Association between severe acute respiratory syndrome coronavirus 2 antibody status and reinfection: A case-control study nested in a Colorado-based prospective cohort study.

The association between the presence of detectable antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and SARS-CoV-2 reinfection is not well established. The objective of this study was to determine the association between antibody seronegativity and reinfection. METHODS: Participants in Colorado, USA, were recruited between June 15, 2020, and March 28, 2021, and encouraged to complete SARS-CoV-2 molecular ribonucleic acid (RNA) and serology testing for antibodies every 28 days for 10 months. Participants with reinfections (positive SARS-CoV-2 RNA test ≥ 90 days after the first positive RNA test) were matched to controls without reinfections by age, sex, date of the first positive RNA test, date of the last serology test, and serology test type. Using conditional logistic regression, case patients were compared to control patients on the last serologic test result, with adjustment for demographic and clinical confounders. RESULTS: The cohort (n = 4,235) included 2,033 participants with ≥ 1 positive RNA test, of whom 120 had reinfection. Among the 80 case patients who could be matched, the last serologic test was negative in 12 of the cases (15.0 %) whereas the last serologic test was negative in 77 of 1,034 (7.5 %) controls. Seronegativity (adjusted OR [aOR] 2.24; 95 % CI 1.07, 4.68), Hispanic ethnicity (aOR 1.87; 95 % 1.10, 3.18), and larger household size (aOR 1.15; 95 % 1.01, 1.30 for each additional household member) were associated with reinfection. CONCLUSIONS: Seronegative status, Hispanic ethnicity, and increasing household size were associated with reinfection. Serologic testing could be considered to reduce vaccine hesitancy in higher risk populations.

An individual segmented trajectory approach for identifying opioid use patterns using longitudinal dispensing data.

PURPOSE: The aim of this study is to use electronic opioid dispensing data to develop an individual segmented trajectory approach for identifying opioid use patterns. The resulting opioid use patterns can be used for examining the association between opioid use and drug overdose. METHODS: We retrospectively assembled a cohort of members on long-term opioid therapy (LTOT) between January 1, 2006 and June 30, 2019 who were 18 years and older and enrolled in one of three health care systems in the US. We have developed an individual segmented trajectory analysis for identifying various opioid use patterns by scanning over the follow-up and finding distinct opioid use patterns based on variability measured with coefficient of variation and trends of milligram morphine equivalents levels. RESULTS: Among 31, 865 members who were on LTOT between January 1, 2006 and June 30, 2019, 58.3% were female, and the average age was 55.4 years (STD = 15.4). The study population had 152 557 person-years of follow-up, with an average follow-up of 4.4 years per enrollment per person (STD = 3.4). This novel approach identified up to 13 distinct patterns including 88 756 episodes of "stable" pattern (42.1%) with an average follow-up of 11.2 months, 29 140 episodes of "increasing" pattern (13.8%) with an average follow-up of 6.0 months, 13 201 episodes of ≤10% dose reduction (6.3%) with an average follow-up of 10.4 months, 7286 episodes of 11%-20% dose reduction (3.5%) with an average follow-up of 5.3 months, 4457 episodes of 21%-30% dose reduction (2.1%) with an average follow-up of 4.0 months, and 9903 episodes of >30% dose reduction (4.7%) with an average follow-up of 2.6 months. CONCLUSIONS: A novel approach was developed to identify 13 distinct opioid use patterns using each individual's longitudinal dispensing data and these patterns can be used in examining overdose risk during the time that these patterns are ongoing.

Association Between Opioid Dose Reduction Rates and Overdose Among Patients Prescribed Long-Term Opioid Therapy.

BACKGROUND: Tapering long-term opioid therapy is an increasingly common practice, yet rapid opioid dose reductions may increase the risk of overdose. The objective of this study was to compare overdose risk following opioid dose reduction rates of ≤10%, 11% to 20%, 21% to 30%, and >30% per month to stable dosing. METHODS: We conducted a retrospective cohort study in three health systems in Colorado and Wisconsin. Participants were patients ≥18 years of age prescribed long-term opioid therapy between January 1, 2006, and June 30, 2019. Five opioid dosing patterns and drug overdoses (fatal and nonfatal) were identified using electronic health records, pharmacy records, and the National Death Index. Cox proportional hazard regression was conducted on a propensity score-weighted cohort to estimate adjusted hazard ratios (aHRs) for follow-up periods of 1, 3, 6, 9, and 12 months after a dose reduction. RESULTS: In a cohort of 17 540 patients receiving long-term opioid therapy, 42.7% of patients experienced a dose reduction. Relative to stable dosing, a dose reduction rate of >30% was associated with an increased risk of overdose and the aHR estimates decreased as the follow-up increased; the aHRs for the 1-, 6- and 12-month follow-ups were 5.33 (95% CI, 1.98-14.34), 1.81 (95% CI,1.08-3.03), and 1.49 (95% CI, 0.97-2.27), respectively. The slower tapering rates were not associated with overdose risk. CONCLUSIONS: Patients receiving long-term opioid therapy exposed to dose reduction rates of >30% per month had increased overdose risk relative to patients exposed to stable dosing. Results support the use of slow dose reductions to minimize the risk of overdose.

Update of a Multivariable Opioid Overdose Risk Prediction Model to Enhance Clinical Care for Long-term Opioid Therapy Patients.

BACKGROUND: Clinical opioid overdose risk prediction models can be useful tools to reduce the risk of overdose in patients prescribed long-term opioid therapy (LTOT). However, evolving overdose risk environments and clinical practices in addition to potential harmful model misapplications require careful assessment prior to widespread implementation into clinical care. Models may need to be tailored to meet local clinical operational needs and intended applications in practice. OBJECTIVE: To update and validate an existing opioid overdose risk model, the Kaiser Permanente Colorado Opioid Overdose (KPCOOR) Model, in patients prescribed LTOT for implementation in clinical care. DESIGN, SETTING, AND PARTICIPANTS: The retrospective cohort study consisted of 33, 625 patients prescribed LTOT between January 2015 and June 2019 at Kaiser Permanente Colorado, with follow-up through June 2021. MAIN MEASURES: The outcome consisted of fatal opioid overdoses identified from vital records and non-fatal opioid overdoses from emergency department and inpatient settings. Predictors included demographics, medication dispensings, substance use disorder history, mental health history, and medical diagnoses. Cox proportional hazards regressions were used to model 2-year overdose risk. KEY RESULTS: During follow-up, 65 incident opioid overdoses were observed (111.4 overdoses per 100,000 person-years) in the study cohort, of which 11 were fatal. The optimal risk model needed to risk-stratify patients and to be easily interpreted by clinicians. The original 5-variable model re-validated on the new study cohort had a bootstrap-corrected C-statistic of 0.73 (95% CI, 0.64-0.85) compared to a C-statistic of 0.80 (95% CI, 0.70-0.88) in the updated model and 0.77 (95% CI, 0.66-0.87) in the final adapted 7-variable model, which was also well-calibrated. CONCLUSIONS: Updating and adapting predictors for opioid overdose in the KPCOOR Model with input from clinical partners resulted in a parsimonious and clinically relevant model that was poised for integration in clinical care.

Opioid Overdose Risk Following Hospital Discharge Among Individuals Prescribed Long-Term Opioid Therapy: a Risk Interval Analysis.

BACKGROUND: Individuals prescribed long-term opioid therapy (LTOT) have increased risk of readmission and death after hospital discharge. The risk of opioid overdose during the immediate post-discharge time period is unknown. OBJECTIVE: To examine the association between time since hospital discharge and opioid overdose among individuals prescribed LTOT. DESIGN: Self-controlled risk interval analysis. PARTICIPANTS: Adults prescribed LTOT with at least one hospital discharge at a safety-net health system and a non-profit healthcare organization in Colorado. MAIN MEASURES: We identified individuals prescribed LTOT who were discharged from January 2006 through June 2019. The outcome was a composite of fatal and non-fatal opioid overdoses during a 90-day post-discharge observation period, identified using electronic health record (EHR) and vital statistics data. Risk intervals included days 0-6 after index and subsequent hospital discharges. Control intervals ranged from days 7 to 89 after index discharge and included all other time during the observation period that did not fall within a risk interval or time readmitted during a subsequent hospitalization, which was excluded. Poisson regression was used to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI) for overdose events during risk in comparison to control intervals. KEY RESULTS: We identified 7695 adults (63.3% over 55 years, 59.4% female, 20.3% Hispanic) who experienced 9499 total discharges during the study period. Twenty-one overdoses occurred during their observation periods (1174 per 100,000 person-years [9 in risk, 12 in control]). Overdose risk was significantly higher during the risk interval in comparison to the control interval (IRR 6.92; 95% CI 2.92-16.43). CONCLUSION: During the first 7 days after hospital discharge, individuals prescribed LTOT appear to be at elevated risk for opioid overdose. Clarifying mechanisms of overdose risk may help inform in-hospital and post-discharge prevention strategies.

Opioid Dose Trajectories and Associations With Mortality, Opioid Use Disorder, Continued Opioid Therapy, and Health Plan Disenrollment.

Importance: Uncertainty remains about the longer-term benefits and harms of different opioid management strategies, such as tapering and dose escalation. For instance, opioid tapering could help patients reduce opioid exposure to prevent opioid use disorder, but patients may also seek care elsewhere and engage in nonprescribed opioid use. Objective: To evaluate the association between opioid dose trajectories observed in practice and patient outcomes. Design, Setting, and Participants: This retrospective cohort study was conducted in 3 health systems in Colorado and Wisconsin. The study population included patients receiving long-term opioid therapy between 50 and 200 morphine milligram equivalents between August 1, 2014, and July 31, 2017. Follow-up ended on December 31, 2019. Data were analyzed from January 2020 to August 2022. Exposures: Group-based trajectory modeling identified 5 dosing trajectories over 1 year: 1 decreasing, 1 high-dose increasing, and 3 stable. Main Outcomes and Measures: Primary outcomes assessed after the trajectory period were 1-year all-cause mortality, incident opioid use disorder, continued opioid therapy at 1 year, and health plan disenrollment. Associations were tested using Cox proportional hazards regression and log-binomial models, adjusting for baseline covariates. Results: A total of 3913 patients (mean [SD] age, 59.2 [14.4] years; 2767 White non-Hispanic [70.7%]; 2237 female patients [57.2%]) were included in the study. Compared with stable trajectories, the decreasing dose trajectory was negatively associated with opioid use disorder (adjusted hazard ratio [aHR], 0.40; 95% CI, 0.29-0.55) and continued opioid therapy (site 1: adjusted relative risk [aRR], 0.39; 95% CI, 0.34-0.44), but was positively associated with health plan disenrollment (aHR, 1.66; 95% CI, 1.24-2.22). The decreasing trajectory was not associated with mortality (aHR, 1.28; 95% CI, 0.87-1.86). In contrast, the high-dose increasing trajectory was positively associated with mortality (aHR, 2.19; 95% CI, 1.44-3.32) and opioid use disorder (aHR, 1.81; 95% CI, 1.39-2.37) but was not associated with disenrollment (aHR, 0.90; 95% CI, 0.56-1.42) or continued opioid therapy (site 1: aRR, 0.98; 95% CI, 0.94-1.03). Conclusions and Relevance: In this cohort study, decreasing opioid dose was associated with reduced risk of opioid use disorder and continued opioid therapy but increased risk of disenrollment compared with stable dosing, whereas the high-dose increasing trajectory was associated with an increased risk of mortality and opioid use disorder. These findings can inform opioid management decision-making.

Naloxone Co-Dispensing with Opioids: a Cluster Randomized Pragmatic Trial.

BACKGROUND: Although naloxone prevents opioid overdose deaths, few patients prescribed opioids receive naloxone, limiting its effectiveness in real-world settings. Barriers to naloxone prescribing include concerns that naloxone could increase risk behavior and limited time to provide necessary patient education. OBJECTIVE: To determine whether pharmacy-based naloxone co-dispensing affected opioid risk behavior. Secondary objectives were to assess if co-dispensing increased naloxone acquisition, increased patient knowledge about naloxone administration, and affected opioid dose and other substance use. DESIGN: Cluster randomized pragmatic trial of naloxone co-dispensing. SETTING: Safety-net health system in Denver, Colorado, between 2017 and 2020. PARTICIPANTS: Seven pharmacies were randomized. Pharmacy patients (N=768) receiving opioids were followed using automated data for 10 months. Pharmacy patients were also invited to complete surveys at baseline, 4 months, and 8 months; 325 survey participants were enrolled from November 15, 2017, to January 8, 2019. INTERVENTION: Intervention pharmacies implemented workflows to co-dispense naloxone while usual care pharmacies provided usual services. MAIN MEASURES: Survey instruments assessed opioid risk behavior; hazardous drinking; tobacco, cannabis, and other drug use; and knowledge. Naloxone dispensings and opioid dose were evaluated using pharmacy data among pharmacy patients and survey participants. Intention-to-treat analyses were conducted using generalized linear mixed models accounting for clustering at the pharmacy level. KEY RESULTS: Opioid risk behavior did not differ by trial group (P=0.52; 8-month vs. baseline adjusted risk ratio [ARR] 1.07; 95% CI 0.78, 1.47). Compared with usual care pharmacies, naloxone dispensings were higher in intervention pharmacies (ARR 3.38; 95% CI 2.21, 5.15) and participant knowledge increased (P=0.02; 8-month vs. baseline adjusted mean difference 1.05; 95% CI 0.06, 2.04). There was no difference in other substance use by the trial group. CONCLUSION: Co-dispensing naloxone with opioids effectively increased naloxone receipt and knowledge but did not increase self-reported risk behavior. TRIAL REGISTRATION: Registered at ClinicalTrials.gov ; Identifier: NCT03337100.

Temporal Trends in Undervaccination: A Population-Based Cohort Study.

INTRODUCTION: Monitoring the trends in undervaccination, including that because of parental vaccine refusal or delay, can inform public health responses directed at improving vaccine confidence and vaccination coverage. METHODS: A retrospective cohort study was conducted in the Vaccine Safety Datalink. The cohort included all children born in 2004-2017 with ≥3 well-child visits between ages 2 and 23 months. Using electronic health record-based vaccination data, the average days undervaccinated was calculated for each child. Undervaccination patterns were assessed through age 23 months. Temporal trends were inspected for inflection points and were analyzed using linear regression. Nested within the cohort study, a survey was conducted to compare parent reports of vaccine refusal or delay with observed vaccination patterns. Data were analyzed in 2020. RESULTS: The study cohort consisted of 808,170 children. The percentage of children with average days undervaccinated=0 (fully vaccinated, no delays) rose from a nadir of 47.1% for the birth year 2008 to 68.4% for the birth year 2017 (ptrend<0.001). The percentage with no vaccines rose from 0.35% for the birth year 2004 to 1.28% for the birth year 2017 (ptrend<0.001). Consistent vaccine limiting was observed in 2.04% for the birth year 2017. Omission of measles, mumps, and rubella vaccine peaked at 4.76% in the birth year 2007 and declined thereafter (ptrend<0.001). On the parent survey (response rate 60.2%), a high proportion of parents of the most undervaccinated children reported refusing or delaying vaccines. CONCLUSIONS: In a 14-year cohort study, vaccination timeliness has improved. However, the small but increasing number of children who received no vaccines by age 23 months warrants additional attention.

Addressing logistical barriers to childhood vaccination using an automated reminder system and online resource intervention: A randomized controlled trial.

BACKGROUND: As the rates of vaccination decline in children with logistical barriers to vaccination, new strategies to increase vaccination are needed. The goal of this study was to develop and evaluate the effectiveness of the Vaccines For Babies (VFB) intervention, an automated reminder system with online resources to address logistical barriers to vaccination in caregivers of children enrolled in an integrated healthcare system. Effectiveness was evaluated in a randomized controlled trial. METHODS: Qualitative interviews were conducted with parents of children less than two years old to identify logistical barriers to vaccination that were used to develop the VFB intervention. VFB included automated reminders to schedule the 6- and 12-month vaccine visit linking caregivers to resources to address logistic barriers, sent to the preferred mode of outreach (text, email, and/or phone). Parents of children between 3 and 10 months of age with indicators of logistical barriers to vaccination were randomized to receive VFB or usual well child care (UC). The primary outcome was percentage of days undervaccinated at 2 years of life. A difference in differences analysis was conducted. RESULTS: Qualitative interviews with 6 parents of children less than 2 years of age identified transportation, scheduling challenges, and knowledge of vaccine timing as logistical barriers to vaccination. We enrolled 250 participants in the trial, 45% were loss to follow-up. There were no significant differences in vaccination uptake between those enrolled in UC or the VFB intervention (0.51%, p = 0.86). In Medicaid enrolled participants, there was a modest decrease in percentage of days undervaccinated in the VFB intervention compared to UC (6.3%, p = 0.07). CONCLUSION: Automated Reminders and with links to heath system resources was not shown to increase infant vaccination uptake demonstrating additional resources are needed to address the needs of caregivers experiencing logistical barriers to vaccination.

Web-Based Tailored Messaging to Increase Vaccination: A Randomized Clinical Trial.

BACKGROUND: To increase vaccine acceptance, we created a Web-based the "Vaccines and Your Baby" intervention (VAYB) that provided new parents with vaccine information messages tailored to vaccine beliefs and values. We evaluated the effectiveness of the VAYB by comparing timely uptake of infant vaccines to an untailored version of the intervention (UT) or usual care intervention (UC) only. METHODS: Between April 2016 and June 2019, we conducted a randomized clinical trial. Pregnant women and new parents were randomly assigned to the VAYB, UT, or UC arms. In the VAYB and UT arms, participants were exposed to interventions at 4 time points from pregnancy until their child was 15 months of age. The primary outcome was up-to-date status for recommended vaccines from birth to 200 days of age. A modified intent-to-treat analysis was conducted. Data were analyzed with logistic regression to generate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: We enrolled 824 participants (276 VAYB, 274 UT, 274 UC), 143 (17.4%) of whom were lost to follow-up. The up-to-date rates in the VAYB, UT, and UC arms were 91.44%, 92.86%, and 92.31%, respectively. Infants in the VAYB arm were not more likely to be up to date than infants in the UC arm (OR = 0.89; 95% CI, 0.45-1.76) or in the UT arm (OR = 0.82; 95% CI, 0.42-1.63). The odds of being up to date did not differ between UT and UC arms (OR = 1.08; 95% CI, 0.54-2.18). CONCLUSIONS: Delivering Web-based vaccine messages tailored to parents' vaccine attitudes and values did not positively impact the timely uptake of infant vaccines.

The Association between Opioid Discontinuation and Heroin Use: A Nested Case-Control Study.

BACKGROUND: Opioid prescribing guidelines recommend reducing or discontinuing opioids for chronic pain if harms of opioid treatment outweigh benefits. As opioid discontinuation becomes more prevalent, it is important to understand whether opioid discontinuation is associated with heroin use. In this study, we sought to assess the association between opioid discontinuation and heroin use documented in the medical record. METHODS: A matched nested case-control study was conducted in an integrated health plan and delivery system in Colorado. Patients receiving opioid therapy in the study period (January 2006-June 2018) were included. Opioid discontinuation was defined as ≥45 days with no opioids dispensed after initiating opioid therapy. The heroin use onset date represented the index date. Case patients were matched to up to 20 randomly selected patients without heroin use (control patients) by age, sex, calendar time, and time between initiating opioid therapy and the index date. Conditional logistic regression models estimated matched odds ratios (mOR) for the association between an opioid discontinuation prior to the index date and heroin use. RESULTS: Among 22,962 patients prescribed opioid therapy, 125 patients (0.54%) used heroin after initiating opioid therapy, of which 74 met criteria for inclusion in the analysis. The odds of opioid discontinuation were approximately two times higher in case patients (n = 74) than control patients (n = 1045; mOR = 2.19; 95% CI 1.27-3.78). CONCLUSIONS: Among patients prescribed chronic opioid therapy, the observed increased risk for heroin use associated with opioid discontinuation should be balanced with potential benefits.

Association of Opioids Prescribed to Family Members With Opioid Overdose Among Adolescents and Young Adults.

Importance: Family members are cited as a common source of prescription opioids used for nonmedical reasons. However, the overdose risk associated with exposure to opioids prescribed to family members among adolescents and young adults is not well established. Objective: To assess the association of opioids prescribed to family members with pharmaceutical opioid overdose among youth. Design, Setting, and Participants: This cohort study included 45 145 family units with a total of 72 040 adolescents and young adults aged 11 to 26 years enrolled in a Kaiser Permanente Colorado health plan in 2006 and observed through June 2018. Exposures: Opioid prescriptions and dosage dispensed to family members and youth in the past month. Main Outcomes and Measures: Fatal pharmaceutical opioid overdoses identified in vital records and nonfatal pharmaceutical opioid overdoses identified in emergency department and inpatient settings. Time to first overdose was modeled using Cox regression. Results: The study population consisted of 72 040 adolescents and young adults (mean [SD] age across follow-up, 19.3 [3.7] years; 36 646 [50.9%] girls and women) nested in 45 145 family units. Youth were more commonly exposed to prescription opioids dispensed to a family member than through their own prescriptions. During follow-up, 26 284 youth (36.5%) filled at least 1 opioid prescription, and 47 461 youth (65.9%) had at least 1 family member with a prescription. Exposure to family members with opioid prescriptions in the past month was associated with increased risk of pharmaceutical opioid overdose (adjusted hazard ratio [aHR], 2.17; 95% CI, 1.24-3.79) independent of opioids prescribed to youth (aHR, 6.62; 95% CI, 3.39-12.91). Concurrent exposure to opioid prescriptions from youth and family members was associated with substantially increased overdose risk (aHR, 12.99; 95% CI, 5.08-33.25). High dosage of total morphine milligram equivalents (MME) prescribed to family members in the past month was associated with youth overdose (0 MME vs >0 to <200 MME: aHR, 1.39; 95% CI, 0.51-3.81; 0 MME vs 200 to <600 MME: aHR, 1.49; 95% CI, 0.59-3.77; 0 MME vs ≥600 MME: aHR, 2.93; 95% CI, 1.55-5.56). Conclusions and Relevance: In this study of youth linked to family members, exposure to family members' prescribed opioids was associated with increased risk of pharmaceutical opioid overdose, independent of opioids prescribed to youth. Further interventions targeting youth and families are needed, including counseling patients about the risks of opioids to youth in their families.

Order of Live and Inactivated Vaccines and Risk of Non-vaccine-targeted Infections in US Children 11-23 Months of Age.

BACKGROUND: Some findings from observational studies have suggested that recent receipt of live vaccines may be associated with decreased non-vaccine-targeted infection risk and mortality. Our objective was to estimate risk of non-vaccine-targeted infections based on most recent vaccine type (live vaccines only, inactivated vaccines only or both concurrently) received in US children 11-23 months of age. METHODS: We conducted a retrospective cohort study within the Vaccine Safety Datalink. We examined electronic health record and immunization data from children born in 2003-2013 who received 3 diphtheria-tetanus-acellular pertussis vaccines before their first birthday. We modeled vaccine type as a time-varying exposure and estimated risk of non-vaccine-targeted infections identified in emergency department and inpatient settings, adjusting for multiple confounders. RESULTS: Among 428,608 children, 48.9% were female, 4.9% had ≥1 immunization visit with live vaccines only and 10.3% had a non-vaccine-targeted infection. In males, lower risk of non-vaccine-targeted infections was observed following last receipt of live vaccines only or live and inactivated vaccines concurrently as compared with last receipt of inactivated vaccines only [live vaccines-only adjusted hazard ratio (aHR) = 0.83, 95% confidence interval (CI): 0.72-0.94; live and inactivated vaccines concurrently aHR: 0.91, 95% CI: 0.88-0.94]. Among females, last receipt of live and inactivated vaccines concurrently was significantly associated with non-vaccine-targeted infection risk (aHR = 0.94, 95% CI: 0.91-0.97 vs. last receipt of inactivated vaccines only). CONCLUSIONS: We observed modest associations between live vaccine receipt and non-vaccine-targeted infections. In this observational study, multiple factors, including healthcare-seeking behavior, may have influenced results.

Efficacy of a Web-Based Intervention to Increase Uptake of Maternal Vaccines: An RCT.

INTRODUCTION: Tetanus, diphtheria, and acellular pertussis (Tdap) and influenza vaccines are recommended for pregnant women in each pregnancy, yet uptake is suboptimal. This study tested the efficacy of an online vaccine resource in increasing uptake of Tdap and influenza vaccines among pregnant women. STUDY DESIGN: RCT. SETTING/PARTICIPANTS: This study was conducted among women in the third trimester of pregnancy in an integrated healthcare system in Colorado in September 2013-July 2016, with data analysis in 2017-2018. INTERVENTION: Women were randomly assigned to 1 of 3 arms: website with vaccine information and interactive social media components, website with vaccine information only, or usual care. Participants in the website with vaccine information and interactive social media components and website with vaccine information only arms had access to the same base vaccine content. The website with vaccine information and interactive social media components also included a blog, discussion forum, and "Ask a Question" portal. MAIN OUTCOME MEASURES: Tdap and influenza vaccination. These outcomes were analyzed separately. RESULTS: For influenza (n=289), women in both the website with vaccine information and interactive social media components (OR=2.19, 95% CI=1.06, 4.53) and website with vaccine information only (OR=2.20, 95% CI=1.03, 4.69) arms had higher vaccine uptake than the usual care arm. The proportions of women receiving the influenza vaccine were 57%, 55%, and 36% in the website with vaccine information and interactive social media components, website with vaccine information only, and usual care arms, respectively. For Tdap (n=173), there were no significant differences in vaccine uptake between study arms. The proportions of women receiving Tdap were 71%, 69%, and 68% in the website with vaccine information and interactive social media components, website with vaccine information only, and usual care arms, respectively. CONCLUSIONS: Web-based vaccination information sent to pregnant women can positively influence maternal influenza vaccine uptake. Because of potential scalability, the impact of robust vaccination information websites should be studied in other settings. TRIAL REGISTRATION: This study is registered at www.clinicaltrials.gov NCT01873040.

Addressing personal parental values in decisions about childhood vaccination: Measure development.

OBJECTIVE: Evidence-based strategies to address vaccine hesitancy are lacking. Personal values are a measurable psychological construct that could be used to deliver personalized messages to influence vaccine hesitancy and behavior. Our objectives were to develop a valid, reliable self-report survey instrument to measure vaccine values based on the Schwartz theory of basic human values, and to test the hypothesis that vaccine values are distinct from vaccine attitudes and are related to vaccine hesitancy and behavior. METHODS: Parental Vaccine Values (PVV) scale items were generated using formative qualitative research and expert input, yielding 24 items for testing. 295 parents of children aged 14-30 months completed a self-report survey with measures of Schwartz's global values, the PVV, vaccine attitudes, and vaccine hesitancy. Factor analysis was used to determine vaccine values factor structure. Associations between vaccine values, vaccine attitudes, vaccine hesitancy, and vaccination behavior were assessed using linear and logistic regression models. Late vaccination was assessed from electronic medical records. RESULTS: A six-factor structure for vaccine values was determined with good fit (RMSEA = 0.07, Bentler's CFI = 0.91) with subscales for Conformity, Universalism, Tradition, Self-Direction, Security- Disease Prevention, and Security- Vaccine Risk. Vaccine values were moderately associated with Schwartz global values and vaccine attitudes, indicating discriminant validity from these constructs. Multivariable linear regression showed vaccine hesitancy was associated with vaccine values Conformity (partial R2 = 0.10) and Universalism (0.04) and vaccine attitudes Vaccine Safety (0.52) and Vaccine Benefit (0.16). Multivariable logistic regression showed that late vaccination was associated with vaccine value Self-direction (OR = 1.80, 95% CI: 1.26-2.65) and vaccine attitude of Vaccine Benefit (OR = 0.44, 95% CI: 0.32-0.60). CONCLUSIONS: The PVV scale had good psychometric properties and appears related to but distinct from Schwartz global values and vaccine attitudes. Vaccine values are associated with vaccine hesitancy and late vaccination and may be useful in tailoring future interventions.

Association Between Opioid Dose Variability and Opioid Overdose Among Adults Prescribed Long-term Opioid Therapy.

Importance: Attempts to discontinue opioid therapy to reduce the risk of overdose and adhere to prescribing guidelines may lead patients to be exposed to variability in opioid dosing. Such dose variability may increase the risk of opioid overdose even if therapy discontinuation is associated with a reduction in risk. Objective: To examine the association between opioid dose variability and opioid overdose. Design, Setting, and Participants: A nested case-control study was conducted in a large Colorado integrated health plan and delivery system from January 1, 2006, through June 30, 2018. Cohort members were individuals prescribed long-term opioid therapy. Exposures: Dose variability was defined as the SD of the milligrams of morphine equivalents across each patient's follow-up and categorized based on the quintile distribution of the SD in the cohort (0-5.3, 5.4-9.1, 9.2-14.6, 14.7-27.2, and >27.2 mg of morphine equivalents). Main Outcomes and Measures: Opioid overdose cases were identified using International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes. Each case patient with overdose was matched to up to 20 control patients using risk set sampling. Conditional logistic regression models were used to generate matched odds ratios and 95% CIs, adjusted for age, sex, race/ethnicity, drug or alcohol use disorder, tobacco use, benzodiazepine dispensings, medical comorbidities, mental health disorder, opioid dose, and opioid formulation. Results: In a cohort of 14 898 patients (mean [SD] age, 56.3 [16.0] years; 8988 [60.3%] female) prescribed long-term opioid therapy, 228 case patients with incident opioid overdose were matched to 3547 control patients. The mean (SD) duration of opioid therapy was 36.7 (33.7) months in case patients and 33.0 (30.9) months in control patients. High-dose variability (SD >27.2 mg of morphine equivalents) was associated with a significantly increased risk of overdose compared with low-dose variability (matched odds ratio, 3.32; 95% CI, 1.63-6.77) independent of opioid dose. Conclusions and Relevance: Variability in opioid dose may be a risk factor for opioid overdose, suggesting that practitioners should seek to minimize dose variability when managing long-term opioid therapy.

Development and evaluation of a standardized research definition for opioid overdose outcomes.

Background: Increasing epidemiologic and intervention research is being conducted on opioid overdose, a serious and potentially fatal outcome. However, there is little consensus on how to verify opioid overdose outcomes for research purposes. To ensure reproducibility, minimize misclassification, and permit data harmonization across studies, standardized and consistent overdose definitions are needed. The aims were to develop a case criteria classification scheme based on information commonly available in medical records and to compare it with reviewing physician clinical impression and simple encounter documentation. Methods: In 2 large health systems, we developed a case criteria classification scheme for opioid overdose based on prior literature, expert opinion, and pilot testing with sample medical records. We then identified emergency department and hospital encounters (n = 259) with at least 1 International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code representing a broad range of opioid and non-opioid related poisonings. Physicians conducted structured medical record reviews to identify the proposed case criteria and generate a clinical impression, and trained abstractors verified documentation. We then compared the case criteria classification scheme with clinical impression and encounter documentation. Results: We developed a quantitative opioid overdose case criteria classification scheme that included 3 sets of major criteria and 9 minor criteria (supporting documentation). For the encounters identified using poisoning codes, the proportion verified as opioid overdoses using the case criteria classification scheme, clinical impression, and encounter documentation ranged from 50.4% to 52.7% at one site and 55.5% to 67.2% at the second site. Discrepancies across approaches and sites related to differences in available records and documentation of clinical signs of overdose. Conclusions: We propose a novel case criteria classification scheme for opioid overdose that could be used to rigorously and consistently define overdose across multiple research settings. However, prior to widespread use, further refinement and validation are needed.

Social Media Vaccine Websites: A Comparative Analysis of Public and Moderated Websites.

The internet is an important source of vaccine information for parents. We evaluated and compared the interactive content on an expert moderated vaccine social media (VSM) website developed for parents of children 24 months of age or younger and enrolled in a health care system to a random sample of interactions extracted from publicly available parenting and vaccine-focused blogs and discussion forums. The study observation period was September 2013 through July 2016. Three hundred sixty-seven eligible websites were located using search terms related to vaccines. Seventy-nine samples of interactions about vaccines on public blogs and discussion boards and 61 interactions from the expert moderated VSM website were coded for tone, vaccine stance, and accuracy of information. If information was inaccurate, it was coded as corrected, partially corrected or uncorrected. Using chi-square or Fisher's exact tests, we compared coded interactions from the VSM website with coded interactions from the sample of publicly available websites. We then identified representative quotes to illustrate the quantitative results. Tone, vaccine stance, and accuracy of information were significantly different (all p < .05). Publicly available vaccine websites tended to be more contentious and have a negative stance toward vaccines. These websites also had inaccurate and uncorrected information. In contrast, the expert moderated website had a more civil tone, minimal posting of inaccurate information, with very little participant-to-participant interaction. An expert moderated, interactive vaccine website appears to provide a platform for parents to gather accurate vaccine information, express their vaccine concerns and ask questions of vaccine experts.

Novel Opioid Safety Clinic Initiative to Deliver Guideline-Concordant Chronic Opioid Therapy in Primary Care.

OBJECTIVE: To develop and evaluate a novel Opioid Safety Clinic (OSC) initiative to enhance adherence to guidelines on the assessment and monitoring of patients prescribed chronic opioid therapy (COT). PATIENTS AND METHODS: The OSC was developed at an urban Federally Qualified Health Center to provide guideline-concordant care for COT, standardize workflows, and efficiently use clinic staff. We evaluated the OSC using a matched cohort study. Five hundred thirty-nine patients participated in the clinic between July 1, 2014, and March 31, 2016. Of these, 472 clinic participants were matched to 472 nonparticipants by sex and age on the date of the OSC visit. The OSC was evaluated by its completion rates of standardized pain assessments, urine toxicology, and naloxone dispensings. We conducted logistic regression comparing OSC participants to OSC nonparticipants. RESULTS: A total of 539 patients attended an OSC visit, representing approximately 53% of patients in the chronic opioid registry. The OSC participants were more likely than nonparticipants to have completed a pain assessment (adjusted odds ratio [aOR], 169.8; 95% CI, 98.3-293.5), completed a urine toxicology (aOR, 46.1; 95% CI, 30.4-69.9), or had naloxone dispensed (aOR, 2.8; 95% CI, 1.9-4.3) over 12 months of follow-up. CONCLUSION: The OSC model improved adherence to guideline-concordant COT in primary care. Future research is needed to assess the impact of these interventions on pain, quality of life, and adverse events from opioid analgesics.

Addressing Parents' Vaccine Concerns: A Randomized Trial of a Social Media Intervention.

INTRODUCTION: Successful strategies are needed to address parental vaccine hesitancy, a significant public health issue. The study objective was to assess whether an Internet-based platform with vaccine information and interactive social media components improved parents' vaccine-related attitudes. STUDY DESIGN: A three-arm RCT. SETTING/PARTICIPANTS: The study was conducted in a large Colorado integrated healthcare organization. Parents were enrolled during September 2013 through October 2015 and followed through November 2016; data were analyzed in 2017. Parents, recruited during pregnancy, were given a survey about vaccine-related attitudes at enrollment (i.e., baseline) and when their child was aged 3-5 months and 12-15 months (Timepoints 1 and 2, respectively). Parental vaccine hesitancy was assessed at baseline. INTERVENTION: Study participants were randomized to the following: a study website with vaccine information and social media components (VSM arm); a website with vaccine information only (VI); or usual care. MAIN OUTCOME MEASURES: Change in parental vaccine attitudes over time by baseline degree of vaccine hesitancy. RESULTS: Among 1,093 study participants, 945 (86.5%) completed all three surveys. Comparing baseline with Timepoint 1 among vaccine-hesitant parents, the VSM and VI arms were associated with significant improvements in attitudes regarding vaccination benefits compared to usual care (VSM mean change 0.23 on a 5-point scale, 95% CI=0.05, 0.40, VI mean change 0.22, 95% CI=0.04, 0.40). Comparing baseline with Timepoint 2 among hesitant parents, the VSM and VI arms were also associated with significant reductions in parental concerns about vaccination risks compared to usual care (VSM mean change -0.37, 95% CI= -0.60, -0.14, VI mean change -0.31, 95% CI= -0.55, -0.07). Self-efficacy around vaccine decision making also improved among vaccine-hesitant parents. No intervention effect was observed among parents not vaccine-hesitant at baseline. CONCLUSIONS: Among vaccine-hesitant parents, an Internet-based intervention improved parents' attitudes about vaccines. TRIAL REGISTRATION: This study was registered at www.clinicaltrials.gov NCT01873040.