The Impact of Medication-Based Risk Adjustment on the Association Between Veteran Health Outcomes and Dual Health System Use

The impact of dual VA-Medicare use on a data-driven clinical management tool for older Veterans with multimorbidity

BACKGROUND

Healthcare systems are increasingly turning to data-driven approaches, such as clustering techniques, to inform interventions for medically complex older adults. However, patients seeking care in multiple healthcare systems may have missing diagnoses across systems, leading to misclassification of resulting groups. We evaluated the impact of multi-system use on the accuracy and composition of multimorbidity groups among older adults in the Veterans Health Administration (VA).

METHODS

Eligible patients were VA primary care users aged ≥65 years and in the top decile of predicted 1-year hospitalization risk in 2018 (n = 558,864). Diagnoses of 26 chronic conditions were coded using a 24-month lookback period and input into latent class analysis (LCA) models. In a random 10% sample (n = 56,008), we compared the resulting model fit, class profiles, and patient assignments from models using only VA system data versus VA with Medicare data.

RESULTS

LCA identified six patient comorbidity groups using VA system data. We labeled groups based on diagnoses with higher within-group prevalence relative to the average: Substance Use Disorders (7% of patients), Mental Health (15%), Heart Disease (22%), Diabetes (16%), Tumor (14%), and High Complexity (10%). VA with Medicare data showed improved model fit and assigned more patients with high accuracy. Over 70% of patients assigned to the Substance, Mental Health, High Complexity, and Tumor groups using VA data were assigned to the same group in VA with Medicare data. However, 41.9% of the Heart Disease group and 14.7% of the Diabetes group were reassigned to a new group characterized by multiple cardiometabolic conditions.

CONCLUSIONS

The addition of Medicare data to VA data for older high-risk adults improved clustering model accuracy and altered the clinical profiles of groups. Accessing or accounting for multi-system data is key to the success of interventions based on empiric grouping in populations with dual-system use.

Medicaid Expansion and Veterans' Reliance on the VA for Depression Care

Background

In 2001, before the Affordable Care Act (ACA), some states expanded Medicaid coverage to include an array of mental health services, changing veterans' reliance on US Department of Veterans Affairs (VA) services.

Methods

Using Medicaid and VA administrative data from 1999 to 2006, we used a difference-in-difference design to calculate shifts in veterans' reliance on the VA for depression care in New York and Arizona after the 2 states expanded Medicaid coverage to adults in 2001. Demographically matched, neighbor states Pennsylvania and New Mexico/Nevada were used as paired comparisons, respectively. Fractional logit was used to capture the distribution of inpatient and outpatient depression care utilization between the VA and Medicaid, while ordered logit and negative binomial regressions were applied to model Medicaid-VA dual users and per capita utilization of total depression care services, respectively.

Results

Medicaid expansion was associated with a 9.50 percentage point (pp) decrease (95% CI, -14.61 to -4.38) in reliance on the VA for inpatient depression care among service-connected veterans and a 13.37 pp decrease (95% CI, -21.12 to -5.61) among income-eligible veterans. For outpatient depression care, VA reliance decreased by 2.19 pp (95% CI, -3.46 to -0.93) among income-eligible veterans. Changes among service-connected veterans were nonsignificant (-0.60 pp; 95% CI, -1.40 to 0.21).

Conclusions

After Medicaid expansion, veterans shifted depression care away from the VA, with effects varying by health care setting, income- vs service-related eligibility, and state of residence. Issues of overall cost, care coordination, and clinical outcomes deserve further study in the ACA era of Medicaid expansions.

Latent Class Analysis of Prescribing Behavior of Primary Care Physicians in the Veterans Health Administration

BACKGROUND

Benzodiazepines, opioids, proton-pump inhibitors (PPIs), and antibiotics are frequently prescribed inappropriately by primary care physicians (PCPs), without sufficient consideration of alternative options or adverse effects. We hypothesized that distinct groups of PCPs could be identified based on their propensity to prescribe these medications.

OBJECTIVE

To identify PCP groups based on their propensity to prescribe benzodiazepines, opioids, PPIs, and antibiotics, and patient and PCP characteristics associated with identified prescribing patterns.

DESIGN

Retrospective cohort study using VA data and latent class regression analyses to identify prescribing patterns among PCPs and examine the association of patient and PCP characteristics with class membership.

PARTICIPANTS

A total of 2524 full-time PCPs and their patient panels (n = 2,939,636 patients), from January 1, 2017, to December 31, 2018.

MAIN MEASURES

We categorized PCPs based on prescribing volume quartiles for the four drug classes, based on total days' supply dispensed of each medication by the PCP to their patients (expressed as days' supply per 1000 panel patient-days). We used latent class analysis to group PCPs based on prescribing and used multinomial logistic regression to examine patient and PCP characteristics associated with latent class membership.

KEY RESULTS

PCPs were categorized into four groups (latent classes): low intensity (23% of cohort), medium-intensity overall/high-intensity PPI (36%), medium-intensity overall/high-intensity opioid (20%), and high intensity (21%). PCPs in the high-intensity group were predominantly in the highest quartile of prescribers for all four drugs (68% in the highest quartile for benzodiazepine, 86% opioids, 64% PPIs, 62% antibiotics). High-intensity PCPs (vs. low intensity) were substantially less likely to be female (OR: 0.30, 95% CI: 0.21-0.42) or practice in the northeast versus other census regions (OR: 0.10, 95% CI: 0.06-0.17).

CONCLUSIONS

VA PCPs can be classified into four clearly differentiated groups based on their prescribing of benzodiazepines, opioids, PPIs, and antibiotics, suggesting an underlying typology of prescribing. High-intensity PCPs were more likely to be male.

Evaluation of Low-Value Diagnostic Testing for 4 Common Conditions in the Veterans Health Administration

IMPORTANCE

Low-value care is associated with harm among patients and with wasteful health care spending but has not been well characterized in the Veterans Health Administration.

OBJECTIVES

To characterize the frequency of and variation in low-value diagnostic testing for 4 common conditions at Veterans Affairs medical centers (VAMCs) and to examine the correlation between receipt of low-value testing for each condition.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used Veterans Health Administration data from 127 VAMCs from fiscal years 2014 to 2015. Data were analyzed from April 2018 to March 2020.

EXPOSURES

Continuous enrollment in Veterans Health Administration during fiscal year 2015.

MAIN OUTCOMES AND MEASURES

Receipt of low-value testing for low back pain, headache, syncope, and sinusitis. For each condition, sensitive and specific criteria were used to evaluate the overall frequency and range of low-value testing, adjusting for sociodemographic and VAMC characteristics. VAMC-level variation was calculated using median adjusted odds ratios. The Pearson correlation coefficient was used to evaluate the degree of correlation between low-value testing for each condition at the VAMC level.

RESULTS

Among 1 022 987 veterans, the mean (SD) age was 60 (16) years, 1 008 336 (92.4%) were male, and 761 485 (69.8%) were non-Hispanic White. A total of 343 024 veterans (31.4%) were diagnosed with low back pain, 79 176 (7.3%) with headache, 23 776 (2.2%) with syncope, and 52 889 (4.8%) with sinusitis. With the sensitive criteria, overall and VAMC-level low-value testing frequency varied substantially across conditions: 4.6% (range, 2.7%-10.1%) for sinusitis, 12.8% (range, 8.6%-22.6%) for headache, 18.2% (range, 10.9%-24.6%) for low back pain, and 20.1% (range, 16.3%-27.7%) for syncope. With the specific criteria, the overall frequency of low-value testing across VAMCs was 2.4% (range, 1.3%-5.1%) for sinusitis, 8.6% (range, 6.2%-14.6%) for headache, 5.6% (range, 3.6%-7.7%) for low back pain, and 13.3% (range, 11.3%-16.8%) for syncope. The median adjusted odds ratio ranged from 1.21 for low back pain to 1.40 for sinusitis. At the VAMC level, low-value testing was most strongly correlated for syncope and headache (ρ = 0.56; P < .001) and low back pain and headache (ρ = 0.48; P < .001).

CONCLUSIONS AND RELEVANCE

In this cohort study, low-value diagnostic testing was common, varied substantially across VAMCs, and was correlated between veterans' receipt of different low-value tests at the VAMC level. The findings suggest a need to address low-value diagnostic testing, even in integrated health systems, with robust utilization management practices.

Use of a medication-based risk adjustment index to predict mortality among veterans dually-enrolled in VA and medicare

BACKGROUND

There is systemic undercoding of medical comorbidities within administrative claims in the Department of Veterans Affairs (VA). This leads to bias when applying claims-based risk adjustment indices to compare outcomes between VA and non-VA settings. Our objective was to compare the accuracy of a medication-based risk adjustment index (RxRisk-VM) to diagnostic claims-based indices for predicting mortality.

METHODS

We modified the RxRisk-V index (RxRisk-VM) by incorporating VA and Medicare pharmacy and durable medical equipment claims in Veterans dually-enrolled in VA and Medicare in 2012. Using the concordance (C) statistic, we compared its accuracy in predicting 1 and 3-year all-cause mortality to the following models: demographics only, demographics plus prescription count, or demographics plus a diagnostic claims-based risk index (e.g., Charlson, Elixhauser, or Gagne). We also compared models containing demographics, RxRisk-VM, and a claims-based index.

RESULTS

In our cohort of 271,184 dually-enrolled Veterans (mean age = 70.5 years, 96.1% male, 81.7% non-Hispanic white), RxRisk-VM (C = 0.773) exhibited greater accuracy in predicting 1-year mortality than demographics only (C = 0.716) or prescription counts (C = 0.744), but was less accurate than the Charlson (C = 0.794), Elixhauser (C = 0.80), or Gagne (C = 0.810) indices (all P < 0.001). Combining RxRisk-VM with claims-based indices enhanced its accuracy over each index alone (all models C ≥ 0.81). Relative model performance was similar for 3-year mortality.

CONCLUSIONS

The RxRisk-VM index exhibited a high level of, but slightly less, accuracy in predicting mortality in comparison to claims-based risk indices.

IMPLICATIONS

Its application may enhance the accuracy of studies examining VA and non-VA care and enable risk adjustment when diagnostic claims are not available or biased.

LEVEL OF EVIDENCE

Level 3.

Dual Receipt of Prescription Opioids From the Department of Veterans Affairs and Medicare Part D and Prescription Opioid Overdose Death Among Veterans: A Nested Case-Control Study

BACKGROUND

More than half of enrollees in the U.S. Department of Veterans Affairs (VA) are also covered by Medicare and can choose to receive their prescriptions from VA or from Medicare-participating providers. Such dual-system care may lead to unsafe opioid use if providers in these 2 systems do not coordinate care or if prescription use is not tracked between systems.

OBJECTIVE

To evaluate the association between dual-system opioid prescribing and death from prescription opioid overdose.

DESIGN

Nested case-control study.

SETTING

VA and Medicare Part D.

PARTICIPANTS

Case and control patients were identified from all veterans enrolled in both VA and Part D who filled at least 1 opioid prescription from either system. The 215 case patients who died of a prescription opioid overdose in 2012 or 2013 were matched (up to 1:4) with 833 living control patients on the basis of date of death (that is, index date), using age, sex, race/ethnicity, disability, enrollment in Medicaid or low-income subsidies, managed care enrollment, region and rurality of residence, and a medication-based measure of comorbid conditions.

MEASUREMENTS

The exposure was the source of opioid prescriptions within 6 months of the index date, categorized as VA only, Part D only, or VA and Part D (that is, dual use). The outcome was unintentional or undetermined-intent death from prescription opioid overdose, identified from the National Death Index. The association between this outcome and source of opioid prescriptions was estimated using conditional logistic regression with adjustment for age, marital status, prescription drug monitoring programs, and use of other medications.

RESULTS

Among case patients, the mean age was 57.3 years (SD, 9.1), 194 (90%) were male, and 181 (84%) were non-Hispanic white. Overall, 60 case patients (28%) and 117 control patients (14%) received dual opioid prescriptions. Dual users had significantly higher odds of death from prescription opioid overdose than those who received opioids from VA only (odds ratio [OR], 3.53 [95% CI, 2.17 to 5.75]; P < 0.001) or Part D only (OR, 1.83 [CI, 1.20 to 2.77]; P = 0.005).

LIMITATION

Data are from 2012 to 2013 and cannot capture prescriptions obtained outside the VA or Medicare Part D systems.

CONCLUSION

Among veterans enrolled in VA and Part D, dual use of opioid prescriptions was independently associated with death from prescription opioid overdose. This risk factor for fatal overdose among veterans underscores the importance of care coordination across health care systems to improve opioid prescribing safety.

PRIMARY FUNDING SOURCE

U.S. Department of Veterans Affairs.

A Qualitative Study of Primary Care Providers' Experiences with the Veterans Choice Program

BACKGROUND

The Veterans Access, Choice and Accountability Act (hereafter, Choice Program) seeks to improve access to care by enabling eligible Veterans to receive care from community providers. Veterans Affairs (VA) primary care providers (PCPs) play a key role in making referrals to community specialists, but their frontline experiences with referrals are not well understood.

OBJECTIVE

To understand VA PCPs' experiences referring patients to community specialists while VA works to expand and refine the implementation of the Choice Program.

DESIGN

Qualitative study using interview methods.

PARTICIPANTS

Semi-structured telephone interviews were conducted with VA primary care providers (N = 72 out of 599 contacted) recruited nationally.

APPROACH

Open-ended interview questions elicited PCP perceptions and experiences with referrals to community specialists via the Choice Program. Keywords were identified using automated coding features in ATLAS.ti and evaluated using conventional content analysis to inductively describe the qualitative data.

KEY RESULTS

VA PCPs emphasized problems with care coordination and continuity between the VA and community specialists (e.g., "It is extremely difficult for us to obtain and continue continuity of care because there's not much communication with the community specialist"). They described difficulties with tracking the initial referral, coordinating care after receiving community specialty care, accessing community medical records, and aligning community specialists' prescriptions with the VA formulary.

CONCLUSIONS

The VA Choice Program provides access to community specialists for VA patients; however, VA primary care providers face challenges tracking referrals to community specialists and in coordinating care. Strategies to improve care coordination between the VA and community providers should focus on providing PCPs with information to follow Veterans throughout the Choice referral process and follow-up.

Receipt of Overlapping Opioid and Benzodiazepine Prescriptions Among Veterans Dually Enrolled in Medicare Part D and the Department of Veterans Affairs: A Cross-sectional Study

BACKGROUND

Overlapping use of opioids and benzodiazepines is associated with increased risk for overdose. Veterans receiving medications concurrently from the U.S. Department of Veterans Affairs (VA) and Medicare may be at higher risk for such overlap.

OBJECTIVE

To assess the association between dual use of VA and Medicare drug benefits and receipt of overlapping opioid and benzodiazepine prescriptions.

DESIGN

Cross-sectional.

SETTING

VA and Medicare.

PARTICIPANTS

All veterans enrolled in VA and Medicare Part D who filled at least 2 opioid prescriptions in 2013 (n = 368 891).

MEASUREMENTS

Outcomes were the proportion of patients with a Pharmacy Quality Alliance (PQA) measure of opioid-benzodiazepine overlap (≥2 filled prescriptions for benzodiazepines with ≥30 days of overlap with opioids) and the proportion of patients with high-dose opioid-benzodiazepine overlap (≥30 days of overlap with a daily opioid dose >120 morphine milligram equivalents). Augmented inverse probability weighting regression was used to compare these measures by prescription drug source: VA only, Medicare only, or VA and Medicare (dual use).

RESULTS

Of 368 891 eligible veterans, 18.3% received prescriptions from the VA only, 30.3% from Medicare only, and 51.4% from both VA and Medicare. The proportion with PQA opioid-benzodiazepine overlap was larger for the dual-use group than the VA-only group (23.1% vs. 17.3%; adjusted risk ratio [aRR], 1.27 [95% CI, 1.24 to 1.30]) and Medicare-only group (23.1% vs. 16.5%; aRR, 1.12 [CI, 1.10 to 1.14]). The proportion with high-dose overlap was also larger for the dual-use group than the VA-only group (4.7% vs. 2.3%; aRR, 2.23 [CI, 2.10 to 2.36]) and Medicare-only group (4.7% vs. 2.9%; aRR, 1.06 [CI, 1.02 to 1.11]).

LIMITATION

Data are from 2013 and cannot capture medications purchased without insurance; unmeasured confounding may remain in this cross-sectional study.

CONCLUSION

Among a national cohort of veterans dually enrolled in VA and Medicare, receiving prescriptions from both sources was associated with greater risk for receiving potentially unsafe overlapping prescriptions for opioids and benzodiazepines.

PRIMARY FUNDING SOURCE

U.S. Department of Veterans Affairs.