Faculty Bibliography

BACKGROUND:We aimed to investigate the impact of reducing drinking in patients with unhealthy alcohol use on improvement of chronic pain interference, substance use, and psychiatric symptoms. METHODS:We analyzed longitudinal data from 2003 to 2015 in the Veterans Aging Cohort Study, a prospective, multisite observational study of US veterans, by emulating a hypothetical randomized trial (a target trial). Alcohol use was assessed using the AUDIT questionnaire, and outcome conditions were assessed via validated survey items. Individuals were followed from the first time their AUDIT score was ≥ 8 (baseline), a threshold consistent with unhealthy alcohol use. We compared individuals who reduced drinking (AUDIT < 8) at the next follow-up visit with individuals who did not (AUDIT ≥ 8). We fit separate logistic regression models to estimate odds ratios for improvement of each condition 2 years postbaseline among individuals who had that condition at baseline: moderate or severe pain interference symptoms, tobacco smoking, cannabis use, cocaine use, depressive symptoms, and anxiety symptoms. Inverse probability weighting was used to account for potential selection bias and confounding. RESULTS:Adjusted 2-year odds ratios (95% confidence intervals) for associations between reducing drinking and improvement or resolution of each condition were as follows: 1.49 (0.91, 2.42) for pain interference symptoms, 1.57 (0.93, 2.63) for tobacco smoking, 1.65 (0.92, 2.95) for cannabis use, 1.83 (1.03, 3.27) for cocaine use, 1.11 (0.64, 1.92) for depressive symptoms, and 1.33 (0.80, 2.22) for anxiety symptoms. CONCLUSIONS:We found some evidence for improvement of pain interference symptoms and substance use after reducing drinking among US veterans with unhealthy alcohol use, but confidence intervals were wide.

BACKGROUND:There are too many plausible permutations and scale-up scenarios of combination hepatitis C (HCV) interventions for exhaustive testing in experimental trials. Therefore, we used computer simulation to project the health and economic impact of alternative combination intervention scenarios for people who inject drugs (PWID), focusing on direct anti-viral agents (DAA) and medication-assisted treatment combined with syringe access programs (MAT+). METHODS:We performed an allocative efficiency study using a mathematical model simulating the progression of HCV in PWID and its related consequences. Two previously validated simulations were combined to estimate the cost-effectiveness of intervention strategies that included a range of coverage levels. Analyses were performed from a health sector and societal perspective with a 15-year time horizon and a discount rate of 3%. RESULTS:From a health-sector perspective (excluding criminal justice system-related costs), four potential strategies fell on the cost-efficiency frontier. DAA at 20% coverage had an ICER of $27,251/QALY. Combinations of DAA 20% with MAT+ at 20%, 40%, and 80% coverage had ICERs of $165,985/QALY, $325,860/QALY, and $399,189/QALY, respectively. When analyzed from a societal perspective (including criminal justice system-related costs), DAA 20% with MAT+ 80% was most effective and was cost saving. While DAA 20% with MAT+ 80% was more expensive (e.g., less cost-saving) than MAT+ 80% alone without DAA, it offered favorable value compared to MAT+ 80% alone ($23,932/QALY). CONCLUSION/CONCLUSIONS:When considering health sector costs alone, DAA alone was the most cost-effective intervention. However, with criminal justice system-related costs, DAA and MAT+ implemented together become the most cost-effective interventions.

Microglia play key roles in regulating synapse development and refinement in the developing brain, but it is unknown whether they are similarly involved during adult neurogenesis. By transiently depleting microglia from the healthy adult mouse brain, we show that microglia are necessary for the normal functional development of adult-born granule cells (abGCs) in the olfactory bulb. Microglial depletion reduces the odor responses of developing, but not preexisting GCs in vivo in both awake and anesthetized mice. Microglia preferentially target their motile processes to interact with mushroom spines on abGCs, and when microglia are absent, abGCs develop smaller spines and receive weaker excitatory synaptic inputs. These results suggest that microglia promote the development of excitatory synapses onto developing abGCs, which may impact the function of these cells in the olfactory circuit.

Importance/UNASSIGNED:Alcohol screening may be associated with health outcomes that cluster with alcohol use (ie, alcohol-clustering conditions), including depression, anxiety, and use of tobacco, marijuana, and illicit drugs. Objective/UNASSIGNED:To quantify the extent to which alcohol screening provides additional information regarding alcohol-clustering conditions and to compare 2 alcohol use screening tools commonly used for this purpose. Design, Setting, and Participants/UNASSIGNED:This longitudinal cohort study used data from the Veterans Aging Cohort Study. Data were collected at 8 Veterans Health Administration facilities from 2003 through 2012. A total of 7510 participants were enrolled, completed a baseline survey, and were followed up. Veterans with HIV were matched with controls without HIV by age, race, sex, and site of care. Data were analyzed from January 2019 to December 2019. Exposures/UNASSIGNED:The Alcohol Use Disorders Identification Test (AUDIT) and Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) were used to assess alcohol use, with 4 risk groups delineated for each test: score 0 to 7 (reference), score 8 to 15, score 16 to 19, and score 20 to 40 (maximum score) for the full AUDIT and score 0 to 3 (reference), score 4 to 5, score 6 to 7, and score 8 to 12 (maximum score) for the AUDIT-C. Main Outcomes and Measures/UNASSIGNED:Alcohol-clustering conditions, including self-reported symptoms of depression and anxiety and use of tobacco, marijuana, cocaine, other stimulants, opioids, and injection drugs. Results/UNASSIGNED:A total of 6431 US patients (6104 [95%] men; median age during survey years 2003-2004, 50 years [range, 28-86 years; interquartile range, 44-55 years]) receiving care in the Veterans Health Administration completed 1 or more follow-up surveys when the AUDIT was administered and were included in the present analyses. Of the male participants, 4271 (66%) were African American, 1498 (24%) were white, and 590 (9%) were Hispanic. The AUDIT and AUDIT-C scores were associated with each alcohol-clustering condition. In particular, an AUDIT score of 20 or higher (vs <8, the reference) was associated with symptoms of depression (odds ratio [OR], 8.37; 95% CI, 6.20-11.29) and anxiety (OR, 8.98; 95% CI, 6.39-12.60) and with self-reported use of tobacco (OR, 14.64; 95% CI, 8.94-23.98), marijuana (OR, 12.41; 95% CI, 8.61-17.90), crack or cocaine (OR, 39.47; 95% CI, 27.38-56.90), other stimulants (OR, 21.31; 95% CI, 12.73-35.67), and injection drugs (OR, 8.67; 95% CI, 5.32-14.13). An AUDIT score of 20 or higher yielded likelihood ratio (sensitivity / 1 - specificity) values greater than 3.5 for depression, anxiety, crack or cocaine use, and other stimulant use. Associations between AUDIT-C scores and alcohol-clustering conditions were more modest. Conclusions and Relevance/UNASSIGNED:Alcohol screening can inform decisions about further screening and diagnostic assessment for alcohol-clustering conditions, particularly for depression, anxiety, crack or cocaine use, and other stimulant use. Future studies using clinical diagnoses rather than screening tools to assess alcohol-clustering conditions may be warranted.

OBJECTIVE/UNASSIGNED:We sought to quantify the extent to which a depression screening instrument commonly used in primary care settings provides additional information regarding pain interference symptoms, anxiety, and substance use. METHODS/UNASSIGNED:Veterans Aging Cohort Study (VACS) data collected from 2003 through 2015 was used to calculate odds ratios (OR) for associations between positive depression screening result cutoffs and clustering conditions. We assessed the test performance characteristics (likelihood ratio value, positive predictive value, and the percentage of individuals correctly classified) of a positive Patient Health Questionnaire (PHQ-9 & PHQ-2) depression screen for the identification of pain interference symptoms, anxiety, and substance use. RESULTS/UNASSIGNED:A total 7731 participants were included in the analyses. The median age was 50 years. The PHQ-9 threshold of ≥20 was strongly associated with pain interference symptoms (OR 21.6, 95% CI 17.5-26.7) and anxiety (OR 72.1, 95% CI 52.8-99.0) and yielded likelihood ratio values of 7.5 for pain interference symptoms and 21.8 for anxiety and positive predictive values (PPV) of 84% and 95%, respectively. A PHQ-9 score of ≥10 still showed significant associations with pain interference symptoms (OR 6.1, 95% CI 5.4-6.9) and symptoms of anxiety (OR 11.3, 95% CI 9.7-13.1) and yet yielded lower likelihood ratio values (4.36 & 8.24, respectively). The PHQ-9 was less strongly associated with various forms of substance use. CONCLUSION/UNASSIGNED:Depression screening provides substantial additional information regarding the likelihood of pain interference symptoms and anxiety and should trigger diagnostic assessments for these other conditions.

Background/UNASSIGNED:Implementation science (IS) has the potential to serve an important role in encouraging the successful uptake of evidence-based interventions. The current state of IS awareness and engagement among health researchers, however, is relatively unknown. Methods/UNASSIGNED:To determine IS awareness and engagement among health researchers, we performed an online survey of health researchers in the USA in 2018. Basic science researchers were excluded from the sample. Engagement in and awareness of IS were measured with multiple questionnaire items that both directly and indirectly ask about IS methods used. Unrecognized IS engagement was defined as participating in research using IS elements and not indicating IS as a research method used. We performed simple logistic regressions and tested multivariable logistic regression models of researcher characteristics as predictors of IS engagement. Results/UNASSIGNED:< 0.001). Conclusion/UNASSIGNED:Overall, awareness of IS is high among health researchers, yet there is also a high prevalence of unrecognized IS engagement. Efforts are needed to further disseminate what constitutes IS research and increase IS awareness among health researchers.

BACKGROUND:Less than 25% of stroke patients arrive to an emergency department within the 3-hour treatment window. OBJECTIVE:We evaluated the cost-effectiveness of a stroke preparedness behavioral intervention study (Stroke Warning Information and Faster Treatment [SWIFT]), a stroke intervention demonstrating capacity to decrease race-ethnic disparities in ED arrival times. METHODS:Using the literature and SWIFT outcomes for 2 interventions, enhanced educational (EE) materials, and interactive intervention (II), we assess the cost-effectiveness of SWIFT in 2 ways: (1) Markov model, and (2) cost-to-outcome ratio. The Markov model primary outcome was the cost per quality-adjusted life-year (QALY) gained using the cost-effectiveness threshold of $100 000/QALY. The primary cost-to-outcome endpoint was cost per additional patient with ED arrival <3 hours, stroke knowledge, and preparedness capacity. We assessed the ICER of II and EE versus standard care (SC) from a health sector and societal perspective using 2015 USD, a time horizon of 5 years, and a discount rate of 3%. RESULTS:The cost-effectiveness of the II and EE programs was, respectively, $227.35 and $74.63 per additional arrival <3 hours, $440.72 and $334.09 per additional person with stroke knowledge proficiency, and $655.70 and $811.77 per additional person with preparedness capacity. Using a societal perspective, the ICER for EE versus SC was $84 643 per QALY gained and the ICER for II versus EE was $59 058 per QALY gained. Incorporating fixed costs, EE and II would need to administered to 507 and 1693 or more patients, respectively, to achieve an ICER of $100 000/QALY. CONCLUSION/CONCLUSIONS:II was a cost-effective strategy compared with both EE and SC. Nevertheless, high initial fixed costs associated with II may limit its cost-effectiveness in settings with smaller patient populations.

In integrated health care systems, techniques that identify successes and opportunities for targeted improvement are needed. The authors propose a new method for estimating population health that provides a more accurate and dynamic assessment of performance and priority setting. Member data from a large integrated health system (n = 96,246, 73.8% female, mean age = 44 ± 0.01 years) were used to develop a mechanistic mathematical simulation, representing the top causes of US mortality in 2014 and their associated risk factors. An age- and sex-matched US cohort served as comparator group. The simulation was recalibrated and retested for validity employing the outcome measure of 5-year mortality. The authors sought to estimate potential population health that could be gained by improving health risk factors in the study population. Potential gains were assessed using both average life years (LY) gained and average quality-adjusted life years (QALYs) gained. The simulation validated well compared to integrated health system data, producing an AUC (area under the curve) of 0.88 for 5-year mortality. Current population health was estimated as a life expectancy of 84.7 years or 69.2 QALYs. Comparing potential health gain in the US cohort to the Kaiser Permanente cohort, eliminating physical inactivity, unhealthy diet, smoking, and uncontrolled diabetes resulted in an increase of 1.5 vs. 1.3 LY, 1.1 vs. 0.8 LY, 0.5 vs. 0.2 LY, and 0.5 vs. 0.5 LY on average per person, respectively. Using mathematical simulations may inform efforts by integrated health systems to target resources most effectively, and may facilitate goal setting.

Background. Reference life expectancies inform frequently used health metrics, which play an integral role in determining resource allocation and health policy decision making. Existing reference life expectancies are not able to account for variation in geographies, populations, and disease states. Using a computer simulation, we developed a reference life expectancy estimation that considers competing causes of mortality, and is tailored to population characteristics. Methods. We developed a Monte Carlo microsimulation model that explicitly represented the top causes of US mortality in 2014 and the risk factors associated with their onset. The microsimulation follows a birth cohort of hypothetical individuals resembling the population of the United States. To estimate a reference life expectancy, we compared current circumstances with an idealized scenario in which all modifiable risk factors were eliminated and adherence to evidence-based therapies was perfect. We compared estimations of years of potential years life lost with alternative approaches. Results. In the idealized scenario, we estimated that overall life expectancy in the United States would increase by 5.9 years to 84.7 years. Life expectancy for men would increase from 76.4 years to 82.5 years, and life expectancy for women would increase from 81.3 years to 86.8 years. Using age-75 truncation to estimate potential years life lost compared to using the idealized life expectancy underestimated potential health gains overall (38%), disproportionately underestimated potential health gains for women (by 70%) compared to men (by 40%), and disproportionately underestimated the importance of heart disease for white women and black men. Conclusion. Mathematical simulations can be used to estimate an idealized reference life expectancy among a population to better inform and assess progress toward targets to improve population health.