Racial and ethnic disparities in influenza vaccination coverage among pregnant women in the United States: The contribution of vaccine-related attitudes.

OBJECTIVE: Racial and ethnic disparities in influenza vaccination coverage among pregnant women in the United States have been documented. This study assessed the contribution of vaccine-related attitudes to coverage disparities. METHODS: Surveys were conducted following the 2019-2020 and 2020-2021 influenza seasons in a US research network. Using electronic health record data to identify pregnant women, random samples were selected for surveying; non-Hispanic Black women and influenza-unvaccinated women were oversampled. Regression-based decomposition analyses were used to assess the contribution of vaccine-related attitudes to racial and ethnic differences in influenza vaccination. Data were combined across survey years, and analyses were weighted and accounted for survey design. RESULTS: Survey response rate was 41.2% (721 of 1748) for 2019-2020 and 39.3% (706 of 1798) for 2020-2021. Self-reported influenza vaccination was higher among non-Hispanic White respondents (79.4% coverage, 95% CI 73.1%-85.7%) than Hispanic (66.2% coverage, 95% CI 52.5%-79.9%) and non-Hispanic Black (55.8% coverage, 95% CI 50.2%-61.4%) respondents. For all racial and ethnic groups, a high proportion (generally >80%) reported being seen for care, recommended for influenza vaccination, and offered vaccination. In decomposition analyses, vaccine-related attitudes (e.g., worry about vaccination causing influenza; concern about vaccine safety and effectiveness) explained a statistically significant portion of the observed racial and ethnic disparities in vaccination. Maternal age, education, and health status were not significant contributors after controlling for vaccine-related attitudes. CONCLUSIONS: In a setting with relatively high influenza vaccination coverage among pregnant women, racial and ethnic disparities in coverage were identified. Vaccine-related attitudes were associated with the disparities observed.

Spinal cord injury and prescribed opioids for pain: a scoping review.

OBJECTIVE: Spinal cord injury (SCI) is a life-altering neurological condition affecting physical and psycho-social functioning and associated high rates of pain. Thus, individuals with SCI may be more likely to be exposed to prescription opioids. A scoping review was conducted to synthesize published research findings on post-acute SCI and prescription opioid use for pain, identify literature gaps, and propose recommendations for future research. METHODS: We searched 6 electronic bibliographic databases (PubMed [MEDLINE], Ovid [MEDLINE], EMBASE, Cochrane Library, CINAHL, PsychNET) for articles published from 2014 through 2021. Terms for "spinal cord injury" and "prescription opioid use" were used. Included articles were in English and peer reviewed. Data were extracted using an electronic database by 2 independent reviewers. Opioid use risk factors for chronic SCI were identified and a gap analysis was performed. RESULTS: Of the 16 articles included in the scoping review, a majority were conducted in the United States (n = 9). Most articles lacked information on income (87.5%), ethnicity (87.5%), and race (75%). Prescription opioid use ranged from 35% to 64% in articles reporting this information (n = 7 articles, n = 3675 participants). Identified risk factors for opioid use included middle age, lower income, osteoarthritis diagnosis, prior opioid use, and lower-level spinal injury. Limited reporting of diversity in study populations, absence of risk of polypharmacy, and limited high quality methodology were identified gaps. CONCLUSIONS: Future research should report data on prescription opioid use in SCI populations, with additional demographics such as race, ethnicity, and income, given their importance to risk outcomes.

Modifying and Evaluating the Opioid Overdose Knowledge Scale for Prescription Opioids: A Pilot Study of the Rx-OOKS.

OBJECTIVE: To develop a validated instrument that measures knowledge about prescription opioid overdose. METHODS: Within an integrated health care system, we adapted, piloted, and tested the reliability and predictive validity of a modified Opioid Overdose Knowledge Scale (OOKS) instrument specific to prescription opioids (Rx-OOKS) with a patient population prescribed long-term opioid therapy and potentially at risk of opioid overdose. We used an interdisciplinary team approach and patient interviews to adapt the instrument. We then piloted the survey on a patient sample and assessed it using Cronbach's alpha and logistic regression. RESULTS: Rx-OOKS (N = 56) resulted in a three-construct, 25-item instrument. Internal consistency was acceptable for the following constructs: "signs of an overdose" (10 items) at α = 0.851, "action to take with opioid overdose" (seven items) at α = 0.692, and "naloxone use knowledge" (eight items) at α = 0.729. One construct, "risks of an overdose" (three items), had an α of 0.365 and was subsequently eliminated from analysis due to poor performance. We conducted logistic regression to determine if any of the constructs was strongly associated with future naloxone receipt. Higher scores on "actions to take in an overdose" had nine times the odds of receiving naloxone (odds ratio [OR] = 9.00, 95% confidence interval [CI] = 1.42-57.12); higher "naloxone use knowledge" scores were 15.8 times more likely to receive naloxone than those with lower scores (OR = 15.83, 95% CI = 1.68-149.17). CONCLUSIONS: The Rx-OOKS survey instrument can reliably measure knowledge about prescription opioid overdose recognition and naloxone use. Further, knowledge about actions to take during an opioid overdose and naloxone use were associated with future receipt of naloxone.

Effect of continuity of care on hospital utilization for seniors with multiple medical conditions in an integrated health care system.

PURPOSE: Lower continuity of care has been associated with higher rates of adverse outcomes for persons with multiple chronic medical conditions. It is unclear, however, whether this relationship also exists within integrated systems that offer high levels of informational continuity through shared electronic health records. METHODS: We conducted a retrospective cohort study of 12,200 seniors with 3 or more chronic conditions within an integrated delivery system. Continuity of care was calculated using the Continuity of Care Index, which reflects visit concentration with individual clinicians. Using Cox proportional hazards regression permitting continuity to vary monthly until the outcome or censoring event, we separately assessed inpatient admissions and emergency department visits as a function of primary care continuity and specialty care continuity. RESULTS: After adjusting for covariates (demographics; baseline, primary, and specialty care visits; baseline outcomes; and morbidity burden), greater primary care continuity and greater specialty care continuity were each associated with a lower risk of inpatient admission (respective hazard ratios (95% CIs) = 0.97 (0.96, 0.99) and 0.95 (0.93, 0.98)) and a lower risk of emergency department visits (respective hazard ratios = 0.97 (0.96, 0.98) and 0.98 (0.96, 1.00)). For the subgroup with 3 or more primary care and 3 or more specialty care visits, specialty care continuity (but not primary care continuity) was independently associated with a decreased risk of inpatient admissions (hazard ratio = 0.94 (0.92, 0.97)), and primary care continuity (but not specialty care continuity) was associated with a decreased risk of emergency department visits (hazard ratio = 0.98 (0.96, 1.00)). CONCLUSIONS: In an integrated delivery system with high informational continuity, greater continuity of care is independently associated with lower hospital utilization for seniors with multiple chronic medical conditions. Different subgroups of patients will benefit from continuity with primary and specialty care clinicians depending on their care needs.

Assessment of morbidity over time in predicting health outcomes.

BACKGROUND: Administratively derived morbidity measures are often used in observational studies as predictors of outcomes. These typically reflect a limited time period before an index event; some outcomes may be affected by rate of morbidity change over longer preindex periods. OBJECTIVES: The aim of the study was to develop statistical models representing the trajectory of individual morbidity over time and to evaluate the performance of trajectory versus other summary morbidity measures in predicting a range of health outcomes. METHODS: From a retrospective cohort study of integrated health system members aged 65 years or older with 3 or more common chronic medical conditions, we used available diagnoses for up to 10 years to examine associations between variations of the Charlson Comorbidity Index (CCI, Quan adaptation) and health outcomes. A linear mixed effects model was used to estimate the trajectory of individual CCI over time; estimated parameters describing individual trajectories were used as predictors for health outcomes. Other variations of CCI were: a "snapshot" measure, a cumulative measure, and actual baseline and rate of change. Models were developed in an initial cohort for whom we had survey data, and verified in a larger cohort. RESULTS: Among 961 surveyed members and 13,163 members of a secondary cohort, cumulative and snapshot measures provided best fit and predictive ability for utilization outcomes. Incorporating trajectory resulted in a slightly better model for self-reported health status. CONCLUSIONS: Modeling longitudinal morbidity trajectories did not add substantially to the association between morbidity and utilization or mortality. Standard snapshot morbidity measures likely sufficiently capture multimorbidity in assessing these outcomes.

Influenza vaccination accuracy among adults: Self-report compared with electronic health record data.

OBJECTIVE: To assess the validity of electronic health record (EHR)-based influenza vaccination data among adults in a multistate network. METHODS: Following the 2018-2019 and 2019-2020 influenza seasons, surveys were conducted among a random sample of adults who did or did not appear influenza-vaccinated (per EHR data) during the influenza season. Participants were asked to report their influenza vaccination status; self-report was treated as the criterion standard. Results were combined across survey years. RESULTS: Survey response rate was 44.7% (777 of 1740) for the 2018-2019 influenza season and 40.5% (505 of 1246) for the 2019-2020 influenza season. The sensitivity of EHR-based influenza vaccination data was 75.0% (95% confidence interval [CI] 68.1, 81.1), specificity 98.4% (95% CI 92.9, 99.9), and negative predictive value 73.9% (95% CI 68.0, 79.3). CONCLUSIONS: In a multistate research network across two recent influenza seasons, there was moderate concordance between EHR-based vaccination data and self-report.

Attitudes Toward COVID-19 Vaccines Among Pregnant and Recently Pregnant Individuals.

Importance: Pregnant people and infants are at high risk of severe COVID-19 outcomes. Understanding changes in attitudes toward COVID-19 vaccines among pregnant and recently pregnant people is important for public health messaging. Objective: To assess attitudinal trends regarding COVID-19 vaccines by (1) vaccination status and (2) race, ethnicity, and language among samples of pregnant and recently pregnant Vaccine Safety Datalink (VSD) members from 2021 to 2023. Design, Setting, and Participants: This cross-sectional surveye study included pregnant or recently pregnant members of the VSD, a collaboration of 13 health care systems and the US Centers for Disease Control and Prevention. Unvaccinated, non-Hispanic Black, and Spanish-speaking members were oversampled. Wave 1 took place from October 2021 to February 2022, and wave 2 took place from November 2022 to February 2023. Data were analyzed from May 2022 to September 2023. Exposures: Self-reported or electronic health record (EHR)-derived race, ethnicity, and preferred language. Main Outcomes and Measures: Self-reported vaccination status and attitudes toward monovalent (wave 1) or bivalent Omicron booster (wave 2) COVID-19 vaccines. Sample- and response-weighted analyses assessed attitudes by vaccination status and 3 race, ethnicity, and language groupings of interest. Results: There were 1227 respondents; all identified as female, the mean (SD) age was 31.7 (5.6) years, 356 (29.0%) identified as Black race, 555 (45.2%) identified as Hispanic ethnicity, and 445 (36.3%) preferred the Spanish language. Response rates were 43.5% for wave 1 (652 of 1500 individuals sampled) and 39.5% for wave 2 (575 of 1456 individuals sampled). Respondents were more likely than nonrespondents to be White, non-Hispanic, and vaccinated per EHR. Overall, 76.8% (95% CI, 71.5%-82.2%) reported 1 or more COVID-19 vaccinations; Spanish-speaking Hispanic respondents had the highest weighted proportion of respondents with 1 or more vaccination. Weighted estimates of somewhat or strongly agreeing that COVID-19 vaccines are safe decreased from wave 1 to 2 for respondents who reported 1 or more vaccinations (76% vs 50%; χ21 = 7.8; P < .001), non-Hispanic White respondents (72% vs 43%; χ21 = 5.4; P = .02), and Spanish-speaking Hispanic respondents (76% vs 53%; χ21 = 22.8; P = .002). Conclusions and Relevance: Decreasing confidence in COVID-19 vaccine safety in a large, diverse pregnant and recently pregnant insured population is a public health concern.

Bias correction of risk estimates in vaccine safety studies with rare adverse events using a self-controlled case series design.

The self-controlled case series (SCCS) method is often used to examine the temporal association between vaccination and adverse events using only data from patients who experienced such events. Conditional Poisson regression models are used to estimate incidence rate ratios, and these models perform well with large or medium-sized case samples. However, in some vaccine safety studies, the adverse events studied are rare and the maximum likelihood estimates may be biased. Several bias correction methods have been examined in case-control studies using conditional logistic regression, but none of these methods have been evaluated in studies using the SCCS design. In this study, we used simulations to evaluate 2 bias correction approaches-the Firth penalized maximum likelihood method and Cordeiro and McCullagh's bias reduction after maximum likelihood estimation-with small sample sizes in studies using the SCCS design. The simulations showed that the bias under the SCCS design with a small number of cases can be large and is also sensitive to a short risk period. The Firth correction method provides finite and less biased estimates than the maximum likelihood method and Cordeiro and McCullagh's method. However, limitations still exist when the risk period in the SCCS design is short relative to the entire observation period.

The RE-AIM framework: a systematic review of use over time.

We provided a synthesis of use, summarized key issues in applying, and highlighted exemplary applications in the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. We articulated key RE-AIM criteria by reviewing the published literature from 1999 to 2010 in several databases to describe the application and reporting on various RE-AIM dimensions. After excluding nonempirical articles, case studies, and commentaries, 71 articles were identified. The most frequent publications were on physical activity, obesity, and disease management. Four articles reported solely on 1 dimension compared with 44 articles that reported on all 5 dimensions of the framework. RE-AIM was broadly applied, but several criteria were not reported consistently.

Effect of an Asthma Exacerbation on Medication Adherence.

BACKGROUND: Few studies have looked at the effect of an asthma exacerbation on asthma medication adherence. OBJECTIVE: To measure asthma medication adherence in the 12 months after an asthma exacerbation and the influence of care type (specialist vs primary care provider) as well as social economic status on adherence. METHODS: We measured portion of days covered (PDC) during the 12 months before and after an exacerbation in a cohort of patients with asthma who were aged 18 years and older. Subanalyses looked at PDC in those who had more than one exacerbation after the sentinel exacerbation, by type of care received (primary care, allergist or pulmonologist, or no care) during both periods and by socioeconomic status (SES), defined as the lower quartile of annual income for the group. RESULTS: In a cohort of 1,697 patients, PDC improved significantly (from 0.44 to 0.53; P < .001) after an asthma exacerbation. Improvement in PDC was even greater (from 0.45 to 0.57; P < .001) if they had more than one exacerbation after the sentinel exacerbation. Being seen by a specialist after the exacerbation but not before it, resulted in the greatest improvement in PDC (0.17 mean change). Patients not seen by a specialist either before the exacerbation or after had a mean change of just 0.07. Those with a lower SES had an overall lower PDC before the exacerbation (0.37 vs 0.43) but saw a similar improvement in the PDC compared with those in a higher SES (0.09 vs 0.10). CONCLUSIONS: An asthma exacerbation is associated with a significant and sustained effect on medication adherence.

Adapting adaptive design methods to accelerate adoption of a digital asthma management intervention.

Investigators conducting translational research in real-world settings may experience changes that create challenges to the successful completion of the trial as well as post-trial adoption and implementation. Adaptive designs support translational research by systematically adapting content and methods to meet the needs of target populations, settings and contexts. This manuscript describes an adaptive implementation research model that provides strategies for changing content, delivery processes, and research methods to correct course when anticipated and unanticipated circumstances occur during a pragmatic trial. The Breathewell Program included two large pragmatic trials of the effectiveness of a digital communication technology intervention to improve symptom management and medication adherence in asthma care. The first trial targeted parents of children with asthma; the second targeted adults with asthma. Adaptations were made iteratively to adjust to dynamic conditions within the healthcare setting, informed by prospectively collected stakeholder input, and were categorized retrospectively by the authors as proactive or reactive. Study outcomes demonstrated improved treatment adherence and clinical efficiency. Kaiser Permanente Colorado, the setting for both studies, adopted the speech recognition intervention into routine care, however, both interventions required numerous adaptations, including changes to target population, intervention content, and internal workflows. Proactive and reactive adaptations assured that both trials were successfully completed. Adaptive research designs will continue to provide an important pathway to move healthcare delivery research into practice while conducting ongoing effectiveness evaluation.

Health care research often moves slowly and consequently important results may take a long time to reach the patients they are intended to help. Implementation studies conducted in routine clinical practice are intended to accelerate the process of delivering new discoveries into settings where they can be more quickly put to use. However, conducting research in real-world settings can be challenging if changes occur in those settings during the course of the study. Therefore, an adaptive implementation approach that allows researchers to make changes during the course of a study can facilitate study completion and improve likelihood of intervention adoption into routine care. This report demonstrates the use of an adaptive implementation model in two large studies of asthma in children and adults. In both studies, communication technology including computerized phone calls, texts, and email helped improve treatment consistency and efficiency.

Influenza Vaccination Among Pregnant Women: Self-report Compared With Vaccination Data From Electronic Health Records, 2018-2020 Influenza Seasons.

OBJECTIVES: Having accurate influenza vaccination coverage estimates can guide public health activities. The objectives of this study were to (1) validate the accuracy of electronic health record (EHR)-based influenza vaccination data among pregnant women compared with survey self-report and (2) assess whether survey respondents differed from survey nonrespondents by demographic characteristics and EHR-based vaccination status. METHODS: This study was conducted in the Vaccine Safety Datalink, a network of 8 large medical care organizations in the United States. Using EHR data, we identified all women pregnant during the 2018-2019 or 2019-2020 influenza seasons. Surveys were conducted among samples of women who did and did not appear vaccinated for influenza according to EHR data. Separate surveys were conducted after each influenza season, and respondents reported their influenza vaccination status. Analyses accounted for the stratified design, sampling probability, and response probability. RESULTS: The survey response rate was 50.5% (630 of 1247) for 2018-2019 and 41.2% (721 of 1748) for 2019-2020. In multivariable analyses combining both survey years, non-Hispanic Black pregnant women had 3.80 (95% CI, 2.13-6.74) times the adjusted odds of survey nonresponse; odds of nonresponse were also higher for Hispanic pregnant women and women who had not received (per EHR data) influenza vaccine during current or prior influenza seasons. The sensitivity, specificity, and positive predictive value of EHR documentation of influenza vaccination compared with self-report were ≥92% for both survey years combined. The negative predictive value of EHR-based influenza vaccine status was 80.5% (95% CI, 76.7%-84.0%). CONCLUSIONS: EHR-based influenza vaccination data among pregnant women were generally concordant with self-report. New data sources and novel approaches to mitigating nonresponse bias may be needed to enhance influenza vaccination surveillance efforts.

A systematic review of collaboration and network research in the public affairs literature: implications for public health practice and research.

OBJECTIVES: We explored and analyzed how findings from public affairs research can inform public health research and practice, specifically in the area of interorganizational collaboration, one of the most promising practice-based approaches in the public health field. METHODS: We conducted a systematic review of the public affairs literature by following a grounded theory approach. We coded 151 articles for demographics and empirical findings (n = 258). RESULTS: Three primary findings stand out in the public affairs literature: network structure affects governance, management strategies exist for administrators, and collaboration can be linked to outcomes. These findings are linked to priorities in public health practice. CONCLUSIONS: Overall, we found that public affairs has a long and rich history of research in collaborations that offers unique organizational theory and management tools to public health practitioners.

Association of patient-centered outcomes with patient-reported and ICD-9-based morbidity measures.

PURPOSE: Evaluating patient-centered care for complex patients requires morbidity measurement appropriate for use with a variety of clinical outcomes. We compared the contributions of self-reported morbidity and morbidity measured using administrative diagnosis data for both patient-reported outcomes and utilization outcomes. METHODS: Using a cohort of 961 persons aged 65 years or older with 3 or more medical conditions, we explored 9 health outcomes as a function of 4 independent variables representing different types of morbidity measures: International Classification of Diseases, Ninth Revision (ICD-9), a self-reported weighted count of conditions, and self-reported symptoms of depression and of anxiety. Outcomes varied from self-reported health status to utilization. Depending on the outcome measure, we used multivariate linear, negative binomial, or logistic regression, adjusting for demographic characteristics and length of enrollment to assess associations between dependent and all 4 independent variables. RESULTS: Higher morbidity measured by ICD-9 diagnoses was independently associated with less favorable levels of 7 of the 9 clinical outcomes. Higher self-reported disease burden was significantly associated with less favorable levels of 8 of the outcomes, controlling for the 3 other morbidity measures. Morbidity measured by diagnosis code was more strongly associated with higher utilization, whereas self-reported disease burden and emotional symptoms were more strongly associated with patient-reported outcomes. CONCLUSIONS: A comprehensive assessment of morbidity requires both subjective and objective measurement of disease burden as well as an assessment of emotional symptoms. Such multidimensional morbidity measurement is particularly relevant for research or quality assessments involving the delivery of patient-centered care to complex patient populations.

Transition to Virtual Asthma Care During the COVID-19 Pandemic: An Observational Study.

BACKGROUND: The COVID-19 pandemic increased reliance on virtual care for patients with persistent asthma. OBJECTIVE: This retrospective cohort study assessed changes from in-person to virtual care during the pandemic. In patients with persistent asthma, compared with the same period before the pandemic. METHODS: Kaiser Permanente Colorado members aged 18 to 99 years with persistent asthma were evaluated during two periods (March to October 2019 and March to October 2020). Comparison of asthma exacerbations (hospitalizations, emergency department visits, and courses of oral prednisone) and asthma medication metrics were evaluated between the two periods and by type of care received during the pandemic (no care, virtual care only, in-person care only, or a mix of virtual and in-person care). Population characteristics by type of care received during the pandemic were also evaluated. RESULTS: Among 7,805 adults with persistent asthma, those who used more virtual care or sought no care during the pandemic were younger and had fewer comorbidities, mental health diagnoses, or financial barriers. Exacerbations decreased (0.264 to 0.214; P <.001) as did courses of prednisone (0.213 to 0.169). Asthma medication adherence (0.53 to 0.54; P <.001) and the asthma medication ratio, a quality-of-care metric (0.755 to 0.762; P = .019), increased slightly. Patients receiving a mix of in-person and virtual care had the highest rate of exacerbations (0.83) and a lower asthma medication ratio (0.74) despite having the highest adherence (.57). CONCLUSIONS: Despite an increase in virtual care, asthma exacerbations decreased except among individuals who received both in-person and virtual care, likely because they had more severe disease.

Can digital communication technology reduce health system personnel time? An evaluation of personnel requirements and costs in a randomized controlled trial.

Use of digital communication technologies (DCT) shows promise for enhancing outcomes and efficiencies in asthma care management. However, little is known about the impact of DCT interventions on healthcare personnel requirements and costs, thus making it difficult for providers and health systems to understand the value of these interventions. This study evaluated the differences in healthcare personnel requirements and costs between usual asthma care (UC) and a DCT intervention (Breathewell) aimed at maintaining guidelines-based asthma care while reducing health care staffing requirements. We used data from a pragmatic, randomized controlled trial conducted in a large integrated health system involving 14,978 patients diagnosed with asthma. To evaluate differences in staffing requirements and cost between Breathewell and UC needed to deliver guideline-based care we used electronic health record (EHR) events, provider time tracking surveys, and invoicing. Differences in cost were reported at the patient and health system level. The Breathewell intervention significantly reduced personnel requirements with a larger percentage of participants requiring no personnel time (45% vs. 5%, p < .001) and smaller percentage of participants requiring follow-up outreach (44% vs. 68%, p < .001). Extrapolated to the total health system, cost for the Breathewell intervention was $16,278 less than usual care. The intervention became cost savings at a sample size of at least 957 patients diagnosed with asthma. At the population level, using DCT to compliment current asthma care practice presents an opportunity to reduce healthcare personnel requirements while maintaining population-based asthma control measures.

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.

The Childhood Vaccination Schedule and the Lack of Association With Type 1 Diabetes.

OBJECTIVES: Safety studies assessing the association between the entire recommended childhood immunization schedule and autoimmune diseases, such as type 1 diabetes mellitus (T1DM), are lacking. To examine the association between the recommended immunization schedule and T1DM, we conducted a retrospective cohort study of children born between 2004 and 2014 in 8 US health care organizations that participate in the Vaccine Safety Datalink. METHODS: Three measures of the immunization schedule were assessed: average days undervaccinated (ADU), cumulative antigen exposure, and cumulative aluminum exposure. T1DM incidence was identified by International Classification of Disease codes. Cox proportional hazards models were used to analyze associations between the 3 exposure measures and T1DM incidence. Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) were calculated. Models were adjusted for sex, race and ethnicity, birth year, mother's age, birth weight, gestational age, number of well-child visits, and study site. RESULTS: In a cohort of 584 171 children, the mean ADU was 38 days, the mean cumulative antigen exposure was 263 antigens (SD = 54), and the mean cumulative aluminum exposure was 4.11 mg (SD = 0.73). There were 1132 incident cases of T1DM. ADU (aHR = 1.01; 95% CI, 0.99-1.02) and cumulative antigen exposure (aHR = 0.98; 95% CI, 0.97-1.00) were not associated with T1DM. Cumulative aluminum exposure >3.00 mg was inversely associated with T1DM (aHR = 0.77; 95% CI, 0.60-0.99). CONCLUSIONS: The recommended schedule is not positively associated with the incidence of T1DM in children. These results support the safety of the recommended childhood immunization schedule.