major difficulty in identifying suicidality and its risk factors in clinical notes is the lack of training samples given the small number of true positive instances among the number of patients screened. This paper describes a novel methodology that identifies suicidality in clinical notes by addressing this data sparsity issue through zero-shot learning. Our general aim was to develop a tool that leveraged zero-shot learning to effectively identify suicidality documentation in all types of clinical notes.

Methods

US Veterans Affairs clinical notes served as data. The training data set label was determined using diagnostic codes of suicide attempt and self-harm. We used a base string associated with the target label of suicidality to provide auxiliary information by narrowing the positive training cases to those containing the base string. We trained a deep neural network by mapping the training documents' contents to a semantic space. For comparison, we trained another deep neural network using the identical training data set labels, and bag-of-words features.

Results

The zero-shot learning model outperformed the baseline model in terms of area under the curve, sensitivity, specificity, and positive predictive value at multiple probability thresholds. In applying a 0.90 probability threshold, the methodology identified notes documenting suicidality but not associated with a relevant ICD-10-CM code, with 94% accuracy.

Conclusion

This method can effectively identify suicidality without manual annotation.

Intimate partner violence among lesbian, gay, and bisexual veterans

The present study describes intimate partner violence (IPV) perpetration and victimization alongside theoretically associated variables in a sample of lesbian, gay, and bisexual veterans. We conducted bivariate analyses (chi-square tests and independent t test) to examine whether the frequencies of IPV perpetration and victimization varied by demographic characteristics, military sexual trauma, alcohol use, and mental health symptoms. Out of the 69 lesbian, gay, and bisexual (LGB) veterans who answered the questions on IPV, 16 (23.2%) reported some form of IPV victimization in the past year, and 38 (55.1%) reported past-year perpetration. Among the 43 veterans who reported psychological IPV, roughly half (48.9%) reported bidirectional psychological IPV, 39.5% reported perpetration only, and 11.6% reported victimization only. LGB veterans who reported bidirectional psychological IPV in their relationships were younger and reported greater symptoms of posttraumatic stress disorder symptoms and depression. The results presented here call for universal screening of IPV perpetration and victimization to both accurately assess and ultimately intervene among all veterans. Inclusive interventions are needed for all genders and sexual orientations, specifically interventions that do not adhere to gendered assumptions of perpetrators and victims. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Association between early nonpharmacological management and follow-up for low back pain in the veterans health administration

Background

Low back pain (LBP) is a common reason individuals seek healthcare. Nonpharmacologic management (NPM) is often recommended as a primary intervention, and earlier use of NPM for LBP shows positive clinical outcomes. Our purpose was to evaluate how timing of engagement in NPM for LBP affects downstream LBP visits during the first year.

Methods

This study was a secondary analysis of an observational cohort study of national electronic health record data. Patients entering the Musculoskeletal Diagnosis/Complementary and Integrative Health Cohort with LBP from October 1, 2016 to September 30, 2017 were included. Exclusive patient groups were defined by engagement in NPM within 30 days of entry ("very early NPM"), between 31 and 90 days ("early NPM"), or not within the first 90 days ("no NPM"). The outcome was time, in days, to the final LBP follow-up after 90 days and within the first year. Cox proportional hazards regression was used to model time to final follow up, controlling for additional demographic and clinical covariables.

Results

The study population included 44,175 patients, with 16.7% engaging in very early NPM and 13.1% in early NPM. Patients with very early NPM (5.2 visits, SD=4.5) or early NPM (5.7 visits, SD=4.6) had a higher mean number of LBP visits within the first year than those not receiving NPM in the first 90 days (3.2 visits, SD = 2.5). The very early NPM (HR=1.50, 95% CI: 1.46-1.54; median=48 days, IQR=97) and early NPM (HR=1.27, 95% CI: 1.23-1.30; median=88 days, IQR=92) had a significantly shorter time to final follow-up than the no NPM group (median=109 days, IQR=150).

Conclusions

Veterans Health Administration patients receiving NPM for LBP within the first 90 days after initially seeking care demonstrate a significantly faster time to final follow-up visit within the first year compared to those who do not.

Complementary and Integrative Health Approaches and Pain Care Quality in the Veterans Health Administration Primary Care Setting: A Quasi-Experimental Analysis

Background: Complementary and integrative health (CIH) approaches have been recommended in national and international clinical guidelines for chronic pain management. We set out to determine whether exposure to CIH approaches is associated with pain care quality (PCQ) in the Veterans Health Administration (VHA) primary care setting. Methods: We followed a cohort of 62,721 Veterans with newly diagnosed musculoskeletal disorders between October 2016 and September 2017 over 1-year. PCQ scores were derived from primary care progress notes using natural language processing. CIH exposure was defined as documentation of acupuncture, chiropractic or massage therapies by providers. Propensity scores (PSs) were used to match one control for each Veteran with CIH exposure. Generalized estimating equations were used to examine associations between CIH exposure and PCQ scores, accounting for potential selection and confounding bias. Results: CIH was documented for 14,114 (22.5%) Veterans over 16,015 primary care clinic visits during the follow-up period. The CIH exposure group and the 1:1 PS-matched control group achieved superior balance on all measured baseline covariates, with standardized differences ranging from 0.000 to 0.045. CIH exposure was associated with an adjusted rate ratio (aRR) of 1.147 (95% confidence interval [CI]: 1.142, 1.151) on PCQ total score (mean: 8.36). Sensitivity analyses using an alternative PCQ scoring algorithm (aRR: 1.155; 95% CI: 1.150-1.160) and redefining CIH exposure by chiropractic alone (aRR: 1.118; 95% CI: 1.110-1.126) derived consistent results. Discussion: Our data suggest that incorporating CIH approaches may reflect higher overall quality of care for patients with musculoskeletal pain seen in primary care settings, supporting VHA initiatives and the Declaration of Astana to build comprehensive, sustainable primary care capacity for pain management. Future investigation is warranted to better understand whether and to what degree the observed association may reflect the therapeutic benefits patients actually received or other factors such as empowering provider-patient education and communication about these approaches.

Evaluation of a Model to Target High-risk Psychiatric Inpatients for an Intensive Postdischarge Suicide Prevention Intervention

Importance

The months after psychiatric hospital discharge are a time of high risk for suicide. Intensive postdischarge case management, although potentially effective in suicide prevention, is likely to be cost-effective only if targeted at high-risk patients. A previously developed machine learning (ML) model showed that postdischarge suicides can be predicted from electronic health records and geospatial data, but it is unknown if prediction could be improved by adding additional information.

Objective

To determine whether model prediction could be improved by adding information extracted from clinical notes and public records.

Design, Setting, and Participants

Models were trained to predict suicides in the 12 months after Veterans Health Administration (VHA) short-term (less than 365 days) psychiatric hospitalizations between the beginning of 2010 and September 1, 2012 (299 050 hospitalizations, with 916 hospitalizations followed within 12 months by suicides) and tested in the hospitalizations from September 2, 2012, to December 31, 2013 (149 738 hospitalizations, with 393 hospitalizations followed within 12 months by suicides). Validation focused on net benefit across a range of plausible decision thresholds. Predictor importance was assessed with Shapley additive explanations (SHAP) values. Data were analyzed from January to August 2022.

Main Outcomes and Measures

Suicides were defined by the National Death Index. Base model predictors included VHA electronic health records and patient residential data. The expanded predictors came from natural language processing (NLP) of clinical notes and a social determinants of health (SDOH) public records database.

Results

The model included 448 788 unique hospitalizations. Net benefit over risk horizons between 3 and 12 months was generally highest for the model that included both NLP and SDOH predictors (area under the receiver operating characteristic curve range, 0.747-0.780; area under the precision recall curve relative to the suicide rate range, 3.87-5.75). NLP and SDOH predictors also had the highest predictor class-level SHAP values (proportional SHAP = 64.0% and 49.3%, respectively), although the single highest positive variable-level SHAP value was for a count of medications classified by the US Food and Drug Administration as increasing suicide risk prescribed the year before hospitalization (proportional SHAP = 15.0%).

Conclusions and Relevance

In this study, clinical notes and public records were found to improve ML model prediction of suicide after psychiatric hospitalization. The model had positive net benefit over 3-month to 12-month risk horizons for plausible decision thresholds. Although caution is needed in inferring causality based on predictor importance, several key predictors have potential intervention implications that should be investigated in future studies.

Temporal and Geographic Patterns of Documentation of Sexual Orientation and Gender Identity Keywords in Clinical Notes

OBJECTIVE

Disclosure of sexual orientation and gender identity correlates with better outcomes, yet data may not be available in structured fields in electronic health record data. To gain greater insight into the care of sexual and gender-diverse patients in the Veterans Health Administration (VHA), we examined the documentation patterns of sexual orientation and gender identity through extraction and analyses of data contained in unstructured electronic health record clinical notes.

METHODS

Salient terms were identified through authoritative vocabularies, the research team's expertise, and frequencies, and the use of consistency in VHA clinical notes. Term frequencies were extracted from VHA clinical notes recorded from 2000 to 2018. Temporal analyses assessed usage changes in normalized frequencies as compared with nonclinical use, relative growth rates, and geographic variations.

RESULTS

Over time most terms increased in use, similar to Google ngram data, especially after the repeal of the "Don't Ask Don't Tell" military policy in 2010. For most terms, the usage adoption consistency also increased by the study's end. Aggregated use of all terms increased throughout the United States.

CONCLUSION

Term usage trends may provide a view of evolving care in a temporal continuum of changing policy. These findings may be useful for policies and interventions geared toward sexual and gender-diverse individuals. Despite the lack of structured data, the documentation of sexual orientation and gender identity terms is increasing in clinical notes.

Mental Health Diagnoses are Not Associated With Indicators of Lower Quality Pain Care in Electronic Health Records of a National Sample of Veterans Treated in Veterans Health Administration Primary Care Settings

Prior research has demonstrated disparities in general medical care for patients with mental health conditions, but little is known about disparities in pain care. The objective of this retrospective cohort study was to determine whether mental health conditions are associated with indicators of pain care quality (PCQ) as documented by primary care clinicians in the Veterans Health Administration (VHA). We used natural language processing to analyze electronic health record data from a national sample of Veterans with moderate to severe musculoskeletal pain during primary care visits in the Fiscal Year 2017. Twelve PCQ indicators were annotated from clinician progress notes as present or absent; PCQ score was defined as the sum of these indicators. Generalized estimating equation Poisson models examined associations among mental health diagnosis categories and PCQ scores. The overall mean PCQ score across 135,408 person-visits was 8.4 (SD = 2.3). In the final adjusted model, post-traumatic stress disorder was associated with higher PCQ scores (RR = 1.006, 95%CI 1.002-1.010, P = .007). Depression, alcohol use disorder, other substance use disorder, schizophrenia, and bipolar disorder diagnoses were not associated with PCQ scores. Overall, results suggest that in this patient population, presence of a mental health condition is not associated with lower quality pain care. PERSPECTIVE: This study used a natural language processing approach to analyze medical records to determine whether mental health conditions are associated with indicators of pain care quality as documented by primary care clinicians. Findings suggest that presence of a diagnosed mental health condition is not associated with lower quality pain care.

Enhancing Clinical Data Analysis by Explaining Interaction Effects between Covariates in Deep Neural Network Models

Deep neural network (DNN) is a powerful technology that is being utilized by a growing number and range of research projects, including disease risk prediction models. One of the key strengths of DNN is its ability to model non-linear relationships, which include covariate interactions. We developed a novel method called interaction scores for measuring the covariate interactions captured by DNN models. As the method is model-agnostic, it can also be applied to other types of machine learning models. It is designed to be a generalization of the coefficient of the interaction term in a logistic regression; hence, its values are easily interpretable. The interaction score can be calculated at both an individual level and population level. The individual-level score provides an individualized explanation for covariate interactions. We applied this method to two simulated datasets and a real-world clinical dataset on Alzheimer's disease and related dementia (ADRD). We also applied two existing interaction measurement methods to those datasets for comparison. The results on the simulated datasets showed that the interaction score method can explain the underlying interaction effects, there are strong correlations between the population-level interaction scores and the ground truth values, and the individual-level interaction scores vary when the interaction was designed to be non-uniform. Another validation of our new method is that the interactions discovered from the ADRD data included both known and novel relationships.

Sleep disturbance and suicide risk among sexual and gender minority people

Sleep disturbance has emerged as an independent, mechanistic, and modifiable risk factor for suicide. Sexual and gender minority (SGM) people disproportionately experience sleep disturbance and are at higher risk of death by suicide relative to cisgender and/or heterosexual individuals. The present narrative review evaluates nascent research related to sleep disturbance and suicide-related thoughts and behaviors (STBs) among SGM populations, and discusses how experiences of minority stress may explain heightened risk among SGM people. Although there is a growing understanding of the link between sleep disturbance and STBs, most research has not been conducted in SGM populations or has not examined suicide as an outcome. Research is needed to examine whether and how aspects of sleep disturbances relate to STBs among SGM people in order to better tailor sleep treatments for SGM populations.

Measuring pain care quality in the Veterans Health Administration primary care setting

ABSTRACT

The lack of a reliable approach to assess quality of pain care hinders quality improvement initiatives. Rule-based natural language processing algorithms were used to extract pain care quality (PCQ) indicators from documents of Veterans Health Administration primary care providers for veterans diagnosed within the past year with musculoskeletal disorders with moderate-to-severe pain intensity across 2 time periods 2013 to 2014 (fiscal year [FY] 2013) and 2017 to 2018 (FY 2017). Patterns of documentation of PCQ indicators for 64,444 veterans and 124,408 unique visits (FY 2013) and 63,427 veterans and 146,507 visits (FY 2017) are described. The most commonly documented PCQ indicators in each cohort were presence of pain, etiology or source, and site of pain (greater than 90% of progress notes), while least commonly documented were sensation, what makes pain better or worse, and pain's impact on function (documented in fewer than 50%). A PCQ indicator score (maximum = 12) was calculated for each visit in FY 2013 (mean = 7.8, SD = 1.9) and FY 2017 (mean = 8.3, SD = 2.3) by adding one point for every indicator documented. Standardized Cronbach alpha for total PCQ scores was 0.74 in the most recent data (FY 2017). The mean PCQ indicator scores across patient characteristics and types of healthcare facilities were highly stable. Estimates of the frequency of documentation of PCQ indicators have face validity and encourage further evaluation of the reliability, validity, and utility of the measure. A reliable measure of PCQ fills an important scientific knowledge and practice gap.

Transphobia, encoded: an examination of trans-specific terminology in SNOMED CT and ICD-10-CM

Transgender people experience harassment, denial of services, and physical assault during healthcare visits. Electronic health record (EHR) structure and language can exacerbate the harm they experience by using transphobic terminology, emphasizing binary genders, and pathologizing transness. Here, we investigate the ways in which SNOMED CT and ICD-10-CM record gender-related terminology and explore their shortcomings as they contribute to this EHR-mediated violence. We discuss how this "standardized" gender-related medical terminology pathologizes transness, fails to accommodate nonbinary patients, and uses derogatory and outmoded language. We conclude that there is no easy fix to the transphobia beleaguering healthcare, provide options to reduce harm to patients, and ultimately call for a critical examination of medicine's role in transphobia. We aim to demonstrate the ways in which the [mis]use and [mis]understanding of gender-specific terminology in healthcare settings has harmed and continues to harm trans people by grounding our discussion in our personal experiences.

Military sexual trauma and suicidal ideation in VHA-care-seeking OEF/OIF/OND veterans without mental health diagnosis or treatment

Sexual trauma is a suicide risk factor. While military sexual trauma (MST) is frequently associated with suicidal ideation (SI) in women and men veterans who served in recent conflicts, less is known about MST's relationship to SI in veterans who have no documented mental health concerns. Of the 1.1 million post-9/11 veterans enrolled in the Veterans Healthcare Administration (VHA) we examined 41,658 (12.3% women, 87.7% men) without evidence of mental health diagnosis or treatment and who were screened for MST and SI using the standard VHA clinical reminders between 2008 and 2013. Relative risk estimates were generated using separate models for women and men. MST was reported by 27.9% of women and 2.9% of men; SI by 14.7% and 16.5%, respectively. The adjusted relative risk of MST on SI was 1.65 (95% CI 1.35, 2.00) in women, and 1.49 (95% CI 1.26, 1.75) in men. In this sample of veterans without evidence of mental health diagnosis or treatment, MST was associated with a high risk of SI in both genders. Positive MST screening should prompt SI screening and risk management if indicated, and further study of barriers to mental healthcare among MST survivors at risk for suicide is warranted.

Documentation of Screening for Firearm Access by Healthcare Providers in the Veterans Healthcare System: A Retrospective Study

INTRODUCTION

Presence of a firearm is associated with increased risk of violence and suicide. United States military veterans are at disproportionate risk of suicide. Routine healthcare provider screening of firearm access may prompt counseling on safe storage and handling of firearms. The objective of this study was to determine the frequency with which Veterans Health Administration (VHA) healthcare providers document firearm access in electronic health record (EHR) clinical notes, and whether this varied by patient characteristics.

METHODS

The study sample is a post-9-11 cohort of veterans in their first year of VHA care, with at least one outpatient care visit between 2012-2017 (N = 762,953). Demographic data, veteran military service characteristics, and clinical comorbidities were obtained from VHA EHR. We extracted clinical notes for outpatient visits to primary, urgent, or emergency clinics (total 105,316,004). Natural language processing and machine learning (ML) approaches were used to identify documentation of firearm access. A taxonomy of firearm terms was identified and manually annotated with text anchored by these terms, and then trained the ML algorithm. The random-forest algorithm achieved 81.9% accuracy in identifying documentation of firearm access.

RESULTS

The proportion of patients with EHR-documented access to one or more firearms during their first year of care in the VHA was relatively low and varied by patient characteristics. Men had significantly higher documentation of firearms than women (9.8% vs 7.1%; P < .001) and veterans >50 years old had the lowest (6.5%). Among veterans with any firearm term present, only 24.4% were classified as positive for access to a firearm (24.7% of men and 20.9% of women).

CONCLUSION

Natural language processing can identify documentation of access to firearms in clinical notes with acceptable accuracy, but there is a need for investigation into facilitators and barriers for providers and veterans to improve a systemwide process of firearm access screening. Screening, regardless of race/ethnicity, gender, and age, provides additional opportunities to protect veterans from self-harm and violence.

The Relationship Between Body Mass Index and Pain Intensity Among Veterans with Musculoskeletal Disorders: Findings from the MSD Cohort Study

OBJECTIVE

To examine the relationship between body mass index (BMI) and pain intensity among veterans with musculoskeletal disorder diagnoses (MSDs; nontraumatic joint disorder; osteoarthritis; low back, back, and neck pain).

SETTING

Administrative and electronic health record data from the Veterans Health Administration (VHA).

SUBJECTS

A national cohort of US military veterans with MSDs in VHA care during 2001-2012 (N = 1,759,338).

METHODS

These cross-sectional data were analyzed using hurdle negative binomial models of pain intensity as a function of BMI, adjusted for comorbidities and demographics.

RESULTS

The sample had a mean age of 59.4, 95% were male, 77% were white/Non-Hispanic, 79% were overweight or obese, and 42% reported no pain at index MSD diagnosis. Overall, there was a J-shaped relationship between BMI and pain (nadir = 27 kg/m2), with the severely obese (BMI ≥ 40 kg/m2) being most likely to report any pain (OR vs normal weight = 1.23, 95% confidence interval = 1.21-1.26). The association between BMI and pain varied by MSD, with a stronger relationship in the osteoarthritis group and a less pronounced relationship in the back and low back pain groups.

CONCLUSIONS

There was a high prevalence of overweight/obesity among veterans with MSD. High levels of BMI (>27 kg/m2) were associated with increased odds of pain, most markedly among veterans with osteoarthritis.

Identifying Multisite Chronic Pain with Electronic Health Records Data

BACKGROUND

Multisite chronic pain (MSCP) is associated with increased chronic pain impact, but methods for identifying MSCP for epidemiological research have not been evaluated.

OBJECTIVE

We assessed the validity of identifying MSCP using electronic health care data compared with survey questionnaires.

METHODS

Stratified random samples of adults served by Kaiser Permanente Northwest and Washington (N = 2,059) were drawn for a survey, oversampling persons with frequent use of health care for pain. MSCP and single-site chronic pain were identified by two methods, with electronic health care data and with self-report of common chronic pain conditions by survey questionnaire. Analyses were weighted to adjust for stratified sampling.

RESULTS

MSCP was somewhat less common when ascertained by electronic health records (14.7% weighted prevalence) than by survey questionnaire (25.9% weighted prevalence). Agreement of the two MSCP classifications was low (kappa agreement statistic of 0.21). Ascertainment of MSCP with electronic health records was 30.9% sensitive, 91.0% specific, and had a positive predictive value of 54.5% relative to MSCP identified by self-report as the standard. After adjusting for age and gender, patients with MSCP identified by either electronic health records or self-report showed higher levels of pain-related disability, pain severity, depressive symptoms, and long-term opioid use than persons with single-site chronic pain identified by the same method.

CONCLUSIONS

Identification of MSCP with electronic health care data was insufficiently accurate to be used as a surrogate or screener for MSCP identified by self-report, but both methods identified persons with heightened chronic pain impact.

ICD-10 Coding of Musculoskeletal Conditions in the Veterans Health Administration

OBJECTIVE

We describe the most frequently used musculoskeletal diagnoses in Veterans Health Administration (VHA) care. We report the number of visits and patients associated with common musculoskeletal ICD-10 codes and compare trends across primary and specialty care settings.

DESIGN

Secondary analysis of a longitudinal cohort study.

SUBJECTS

Veterans included in the Musculoskeletal Diagnosis Cohort with a musculoskeletal diagnosis from October 1, 2015 through September 30, 2017.

METHODS

We obtained counts and proportions of all musculoskeletal diagnosis codes used and the number of unique patients with each musculoskeletal diagnosis. Diagnosis use was compared between primary and specialty care settings.

RESULTS

Of over 6,400 possible ICD-10 M-codes describing "Diseases of the Musculoskeletal System and Connective Tissue", 5,723 codes were used at least once. The most frequently used ICD-10 M-code was "Low Back Pain" (18.3%) followed by "Cervicalgia" (3.6%). Collectively, the 100 most frequently used codes accounted for 80% of M-coded visit diagnoses, and 95% of patients had at least one of these diagnoses. The most common diagnoses (spinal pain, joint pain, osteoarthritis) were used similarly in primary and specialty care settings.

CONCLUSION

A diverse sample of all available musculoskeletal diagnosis codes were used; however, less than 2% of all possible codes accounted for 80% of the diagnoses used. This trend was consistent across primary and specialty care settings. The most frequently used diagnosis codes describe the types of musculoskeletal conditions, among a large pool of potential diagnoses, that prompt veterans to present to VHA for musculoskeletal care.

Examining Health Care Mobility of Transgender Veterans Across the Veterans Health Administration

Purpose: Transgender veterans are overrepresented in the Veterans Health Administration (VHA) compared with in the general population. Utilization of multiple different health care systems, or health care mobility, can affect care coordination and potentially affect outcomes, either positively or negatively. This study examines whether transgender veterans are more or less health care mobile than nontransgender veterans and compares the patterns of geographic mobility in these groups. Methods: Using an established cohort (n = 5,414,109), we identified 2890 transgender veterans from VHA electronic health records from 2000 to 2012. We compared transgender and nontransgender veterans on sociodemographic, clinical, and health care system-level measures and conducted conditional logistic regression models of mobility. Results: Transgender veterans were more likely to be younger, White, homeless, have depressive disorders, post-traumatic stress disorder (PTSD), and hepatitis C. Transgender veterans were more likely to have been health care mobile (9.9%) than nontransgender veterans (5.2%) (unadjusted odds ratio = 2.02, 95% confidence interval = 1.73-2.36). In a multivariable model, transgender status, being separated/divorced, receiving care in less-complex facilities, and diagnoses of depression, PTSD, or hepatitis C were associated with more mobility, whereas older age was associated with less mobility. For the top three health care systems utilized, a larger proportion of transgender veterans visited a second health care system in a different state (56.2%) than nontransgender veterans (37.5%). Conclusions: Transgender veterans were more likely to be health care mobile and more likely to travel out of state for health care services. They were also more likely to have complex chronic health conditions that require multidisciplinary care.

The architecture of co-morbidity networks of physical and mental health conditions in military veterans

Co-morbidity between medical and psychiatric conditions is commonly considered between individual pairs of conditions. However, an important alternative is to consider all conditions as part of a co-morbidity network, which encompasses all interactions between patients and a healthcare system. Analysis of co-morbidity networks could detect and quantify general tendencies not observed by smaller-scale studies. Here, we investigate the co-morbidity network derived from longitudinal healthcare records from approximately 1 million United States military veterans, a population disproportionately impacted by psychiatric morbidity and psychological trauma. Network analyses revealed marked and heterogenous patterns of co-morbidity, including a multi-scale community structure composed of groups of commonly co-morbid conditions. Psychiatric conditions including posttraumatic stress disorder were strong predictors of future medical morbidity. Neurological conditions and conditions associated with chronic pain were particularly highly co-morbid with psychiatric conditions. Across conditions, the degree of co-morbidity was positively associated with mortality. Co-morbidity was modified by biological sex and could be used to predict future diagnostic status, with out-of-sample prediction accuracy of 90-92%. Understanding complex patterns of disease co-morbidity has the potential to lead to improved designs of systems of care and the development of targeted interventions that consider the broader context of mental and physical health.

Exploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization

BACKGROUND

Chronic spinal pain conditions affect millions of US adults and carry a high healthcare cost burden, both direct and indirect. Conservative interventions for spinal pain conditions, including chiropractic care, have been associated with lower healthcare costs and improvements in pain status in different clinical populations, including veterans. Little is currently known about predicting healthcare service utilization in the domain of conservative interventions for spinal pain conditions, including the frequency of use of chiropractic services. The purpose of this retrospective cohort study was to explore the use of supervised machine learning approaches to predicting one-year chiropractic service utilization by veterans receiving VA chiropractic care.

METHODS

We included 19,946 veterans who entered the Musculoskeletal Diagnosis Cohort between October 1, 2003 and September 30, 2013 and utilized VA chiropractic services within one year of cohort entry. The primary outcome was one-year chiropractic service utilization following index chiropractic visit, split into quartiles represented by the following classes: 1 visit, 2 to 3 visits, 4 to 6 visits, and 7 or greater visits. We compared the performance of four multiclass classification algorithms (gradient boosted classifier, stochastic gradient descent classifier, support vector classifier, and artificial neural network) in predicting visit quartile using 158 sociodemographic and clinical features.

RESULTS

The selected algorithms demonstrated poor prediction capabilities. Subset accuracy was 42.1% for the gradient boosted classifier, 38.6% for the stochastic gradient descent classifier, 41.4% for the support vector classifier, and 40.3% for the artificial neural network. The micro-averaged area under the precision-recall curve for each one-versus-rest classifier was 0.43 for the gradient boosted classifier, 0.38 for the stochastic gradient descent classifier, 0.43 for the support vector classifier, and 0.42 for the artificial neural network. Performance of each model yielded only a small positive shift in prediction probability (approximately 15%) compared to naïve classification.

CONCLUSIONS

Using supervised machine learning to predict chiropractic service utilization remains challenging, with only a small shift in predictive probability over naïve classification and limited clinical utility. Future work should examine mechanisms to improve model performance.

Treatment of a Large Cohort of Veterans Experiencing Musculoskeletal Disorders with Spinal Cord Stimulation in the Veterans Health Administration: Veteran Characteristics and Outcomes

OBJECTIVE

Spinal cord stimulator (SCS) implantation is used to treat chronic pain, including painful musculoskeletal disorders (MSDs). This study examined the characteristics and outcomes of veterans receiving SCSs in Veterans Health Administration (VHA) facilities.

METHODS

The sample was drawn from the MSD Cohort and limited to three MSDs with the highest number of implants (N=815,475). There were 1490 veterans with these conditions who received SCS implants from 2000 to 2012, of which 95% (n=1414) had pain intensity numeric rating scale (NRS) data both pre- and post-implant.

RESULTS

Veterans who were 35-44 years old, White, and married reported higher pain NRS ratings, had comorbid inclusion diagnoses, had no medical comorbidities, had a BMI 25-29.9, or had a depressive disorder diagnosis were more likely to receive an SCS. Veterans 55+ years old or with an alcohol or substance use disorder were less likely to receive an SCS. Over 90% of those receiving an SCS were prescribed opioids in the year prior to implant. Veterans who had a presurgical pain score ≥4 had a clinically meaningful decrease in their pain score in the year following their 90-day recovery period (Day 91-456) greater than expected by chance alone. Similarly, there was a significant decrease in the percent of veterans receiving opioid therapy (92.4% vs 86.6%, p<0.0001) and a significant overall decrease in opioid dose [morphine equivalent dose per day (MEDD) =26.48 vs MEDD=22.59, p<0.0003].

CONCLUSION

Results offer evidence of benefit for some veterans with the examined conditions. Given known risks of opioid therapy, the reduction is an important potential benefit of SCS implants.

Sex Differences in Military Sexual Trauma and Severe Self-Directed Violence

INTRODUCTION

Previous research has demonstrated an association between military sexual trauma and risk for suicide; however, risk for self-directed violence such as suicide attempt or nonsuicidal self-injury following military sexual trauma is understudied. This study examines the relationship between military sexual trauma and serious self-directed violence resulting in hospitalization, as well as whether this relationship differs by sex.

METHODS

Participants were 750,176 Operations Enduring Freedom/Iraqi Freedom/New Dawn veterans who were enrolled in Veterans Health Administration care during the period of October 1, 2001-September 30, 2014 and who were screened for military sexual trauma. Data were analyzed in 2019. Bivariate analyses and Cox proportional hazards regression models were employed.

RESULTS

Women veterans were more likely to screen positive for military sexual trauma (21.33% vs 1.63%), and women and men were equally likely to experience serious self-directed violence (1.19% women vs 1.18% men). Controlling for demographic variables and psychiatric morbidity, military sexual trauma predicted serious self-directed violence for both men and women. Further, men with military sexual trauma were 15% less likely to experience self-directed violence compared with women with military sexual trauma (hazard ratio=0.85, 95% CI=0.74, 0.98).

CONCLUSIONS

Military sexual trauma is associated with risk for serious self-directed violence for both men and women veterans, and the relationship may be pronounced among women. Results underscore the importance of incorporating military sexual trauma into treatment and preventative efforts for self-directed violence.

Suicidal ideation, behavior, and mortality in male and female US veterans with severe mental illness

BACKGROUND

We compared male and female American veterans with schizophrenia or bipolar disorder regarding clinical characteristics associated with lifetime suicidal ideation and behavior. Subsequent mortality, including death by suicide, was also assessed.

METHODS

Data from questionnaires and face-to-face evaluations were collected during 2011-2014 from 8,049 male and 1,290 female veterans with schizophrenia or bipolar disorder. In addition to comparing male-female characteristics, Cox regression models-adjusted for demographic information, medical-psychiatric comorbidities, and self-reported suicidal ideation and behavior-were used to examine gender differences in associations of putative risk factors with suicide-specific and all-cause mortality during up to six years of follow-up.

RESULTS

Women overall were younger, more likely to report a history of suicidal behavior, less likely to be substance abusers, and had lower overall mortality during follow-up. Among women only, psychiatric comorbidity was paradoxically associated with lower all-cause mortality (hazard ratio [HR]=0.53, 95% CI, 0.29-0.96, p = 0.037 for 1 disorder vs. none; HR=0.44, 95% CI, 0.25-0.77, p = 0.004 for ≥2 disorders vs. none). Suicide-specific mortality involved relatively few events, but crude rates were an order of magnitude higher than in the U.S. general and overall veteran populations.

LIMITATIONS

Incomplete cause-of-death information and low statistical power for male-female comparisons regarding mortality.

CONCLUSIONS

Female veterans with SMI differed from females in the general population by having a higher risk of suicide attempts. They also had more lifetime suicide attempts than male veterans with same diagnoses. These differences should inform public policy and clinical planning.

Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System

There is a very high suicide rate in the year after psychiatric hospital discharge. Intensive postdischarge case management programs can address this problem but are not cost-effective for all patients. This issue can be addressed by developing a risk model to predict which inpatients might need such a program. We developed such a model for the 391,018 short-term psychiatric hospital admissions of US veterans in Veterans Health Administration (VHA) hospitals 2010-2013. Records were linked with the National Death Index to determine suicide within 12 months of hospital discharge (n=771). The Super Learner ensemble machine learning method was used to predict these suicides for time horizon between 1 week and 12 months after discharge in a 70% training sample. Accuracy was validated in the remaining 30% holdout sample. Predictors included VHA administrative variables and small area geocode data linked to patient home addresses. The models had AUC=.79-.82 for time horizons between 1 week and 6 months and AUC=.74 for 12 months. An analysis of operating characteristics showed that 22.4%-32.2% of patients who died by suicide would have been reached if intensive case management was provided to the 5% of patients with highest predicted suicide risk. Positive predictive value (PPV) at this higher threshold ranged from 1.2% over 12 months to 3.8% per case manager year over 1 week. Focusing on the low end of the risk spectrum, the 40% of patients classified as having lowest risk account for 0%-9.7% of suicides across time horizons. Variable importance analysis shows that 51.1% of model performance is due to psychopathological risk factors accounted, 26.2% to social determinants of health, 14.8% to prior history of suicidal behaviors, and 6.6% to physical disorders. The paper closes with a discussion of next steps in refining the model and prospects for developing a parallel precision treatment model.

Gender Differences in Suicide and Self-Directed Violence Risk Among Veterans With Post-traumatic Stress and Substance Use Disorders

BACKGROUND

Veterans have a high prevalence of both post-traumatic stress disorder (PTSD) and substance use disorders (SUDs), which are related to suicide risk. Exploring gender-related differences in suicidal behavior risk among this subgroup of veterans is important to improve prevention and treatment strategies. To date, few studies have explored these differences.

METHODS

The sample included 352,476 men and women veterans from the Women Veterans Cohort Study with a diagnosis of PTSD. First, we conducted analyses to assess gender-related differences in sociodemographic and clinical variables at baseline, as well as by suicidal behavior. Then, we conducted a series of Cox proportional hazards regression models to estimate the hazard ratios of engaging in self-directed violence (SDV) and dying by suicide by SUD status and gender, controlling for potential confounders.

RESULTS

Adjusted analyses showed that, among veterans with PTSD, the presence of a SUD significantly increased the risk of SDV and death by suicide. Women with PTSD had a decreased risk of dying by suicide compared with men. No gender-related difference was observed for SDV. SUD increased the risk of SDV behavior in both women and men but increased the risk of dying by suicide only among men.

CONCLUSIONS

Our findings revealed gender-related differences in SDV and suicide among veterans with a PTSD diagnosis with or without a SUD. Our study, along with the increasing numbers of women serving in the military, stresses the need to conduct gender-based analyses to help improve prevention and treatment strategies.

USE OF EXPOSURE CROSSOVER DESIGN TO CONTROL FOR UNMEASURED BASELINE CONFOUNDING IN OBSERVATIONAL STUDIES

Observational comparative effectiveness studies face the challenge of selection bias. Due to lack of randomization, an alleged treatment effect may reflect inherent differences in baseline characteristics between comparison groups, rather than the outcome of treatment. Propensity score methods were devised to “resample” a most comparable comparison group, under a strong yet untestable assumption of no unmeasured confounding. We present an “exposure crossover” study evaluating complementary and integrative health approaches (CIH) among 6,379 US veterans who received acupuncture, massage or chiropractic therapies between 10/1/2011-9/30/2013. Their average pain intensity ratings (PIRs) during the 12-months after CIH initiation (effect period, EP) were compared with the 12-months before (baseline period, BP). Through this built-in self-matching, veterans’ characteristics and other stable baseline confounding, measured and unmeasured, were presumably eliminated. After accounting for time-varying opioid use and within-subject correlations using a generalized estimating equation, we found that in comparison to the BP, the adjusted mean PIR during the EP was -0.40 (95% Confidence Interval (CI): -0.51, -0.29) points lower; while the adjusted rate ratio of moderate to severe pain (PIRs ≥ 4) was 34% lower [0.66 (95% CI: 0.62, 0.70)]. The effect sizes were greater among veterans older than 65 years, yet diminished to null after 6-9 months. Assuming a 3-month induction period, using alternative random-intercept model, and examining post-CIH opioid use as an alternative outcome, derived similar results. These observations echo some randomized trials suggesting a modest, short-term CIH benefit, and highlight the merits and usefulness of exposure-crossover design to observational studies of medical interventions.

Predictors of initiation of and retention on medications for alcohol use disorder among people living with and without HIV

INTRODUCTION

Infrequent use of and poor retention on evidence-based medications for alcohol use disorder (MAUD) represent a treatment gap, particularly among people living with HIV (PLWH). We examined predictors of MAUD initiation and retention across HIV status.

METHODS

From Veterans Aging Cohort Study (VACS) data, we identified new alcohol use disorder (AUD) diagnoses from 1998 to 2015 among 163,339 individuals (50,826 PLWH and 112,573 uninfected, matched by age, sex, and facility). MAUD initiation was defined as a prescription fill for naltrexone, acamprosate or disulfiram within 30 days of a new diagnosis. Among those who initiated, retention was defined as filling medication for ≥80% of days over the following six months. We used multivariable logistic regression to assess patient- and facility-level predictors of AUD medication initiation across HIV status.

RESULTS

Among 10,603 PLWH and 24,424 uninfected individuals with at least one AUD episode, 359 (1.0%) initiated MAUD and 49 (0.14%) were retained. The prevalence of initiation was lower among PLWH than those without HIV (adjusted odds ratio [AOR] 0.66, 95% confidence interval [CI] 0.51-0.85). Older age (for PLWH: AOR 0.78, 95% CI 0.61-0.99; for uninfected: AOR 0.70, 95% CI 0.61-0.80) and black race (for PLWH: AOR 0.63, 95% CI 0.0.49-0.1.00; for uninfected: AOR 0.63, 95% CI 0.48-0.83), were associated with decreased odds of initiation for both groups. The low frequency of retention precluded multivariable analyses for retention.

CONCLUSIONS

For PLWH and uninfected individuals, targeted implementation strategies to expand MAUD are needed, particularly for specific subpopulations (e.g. black PLWH).

Impact of Cigarette Smoking Status on Pain Intensity Among Veterans With and Without Hepatitis C

Objective

Chronic pain is a significant problem in patients living with hepatitis C virus (HCV). Tobacco smoking is an independent risk factor for high pain intensity among veterans. This study aims to examine the independent associations with smoking and HCV on pain intensity, as well as the interaction of smoking and HCV on the association with pain intensity.

Design/Particpants

Cross-sectional analysis of a cohort study of veterans of Operations Enduring Freedom/Iraqi Freedom/New Dawn (OEF/OIF/OND) who had at least one visit to a Veterans Health Administration (VHA) primary care clinic between 2001 and 2014.

Methods

HCV was identified using ICD-9 codes from electronic medical records (EMRs). Pain intensity, reported on a 0-10 numeric rating scale, was categorized as none/mild (0-3) and moderate/severe (4-10).

Results

Among 654,841 OEF/OIF/OND veterans (median age [interquartile range] = 26 [23-36] years), 2,942 (0.4%) were diagnosed with HCV. Overall, moderate/severe pain intensity was reported in 36% of veterans, and 37% were current smokers. The adjusted odds of reporting moderate/severe pain intensity were 1.23 times higher (95% confidence interval [CI] = 1.14-1.33) for those with HCV and 1.26 times higher (95% CI = 1.25-1.28) for current smokers. In the interaction model, there was a significant Smoking Status × HCV interaction (P = 0.03). Among veterans with HCV, smoking had a significantly larger association with moderate/severe pain (adjusted odds ratio [OR] = 1.50, P < 0.001) than among veterans without HCV (adjusted OR = 1.26, P < 0.001).

Conclusions

We found that current smoking is more strongly linked to pain intensity among veterans with HCV. Further investigations are needed to explore the impact of smoking status on pain and to promote smoking cessation and pain management in veterans with HCV.

Project STEP: Implementing the Veterans Health Administration's Stepped Care Model of Pain Management

Objective

The "stepped care model of pain management" (SCM-PM) prioritizes the role of primary care providers in optimizing pharmacological management and timely and equitable access to patient-centered, evidence-based nonpharmacological approaches, when indicated. Over the past several years, the Veterans Health Administration (VHA) has supported implementation of SCM-PM, but few data exist regarding changes in pain care resulting from implementation. We examined trends in prescribing and referral practices of primary care providers with hypotheses of decreased opioid prescribing, increased nonopioid prescribing, and increased referrals to specialty care for nonpharmacological services.

Design

An initiative was designed to foster implementation and systematic evaluation of the SCM-PM over a five-year period at the VA Connecticut Healthcare System (VACHS) while fostering collaborative, partnered initiatives to promote organizational improvements in the delivery of pain care.

Subjects

Participants were veterans receiving care at VACHS with at least one pain intensity rating ≥4/10 over the course of the study period (7/2008-6/2013).

Methods

We used electronic health record data to examine changes in indicators of pain care including pharmacy and health care utilization data.

Results

We observed hypothesized changes in long-term opioid and nonopioid analgesic prescribing and increased utilization of nonpharmacological treatments such as physical therapy, occupational therapy, and clinical health psychology.

Conclusions

Through a multifaceted comprehensive implementation approach, primary care providers demonstrated increases in guideline-concordant pain care practices. Findings suggest that engagement of interdisciplinary teams and partnerships to promote organizational improvements is a useful strategy to increase the use of integrated, multimodal pain care for veterans, consistent with VHA's SCM-PM.

Development and Assessment of a Crosswalk Between ICD-9-CM and ICD-10-CM to Identify Patients with Common Pain Conditions

Effective management of patients with pain requires accurate information about the prevalence, outcomes, and co-occurrence of common pain conditions. However, the transition from ICD-9-CM to ICD-10-CM diagnostic coding in 2015 left researchers without methods for comparing the prevalence of pain conditions before and after the transition. In this study, we developed and assessed a diagnostic framework to serve as a crosswalk between ICD-9-CM and ICD-10-CM diagnosis codes for common pain-related health conditions. We refined existing ICD-9-CM definitions for diagnostic clusters of common pain conditions consistent with the US National Pain Strategy and developed corresponding ICD-10-CM definitions. We then assessed the stability of prevalence estimates and associated patient socio-demographic features of each diagnostic cluster during 1-year periods before and after the transition to ICD-10-CM in 3 US health care systems using electronic health records data for in-person encounters. Prevalence estimates and socio-demographic characteristics were similar before and after the transition. The Pain Condition ICD-9-CM to ICD-10-CM Crosswalk includes a full spectrum of common pain conditions to enable prevalence estimates of multiple and chronic overlapping pain conditions. This allows the tool to serve as a foundation for a broad array of pain-related health services research utilizing electronic databases. PERSPECTIVE: This article details the development and assessment of the Pain Condition ICD-9-CM to ICD-10-CM Crosswalk, a diagnostic framework for assessing pain condition prevalence across the ICD-9-CM to ICD-10-CM transition. This framework can serve as a standardized tool for research on pain conditions, including health services and epidemiologic research.

Depression and all-cause mortality risk in HIV-infected and HIV-uninfected US veterans: a cohort study

OBJECTIVES

The contribution of depression to mortality in adults with and without HIV infection is unclear. We hypothesized that depression increases mortality risk and that this association is stronger among those with HIV infection.

METHODS

Veterans Aging Cohort Study (VACS) data were analysed from the first clinic visit on or after 1 April 2003 (baseline) to 30 September 2015. Depression definitions were: (1) major depressive disorder defined using International Classification of Diseases, Ninth Revision (ICD-9) codes; (2) depressive symptoms defined as Patient Health Questionnaire (PHQ)-9 scores ≥ 10. The outcome was all-cause mortality. Covariates were demographics, comorbid conditions and health behaviours.

RESULTS

Among 129 140 eligible participants, 30% had HIV infection, 16% had a major depressive disorder diagnosis, and 24% died over a median follow-up time of 11 years. The death rate was 25.3 [95% confidence interval (CI) 25.0-25.6] deaths per 1000 person-years. Major depressive disorder was associated with mortality [hazard ratio (HR) 1.04; 95% CI 1.01, 1.07]. This association was modified by HIV status (interaction P-value = 0.02). In HIV-stratified analyses, depression was significantly associated with mortality among HIV-uninfected veterans but not among those with HIV infection. Among those with PHQ-9 data (n = 7372), 50% had HIV infection, 22% had PHQ-9 scores ≥ 10, and 28% died over a median follow-up time of 12 years. The death rate was 27.3 (95% CI 26.1-28.5) per 1000 person-years. Depressive symptoms were associated with mortality (HR 1.16; 95% CI 1.04, 1.28). This association was modified by HIV status (interaction P-value = 0.05). In HIV-stratified analyses, depressive symptoms were significantly associated with mortality among veterans with HIV infection but not among those without HIV infection.

CONCLUSIONS

Depression was associated with all-cause mortality. This association was modified by HIV status and method of depression ascertainment.

Evaluation of Complementary and Integrative Health Approaches Among US Veterans with Musculoskeletal Pain Using Propensity Score Methods

Objectives

To examine the treatment effectiveness of complementary and integrative health approaches (CIH) on chronic pain using Propensity Score (PS) methods.

Design, Settings, and Participants

A retrospective cohort of 309,277 veterans with chronic musculoskeletal pain assessed over three years after initial diagnosis.

Methods

CIH exposure was defined as one or more clinical visits for massage, acupuncture, or chiropractic care. The treatment effect of CIH on self-rated pain intensity was examined using a longitudinal model. PS-matching and inverse probability of treatment weighting (IPTW) were used to account for potential selection and confounding biases.

Results

At baseline, veterans with (7,621) and without (301,656) CIH exposure differed significantly in 21 out of 35 covariates. During the follow-up period, on average CIH recipients had 0.83 (95% confidence interval [CI] = 0.77 to 0.89) points higher pain intensity ratings (range = 0-10) than nonrecipients. This apparent unfavorable effect size was reduced to 0.37 (95% CI = 0.28 to 0.45) after PS matching, 0.36 (95% CI = 0.29 to 0.44) with IPTW on the treated (IPTW-T) weighting, and diminished to null when integrating IPTW-T with PS matching (0.004, 95% CI = -0.09 to 0.10). An alternative IPTW model and conventional covariate adjustment appeared least powerful in terms of potential bias reduction. Sensitivity analyses restricting the follow-up period to one year after CIH initiation derived consistent results.

Conclusions

PS-based causal methods successfully eliminated baseline difference between exposure groups in all measured covariates, yet they did not detect a significant difference in the self-rated pain intensity outcome between veterans who received CIHs and those who did not during the follow-up period.

Patterns of Alcohol Use Among Patients Living With HIV in Urban, Large Rural, and Small Rural Areas

BACKGROUND

For people living with HIV (PLWH), alcohol use is harmful and may be influenced by unique challenges faced by PLWH living in rural areas. We describe patterns of alcohol use across rurality among PLWH.

METHODS

Veterans Aging Cohort Study electronic health record data were used to identify patients with HIV (ICD-9 codes for HIV or AIDS) who completed AUDIT-C alcohol screening between February 1, 2008, and September 30, 2014. Regression models estimated and compared 4 alcohol use outcomes (any use [AUDIT-C > 0] and alcohol use disorder [AUD; ICD-9 codes for abuse or dependence] diagnoses among all PLWH, and AUDIT-C risk categories: lower- [1-3 men/1-2 women], moderate- [4-5 men/3-5 women], higher- 6-7]), and severe-risk [8-12], and heavy episodic drinking (HED; ≥1 past-year occasion) among PLWH reporting use) across rurality (urban, large rural, small rural) and census-defined region.

FINDINGS

Among 32,699 PLWH (29,540 urban, 1,301 large rural, and 1,828 small rural), both any alcohol use and AUD were highest in urban areas, although this varied across region. Predicted prevalence of any alcohol use was 54.1% (53.5%-54.7%) in urban, 49.6% (46.9%-52.3%) in large rural, and 50.6% (48.3%-52.9%) in small rural areas (P < .01). Predicted prevalence of AUD was 14.4% (14.0%-14.8%) in urban, 11.8% (10.0%-13.5%) in large rural, and 12.3% (10.8%-13.8%) in small rural areas (P < .01). Approximately 12% and 25% had higher- or severe-risk drinking and HED, respectively, but neither differed across rurality.

CONCLUSION

Though some variation across rurality and region was observed, alcohol-related interventions are needed for PLWH across all geographic locations.

Dual Use of Department of Veterans Affairs and Medicare Benefits on High-Risk Opioid Prescriptions in Veterans Aged 65 Years and Older: Insights from the VA Musculoskeletal Disorders Cohort

OBJECTIVE

To examine the association of dual use of both Veterans Health Administration (VHA) and Medicare benefits with high-risk opioid prescriptions among Veterans aged 65 years and older with a musculoskeletal disorder diagnosis.

DATA SOURCES/STUDY SETTING

Data were obtained from the VA Musculoskeletal Disorder (MSD) cohort and national Medicare claims data from 2008 to 2010.

STUDY DESIGN

We conducted a retrospective analysis of Veterans enrolled in Medicare to examine the association of dual use with long-term opioid use (>90 days of prescription opioids/year) and overlapping opioid prescriptions. Multivariable logistic regression was performed adjusting for demographic and clinical characteristics.

DATA COLLECTION/EXTRACTION METHODS

We identified 21,111 Veterans enrolled in Medicare who entered the MSD cohort in 2008 and received an opioid prescription in 2010. We linked VHA data with Medicare claims data to identify opioid prescriptions for these Veterans in 2010.

PRINCIPAL FINDINGS

As compared to Veterans who used only VHA or Medicare, Veterans with dual use of VHA and Medicare were significantly more likely to be prescribed long-term opioid therapy (OR = 4.61 (95 percent CI 4.05-5.25) and were also found to have higher median number of opioid prescriptions and higher odds of overlapping opioid prescriptions in 1 year. Patients reporting moderate-to-severe pain, non-white-race/ethnicity, and higher scoring on the Charlson comorbidity index had significantly higher odds of long-term opioid prescriptions.

CONCLUSIONS

Among Veterans aged 65 years or older, dual use of both VHA and Medicare was associated with higher odds of long-term opioid therapy. Our findings suggest there may be benefit to combining VHA and non-VHA electronic health record data to minimize exposure to high-risk opioid prescribing.

Relationships Between Temporomandibular Disorders, MSD Conditions, and Mental Health Comorbidities: Findings from the Veterans Musculoskeletal Disorders Cohort

Objective

Temporomandibular disorders (TMDs) have been associated with other chronic painful conditions (e.g., fibromyalgia, headache) and suicide and mood disorders. Here we examined musculoskeletal, painful, and mental health comorbidities in men vs women veterans with TMD (compared with non-TMD musculoskeletal disorders [MSDs] cases), as well as comorbidity patterns within TMD cases.

Design

Observational cohort.

Setting

National Veterans Health Administration.

Subjects

A cohort of 4.1 million veterans having 1+ MSDs, entering the cohort between 2001 and 2011.

Methods

Chi-square tests, t tests, and logistic regression were utilized for cross-sectional analysis.

Results

Among veterans with any MSD, those with TMD were younger and more likely to be women. The association of TMD with race/ethnicity differed by sex. Odds of TMD were higher in men of Hispanic ethnicity (OR = 1.38, 95% CI = 1.27-1.48) and nonwhite race/ethnicity other than black or Hispanic (OR = 1.29, 95% CI = 1.16-1.45) compared with white men. Odds of TMD were significantly lower for black (OR = 0.54, 95% CI = 0.49-0.60) and Hispanic women (OR = 0.84, 95% CI = 0.73-0.995) relative to white women. Non-MSD comorbidities (e.g., irritable bowel syndrome, mental health, headaches) were significantly associated with TMD in male veterans; their pattern was similar in women. Veterans with back pain, nontraumatic joint disorder, or osteoarthritis had more MSD multimorbidity than those with TMD.

Conclusions

Complex patterns of comorbidity in TMD cases may indicate different underlying mechanisms of association in subgroups or phenotypes, thereby suggesting multiple targets to improve TMD. Longitudinal comprehensive studies powered to look at sex and racial/ethnic groupings are needed to identify targets to personalize care.

Examining Gender as a Correlate of Self-Reported Pain Treatment Use Among Recent Service Veterans with Deployment-Related Musculoskeletal Disorders

Objective

Women veterans with chronic pain utilize health care with greater frequency than their male counterparts. However, little is known about gender differences in the use of specialty pain care in this population. This investigation examined gender differences in self-reported use of opioids, interventional pain treatments, rehabilitation therapies, and complementary and integrative health (CIH) services for chronic pain treatment both within and outside of the Veterans Health Administration in a sample of veterans who served in support of recent conflicts.

Methods

Participants included 325 veterans (54% women) who completed a baseline survey as part of the Women Veterans Cohort Study and reported deployment-related musculoskeletal conditions and chronic pain. Measures included self-reported use of pain treatment modalities, pain severity, self-rated health, access to specialty care, disability status, and presence of a mental health condition.

Results

Men were more likely to report a persistent deployment-related musculoskeletal condition but were no more likely than women to report chronic pain. Overall, 21% of the sample reported using opioids, 27% used interventional strategies, 59% used rehabilitation therapies, and 57% used CIH services. No significant gender differences in use of any pain treatment modality were observed.

Conclusions

Use of pain specialty services was common among men and women, particularly rehabilitative and CIH services. There were no gender differences in the self-reported use of different modalities. These results are inconsistent with documented gender differences in pain care. They encourage further examination of gender differences in preferences and other individual difference variables as predictors of specialty pain care utilization.

Cigarette Smoking Status and Receipt of an Opioid Prescription Among Veterans of Recent Wars

Objective

Cigarette smokers seeking treatment for chronic pain have higher rates of opioid use than nonsmokers. This study aims to examine whether veterans of Operations Enduring Freedom/Iraqi Freedom/New Dawn (OEF/OIF/OND) who smoke are more likely to receive an opioid prescription than nonsmokers, adjusting for current pain intensity.

Design

Cross-sectional analysis of a cohort study of OEF/OIF/OND veterans who had at least one visit to a Veterans Health Administration primary care clinic between 2001 and 2012.

Methods

Smoking status was defined as current, former, and never. Current pain intensity (+/- 30 days of smoking status), based on the 0-10 numeric rating scale, was categorized as no pain/mild (0-3) and moderate/severe (4-10). Opioid receipt was defined as at least one prescription filled +/- 30 days of smoking status.

Results

We identified 406,954 OEF/OIF/OND veterans: The mean age was 30 years, 12.5% were women (n = 50,988), 66.3% reported no pain or mild pain intensity, 33.7% reported moderate or severe pain intensity, 37.2% were current smokers, and 16% were former smokers. Overall, 33,960 (8.3%) veterans received one or more opioid prescription. Current smoking (odds ratio [OR] = 1.56, 95% confidence interval [CI] = 1.52-1.61) and former smoking (OR = 1.27, 95% CI = 1.22-1.32) were associated with a higher likelihood of receipt of an opioid prescription compared with never smoking, after controlling for other covariates.

Conclusions

We found an association between smoking status and receipt of an opioid prescription. The effect was stronger for current smokers than former smokers, highlighting the need to determine whether smoking cessation is associated with a reduction in opioid use among veterans.

Posttraumatic stress disorder diagnosis and gender are associated with accelerated weight gain trajectories in veterans during the post-deployment period

BACKGROUND

Veterans are disproportionately affected by overweight/obesity and growing evidence suggests that post-deployment is a critical period of accelerated weight gain.

OBJECTIVE

We explored the relationship between posttraumatic stress disorder (PTSD) diagnosis, gender, and post-deployment weight trajectories among U.S. Operations Iraqi Freedom, Enduring Freedom, and New Dawn veterans.

DESIGN

We used Veterans Affairs electronic health record data from 248,089 veterans (87% men) who, after their last deployment, had at least one medical visit between October 2001 and January 2009 and more than one BMI recorded through September 2010. We analyzed repeated BMI measurements using linear mixed models, with demographics, PTSD and other relevant psychiatric diagnoses as predictors.

RESULTS

At the first recorded BMI, veterans' median age was 29, and 59% of women and 77% of men were overweight/obese. They had a median of 6 BMI measurements during a median follow-up of 2.4 years. Controlling for potential confounders, women with a PTSD diagnosis had a yearly BMI growth rate of 0.11 kg/m² (95% CI 0.09 to 0.13, p < 0.001) higher than women without PTSD. For men, the corresponding PTSD effect was also significant, but slightly lower: 0.07 kg/m² ((95% CI 0.05 to 0.09, p < 0.001); women-men difference: 0.03 (95% CI 0.01 to 0.06) kg/m², p = 0.006).

CONCLUSIONS

The post-deployment period is critical for weight gain, particularly for veterans diagnosed with PTSD and women veterans with PTSD. Efforts are needed to engage post-deployment veterans in weight management services, and to determine whether tailored recruitment/treatment interventions will reduce disparities for veterans with PTSD.

Discontinuing a non-steroidal anti-inflammatory drug (NSAID) in patients with knee osteoarthritis: Design and protocol of a placebo-controlled, noninferiority, randomized withdrawal trial

BACKGROUND

Knee osteoarthritis (OA) is the most common cause of knee pain in older adults. Despite the limited data supporting their use, non-steroidal anti-inflammatory drugs (NSAID) are among the most commonly prescribed medications for knee OA. The use of NSAIDs for knee pain warrants careful examination because of toxicity associated with this class of medications.

METHODS

We describe the design of a placebo-controlled, noninferiority, randomized withdrawal trial to examine discontinuation of an NSAID in patients with painful knee OA. Participants will be veterans enrolled in the VA Healthcare System with knee OA pain despite NSAID use and/or relatively higher risk of NSAID toxicity. After a two-week run-in period where eligible subjects will replace their current NSAID with the study NSAID (meloxicam), those remaining eligible (target N=544) will be randomized to receive four weeks of either placebo or continued meloxicam. The primary outcome is knee pain (Western Ontario and McMaster Universities Osteoarthritis Index pain subscale, range 0-20) at four weeks post-randomization. The primary hypothesis is that placebo will be noninferior to (that is, not much worse than) meloxicam within a noninferiority margin of 1. Secondary outcomes include lower extremity disability, global impression of change, adherence to study medication and use of co-therapies.

DISCUSSION

This study is the first clinical trial to date examining the effects of withdrawing an NSAID for OA knee pain. If successful, this trial will provide evidence against the continued use of NSAIDs in patients with OA knee pain.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01799213. Registered February 22, 2013.

Racial and Ethnic Differences in Total Knee Arthroplasty in the Veterans Affairs Health Care System, 2001-2013

OBJECTIVE

To examine black-white and Hispanic-white differences in total knee arthroplasty from 2001 to 2013 in a large cohort of patients diagnosed with osteoarthritis (OA) in the Veterans Affairs (VA) health care system.

METHODS

Data were from the VA Musculoskeletal Disorders cohort, which includes data from electronic health records of more than 5.4 million veterans with musculoskeletal disorders diagnoses. We included white (non-Hispanic), black (non-Hispanic), and Hispanic (any race) veterans, age ≥50 years, with an OA diagnosis from 2001-2011 (n = 539,841). Veterans were followed from their first OA diagnosis until September 30, 2013. As a proxy for increased clinical severity, analyses were also conducted for a subsample restricted to those who saw an orthopedic or rheumatology specialist (n = 148,844). We used Cox proportional hazards regression to examine racial and ethnic differences in total knee arthroplasty by year of OA diagnosis, adjusting for age, sex, body mass index, physical and mental diagnoses, and pain intensity scores.

RESULTS

We identified 12,087 total knee arthroplasty procedures in a sample of 473,170 white, 50,172 black, and 16,499 Hispanic veterans. In adjusted models examining black-white and Hispanic-white differences by year of OA diagnosis, total knee arthroplasty rates were lower for black than for white veterans diagnosed in all but 2 years. There were no Hispanic-white differences regardless of when diagnosis occurred. These patterns held in the specialty clinic subsample.

CONCLUSION

Black-white differences in total knee arthroplasty appear to be persistent in the VA, even after controlling for potential clinical confounders.

Interactive Voice Response-Based Self-management for Chronic Back Pain: The COPES Noninferiority Randomized Trial

IMPORTANCE

Recommendations for chronic pain treatment emphasize multimodal approaches, including nonpharmacologic interventions to enhance self-management. Cognitive behavioral therapy (CBT) is an evidence-based treatment that facilitates management of chronic pain and improves outcomes, but access barriers persist. Cognitive behavioral therapy delivery assisted by health technology can obviate the need for in-person visits, but the effectiveness of this alternative to standard therapy is unknown. The Cooperative Pain Education and Self-management (COPES) trial was a randomized, noninferiority trial comparing IVR-CBT to in-person CBT for patients with chronic back pain.

OBJECTIVE

To assess the efficacy of interactive voice response-based CBT (IVR-CBT) relative to in-person CBT for chronic back pain.

DESIGN, SETTING, AND PARTICIPANTS

We conducted a noninferiority randomized trial in 1 Department of Veterans Affairs (VA) health care system. A total of 125 patients with chronic back pain were equally allocated to IVR-CBT (n = 62) or in-person CBT (n = 63).

INTERVENTIONS

Patients treated with IVR-CBT received a self-help manual and weekly prerecorded therapist feedback based on their IVR-reported activity, coping skill practice, and pain outcomes. In-person CBT included weekly, individual CBT sessions with a therapist. Participants in both conditions received IVR monitoring of pain, sleep, activity levels, and pain coping skill practice during treatment.

MAIN OUTCOMES AND MEASURES

The primary outcome was change from baseline to 3 months in unblinded patient report of average pain intensity measured by the Numeric Rating Scale (NRS). Secondary outcomes included changes in pain-related interference, physical and emotional functioning, sleep quality, and quality of life at 3, 6, and 9 months. We also examined treatment retention.

RESULTS

Of the 125 patients (97 men, 28 women; mean [SD] age, 57.9 [11.6] years), the adjusted average reduction in NRS with IVR-CBT (-0.77) was similar to in-person CBT (-0.84), with the 95% CI for the difference between groups (-0.67 to 0.80) falling below the prespecified noninferiority margin of 1 indicating IVR-CBT is noninferior. Fifty-four patients randomized to IVR-CBT and 50 randomized to in-person CBT were included in the analysis of the primary outcome. Statistically significant improvements in physical functioning, sleep quality, and physical quality of life at 3 months relative to baseline occurred in both treatments, with no advantage for either treatment. Treatment dropout was lower in IVR-CBT with patients completing on average 2.3 (95% CI, 1.0-3.6) more sessions.

CONCLUSIONS AND RELEVANCE

IVR-CBT is a low-burden alternative that can increase access to CBT for chronic pain and shows promise as a nonpharmacologic treatment option for chronic pain, with outcomes that are not inferior to in-person CBT.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT01025752.

Trends in diagnosis of painful neck and back conditions, 2002 to 2011

Neck and back pain are pervasive problems. Some have suggested that rising incidence may be associated with the evidence of rising prevalence.To describe the trends in diagnosis of painful neck and back conditions in a large national healthcare system.A retrospective observational cohort study to describe the incidence and prevalence of diagnosis of neck and back pain in a national cohort.Patients were identified by International Classification of Diseases, 9 Revision (ICD-9) codes in Department of Veterans Affairs (VA) national utilization datasets in calendar years 2002 to 2011.Descriptive statistics were used to analyze the data. Prevalent cases were compared with all veterans who sought health care in each year. Incident cases were identified following a 2 years clean period in which the patient was enrolled and received care, but not services for any back or neck pain conditions.From 2004 to 2011, 3% to 4% of the population was diagnosed with incident back pain problems, the rate increasing on average, 1.75% per year. During the same period, 12.3% to 16.2% of the population was diagnosed with a prevalent back pain problem, the rate increasing on average 4.09% per year.In a national population, the prevalence rate for diagnosis of neck and back pain grew 1.8 to 2.3 times faster than the incidence rate. This suggests that the average duration of episodes of care is increasing. Additional research is needed to understand the influences on the differential rate of change and to develop efficient and effective care systems.

Minority Men Who Have Sex with Men Demonstrate Increased Risk for HIV Transmission

Black and Hispanic (minority) MSM have a higher incidence of HIV than white MSM. Multiple sexual partners, being under the influence of drugs and/or alcohol during sex, having a detectable HIV-1 RNA, and non-condom use are factors associated with HIV transmission. Using data from the Veterans Aging Cohort Study, we consider minority status and sexual orientation jointly to characterize and compare these factors. White non-MSM had the lowest prevalence of these factors (p < 0.001) and were used as the comparator group in calculating odds ratios (OR). Both MSM groups were more likely to report multiple sex partners (white MSM OR 7.50; 95 % CI 5.26, 10.71; minority MSM OR 10.24; 95 % CI 7.44, 14.08), and more likely to be under the influence during sex (white MSM OR 2.15; 95 % CI 1.49, 3.11; minority MSM OR 2.94; 95 % CI 2.16, 4.01). Only minority MSM were more likely to have detectable HIV-1 RNA (OR 1.87; 95 % CI 1.12, 3.11). Both MSM groups were more likely to use condoms than white non-MSM. These analyses suggest that tailored interventions to prevent HIV transmission among minority MSM are needed, with awareness of the potential co-occurrence of risk factors.