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.

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.

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.

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.

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.

A Values-Tailored Web-Based Intervention for New Mothers to Increase Infant Vaccine Uptake: Development and Qualitative Study.

BACKGROUND: Vaccine hesitancy among parents leads to childhood undervaccination and outbreaks of vaccine-preventable disease. As the reasons for vaccine hesitancy are diverse, there is often not enough time during regular clinical visits for medical providers to adequately address all the concerns that parents have. Providing individually tailored vaccine information via the internet before a clinical visit may be a good mechanism for effectively allaying parents' vaccination concerns while also being time efficient. Including tailoring based on values is a promising, but untested, approach to message creation. OBJECTIVE: This study aimed to describe the process by which we developed a Web-based intervention that is being used in an ongoing randomized controlled trial aimed at improving the timeliness of infant vaccination by reducing parental vaccine hesitancy. METHODS: Development of the intervention incorporated evidence-based health behavior theories. A series of interviews, surveys, and feedback sessions were used to iteratively develop the intervention in collaboration with vaccination experts and potential end users. RESULTS: In all, 41 specific content areas were identified to be included in the intervention. User feedback elucidated preferences for specific design elements to be incorporated throughout the website. The tile-based architecture chosen for the website was perceived as easy to use. Creating messages that were two-sided was generally preferred over other message formats. Quantitative surveys identified associations between specific vaccine values and vaccination beliefs, suggesting that values tailoring should vary, depending on the specific belief being endorsed. CONCLUSIONS: Using health behavior theories, qualitative and quantitative data, and significant expert and end user input, we created a novel, Web-based intervention to improve infant vaccination timeliness. The intervention is based on tailoring messages according to each individual's values and beliefs. This intervention is currently being tested in a controlled randomized clinical trial.

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.

Prediction Model for Two-Year Risk of Opioid Overdose Among Patients Prescribed Chronic Opioid Therapy.

BACKGROUND: Naloxone is a life-saving opioid antagonist. Chronic pain guidelines recommend that physicians co-prescribe naloxone to patients at high risk for opioid overdose. However, clinical tools to efficiently identify patients who could benefit from naloxone are lacking. OBJECTIVE: To develop and validate an overdose predictive model which could be used in primary care settings to assess the need for naloxone. DESIGN: Retrospective cohort. SETTING: Derivation site was an integrated health system in Colorado; validation site was a safety-net health system in Colorado. PARTICIPANTS: We developed a predictive model in a cohort of 42,828 patients taking chronic opioid therapy and externally validated the model in 10,708 patients. MAIN MEASURES: Potential predictors and outcomes (nonfatal pharmaceutical and heroin overdoses) were extracted from electronic health records. Fatal overdose outcomes were identified from state vital records. To match the approximate shelf-life of naloxone, we used Cox proportional hazards regression to model the 2-year risk of overdose. Calibration and discrimination were assessed. KEY RESULTS: A five-variable predictive model showed good calibration and discrimination (bootstrap-corrected c-statistic = 0.73, 95% confidence interval [CI] 0.69-0.78) in the derivation site, with sensitivity of 66.1% and specificity of 66.6%. In the validation site, the model showed good discrimination (c-statistic = 0.75, 95% CI 0.70-0.80) and less than ideal calibration, with sensitivity and specificity of 82.2% and 49.5%, respectively. CONCLUSIONS: Among patients on chronic opioid therapy, the predictive model identified 66-82% of all subsequent opioid overdoses. This model is an efficient screening tool to identify patients who could benefit from naloxone to prevent overdose deaths. Population differences across the two sites limited calibration in the validation site.

Association Between Estimated Cumulative Vaccine Antigen Exposure Through the First 23 Months of Life and Non-Vaccine-Targeted Infections From 24 Through 47 Months of Age.

Importance: Some parents are concerned that multiple vaccines in early childhood could weaken their child's immune system. Biological data suggest that increased vaccine antigen exposure could increase the risk for infections not targeted by vaccines. Objective: To examine estimated cumulative vaccine antigen exposure through the first 23 months of life in children with and without non-vaccine-targeted infections from 24 through 47 months of age. Design, Setting, and Participants: A nested case-control study was conducted in 6 US health care organizations participating in the Vaccine Safety Datalink. Cases were identified by International Classification of Diseases codes for infectious diseases in the emergency department and inpatient medical settings and then validated by medical record review. Cases of non-vaccine-targeted infection were matched to controls by age, sex, health care organization site, and chronic disease status. Participants were children ages 24 through 47 months, born between January 1, 2003, and September 31, 2013, followed up until December 31, 2015. Exposures: Cumulative vaccine antigen exposure, estimated by summing the number of antigens in each vaccine dose received from birth through age 23 months. Main Outcomes and Measures: Non-vaccine-targeted infections, including upper and lower respiratory infections and gastrointestinal infections, from 24 through 47 months of age, and the association between these infections and estimated cumulative vaccine exposure from birth through 23 months. Conditional logistic regression was used to estimate matched odds ratios representing the odds of non-vaccine-targeted infections for every 30-unit increase in estimated cumulative number of antigens received. Results: Among the 944 patients (193 cases and 751 controls), the mean (SD) age was 32.5 (6.3) months, 422 (45%) were female, and 61 (7%) had a complex chronic condition. Through the first 23 months, the estimated mean (SD) cumulative vaccine antigen exposure was 240.6 (48.3) for cases and 242.9 (51.1) for controls. The between-group difference for estimated cumulative antigen exposure was -2.3 (95% CI, -10.1 to 5.4; P = .55). Among children with vs without non-vaccine-targeted infections from 24 through 47 months of age, the matched odds ratio for estimated cumulative antigen exposure through age 23 months was not significant (matched odds ratio, 0.94; 95% CI, 0.84 to 1.07). Conclusions and Relevance: Among children from 24 through 47 months of age with emergency department and inpatient visits for infectious diseases not targeted by vaccines, compared with children without such visits, there was no significant difference in estimated cumulative vaccine antigen exposure through the first 23 months of life.

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.

Association of chronic opioid therapy and opioid use disorder with COVID-19-related hospitalization and mortality: Evidence from three health systems in the United States.

Objective: Chronic opioid use can lead to detrimental effects on the immune and various organ systems that put individuals prescribed chronic opioid therapy (COT) for pain and those with an opioid use disorder (OUD) at risk for severe COVID-19 disease. We assessed the association of COT and OUD with COVID-19-related hospitalization and death to inform targeted interventions to improve clinical outcomes in COVID-19 patients who use opioids. Methods: We conducted a retrospective cohort study of adults ages ≥ 18 with laboratory-confirmed SARS-CoV-2 infection in 2020 and 2021 from three US health systems. We used Cox proportional hazards regression to estimate the 30-day risk of COVID-19-related hospitalization and death associated with two opioid exposures (COT and OUD) following an infection. Results: The study cohort included 53,123 patients with SARS-CoV-2 infection and a mean (SD) age of 45.1 (16.5), of whom 1,059 (2.0 %) were exposed to COT and 269 (0.5 %) had an OUD diagnosis in the year prior to infection. There were 2,270 observed COVID-19-related hospitalizations or deaths (1.6 per 1,000 person-days, 95 % CI 1.5-1.7). In the fully adjusted model, COT was not associated with increased risk (HR 1.19; 95 % CI, 0.98-1.43), while past-year OUD was independently associated with severe COVID-19 disease (HR 1.82; 95 % CI, 1.18-2.80). Past-year OUD remained associated with increased risk in post-hoc analysis with COVID-19-related hospitalization alone as the outcome (HR 2.00; 95 % CI, 1.30-3.08). Conclusions: Past-year OUD is a potential independent risk factor for severe COVID-19 disease that warrants monitoring to improve the prognosis of patients with COVID-19.

Assessing the association between antibody status and symptoms of long COVID: A multisite study.

The association between SARS-CoV-2 humoral immunity and post-acute sequelae of COVID-19 (long COVID) remains uncertain. The objective of this population-based cohort study was to assess the association between SARS-CoV-2 seropositivity and symptoms consistent with long COVID. English and Spanish-speaking members ≥ 18 years old with SARS-CoV-2 serologic testing conducted prior to August 2021 were recruited from Kaiser Permanente Southern California and Kaiser Permanente Colorado. Between November 2021 and April 2022, participants completed a survey assessing symptoms, physical health, mental health, and cognitive function consistent with long COVID. Survey results were linked to SARS-CoV-2 antibody (Ab) and viral (RNA) lab results in electronic health records. Weighted descriptive analyses were generated for five mutually exclusive patient groups: (1) +Ab/+RNA; (2) +Ab/- or missing RNA; (3) -Ab/+RNA; (4a) -Ab/-RNA reporting no prior infection; and (4b) -Ab/-RNA reporting prior infection. The proportions reporting symptoms between the +Ab/+RNA and -Ab/+RNA groups were compared, adjusted for covariates. Among 3,946 participants, the mean age was 52.1 years old (SD 15.6), 68.3% were female, 28.4% were Hispanic, and the serologic testing occurred a median of 15 months prior (IQR = 12-18). Three quarters (74.5%) reported having had COVID-19. Among people with laboratory-confirmed COVID-19, there was no association between antibody positivity (+Ab/+RNA vs. -Ab/+RNA) and any symptoms, physical health, mental health, or cognitive function. As expected, physical health, cognitive function, and fatigue were worse, and palpitations and headaches limiting the ability to work were more prevalent among people with laboratory-confirmed prior infection and positive serology (+Ab/+RNA) compared to those without reported or confirmed prior infection and negative serology (-Ab/-RNA/no reported COVID-19). Among people with laboratory-confirmed COVID-19, SARS-CoV-2 serology from practice settings were not associated with long COVID symptoms and health status suggesting limited utility of serology testing for long COVID.

Further evidence for bias in observational studies of influenza vaccine effectiveness: the 2009 influenza A(H1N1) pandemic.

Preinfluenza periods have been used to test for uncontrolled confounding in studies of influenza vaccine effectiveness, but some authors have claimed that confounding differs in preinfluenza and influenza periods. We tested this claim by comparing estimates of the vaccine-mortality association during the 2009/2010 influenza year, when there was essentially no circulation of seasonal influenza in the United States, and 2007/2008, a typical influenza year. We pooled data on seniors (adults aged ≥65 years) from 7 US managed care organizations that participated in the Vaccine Safety Datalink Project. We defined influenza vaccination, all-cause mortality, and potential confounders from administrative databases. We quantified the vaccine-mortality association using Cox regression. During 2007/2008, the adjusted hazard ratio was 0.44 prior to influenza season, 0.62 during influenza season, and 0.71 after influenza season. A similar pattern was observed during 2009/2010, when any effect of seasonal influenza vaccine observed during all time periods must have resulted from confounding: 0.65 during the autumn, 0.80 during the winter, and 0.84 during the summer. In a year with minimal seasonal influenza, we found no evidence that confounding in autumn preinfluenza periods is qualitatively different from confounding in winter. This supports the use of preinfluenza periods as control time periods in studies of influenza vaccine effectiveness.

Risk of adverse events following oseltamivir treatment in influenza outpatients, Vaccine Safety Datalink Project, 2007-2010.

PURPOSE: An association between the influenza antiviral medication oseltamivir and neuropsychiatric events has been suggested by post-marketing case reports in Japan. This possible association was not supported by cohort studies in the U.S. conducted prior to the 2009 influenza A (H1N1) pandemic, when usage rates were comparatively low. We assessed oseltamivir safety before and during the pandemic using biologically plausible risk intervals, particularly focusing on psychiatric events. METHODS: Outpatients with influenza episodes from January 2007 through June 2010 were identified using diagnosis codes and positive tests at eight health care systems (sites) in the Vaccine Safety Datalink Project. Oseltamivir-treated and untreated patients were matched according to calendar week, age, sex, site, and propensity for treatment. Within this matched cohort, conditional logistic regression models were used to estimate the risk of four neuropsychiatric and five other adverse events (AEs) during pre-specified risk intervals. RESULTS: Among 27,684 matched pairs, no associations were identified between oseltamivir treatment and any pre-defined AE. The absolute risks of incident psychiatric events in the 1-7 day risk interval were 0.126% for oseltamivir-treated and 0.105% for untreated patients (odds ratio = 1.21, 95% confidence interval [CI]: 0.74, 1.97; risk difference = 0.022%, 95% CI: -0.035%, 0.078%); the most common diagnosis was unspecified anxiety state. Results were similar for 1-14 and 1-2 day risk intervals and for pediatric/adolescent subgroups. CONCLUSIONS: Consistent with prior U.S. cohort studies, no evidence was identified for an increased risk of neuropsychiatric or other AEs following oseltamivir treatment. Safety should be prospectively monitored to inform antiviral medication usage recommendations.

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.

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.

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.

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.

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.

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.