A randomized controlled trial evaluating the effects of nurse-led triage of 911 calls.

To better connect non-emergent 911 callers to appropriate care, Washington, DC, routed low-acuity callers to nurses. Nurses could provide non-emergent transportation to a health centre, recommend self-care or return callers to the traditional 911 system. Over about one year, 6,053 callers were randomized (1:1) to receive a business-as-usual response (ncontrol = 3,023) or further triage (ntreatment = 3,030). We report on seven of nine outcomes, which were pre-registered ( https://osf.io/xderw ). The proportion of calls resulting in an ambulance dispatch dropped from 97% to 56% (ß = -1.216 (-1.324, -1.108), P < 0.001), and those resulting in an ambulance transport dropped from 73% to 45% (ß = -3.376 (-3.615, -3.137), P < 0.001). Among those callers who were Medicaid beneficiaries, within 24 hours, the proportion of calls resulting in an emergency department visit for issues classified as non-emergent or primary care physician (PCP) treatable dropped from 29.5% to 25.1% (ß = -0.230 (-0.391, -0.069), P < 0.001), and the proportion resulting in the caller visiting a PCP rose from 2.5% to 8.2% (ß = 1.252 (0.889, 1.615), P < 0.001). Over the longer time span of six months, we failed to detect evidence of impacts on emergency department visits, PCP visits or Medicaid expenditures. From a safety perspective, 13 callers randomized to treatment were eventually diagnosed with a time-sensitive illness, all of whom were quickly triaged to an ambulance response. These short-term effects suggest that nurse-led triage of non-emergent calls can safely connect callers to more appropriate, timely care.

The influence of social norms varies with "others" groups: Evidence from COVID-19 vaccination intentions.

The theory that health behaviors spread through social groups implies that efforts to control COVID-19 through vaccination will succeed if people believe that others in their groups are getting vaccinated. But "others" can refer to many groups, including one's family, neighbors, fellow city or state dwellers, or copartisans. One challenge to examining these understudied distinctions is that many factors may confound observed relationships between perceived social norms (what people believe others do) and intended behaviors (what people themselves will do), as there are plausible common causes for both. We address these issues using survey data collected in the United States during late fall 2020 (n = 824) and spring 2021 (n = 996) and a matched design that approximates pair-randomized experiments. We find a strong relationship between perceived vaccination social norms and vaccination intentions when controlling for real risk factors (e.g., age), as well as dimensions known to predict COVID-19 preventive behaviors (e.g., trust in scientists). The strength of the relationship declines as the queried social group grows larger and more heterogeneous. The relationship for copartisans is second in magnitude to that of family and friends among Republicans but undetectable for Democrats. Sensitivity analysis shows that these relationships could be explained away only by an unmeasured variable with large effects (odds ratios between 2 and 15) on social norms perceptions and vaccination intentions. In addition, a prediction from the "false consensus" view that intentions cause perceived social norms is not supported. We discuss the implications for public health policy and understanding social norms.

Predictors of enrollment in opioid agonist therapy after opioid overdose or diagnosis with opioid use disorder: A cohort study.

BACKGROUND: Medicaid recipients have a high burden of opioid overdose and opioid use disorder (OUD). Opioid agonist therapies are an effective treatment for OUD, but there is a wide and persisting gap between those who are indicated and those who receive treatment. The objective of this study was to identify the predictors of enrollment in opioid agonist therapy within 6 months of an opioid overdose or OUD diagnosis in a cohort of Medicaid recipients. METHODS: Using multiple linked, state-level databases, we conducted a retrospective cohort study of 17,449 Medicaid recipients in Rhode Island who had an opioid overdose or an OUD diagnosis between July 2013 and June 2018. RESULTS: The majority (58 %) of Medicaid recipients did not enroll in opioid agonist therapy within 6 months. In adjusted models, having one or more prior overdose (adjusted risk ratio [ARR] = 0.33, 95 % CI: 0.28, 0.38), alcohol use disorder (ARR = 0.56, 95 % CI: 0.52, 0.60), or back problems (ARR = 0.58, 95 % CI: 0.55, 0.61) were strong predictors of non-enrollment. Conversely, emergency department (ARR = 1.31, 95 % CI: 1.28-1.34) and primary care provider (ARR = 1.03, 95 % CI: 1.01-1.34) visit frequency above the 75th percentile were associated with timely enrollment in opioid agonist therapy. CONCLUSIONS: Our findings underscore the need to enhance pathways to treatment for OUD through varied nodes of engagement with healthcare systems. Interventions to improve screening for OUD and referrals to opioid agonist therapies should include high-impact settings, such as treatment programs for alcohol and substance use disorders, pain clinics, and outpatient behavioral care settings.