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Introduction/Aim: Treatable traits based personalised medicine has been shown to improve outcomes in severe asthma clinic. We assessed the feasibility of a randomised controlled trial of protocolised 'focused' and 'extended' treatable trait guided asthma management in patients not under a severe asthma clinic. Method(s): Ten week single-group cohort study. Participants had a doctor's diagnosis of asthma, asthma control questionnaire (ACQ) score >1, and a history of exacerbation in the last year. Patients already under the care of a severe asthma clinic or receiving high-dose inhaled corticosteroids, biological therapy or maintenance oral corticosteroids were excluded. Intervention(s): asthma medication according to application of a 'focused' treatable trait algorithm, targeting type-2 inflammation and airflow obstruction. Feasibility outcomes: recruitment rates, acceptability of intervention, willingness to enrol in a full RCT, need for 'extended' trait assessment after 10 weeks, and estimation of trait prevalence. Result(s): Recruitment ceased after 14 months with 30/50 participants due to difficulties associated with COVID-19. 92% found the intervention acceptable and were willing to be randomised in a future study. 65% remained not well-controlled with an ACQ >1 after 10 weeks and would have required the 'extended' algorithm. Participants had a mean (SD) 4.8(2.3) of 13 traits assessed. Participation in the study was associated with clinically important improvements in ACQ, -1.0 (1.5) units;St George Respiratory Questionnaire, -15.1 (14.7) units;Asthma Quality of Life Questionnaire, +1.0 (1.1) units;and FEV1, +0.4 (0.4) L. Post-bronchodilator airflow obstruction reduced from 60% of participants at study commencement to 35%. 53% of participants were allocated continuous oral corticosteroids at some point during the study. Conclusion(s): Protocolised treatable trait management was acceptable, associated with significant clinical benefit and a full trial appears feasible. Targeting two traits was insufficient to control asthma in the majority of patients over the timeframe of this study, despite significant corticosteroid exposure.
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Background: RA has been associated with poor COVID-19 outcomes, but few studies have investigated outcomes in RA features such as interstitial lung disease. Objectives: To assess COVID-19 outcomes in patients with RA overall, and those with and without ILD, compared to general population comparators. Methods: A multicenter, retrospective cohort study was conducted at Mayo Clinic (19 hospitals and affiliated outpatient centers in 4 states) and Mass General Brigham (14 hospitals and affiliated outpatient centers in New England). Consecutive patients with RA meeting ACR/EULAR criteria and a positive COVID-19 test from March 1, 2020 through June 6, 2021 were matched 1:5 on age, sex, race, and COVID-19 test date with general population comparators without RA. RA features assessed included: RA-ILD per Bongartz criteria [1], duration, rheumatoid factor (RF), cyclic citrullinated peptide antibody (CCP), bone erosions, and treatments. The primary outcome was a composite of hospitalization or death following COVID-19 diagnosis. We used multivariable Cox regression to investigate the association of RA, and features such as ILD, with COVID-19 outcomes compared to matched comparators. Results: We analyzed 582 patients with RA and 2892 comparators without RA, all with COVID-19. Mean age was 62 years, 51% were female, and 79% were White. Mean RA duration was 11 years, 67% were seropositive (52% RF+ and 54% CCP+), 27% had bone erosions, 28% were on steroids, and 79% were on DMARDs. 50/582 (9%) patients with RA had ILD. The COVID-19 hospitalization or death rate for RA patients was higher than comparators (3.0 per 1,000 days [95% CI 2.5-3.6] vs. 1.9 per 1,000 days [95% CI 1.7-2.1], respectively). Overall, RA patients had a 53% higher risk of hospitalization or death than comparators after adjustment (95% CI 1.20-1.94). Among those with RA-ILD, the hospitalization or death rate was signifcantly higher than comparators (10.9 [95% CI 6.7-15.2] vs. 2.5 per 1,000 days [1.8-3.2], respectively). RA-ILD was associated with nearly 3-fold higher risk for hospitalization or death than comparators (multivariable HR 2.84 [95% CI 1.64-4.91], Table 1). There was a signifcant interaction between RA/comparator status and presence/absence of ILD for risk of severe COVID-19 (p<0.001, Figure 1). The elevated risk for severe COVID-19 was similar for RA subgroups defned by serostatus or bone erosions. Conclusion: We confrmed that RA was associated with severe COVID-19 outcomes compared to the general population. We found evidence that ILD may be an effect modifer for the relationship between RA and severe COVID-19 outcomes, but RA subgroups defned by serostatus and bone erosions had similarly elevated risk. These fndings suggest that ILD or its treatment may be a major contributor to severe COVID-19 outcomes in RA.
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Background: Systemic autoimmune rheumatic disease (SARD) patients may be at risk for disease fare and prolonged symptom duration after COVID-19, perhaps related to DMARD disruption and immune activation. Objectives: To describe DMARD disruption and identify differences in SARD activity among patients with and without prolonged COVID-19 symptom duration. Methods: We identifed all SARD patients with confrmed COVID-19 at the Mass General Brigham healthcare system in Boston, USA;prospective recruitment is ongoing. Surveys were used to collect demographics, clinical characteristics, DMARD disruption, COVID-19 course, and SARD disease activity before and after COVID-19. The survey included validated instruments measuring disease activity, pain, fatigue, functional status, and respiratory quality of life. Prolonged symptom duration was defned as COVID-19 symptoms lasting ≥28 days. We compared differences in patient-reported measures between those with and without prolonged symptoms. Results: We analyzed survey responses from 174 COVID-19 survivors with SARDs (mean age 52±16 years, 81% female, 80% White). The most common SARDs were RA (40%) and SLE (14%). Fifty-one percent of the 127 respondents on any DMARD reported a disruption to their regimen at COVID-19 onset (Figure 1). Among individual DMARDs, 56-77% were reported to have any change, except for hydroxychloroquine (23%) and rituximab (46%). SARD fare after COVID-19 was reported by 41% of respondents (Table 1). Patient global assessment of SARD activity was worse after COVID-19 (mean 7.6±2.3 before vs. 6.6±2.9 after COVID-19, p<0.001). Prolonged symptom duration was reported by 45% of participants. Those with prolonged symptoms had a higher initial COVID-19 symptom count (median 7 vs. 4, p<0.001) and were more likely to be hospitalized for COVID-19 (28% vs. 17%, p=0.001). Respondents experiencing prolonged symptom duration had higher disease activity on RAPID3 (p=0.007) as well as more pain (p<0.001) and fatigue (p=0.03) compared to those without prolonged symptoms. Conclusion: DMARD disruption, SARD fare, and prolonged symptoms were common in this prospective study of COVID-19 survivors with SARDs. Those with prolonged COVID-19 symptom duration, defned as ≥28 days, had higher SARD activity, more pain, and more fatigue compared to those without prolonged symptoms. These fndings suggest that post-acute sequelae of COVID-19 may have a large impact on underlying SARD activity and quality of life.
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Background: The negative impacts of COVID-19 are higher in Blacks compared to Whites in the United States (US). Systemic inequities and differences in health behaviors may contribute to COVID-19 disparities. The aim of this study was to examine the impact of COVID-19 stay-at- home orders on health behaviors and anxiety in Blacks and Whites with overweight or obesity (OW/OB). Methods: In April 2020, the COVID-19 Health Behaviors Survey collected demographic information and changes to employment, income, diet (Rapid Eating Assessment for Participants), physical activity (PA;MET-minutes/ week), sleep patterns, and anxiety (General Anxiety Disorder-7) through an online survey. Of the 7753 respondents globally, adults residing in the US and BMI ≥25 kg/m2 were analyzed. Data presented as proportion (%) or Mean ± SD. Analyses were adjusted for baseline characteristics. Significance was set at p < 0.05. Results: Overall, 4008 respondents identified as Black (6.4%) or White (93.6%). Blacks reported being younger (-3.5 years), weighing more (+5.2 kg), single (18.4% greater proportion), and a lower annual income (2.9% lower proportion earning ≥US$50,000/year) compared to Whites (p < 0.004 for all). A greater proportion of Blacks reported being laid off (+13.5%), working fewer hours (+6.7%), and working from home (+4.6%) during COVID-19 stay-at- home orders (p < 0.0001 for all). In the overall sample, eating behaviors improved (+0.1 ± 0.3), PA decreased (-72.0 ± 1417.4 MET-minutes/ week), sleep time extended (+0.3 ± 2.5 hours), and anxiety heightened (+8.9 ± 13.2) during COVID-19 stay-at- home orders (p < 0.01 for all). These findings were universal between Blacks and Whites (p≥0.05 for all). Conclusions: This study highlights the disproportionate employment and income changes in Blacks compared to Whites with OW/OB, with no differential impact on health behaviors and anxiety. As the COVID-19 pandemic persists, disproportionate changes to employment and income may widen among Blacks and Whites, which may influence health behaviors and anxiety.
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Background: An increased risk of severe COVID-19 outcomes may be seen in patients with autoimmune diseases on moderate to high daily doses of glucocorticoids, as well as in those with comorbidities. However, specific information about COVID-19 outcomes in SLE is scarce. Objectives: To determine the characteristics associated with severe COVID-19 outcomes in a multi-national cross-sectional registry of COVID-19 patients with SLE. Methods: SLE adult patients from a physician-reported registry of the COVID-19 GRA were studied. Variables collected at COVID-19 diagnosis included age, sex, race/ethnicity, region, comorbidities, disease activity, time period of COVID-19 diagnosis, glucocorticoid (GC) dose, and immunomodulatory therapy. Immunomodulatory therapy was categorized as: antimalarials only, no SLE therapy, traditional immunosuppressive (IS) drug monotherapy, biologics/targeted synthetic IS drug monotherapy, and biologic and traditional IS drug combination therapy. We used an ordinal COVID-19 severity outcome defined as: not hospitalized/hospitalized without supplementary oxygen;hospitalized with non-invasive ventilation;hospitalized with mechanical ventilation/extracorporeal membrane oxygenation;and death. An ordinal logistic regression model was constructed to assess the association between demographic characteristics, comorbidities, medications, disease activity and COVID-19 severity. This assumed that the relationship between each pair of outcome groups is of the same direction and magnitude. Results: Of 1069 SLE patients included, 1047 (89.6%) were female, with a mean age of 44.5 (SD: 14.1) years. Patient outcomes included 815 (78.8%) not hospitalized/hospitalized without supplementary oxygen;116 (11.2) hospitalized with non-invasive ventilation, 25 (2.4%) hospitalized with mechanical ventilation/ extracorporeal membrane oxygenation and 78 (7.5%) died. In a multivariate model (n=804), increased age [OR=1.03 (1.01, 1.04)], male sex [OR =1.93 (1.21, 3.08)], COVID-19 diagnosis between June 2020 and January 2021 (OR =1.87 (1.17, 3.00)), no IS drug use [OR =2.29 (1.34, 3.91)], chronic renal disease [OR =2.34 (1.48, 3.70)], cardiovascular disease [OR =1.93 (1.34, 3.91)] and moderate/ high disease activity [OR =2.24 (1.46, 3.43)] were associated with more severe COVID-19 outcomes. Compared with no use of GC, patients using GC had a higher odds of poor outcome: 0-5 mg/d, OR =1.98 (1.33, 2.96);5-10 mg/d, OR =2.88 (1.27, 6.56);>10 mg/d, OR =2.01 (1.26, 3.21) (Table 1). Conclusion: Increased age, male sex, glucocorticoid use, chronic renal disease, cardiovascular disease and moderate/high disease activity at time of COVID-19 diagnosis were associated with more severe COVID-19 outcomes in SLE. Potential limitations include possible selection bias (physician reporting), the cross-sectional nature of the data, and the assumptions underlying the outcomes modelling.
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Background: The COVID-19 pandemic has disrupted healthcare delivery and education of physicians, including rheumatology trainees. Objectives: To assess the impact of the COVID-19 pandemic on the clinical experiences, research opportunities, and well-being of rheumatology trainees. Methods: A voluntary, anonymous, web-based survey was administered in English, Spanish, or French from 19/08/2020 to 05/10/2020. Adult and paediatric rheumatology trainees worldwide in training in 2020 were invited to participate via social media and email. Using multiple choice questions, Likert scales, and free text answers, we assessed trainee patient care activities, redeployment, research, and well-being. Results: The 302 respondents were from 33 countries, with most (83%, 252/302) in adult rheumatology training. Many trainees (45%, 135/300) reported an increase in non-rheumatology clinical work (e.g. care of COVID-19 patients), with 52% of these (70/135) also continuing rheumatology clinical work. COVID-19 redeployment was not optional for 68% (91/134). Trainees reported a negative impact of the pandemic in their growth in rheumatology (Figure 1). They also reported a substantial impact on several training areas: outpatient clinics (79%, 238/302), inpatient consultations (59%, 177/302), formal teaching (55%, 167/302), procedures (53%, 147/302), teaching opportunities (52%, 157/302), and ultrasonography (36%, 110/302), with 87-96% perceiving a negative impact on these areas. Only 54% (159/294) reported feeling comfortable with their level of clinical supervision during the pandemic (Figure 1). Many trainees (46%, 128/280) reported changes in research experiences during the pandemic;39% (110/285) reported that COVID-19 negatively affected their ability to continue their pre-pandemic research and 50% (142/285) reported difficulty maintaining research goals (Figure 1). Some rheumatology trainees reported having health condition(s) putting them at high risk for COVID-19 (10%, 30/302) and 14% of trainees (41/302) reported having had COVID-19 (Table 1). Only 53% (160/302) reported feeling physically safe in the workplace while 25% (76/302) reported not feeling physically safe;reasons included lack of training about COVID-19, lack of comfort in the clinical setting, insufficient personal protective equipment, immunocompromised state, and pregnancy. Half (151/302) reported burnout and 68% (204/302) an increase in stress from work during the pandemic (Figure 1), whilst 25% (75/302) reported that changes to their training programme negatively impacted their physical health. Conclusion: The COVID-19 pandemic has negatively impacted the experience of rheumatology training as well as the well-being of trainees globally. Our data highlight concerns for rheumatology trainees including research opportunities and clinical care which should be a focus for curriculum planning.
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Background: The COVID-19 pandemic led to a rapid increase in remote consultations in rheumatology care. Due to the potential impact of this change on rheumatology clinical training, we investigated trainees' experiences with telemedicine. Objectives: To assess the impact of telemedicine use during the COVID-19 pandemic on rheumatology training, including supervision. Methods: A voluntary, anonymous web-based survey was administered in English, Spanish, or French from 19/08/2020 to 05/10/2020. Adult and paediatric rheumatology trainees worldwide in training in 2020 were invited to participate via social media and email. Using multiple choice questions, Likert scales, and free text answers, we collected data regarding prior and current telemedicine use, training, and supervision. Results: 302 respondents from 33 countries completed the survey, with most (83%, 252/302) in adult rheumatology training. Reported use of telemedicine increased from 13% (39/302) pre-pandemic to 82% (247/302) (Table 1). European trainees predominantly utilised audio-only compared to trainees from the rest of the world (ROW) who predominantly utilised audio-video telemedicine. Most trainees continued to evaluate new patients using telemedicine (65%, 161/247). A larger proportion of trainees were comfortable using telemedicine to evaluate follow-up (69% 170/247) versus new patients (25%, 41/161) (Figure 1). Only 32% (97/302) were trained in telemedicine, with the highest proportion among United States (US) trainees (59%, 69/116);subjects included software, clinical skills, and billing. The majority of trainees found this helpful (92%, 89/97). Supervision was most frequently in the form of verbal discussion after the consultation (Table 1);24% (59/247) had no telemedicine supervision during the pandemic. In general, trainees found telemedicine negatively impacted their supervision (51%, 123/242) and clinical teaching quality (70%, 171/244);only 9% reported a positive impact on these areas. Conclusion: Adoption of telemedicine during the COVID-19 pandemic has led to areas of concern for rheumatology trainees including inadequate supervision and clinical teaching. Our results suggest a need for education on evaluation of new patients using telemedicine, increasing telemedicine training, and ensuring adequate supervisory arrangements.
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Background: Targeted DMARDs may dampen the inflammatory response in COVID-19, perhaps leading to a less severe clinical course. However, some DMARD targets may impair viral immune defenses. Due to sample size limitations, previous studies of DMARD use and COVID-19 outcomes have combined several heterogeneous rheumatic diseases and medications, investigating a single outcome (e.g., hospitalization). Objectives: To investigate the associations of baseline use of biologic or targeted synthetic (b/ts) DMARDs with a range of poor COVID-19 outcomes in rheumatoid arthritis (RA). Methods: We analyzed voluntarily reported cases of COVID-19 in patients with rheumatic diseases in the COVID-19 Global Rheumatology Alliance physician registry (March 12, 2020 -January 6, 2021). We investigated RA treated with b/ tsDMARD at the clinical onset of COVID-19 (baseline): abatacept (ABA), rituximab (RTX), Janus kinase inhibitors (JAK), interleukin-6 inhibitors (IL6i), or tumor necrosis factor inhibitors (TNFi). The outcome was an ordinal scale (1-4) for COVID-19 severity: 1) no hospitalization, 2) hospitalization without oxygen need, 3) hospitalization with any oxygen need or ventilation, or 4) death. Baseline covariates including age, sex, smoking, obesity, comorbidities (e.g., cardiovascular disease, cancer, interstitial lung disease [ILD]), concomitant non-biologic DMARD use, glucocorticoid use/ dose, RA disease activity, country, and calendar time were used to estimate propensity scores (PS) for b/tsDMARD. The primary analysis used PS matching to compare each drug class to TNFi. Ordinal logistic regression estimated ORs for the COVID-19 severity outcome. In a sensitivity analysis, we used traditional multivariable ordinal logistic regression adjusting for covariates without matching. Results: Of the 1,673 patients with RA on b/tsDMARDs at the onset of COVID-19, (mean age 56.7 years, 79.6% female) there were n=154 on ABA, n=224 on RTX, n=306 on JAK, n=180 on IL6i, and n=809 on TNFi. Overall, 498 (34.3%) were hospitalized and 112 (6.7%) died. Among all patients, 353 (25.3%) were ever smokers, 197 (11.8%) were obese, 462 (27.6%) were on glucocorticoids, 1,002 (59.8%) were on concomitant DMARDs, and 299 (21.7%) had moderate/ high RA disease activity. RTX users were more likely than TNFi users to have ILD (11.6% vs. 1.7%) and history of cancer (7.1% vs. 2.0%);JAK users were more likely than TNFi users to be obese (17.3% vs. 9.0%). After propensity score matching, RTX was strongly associated with greater odds of having a worse outcome compared to TNFi (OR 3.80, 95% CI 2.47, 5.85;Figure). Among RTX users, 42 (18.8%) died compared to 27 (3.3%) of TNFi users (Table). JAK use was also associated with greater odds of having a worse COVID-19 severity (OR 1.52, 95%CI 1.02, 2.28). ABA or IL6i use were not associated with COVID-19 severity compared to TNFi. Results were similar in the sensitivity analysis and after excluding cancer or ILD. Conclusion: In this large global registry of patients with RA and COVID-19, baseline use of RTX or JAK was associated with worse severity of COVID-19 compared to TNFi use. The very elevated odds for poor COVID-19 outcomes in RTX users highlights the urgent need for risk-mitigation strategies, such as the optimal timing of vaccination. The novel association of JAK with poor COVID-19 outcomes requires replication.
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Background: COVID-19 can induce a hyperinflammatory state resulting in cytokine storm, which can lead to poor outcomes. Patients with systemic rheumatic diseases may be at increased risk for respiratory failure with COVID-19. Therefore, we investigated the relationship between rheumatic disease, hyperinflammation, and clinical outcomes among hospitalized COVID-19 patients. Objectives: To compare laboratory values, hyperinflammation, and clinical outcomes of hospitalized COVID-19 rheumatic patients and matched comparators. Methods: We performed a comparative cohort study of patients with polymerase chain reaction (PCR)-confirmed COVID-19 requiring hospitalization between 3/1/20-7/7/20 at a large health care system. We compared each systemic rheumatic disease case to up to 5 matched (by age, sex, and date of +SARS-CoV-2 PCR) comparators without systemic rheumatic disease. We extracted laboratory values from their hospitalization to compare peaks/troughs of individual laboratory results by case status and derived the COVID-19-associated hyperinflammation score (cHIS), a composite of 6 laboratory domains (0-6, ≥2 indicating hyperinflammation), as previously developed1. We used multivariable logistic regression to estimate ORs for COVID-19 outcomes by hyperinflammation and case status. Results: We identified 57 hospitalized rheumatic disease cases (mean age 67 years, 67% female) and 232 matched comparators hospitalized with PCR-confirmed COVID-19. Among cases, 26 (46%) had rheumatoid arthritis and 14 (25%) had systemic lupus erythematosus. Most cases (34, 60%) had active rheumatic disease. At baseline, 15 (27%) of cases were treated with biologic DMARDs, and 32 (56%) were using glucocorticoids. We analyzed 39,900 total laboratory results (median 85 per patient). Cases had higher peak neutrophil-to-lymphocyte ratio (9.6 vs 7.8, p=0.02), LDH (421 vs 345 U/L, p=0.04), creatinine (1.2 vs 1.0 mg/dL, p=0.01), and BUN (31 vs 23 mg/dL, p=0.03) than comparators but similar peak CRP (149 vs 116 mg/L, p=0.11, Figure 1). Cases had higher peak median cHIS (3 vs 2, p=0.01). Peak cHIS ≥2 had higher odds of intensive care unit (ICU) admission (OR 3.45, 95%CI 1.98-5.99), mechanical ventilation (OR 66.0, 95%CI 9.0-487.8), and mortality (OR 16.4, 95%CI 4.8-56.4) compared to cHIS <2 (Table 1). Cases had increased risk of ICU admission (OR 2.0, 95%CI 1.1-3.7) and mechanical ventilation (OR 2.7, 95%CI 1.4-5.2) than comparators Conclusion: Patients with systemic rheumatic disease hospitalized for COVID-19 had higher risk for hyperinflammation, kidney injury, and mechanical ventilation than non-rheumatic comparators. We validated the cHIS in our cohort, which was strongly associated with poor COVID-19 outcomes. These findings highlight that hospitalized patients with rheumatic diseases may be vulnerable to poor COVID-19 outcomes.
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Background: Acute Respiratory Distress Syndrome (ARDS) is a life-threatening complication of COVID-19 and has been reported in approximately one-third of hospitalized patients with COVID-191. Risk factors associated with the development of ARDS include older age and diabetes2. However, little is known about factors associated with ARDS in the setting of COVID-19, in patients with rheumatic disease or those receiving immunosuppressive medications. Prediction algorithms using traditional regression methods perform poorly with rare outcomes, often yielding high specificity but very low sensitivity. Machine learning algorithms optimized for rare events are an alternative approach with potentially improved sensitivity for rare events, such as ARDS in COVID-19 among patients with rheumatic disease. Objectives: We aimed to develop a prediction model for ARDS in people with COVID-19 and pre-existing rheumatic disease using a series of machine learning algorithms and to identify risk factors associated with ARDS in this population. Methods: We used data from the COVID-19 Global Rheumatology Alliance (GRA) Registry from March 24 to Nov 1, 2020. ARDS diagnosis was indicated by the reporting clinician. Five machine learning algorithms optimized for rare events predicted ARDS using 42 variables covering patient demographics, rheumatic disease diagnoses, medications used at the time of COVID-19 diagnosis, and comorbidities. Model performance was assessed using accuracy, area under curve, sensitivity, specificity, positive predictive value, and negative predictive value. Adjusted odds ratios corresponding to the 10 most influential predictors from the best performing model were derived using hierarchical multivariate mixed-effects logistic regression that accounted for within-country correlations. Results: A total of 5,931 COVID-19 cases from 67 countries were included in the analysis. Mean (SD) age was 54.9 (16.0) years, 4,152 (70.0%) were female, and 2,399 (40.5%) were hospitalized. ARDS was reported in 388 (6.5% of total and 15.6% of hospitalized) cases. Statistically significant differences in the risk of ARDS were observed by demographics, diagnoses, medications, and comorbidities using unadjusted univariate comparisons (data not shown). Gradient boosting machine (GBM) had the highest sensitivity (0.81) and was considered the best performing model (Table 1). Hypertension, interstitial lung disease, kidney disease, diabetes, older age, glucocorticoids, and anti-CD20 monoclonal antibodies were associated with the development of ARDS while tumor necrosis factor inhibitors were associated with a protective effect (Figure 1). Conclusion: In this global cohort of patients with rheumatic disease, a machine learning model, GBM, predicted the onset of ARDS with 81% sensitivity using baseline information obtained at the time of COVID-19 diagnosis. These results identify patients who may be at higher risk of severe COVID-19 outcomes. Further studies are necessary to validate the proposed prediction model in external cohorts and to evaluate its clinical utility. Disclaimer: The views expressed here are those of the authors and participating members of the COVID-19 Global Rheumatology Alliance, and do not necessarily represent the views of the ACR, NIH, (UK) NHS, NIHR, or the department of Health.
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Many Americans fail to get life-saving vaccines each year, and the availability of a vaccine for COVID-19 makes the challenge of encouraging vaccination more urgent than ever. We present a large field experiment (N = 47,306) testing 19 nudges delivered to patients via text message and designed to boost adoption of the influenza vaccine. Our findings suggest that text messages sent prior to a primary care visit can boost vaccination rates by an average of 5%. Overall, interventions performed better when they were 1) framed as reminders to get flu shots that were already reserved for the patient and 2) congruent with the sort of communications patients expected to receive from their healthcare provider (i.e., not surprising, casual, or interactive). The best-performing intervention in our study reminded patients twice to get their flu shot at their upcoming doctor's appointment and indicated it was reserved for them. This successful script could be used as a template for campaigns to encourage the adoption of life-saving vaccines, including against COVID-19.