Incidence of Guillain-Barré Syndrome After COVID-19 Vaccination in the Vaccine Safety Datalink.

Importance: Postauthorization monitoring of vaccines in a large population may detect rare adverse events not identified in clinical trials such as Guillain-Barré syndrome (GBS), which has a background rate of 1 to 2 per 100 000 person-years. Objective: To describe cases and incidence of GBS following COVID-19 vaccination and assess the risk of GBS after vaccination for Ad.26.COV2.S (Janssen) and mRNA vaccines. Design, Setting, and Participants: This cohort study used surveillance data from the Vaccine Safety Datalink at 8 participating integrated health care systems in the United States. There were 10 158 003 participants aged at least 12 years. Data analysis was performed from November 2021 to February 2022. Exposures: Ad.26.COV2.S, BNT162b2 (Pfizer-BioNTech), or mRNA-1273 (Moderna) COVID-19 vaccine, including mRNA vaccine doses 1 and 2, December 13, 2020, to November 13, 2021. Main Outcomes and Measures: GBS with symptom onset in the 1 to 84 days after vaccination, confirmed by medical record review and adjudication. Descriptive characteristics of confirmed cases, GBS incidence rates during postvaccination risk intervals after each type of vaccine compared with the background rate, rate ratios (RRs) comparing GBS incidence in the 1 to 21 vs 22 to 42 days postvaccination, and RRs directly comparing risk of GBS after Ad.26.COV2.S vs mRNA vaccination, using Poisson regression adjusted for age, sex, race and ethnicity, site, and calendar day. Results: From December 13, 2020, through November 13, 2021, 15 120 073 doses of COVID-19 vaccines were administered to 7 894 989 individuals (mean [SE] age, 46.5 [0.02] years; 8 138 318 doses received [53.8%] by female individuals; 3 671 199 doses received [24.3%] by Hispanic or Latino individuals, 2 215 064 doses received [14.7%] by Asian individuals, 6 266 424 doses received [41.4%] by White individuals), including 483 053 Ad.26.COV2.S doses, 8 806 595 BNT162b2 doses, and 5 830 425 mRNA-1273 doses. Eleven cases of GBS after Ad.26.COV2.S were confirmed. The unadjusted incidence rate of GBS per 100 000 person-years in the 1 to 21 days after Ad.26.COV2.S was 32.4 (95% CI, 14.8-61.5), significantly higher than the background rate, and the adjusted RR in the 1 to 21 vs 22 to 42 days following Ad.26.COV2.S was 6.03 (95% CI, 0.79-147.79). Thirty-six cases of GBS after mRNA vaccines were confirmed. The unadjusted incidence rate per 100 000 person-years in the 1 to 21 days after mRNA vaccines was 1.3 (95% CI, 0.7-2.4) and the adjusted RR in the 1 to 21 vs 22 to 42 days following mRNA vaccines was 0.56 (95% CI, 0.21-1.48). In a head-to-head comparison of Ad.26.COV2.S vs mRNA vaccines, the adjusted RR was 20.56 (95% CI, 6.94-64.66). Conclusions and Relevance: In this cohort study of COVID-19 vaccines, the incidence of GBS was elevated after receiving the Ad.26.COV2.S vaccine. Surveillance is ongoing.

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.

Adults With Asthma Experience No Increase in Asthma-related Exacerbations When Digital Communication Technology Tools Are Employed to Offset Provider Workload: A Pragmatic Randomized Trial.

BACKGROUND: Challenges to health care efficiency are increasingly addressed with the help of digital communication technology tools (DCTs). OBJECTIVE: The objective of this study was to test whether DCT, compared with Usual Care, can reduce health care clinician burden without increasing asthma-related exacerbations among patients with asthma in a large integrated health care system. RESEARCH DESIGN: The (Breathewell) program was a pragmatic, randomized trial at (Kaiser Permanente Colorado), where asthma nurses screen patients for poor symptom control when beta2-agonist refill requests came within 60 days of previous fill or in the absence of a controller medication fill within 4 months (beta2-agonist overfill). A total of 14,978 adults with asthma were randomized to Usual Care or 1 of 2 DCT intervention groups (Text/Phone call or Email). SUBJECTS: Participants included adults 18 and older with an asthma diagnosis at the time of randomization and no history of chronic obstructive pulmonary disease. MEASURES: Primary outcome measures included asthma-related health care resource utilization (eg, asthma nurse contacts), medication use, and exacerbations. RESULTS: A total of 1933 patients had 4337 events which met beta2-agonist overfill criteria. Of the 2874 events in the intervention arm, 1188 (41%) were resolved by DCT contact and did not require additional clinician contact. Asthma medication use and exacerbations over 12 months did not differ among the 3 groups. CONCLUSIONS: DCT tools can successfully contact adult asthma patients to screen for symptoms and facilitate intervention. The absence of differences in medication fills and health care utilization indicates that the strategic replacement of nursing interventions by digital outreach did not reduce treatment adherence or compromise health care outcomes.

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.

Reducing Missed Primary Care Appointments in a Learning Health System: Two Randomized Trials and Validation of a Predictive Model.

BACKGROUND: Collaborations between clinical/operational leaders and researchers are advocated to develop "learning health systems," but few practical examples are reported. OBJECTIVES: To describe collaborative efforts to reduce missed appointments through an interactive voice response and text message (IVR-T) intervention, and to develop and validate a prediction model to identify individuals at high risk of missing appointments. RESEARCH SUBJECTS AND DESIGN: Random assignment of 8804 adults with primary care appointments to a single IVR-T reminder or no reminder at an index clinic (IC) and 7497 at a replication clinic (RC) in an integrated health system in Denver, CO. MEASURES: Proportion of missed appointments; demographic, clinical, and appointment-specific predictors of missed appointments. RESULTS: Patients receiving IVR-T had a lower rate of missed appointments than those receiving no reminder at the IC (6.5% vs. 7.5%, relative risk=0.85, 95% confidence interval, 0.72-1.00) and RC (8.2% vs. 10.5%, relative risk=0.76, 95% confidence interval, 0.65-0.89). A 10-variable prediction model for missed appointments demonstrated excellent discrimination (C-statistic 0.90 at IC, 0.89 at RC) and calibration (P=0.99 for Osius and McCullagh tests). Patients in the 3 lowest-risk quartiles missed 0.4% and 0.4% of appointments at the IC and RC, respectively, whereas patients in the highest-risk quartile missed 24.1% and 28.9% of appointments, respectively. CONCLUSIONS: A single IVR-T call reduced missed appointments, whereas a locally validated prediction model accurately identified patients at high risk of missing appointments. These rigorous studies promoted dissemination of the intervention and prompted additional research questions from operational leaders.