Non-response to ACE items is associated with demographic variables and health indicators in the 2021 Behavioral Risk Factor Surveillance System.

Background: Adverse childhood experiences (ACE) encompass traumatic events occurring before age 18, with lasting impacts on health. While ACE disclosure is important for understanding these effects, some individuals decline to respond to ACE-related survey items due to sensitivity, privacy concerns, or psychological distress. This study explores the relationship between non-response to ACE items and health outcomes, shedding light on the implications for those who choose not to disclose. Methods: We performed a secondary analysis of the 2021 Behavioral Risk Factor Surveillance System (BRFSS)-a national telephone survey querying health behaviors and conditions. Sociodemographic factors, ACE exposure, and non-response to ACE items were analyzed. Results: Individuals who decline to respond to ACE items exhibit similar patterns of health behaviors and conditions as those reporting ACE exposure. Non-response is linked to both healthier behaviors (lifetime HIV testing) and riskier behaviors (higher odds of smoking and e-cigarette use). Moreover, non-responders have higher odds of being underweight or obese, experiencing concentration difficulties, reporting poor self-rated health, and reporting multiple health diagnoses including depression, diabetes, high blood pressure, heart attack, and stroke. Conclusions: The study underscores the need to address health disparities associated with ACE, regardless of disclosure status. Healthcare interventions should target respondents and non-respondents of ACE screeners, tailoring strategies to promote healthier coping mechanisms and mitigate maladaptive behaviors. These results emphasize the importance of trauma-informed care, early intervention, and targeted public health initiatives for individuals affected by ACE, irrespective of their disclosure choices.

Dose Changes for Long-term Opioid Patients Following a State Opioid Prescribing Policy.

BACKGROUND: In 2018, Nevada implemented opioid prescribing legislation (AB474) to support the uptake of CDC pain care guidelines. We studied the law's association with doses over threshold levels of morphine milligram equivalents (MMEs) and with time to dose increases and decreases, among long-term opioid patients. METHODS: A difference-in-difference study examined dosing changes across opioid prescription episodes (ie, prescriptions within 30 day and within the same dosing threshold). Patients with at least 120 days supply over 6 months in Nevada and Colorado Medicaid pharmacy claims were included. Using a logistic regression model, we compare the predicted probabilities that opioid episodes exceeded 50 MME before and after implementation of the law, in both states. Adjusted hazard ratios (aHR) from a gap time survival model estimated time to escalate above 50 MME among low-dose episodes (<50 MME), and time to de-escalate below 50 MME among high-dose episodes (≥50 MME). RESULTS: Among 453,577 episodes (74,292 patients), the Nevada law was associated with a 2.9% reduction in prescriptions over 50 MME (95% CI: -3.5, -2.3) compared with Colorado. While the law was also associated with slower escalation (Nevada: aHR = 0.75; 95% CI: 0.72, 0.77, Colorado: aHR = 1.04; 95% CI: 1.01, 1.06), it was also associated with slower de-escalation (Nevada: aHR = 0.87; 95% CI: 0.84, 0.89, Colorado: aHR = 0.97; 95% CI: 0.96, 0.99). CONCLUSIONS: Slower dose escalations, rather than faster dose de-escalation, likely explain post-law reductions in doses over 50 MME. Slower dose de-escalations may be due to longer days supply post-policy.

Variation in Nevada primary care clinicians' use of urine drug testing to mitigate opioid harm.

INTRODUCTION: The prescription opioid epidemic led to federal, state, and health system guidelines and policies aimed at mitigating opioid misuse, including presumptive urine drug testing (UDT). This study identifies whether a difference exists in UDT use among different primary care medical license types. METHODS: The study used January 2017-April 2018 Nevada Medicaid pharmacy and professional claims data to examine presumptive UDTs. We examined correlations between UDTs and clinician characteristics (medical license type, urban/rural status, care setting) along with clinician-level measures of patient mix characteristics (proportions of patients with behavioral health diagnoses, early refills). Adjusted odds ratios (AORs) and predicted probabilities (PPs) from a logistic regression with a binomial distribution are reported. The analysis included 677 primary care clinicians (medical doctors [MD], physician assistants [PA], nurse practitioners [NP]). RESULTS: Of those in the study, 85.1 % of clinicians did not order any presumptive UDTs. NPs had the highest proportion of UDT use (21.2 % of NPs), followed by PAs (20.0 % of PAs), and MDs (11.4 % of MDs). Adjusted analyses showed that being a PA or NP was associated with higher odds of UDT (PA: AOR: 3.6; 95 % CI: 3.1-4.1; NP: AOR: 2.5; 95 % CI: 2.2-2.8) compared to being an MD. PAs had the highest PP for ordering UDTs (2.1 %, 95 % CI: 0.5 %-8.4 %). Among clinicians who ordered UDTs, midlevel clinicians had higher mean and median UDT use (PA and NP mean: 24.3 % vs. MDs: 19.4 %; PA and NP median: 17.7 % vs. MDs: 12.5 %). CONCLUSION: In Nevada Medicaid, UDTs are concentrated among 15 % of primary care clinicians who are frequently non-MDs. More research should include PAs and NPs when examining clinician variation in mitigating opioid misuse.

A cohort-based nutrition ECHO for community health workers.

Project Extension for Community Healthcare Outcomes (ECHO) Nevada applied the ECHO virtual hub-and-spoke telementoring model over nine 6-week cohorts (between November 2019 and November 2021) supporting community health workers (CHWs) who advise clients with diabetes or pre-diabetes. This study describes the program implementation, including evaluation data collection efforts. Didactic topics included 'Intro to Healthy Eating and Easy Wins' to 'Grocery Shopping, Cooking Tips, Reading Labels, Meal Plans' and 'Reducing Bias and Being a Good Role Model'. Spoke participants signed up to review cases. Seventy-three of the enrolled participants (n = 100) attended three or more of the six sessions. Spoke participants completed 42 case presentations. The average self-efficacy increased from 2.7 [standard deviation (SD): 1.1] before completing the program to 4.1 (SD: 0.8) after completing the program. Average knowledge scores increased from 71 (SD: 16) before completing the program to 83 (SD: 14) after completing the program. Five group interviews drew actionable feedback that was incorporated into the program. Key elements of the ECHO model were successfully incorporated to support educational goals of a cohort of CHWs in nutritional coaching. Our program evaluation data tracking system shows non-significant but encouraging results regarding self-efficacy improvement and knowledge retention.