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.

Telemedicine in a primary care clinic in Fairbanks, Alaska: Not a magic bullet for providing treatment during COVID-19.

Stay-at-home orders due to the COVID-19 pandemic have increased patients' reliance on virtual physician visits, via telemedicine. Telemedicine has benefits of use during the pandemic and has benefits outside of the pandemic. It is underutilized in certain types of medical organizations, providers, and among specific populations in the United States. It is important to understand the barriers to incorporating telemedicine effectively in the areas that it is underutilized, especially in rural locations. The researcher discussed the telemedicine expansion for two family practice doctors in Fairbanks, Alaska (AK). The family practice doctors experienced barriers that partially echo what has been stated in research. Research suggests that changes to Medicare and Medicaid telemedicine policies may not be enough to address these barriers. Other supports to expand telemedicine where it is needed includes providing more incentives to providers, waivers from insurance companies for patients to purchase equipment, and more education to patients about when, how, and where to receive telemedicine. More supports need to be provided to those underserved by telemedicine, especially for clients who are on Medicaid, living in low-income areas, and/or living in rural locations.

Comparison of Quality Measures From US Hospitals With Physician vs Nonphysician Chief Executive Officers.

Importance: Patient experience and patient safety are 2 major domains of health care quality; however empirical data on the association of physician vs nonphysician chief executive officers (CEOs) with public and private quality measures are rare but critical to evaluate as hospitals increasingly seek out physician CEOs. Objectives: To evaluate whether there is an association of CEO background with hospital quality and to investigate differences in hospital characteristics between hospitals with a physician CEO vs those with a nonphysician CEO. Design, Setting, and Participants: This cross-sectional study used 2019 data from 3 sources (ie, the American Hospital Association [AHA] Annual Survey, the Hospital Consumer Assessment of Healthcare Providers and Systems [HCAHPS], and the Leapfrog Hospital Safety Grades) to identify statistical differences in hospital characteristics and outcomes. Data were analyzed from April to December 2021 . Main Outcomes and Measures: Multivariable ordinal logistic regression was used to examine the association of physician CEOs with hospital quality assessment outcomes while controlling for other confounding factors. Characteristics from the AHA Annual Survey database were assessed as potential confounders, including hospital control, bed size, region, teaching status, and patient volume. Results: The AHA database contained 6162 hospitals; 1759 (29%) had HCAHPS ratings, 1824 (30%) had Leapfrog grades, and 383 (6%) had physician CEOs. A positive Spearman correlation coefficient was found between physician CEOs and HCAHPS patient willingness to recommend the hospital (ρ = 0.0756; P = .002), but the association between CEO medical background and Leapfrog safety grades or HCAHPS ratings did not reach a level of significance in the multivariable ordinal logistic regression models. Conclusions and Relevance: In this study, a positive correlation was found between physician CEOs and HCAHPS patient willingness to recommend the hospital, but the multivariable analysis did not find an association between hospital physician CEOs and the examined quality and safety outcomes.

Urine Drug Testing among Opioid-Naïve and Long-Term Opioid Nevada Medicaid Beneficiaries.

BACKGROUND: Current guidelines recommend that, when prescribing opioids, providers use urine drug testing (UDT) for harm reduction. Objective: To identify whether Medicaid beneficiaries in Nevada at increased risk for opioid misuse received UDT. Methods: We used Nevada Medicaid claims data (2017-2018) to describe UDT among three samples: opioid naïve patients (N = 11,326), opioid naïve patients with a second follow-up prescription (N = 8,910), and long-term opioid patients (N = 19,173). Predictors of opioid misuse include past diagnoses of mental health and substance use, demographic characteristics and potentially risky behaviors. Outcomes include receiving UDT prior to opioid prescription among the two naïve samples and within six months for the long-term sample. We report predicted probabilities (PP) from logistic regressions and hazard ratios (HR) and Kaplan-Meier curves. Results: A small percentage of patients received UDT (naïve sample: 2.5%; naïve with a second follow-up prescription sample: 3.5%; long-term sample: 9.9%). Adults with alcohol disorders and other substance use disorders had the highest PP of UDT, among both the naïve (alcohol related disorder: 3.1%; other substance use disorder: 7.7%) and the naïve with a second follow-up prescription (alcohol related disorder: 4.1%; other substance use disorder: 11.7%) samples. Among the long-term sample, similar predictors were significant. Conclusions: Although there was an association between having risk factors for opioid misuse (e.g. past alchohol disorders and other substance use disorder diagnoses) and receiving UDT, the percentage of patients who received UDT was unexpectedly low, pointing to the need to increase guideline adherence and implementation among providers who prescribe opioids.