We estimated the prevalence and incidence of gender identity disorder (GID) diagnoses among veterans in the Veterans Health Administration (VHA) health care system and examined suicide risk among ...veterans with a GID diagnosis.
We examined VHA electronic medical records from 2000 through 2011 for 2 official ICD-9 diagnosis codes that indicate transgender status. We generated annual period prevalence estimates and calculated incidence using the prevalence of GID at 2000 as the baseline year. We cross-referenced GID cases with available data (2009-2011) of suicide-related events among all VHA users to examine suicide risk.
GID prevalence in the VHA is higher (22.9/100 000 persons) than are previous estimates of GID in the general US population (4.3/100 000 persons). The rate of suicide-related events among GID-diagnosed VHA veterans was more than 20 times higher than were rates for the general VHA population.
The prevalence of GID diagnosis nearly doubled over 10 years among VHA veterans. Research is needed to examine suicide risk among transgender veterans and how their VHA utilization may be enhanced by new VA initiatives on transgender care.
There are many statistics available to the applied statistician for assessing model fit and even more methods for assessing internal and external validity. We detail a useful approach using a grid ...search technique that balances the internal model consistency with generalizability and can be used with models that naturally lend themselves to multiple assessment techniques. Our method relies on resampling and a simple grid search method over 3 commonly used statistics that are simple to calculate. We apply this method in a latent traits framework using a mixture Item Response Theory (MIXIRT) model of common chronic health conditions. Model fit is assessed using Akaike's Information Criteria (AIC), latent class similarity is measured with the Variance of Information (VI), and the consistency of condition complexity and prevalence across latent classes is compared using Kendall's τ rank order statistic. From two patient cohorts at high risk for hospitalization in 2014 and 2018, we generated 19 MIXIRT models (allowing 2-20 latent classes) on 21 common comorbid conditions identified via healthcare encounter diagnosis codes. We ran these models on 100 bootstrap samples of size 10% for each cohort. Among the resulting models, combined AIC and VI statistics identified 5-7 latent classes, but the rank order correlation of condition complexity revealed that only the 5 class solutions had consistent condition complexity. The 5 class solutions were combined to produce a single parsimonious MIXIRT solution that balanced clinical significance with model fit, cluster similarity, and consistency of condition complexity.
Objective
Many healthcare systems employ population-based risk scores to prospectively identify patients at high risk of poor outcomes, but it is unclear whether single point-in-time scores ...adequately represent future risk. We sought to identify and characterize latent subgroups of high-risk patients based on risk score trajectories.
Study Design
Observational study of 7289 patients discharged from Veterans Health Administration (VA) hospitals during a 1-week period in November 2012 and categorized in the top 5th percentile of risk for hospitalization.
Methods
Using VA administrative data, we calculated weekly risk scores using the validated Care Assessment Needs model, reflecting the predicted probability of hospitalization. We applied the non-parametric k-means algorithm to identify latent subgroups of patients based on the trajectory of patients’ hospitalization probability over a 2-year period. We then compared baseline sociodemographic characteristics, comorbidities, health service use, and social instability markers between identified latent subgroups.
Results
The best-fitting model identified two subgroups: moderately high and persistently high risk. The moderately high subgroup included 65% of patients and was characterized by moderate subgroup-level hospitalization probability decreasing from 0.22 to 0.10 between weeks 1 and 66, then remaining constant through the study end. The persistently high subgroup, comprising the remaining 35% of patients, had a subgroup-level probability increasing from 0.38 to 0.41 between weeks 1 and 52, and declining to 0.30 at study end. Persistently high-risk patients were older, had higher prevalence of social instability and comorbidities, and used more health services.
Conclusions
On average, one third of patients initially identified as high risk stayed at very high risk over a 2-year follow-up period, while risk for the other two thirds decreased to a moderately high level. This suggests that multiple approaches may be needed to address high-risk patient needs longitudinally or intermittently.
Evidence has suggested increased risk for homelessness and suicide among US veterans, but little is known about the associations between housing instability and psychological distress (including ...suicidal ideation). We examined frequent mental distress (FMD) and suicidal ideation among a probability-based sample of 1767 Nebraska veterans who participated in the 2010 Behavioral Risk Factor Surveillance Survey who had and had not experienced housing instability in the past 12 months. Veterans experiencing housing instability had increased odds of FMD and suicidal ideation.
Objective
To examine associations between clinics’ extent of patient‐centered medical home (PCMH) implementation and improvements in chronic illness care quality.
Data Source
Data from 808 Veterans ...Health Administration (VHA) primary care clinics nationwide implementing the Patient Aligned Care Teams (PACT) PCMH initiative, begun in 2010.
Design
Clinic‐level longitudinal observational study of clinics that received training and resources to implement PACT. Clinics varied in the extent they had PACT components in place by 2012.
Data Collection
Clinical care quality measures reflecting intermediate outcomes and care processes related to coronary artery disease (CAD), diabetes, and hypertension care were collected by manual chart review at each VHA facility from 2009 to 2013.
Findings
In adjusted models containing 808 clinics, the 77 clinics with the most PACT components in place had significantly larger improvements in five of seven chronic disease intermediate outcome measures (e.g., BP < 160/100 in diabetes), ranging from 1.3 percent to 5.2 percent of the patient population meeting measures, and two of eight process measures (HbA1c measurement, LDL measurement in CAD) than the 69 clinics with the least PACT components. Clinics with moderate levels of PACT components showed few significantly larger improvements than the lowest PACT clinics.
Conclusions
Veterans Health Administration primary care clinics with the most PCMH components in place in 2012 had greater improvements in several chronic disease quality measures in 2009–2013 than the lowest PCMH clinics.
In the United States, suicide rates are increasing among nearly all age groups. Primary care is a critical setting for suicide prevention, where interventions often rely on identifying mental health ...conditions as indicators of elevated suicide risk.
Quantify the proportion of suicide decedents within primary care who had no antecedent mental health or substance use diagnosis.
Retrospective cohort study.
Veterans who received Veterans Health Administration (VHA) primary care any time from 2000 to 2014 and died by suicide before 2015 (n = 27,741).
We categorized decedents by whether they had any mental health or substance use diagnosis (yes/no) using ICD-9 codes available from VHA records. We compared sociodemographic, clinical, and suicide mechanism characteristics between groups using chi-square, Student's T, or Wilcoxon tests.
Forty-five percent of decedents had no mental health or substance use diagnosis. Decedents without such a diagnosis were older (68 vs. 57 years, p < 0.001), and more likely to be male (98.3% vs. 95.8%, p < 0.001), non-Hispanic White (90.6% vs. 87.9%, p < 0.001), married/partnered (50.4% vs. 36.6%, p < 0.001), and without military service-connected disability benefits (72.6% vs. 56.9%, p < 0.001). They were also more likely to die from firearm injury (78.9% vs. 60.7%, p < 0.001). There were statistically significant differences in physical health between groups, but the magnitudes of those differences were small. Decedents without a mental health or substance use diagnosis had significantly shorter durations of enrollment in VHA healthcare, less healthcare utilization in their last year of life, and had little utilization aside from primary care visits.
From 2000 to 2014, of nearly thirty thousand VHA primary care patients who died by suicide, almost half had no antecedent mental health or substance use diagnosis. Within VHA primary care settings, suicide risk screening for those with and without such a diagnosis is indicated.
The relationships between military service and suicide are not clear, and comparatively little is known about the characteristics and correlates of suicide ideation and attempts among those with ...history of military service. We used data from a national health survey to estimate the prevalence and correlates of suicidal behaviors among veterans and service members in 2 states. The prevalence of suicidal behaviors among Veterans was similar to previous estimates of ideation and attempts among adults in the US general population.
Background
Premature mortality observed among the mentally ill is largely attributable to chronic illnesses. Veterans seen within Veterans Affairs (VA) have a higher prevalence of mental illness than ...the general population but there is limited investigation into the common causes of death of Veterans with mental illnesses.
Objective
To characterize the life expectancy of mentally ill Veterans seen in VA primary care, and to determine the most death rates of combinations of mental illnesses.
Design
Retrospective cohort study of decedents.
Setting/Participants
Veterans seen in VA primary care clinics between 2000 and 2011 were included. Records from the VA Corporate Data Warehouse (CDW) were merged with death information from the National Death Index.
Main Measures
Mental illnesses were determined using ICD9 codes. Direct standardization methods were used to calculate age-adjusted gender and cause-specific death rates per 1000 deaths for patients with and without depression, anxiety, post-traumatic stress disorder (PTSD), substance use disorder (SUD), serious mental illness (SMI), and combinations of those diagnoses.
Key Results
Of the 1,763,982 death records for Veterans with 1 + primary care visit, 556,489 had at least one mental illness. Heart disease and cancer were the two leading causes of death among Veterans with or without a mental illness, accounting for approximately 1 in 4 deaths. Those with SUD (
n
= 204,950) had the lowest mean age at time of death (64 ± 12 years). Among men, the death rates were as follows: SUD (55.9/1000); anxiety (49.1/1000); depression (45.1/1000); SMI (40.3/1000); and PTSD (26.2/1000). Among women, death rates were as follows: SUD (55.8/1000); anxiety (36.7/1000); depression (45.1/1000); SMI (32.6/1000); and PTSD (23.1/1000 deaths). Compared to men (10.8/1000) and women (8.7/1000) without a mental illness, these rates were multiple-fold higher in men and in women with a mental illness. A greater number of mental illness diagnoses was associated with higher death rates among men and women (
p
< 0.0001).
Conclusions
Veterans with mental illnesses, particularly those with SUD, and those with multiple diagnoses, had shorter life expectancy than those without a mental illness. Future studies should examine both patient and systemic sources of disparities in providing chronic illness care to Veterans with a mental illness.
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