Abstract
Background
Increasing vaccine coverage remains the best way to control the COVID-19 pandemic. Healthcare personnel (HCP) have long been the most credible and frequently used source of vaccine information for the public, and an HCP recommendation is a strong predictor of vaccination.
Methods
A survey of HCP was conducted in September 2021 via a double opt-in network panel. Responses to survey items were summarized and stratified by HCP type and adjusted logistic regression models were fitted.
Results
>94% of the 1074 HCP surveyed reported receiving at least one dose of COVID-19 vaccine or intending to soon, with vaccinating most common among pediatricians (98%), followed by family medicine doctors (96%), pharmacists (94%), and nurses/nurse practitioners/physician assistants (88%). HCP with high trust in the Centers for Disease Control and Prevention had 26 times the odds of vaccinating of HCP with low trust (95%CI: 9, 74). Nearly half of unvaccinated HCP (47%) were concerned about side effects, and one third of unvaccinated HCP (33%) were concerned the vaccine was developed too quickly. About three quarters of HCP reported strongly recommending the Pfizer-BioNTech (75%) and Moderna (70%) vaccines to their patients, compared to about one quarter (24%) strongly recommending Johnson & Johnson.
Conclusions
Although most HCP are vaccinated against COVID-19 and strongly recommend vaccination to their patients, some harbor similar concerns to the public. Additional resources – regularly updated to explain the progressing scientific landscape and address ever evolving public concerns – are needed to further improve vaccine coverage among HCP and aid them in supporting the decision-making of their patients.
Keywords: Health Personnel, COVID-19, COVID-19 vaccines, Patient Acceptance of Health Care
Abbreviations: CDC, Centers for Disease Control and Prevention; CI, Confidence Intervals; CME, Continuing Medical Education; COVID-19, Coronavirus Disease 2019; EUA, Emergency Use Authorization; FDA, Food and Drug Administration; HCP, Healthcare personnel; HHS, Health and Human Services; IARM, Immunization Adverse Reaction Monitoring; J&J, Johnson & Johnson; NP, Nurse Practitioner; OR, Odds Ratio; PA, Physician Assistants; PCP, Primary Care Provider; US, United States; VAERS, Vaccine Adverse Event Reporting System
1. Introduction
Four vaccines against Coronavirus Disease 2019 (COVID-19) have been authorized by the United States (US) Food and Drug Administration (FDA): the Pfizer-BioNTech vaccine BNT162b2 and the Moderna vaccine mRNA-1273 both received Emergency Use Authorization (EUA) in December 2020,[1], [2] the Johnson & Johnson (J&J) vaccine Ad26.COV2.S received EUA in February 2021,[3] and the Novavax vaccine NVX-CoV2373 received EUA in July 2022.[4] Rates of COVID-19 cases, hospitalizations, and deaths initially plummeted in the spring of 2021 as vaccines became widely available.[5] However, these rates have since resurged due to more contagious variants as well as waning immunity from both vaccination and natural infection.[6], [7] Although vaccine effectiveness is lower against variants such as Delta and Omicron compared to the original strain, vaccines remain effective against these variants, especially after booster shots and for severe outcomes like hospitalization and death.[5], [8], [9], [10], [11], [12].
Although 90 % of US adults have received at least one dose of COVID-19 vaccine as of August 2022, only about three quarters had a year prior in September 2021.[5], [13] More than half of those still unvaccinated in September remained uncertain about COVID-19 vaccination, indicating an opportunity to support their decision-making. Healthcare personnel (HCP) have long been the most credible and frequently used source of vaccine information,[14] and a recommendation to vaccinate from one's doctor is a strong predictor of uptake for COVID-19 [13], [15] and other vaccines.[16], [17].
Herein we describe a cross-sectional survey of HCP conducted in September 2021, after vaccines were widely available and in the midst of the Delta surge. We examine differences in COVID-19 vaccine acceptance by HCP type and trust in the Centers for Disease Control and Prevention (CDC), and summarize the reported reasons for not yet vaccinating among unvaccinated HCP. We also examine differences in recommendations to patients for COVID-19 and other vaccines by HCP type, and explore the impact of the pandemic on routine vaccination practices.
2. Methods
2.1. Recruitment
From September 2–9, 2021, we recruited pediatricians, family medicine doctors, physician assistants (PAs), nurse practitioners (NPs), nurses (including registered nurses and licensed practical nurses), and pharmacists who provided direct patient care, using SurveyHealthcareGlobus.[18] SurveyHealthcareGlobus is a double opt-in network panel that comes from a population of>2 million persons regularly updated and validated from standard core sources including the American Medical Association, hospital and medical directories, and verified healthcare webpages. Recruitment continued until at least 225 HCP of each of the four main categories (pediatricians, family medicine doctors, pharmacists, and PAs/NPs/nurses) were surveyed. Quotas ensured the sample was representative of each HCP type in terms of geographical region, race, and years of clinical practice. Respondents were provided a $10 honorarium. The study was approved by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board.
2.2. Survey content
The survey collected data on practice characteristics (e.g., type, size, location), patient population (e.g., age, race/ethnicity, insurance), COVID-19 vaccination (with at least one dose), vaccine intention (among unvaccinated), reasons for not yet vaccinating (among unvaccinated), strength of recommendations for COVID-19 and other vaccines, and impact of the pandemic on routine vaccination practices. Trust in CDC was measured as a 14-question construct scale.[19] The survey also assessed familiarity and history with vaccine adverse event reporting; respondents were randomized to questions about either the CDC's Vaccine Adverse Event Reporting System (VAERS) or the fictitious Immunization Adverse Reaction Monitoring (IARM) system to illuminate the potential effects of social desirability bias.
2.3. Data analyses
Data were analyzed using Stata (version 17).[20] PAs, NPs, and nurses were combined into one HCP type category to facilitate simpler comparison and improve statistical power (though a secondary analysis kept PAs/NPs separate from nurses to check that these groups were similar enough in COVID-19 vaccine acceptance to combine). Responses to survey items were summarized and stratified by HCP type, and differences were tested for statistical significance (p < 0.05) using Pearson's Chi-Squared Test.
For the trust in CDC construct scale, a composite, linear score was generated (Appendix 1). The numerator equaled the sum of responses to all answered items within the scale (each 4-point Likert scale response was scored 0–3). The denominator equaled the total possible score, accounting for missing variables, thus creating a scale from 0 to 100 (0 being complete disagreement and 100 being complete agreement). The Cronbach's alpha coefficient for this scale was estimated to be 0.91, indicating strong reliability.[21] The score was dichotomized at the median creating ‘‘high trust” and ‘‘low trust” groups.
We conducted multiple logistic regression to assess whether vaccinating (a binary dependent variable indicating HCP who received at least one dose of COVID-19 vaccine or were intending to soon) was associated with HCP type or trust in CDC, by including independent variables for trust (dichotomous) and HCP type (categorical). We used the logistic command to obtain odds ratios (ORs) and 95 % confidence intervals (CIs) of HCP vaccinating versus not. We followed a conservative approach given the small numbers in each strata by running 100 bootstrap replications, resulting in slightly wider CIs. The command linktest was used to assess model specification, and the command lfit was used to test goodness of fit (Hosmer-Lemshow).
3. Results
3.1. Study population
Characteristics of the HCP surveyed (N = 1074) and their practice and patient populations are presented in Table 1 . About one quarter (22–28 %) fell into each of the four main HCP type categories (pediatricians, family medicine doctors, pharmacists, and PAs/NPs/nurses). >70 % of HCP had regularly cared for patients with COVID-19, most frequently family medicine doctors (82 %), followed by PAs/NPs/nurses (76 %), pediatricians (70 %), and pharmacists (57 %) (p < 0.01).
Table 1.
Characteristics of Participating Healthcare Personnel, their Practices, and their Patient Populations.
| Total | PA, NP, Nursea | Pediatrician | Family Medicine | Pharmacist | p-valueb | |
|---|---|---|---|---|---|---|
| N = 1,074 | N = 260 | N = 277 | N = 234 | N = 303 | ||
| Practice characteristics | ||||||
| Practice location, urban/suburban/rural | <0.01 | |||||
| Urban | 412 (38.4 %) | 112 (43.1 %) | 97 (35.0 %) | 76 (32.5 %) | 127 (41.9 %) | |
| Suburban | 486 (45.3 %) | 111 (42.7 %) | 153 (55.2 %) | 104 (44.4 %) | 118 (38.9 %) | |
| Rural | 176 (16.4 %) | 37 (14.2 %) | 27 (9.7 %) | 54 (23.1 %) | 58 (19.1 %) | |
| U.S. region | <0.01 | |||||
| Northeast | 219 (20.4 %) | 60 (23.1 %) | 69 (24.9 %) | 44 (18.8 %) | 46 (15.2 %) | |
| Midwest | 294 (27.4 %) | 75 (28.8 %) | 68 (24.5 %) | 67 (28.6 %) | 84 (27.7 %) | |
| South | 395 (36.8 %) | 91 (35.0 %) | 90 (32.5 %) | 78 (33.3 %) | 136 (44.9 %) | |
| West | 166 (15.5 %) | 34 (13.1 %) | 50 (18.1 %) | 45 (19.2 %) | 37 (12.2 %) | |
| Practice setting | <0.01 | |||||
| Private, independent practice | 439 (40.9 %) | 121 (46.5 %) | 172 (62.1 %) | 146 (62.4 %) | 0 (0.0 %) | |
| Practice network/HMO | 79 (7.4 %) | 27 (10.4 %) | 24 (8.7 %) | 28 (12.0 %) | 0 (0.0 %) | |
| Hospital or medical center | 179 (16.7 %) | 92 (35.4 %) | 54 (19.5 %) | 33 (14.1 %) | 0 (0.0 %) | |
| Community health center / Federally Qualified Health Center (FQHC) |
45 (4.2 %) | 16 (6.2 %) | 17 (6.1 %) | 12 (5.1 %) | 0 (0.0 %) | |
| Other | 29 (2.7 %) | 4 (1.5 %) | 10 (3.6 %) | 15 (6.4 %) | 0 (0.0 %) | |
| Missing | 303 (28.2 %) | 0 (0.0 %) | 0 (0.0 %) | 0 (0.0 %) | 303 (100.0 %) | |
| Average number of patients per day | <0.01 | |||||
| <10 | 46 (4.3 %) | 14 (5.4 %) | 7 (2.5 %) | 7 (3.0 %) | 18 (5.9 %) | |
| 10–24 | 552 (51.4 %) | 162 (62.3 %) | 184 (66.4 %) | 150 (64.1 %) | 56 (18.5 %) | |
| >=25 | 476 (44.3 %) | 84 (32.3 %) | 86 (31.0 %) | 77 (32.9 %) | 229 (75.6 %) | |
| Service population | <0.01 | |||||
| Children (<18 yrs) | 187 (17.4 %) | 14 (5.4 %) | 171 (61.7 %) | 0 (0.0 %) | 2 (0.7 %) | |
| Adults (>=18 yrs) | 202 (18.8 %) | 114 (43.8 %) | 3 (1.1 %) | 31 (13.2 %) | 54 (17.8 %) | |
| Both children and adults | 685 (63.8 %) | 132 (50.8 %) | 103 (37.2 %) | 203 (86.8 %) | 247 (81.5 %) | |
| Practice was currently administering vaccines | 1,028 (95.7 %) | 245 (94.2 %) | 269 (97.1 %) | 225 (96.2 %) | 289 (95.4 %) | 0.41 |
| Offered seasonal influenza vaccination in… | ||||||
| 2019–2020 season | 558 (94.3 %) | 125 (91.2 %) | 136 (97.1 %) | 98 (96.1 %) | 199 (93.4 %) | 0.15 |
| 2020–2021 season | 548 (92.6 %) | 125 (91.2 %) | 136 (97.1 %) | 91 (89.2 %) | 196 (92.0 %) | 0.10 |
| Offered COVID-19 vaccines | 723 (67.3 %) | 172 (66.2 %) | 148 (53.4 %) | 120 (51.3 %) | 283 (93.4 %) | <0.01 |
| Offered Pfizer-BioNTech vaccine | 554 (76.6 %) | 130 (75.6 %) | 135 (91.2 %) | 85 (70.8 %) | 204 (72.1 %) | <0.01 |
| Offered Moderna vaccine | 467 (64.6 %) | 112 (65.1 %) | 52 (35.1 %) | 80 (66.7 %) | 223 (78.8 %) | <0.01 |
| Offered Johnson & Johnson vaccine | 198 (27.4 %) | 39 (22.7 %) | 17 (11.5 %) | 35 (29.2 %) | 107 (37.8 %) | <0.01 |
| Strategies used to improve COVID-19 vaccine series completion: | ||||||
| paper reminder cards | 422 (59.7 %) | 113 (67.7 %) | 66 (44.9 %) | 57 (49.1 %) | 186 (67.1 %) | <0.01 |
| reminder telephone calls | 379 (53.6 %) | 85 (50.9 %) | 77 (52.4 %) | 60 (51.7 %) | 157 (56.7 %) | 0.62 |
| flagging patient charts | 232 (32.8 %) | 67 (40.1 %) | 41 (27.9 %) | 48 (41.4 %) | 76 (27.4 %) | <0.01 |
| scheduling next dose at current visit | 587 (83.0 %) | 141 (84.4 %) | 123 (83.7 %) | 91 (78.4 %) | 232 (83.8 %) | 0.55 |
| using a computerized immunization database/registry | 358 (50.6 %) | 73 (43.7 %) | 68 (46.3 %) | 59 (50.9 %) | 158 (57.0 %) | 0.03 |
| Practice participated in the Vaccines for Children (VFC) program | <0.01 | |||||
| Yes | 523 (50.9 %) | 96 (39.2 %) | 225 (83.6 %) | 112 (49.8 %) | 90 (31.1 %) | |
| Never has | 308 (30.0 %) | 90 (36.7 %) | 21 (7.8 %) | 71 (31.6 %) | 126 (43.6 %) | |
| Not currently, but did previously | 69 (6.7 %) | 16 (6.5 %) | 14 (5.2 %) | 28 (12.4 %) | 11 (3.8 %) | |
| Unsure | 128 (12.5 %) | 43 (17.6 %) | 9 (3.3 %) | 14 (6.2 %) | 62 (21.5 %) | |
| Patient characteristics | ||||||
| Percent insured, private insurance | <0.01 | |||||
| <25 % | 141 (13.1 %) | 33 (12.7 %) | 33 (11.9 %) | 23 (9.8 %) | 52 (17.2 %) | |
| 25–50 % | 400 (37.2 %) | 94 (36.2 %) | 73 (26.4 %) | 92 (39.3 %) | 141 (46.5 %) | |
| 51–75 % | 310 (28.9 %) | 87 (33.5 %) | 85 (30.7 %) | 75 (32.1 %) | 63 (20.8 %) | |
| >75 % | 203 (18.9 %) | 39 (15.0 %) | 86 (31.0 %) | 42 (17.9 %) | 36 (11.9 %) | |
| Unsure | 20 (1.9 %) | 7 (2.7 %) | 0 (0.0 %) | 2 (0.9 %) | 11 (3.6 %) | |
| Percent insured, Medicaid / CHIP | <0.01 | |||||
| <25 % | 524 (48.8 %) | 133 (51.2 %) | 109 (39.4 %) | 159 (67.9 %) | 123 (40.6 %) | |
| 25–50 % | 378 (35.2 %) | 79 (30.4 %) | 109 (39.4 %) | 59 (25.2 %) | 131 (43.2 %) | |
| 51–75 % | 100 (9.3 %) | 23 (8.8 %) | 36 (13.0 %) | 9 (3.8 %) | 32 (10.6 %) | |
| >75 % | 35 (3.3 %) | 8 (3.1 %) | 23 (8.3 %) | 1 (0.4 %) | 3 (1.0 %) | |
| Unsure | 37 (3.4 %) | 17 (6.5 %) | 0 (0.0 %) | 6 (2.6 %) | 14 (4.6 %) | |
| Percent insured, Medicare | <0.01 | |||||
| <25 % | 398 (37.1 %) | 61 (23.5 %) | 217 (78.3 %) | 66 (28.2 %) | 54 (17.8 %) | |
| 25–50 % | 446 (41.5 %) | 116 (44.6 %) | 11 (4.0 %) | 141 (60.3 %) | 178 (58.7 %) | |
| 51–75 % | 123 (11.5 %) | 52 (20.0 %) | 2 (0.7 %) | 22 (9.4 %) | 47 (15.5 %) | |
| >75 % | 29 (2.7 %) | 13 (5.0 %) | 1 (0.4 %) | 4 (1.7 %) | 11 (3.6 %) | |
| Unsure | 78 (7.3 %) | 18 (6.9 %) | 46 (16.6 %) | 1 (0.4 %) | 13 (4.3 %) | |
| Percent insured, Uninsured | <0.01 | |||||
| <25 % | 878 (81.8 %) | 201 (77.3 %) | 239 (86.3 %) | 204 (87.2 %) | 234 (77.2 %) | |
| 25–50 % | 74 (6.9 %) | 19 (7.3 %) | 9 (3.2 %) | 13 (5.6 %) | 33 (10.9 %) | |
| 51–75 % | 7 (0.7 %) | 5 (1.9 %) | 0 (0.0 %) | 0 (0.0 %) | 2 (0.7 %) | |
| >75 % | 13 (1.2 %) | 4 (1.5 %) | 2 (0.7 %) | 2 (0.9 %) | 5 (1.7 %) | |
| Unsure | 102 (9.5 %) | 31 (11.9 %) | 27 (9.7 %) | 15 (6.4 %) | 29 (9.6 %) | |
| Percent race/ethnicity, Hispanic / Latino | <0.01 | |||||
| <25 % | 702 (65.4 %) | 152 (58.5 %) | 178 (64.3 %) | 170 (72.6 %) | 202 (66.7 %) | |
| 25–50 % | 273 (25.4 %) | 78 (30.0 %) | 71 (25.6 %) | 52 (22.2 %) | 72 (23.8 %) | |
| 51–75 % | 54 (5.0 %) | 19 (7.3 %) | 17 (6.1 %) | 7 (3.0 %) | 11 (3.6 %) | |
| >75 % | 24 (2.2 %) | 7 (2.7 %) | 7 (2.5 %) | 5 (2.1 %) | 5 (1.7 %) | |
| Unsure | 21 (2.0 %) | 4 (1.5 %) | 4 (1.4 %) | 0 (0.0 %) | 13 (4.3 %) | |
| Percent race/ethnicity, Black / African American | <0.01 | |||||
| <25 % | 617 (57.4 %) | 121 (46.5 %) | 160 (57.8 %) | 164 (70.1 %) | 172 (56.8 %) | |
| 25–50 % | 351 (32.7 %) | 105 (40.4 %) | 92 (33.2 %) | 55 (23.5 %) | 99 (32.7 %) | |
| 51–75 % | 70 (6.5 %) | 24 (9.2 %) | 19 (6.9 %) | 12 (5.1 %) | 15 (5.0 %) | |
| >75 % | 16 (1.5 %) | 6 (2.3 %) | 3 (1.1 %) | 3 (1.3 %) | 4 (1.3 %) | |
| Unsure | 20 (1.9 %) | 4 (1.5 %) | 3 (1.1 %) | 0 (0.0 %) | 13 (4.3 %) | |
| Percent race/ethnicity, Asian | <0.01 | |||||
| <25 % | 911 (84.8 %) | 211 (81.2 %) | 234 (84.5 %) | 203 (86.8 %) | 263 (86.8 %) | |
| 25–50 % | 105 (9.8 %) | 27 (10.4 %) | 33 (11.9 %) | 27 (11.5 %) | 18 (5.9 %) | |
| 51–75 % | 22 (2.0 %) | 12 (4.6 %) | 3 (1.1 %) | 3 (1.3 %) | 4 (1.3 %) | |
| >75 % | 5 (0.5 %) | 1 (0.4 %) | 2 (0.7 %) | 1 (0.4 %) | 1 (0.3 %) | |
| Unsure | 31 (2.9 %) | 9 (3.5 %) | 5 (1.8 %) | 0 (0.0 %) | 17 (5.6 %) | |
| Provider characteristics | ||||||
| Current medical profession | <0.01 | |||||
| Physician | 511 (47.6 %) | 0 (0.0 %) | 277 (100.0 %) | 234 (100.0 %) | 0 (0.0 %) | |
| Physician Assistant | 59 (5.5 %) | 59 (22.7 %) | 0 (0.0 %) | 0 (0.0 %) | 0 (0.0 %) | |
| Nurse Practitioner | 100 (9.3 %) | 100 (38.5 %) | 0 (0.0 %) | 0 (0.0 %) | 0 (0.0 %) | |
| Nurse (RN or LPN) | 101 (9.4 %) | 101 (38.8 %) | 0 (0.0 %) | 0 (0.0 %) | 0 (0.0 %) | |
| Pharmacist | 303 (28.2 %) | 0 (0.0 %) | 0 (0.0 %) | 0 (0.0 %) | 303 (100.0 %) | |
| Specialty | <0.01 | |||||
| Internal Medicine | 110 (10.2 %) | 110 (42.3 %) | 0 (0.0 %) | 0 (0.0 %) | 0 (0.0 %) | |
| Family Practice | 361 (33.6 %) | 127 (48.8 %) | 0 (0.0 %) | 234 (100.0 %) | 0 (0.0 %) | |
| General Pediatrics | 300 (27.9 %) | 23 (8.8 %) | 277 (100.0 %) | 0 (0.0 %) | 0 (0.0 %) | |
| Missing | 303 (28.2 %) | 0 (0.0 %) | 0 (0.0 %) | 0 (0.0 %) | 303 (100.0 %) | |
| Highest clinical degree | <0.01 | |||||
| Associate degree | 23 (2.1 %) | 23 (8.8 %) | 0 (0.0 %) | 0 (0.0 %) | 0 (0.0 %) | |
| Bachelor's degree | 181 (16.9 %) | 63 (24.2 %) | 0 (0.0 %) | 0 (0.0 %) | 118 (38.9 %) | |
| Master's degree | 161 (15.0 %) | 148 (56.9 %) | 0 (0.0 %) | 1 (0.4 %) | 12 (4.0 %) | |
| Doctorate level | 691 (64.3 %) | 22 (8.5 %) | 277 (100.0 %) | 229 (97.9 %) | 163 (53.8 %) | |
| Missing | 18 (1.7 %) | 4 (1.5 %) | 0 (0.0 %) | 4 (1.7 %) | 10 (3.3 %) | |
| Graduation year, highest completed clinical degreec | 1999 (1990–2007) | 2007 (1999.5–2013) | 1995 (1986–2002) | 1995 (1986–2001) | 2001 (1993–2008) | <0.01 |
| Regularly cared for COVID-19 patients | 757 (70.5 %) | 197 (75.8 %) | 195 (70.4 %) | 192 (82.1 %) | 173 (57.1 %) | <0.01 |
| Vaccinated against COVID-19 | 993 (92.5 %) | 222 (85.4 %) | 269 (97.1 %) | 222 (94.9 %) | 280 (92.4 %) | <0.01 |
| Vaccinated or intending to soon vaccinate against COVID-19 | 1,009 (94.0 %) | 228 (87.7 %) | 271 (97.8 %) | 224 (95.7 %) | 286 (94.4 %) | <0.01 |
| COVID-19 vaccines should be ____ for HCP | <0.01 | |||||
| Voluntary | 270 (25.1 %) | 87 (33.5 %) | 33 (11.9 %) | 48 (20.5 %) | 102 (33.7 %) | |
| Mandated | 695 (64.7 %) | 149 (57.3 %) | 223 (80.5 %) | 160 (68.4 %) | 163 (53.8 %) | |
| Not sure | 109 (10.1 %) | 24 (9.2 %) | 21 (7.6 %) | 26 (11.1 %) | 38 (12.5 %) | |
| More information would help with COVID-19 vaccine patient recommendations | 181 (25.6 %) | 48 (28.7 %) | 25 (23.8 %) | 23 (19.8 %) | 75 (27.1 %) | 0.33 |
| Interest in resources to improve patient discussions re: COVID-19 and other vaccines | ||||||
| CME module | 324 (45.8 %) | 84 (50.3 %) | 67 (45.6 %) | 51 (44.0 %) | 122 (44.0 %) | 0.60 |
| Informational website/e-book | 498 (46.4 %) | 125 (48.1 %) | 121 (43.7 %) | 98 (41.9 %) | 154 (50.8 %) | 0.14 |
PA = Physician Assistant; NP = Nurse Practitioner.
boldface indicates statistical significance (p < 0.05) using Pearson's Chi-Squared Test.
median (interquartile range).
3.2. COVID-19 vaccination among HCP
Nearly 93 % of HCP reported having received at least one dose of COVID-19 vaccine, and > 94 % of HCP reported either having already vaccinated or intending to vaccinate soon (Table 1). Vaccinating was most common among pediatricians (98 %), followed by family medicine doctors (96 %), pharmacists (94 %), and PAs/NPs/nurses (88 %) (p < 0.01). Nearly all HCP with high trust in CDC (>99 %) were vaccinating, compared to 90 % of HCP with low trust in CDC (p < 0.01).
PAs/NPs/nurses had one fifth the odds (OR: 0.2; 95 %CI: 0.1–0.4) of vaccinating compared to pediatricians (Table 2 ). HCP with high trust in CDC had 26 times the odds of vaccinating than HCP with low trust in CDC, even when controlling for HCP type (p < 0.01).
Table 2.
Odds of Vaccinating (or Intending to Soon Vaccinate) Against COVID-19 by Type of Healthcare Personnel and Trust in CDC.
| Total | Vaccinating | Not Vaccinating | Vaccinating (versus not) |
||||||
|---|---|---|---|---|---|---|---|---|---|
| Covariate | N | N (%) | N (%) | Crude OR | 95 % CI | p-valueb | aORa | 95 % CI | p-valueb |
| HCP type | |||||||||
| Pediatrician | 277 | 271 (97.8 %) | 6 (2.2 %) | Ref | Ref | ||||
| PA, NP, Nursec | 260 | 228 (87.7 %) | 32 (12.3 %) | 0.2 | (0.1, 0.4) | <0.01 | 0.2 | (0.1, 0.5) | <0.01 |
| Family Medicine | 234 | 224 (95.7 %) | 10 (4.3 %) | 0.5 | (0.1, 1.7) | 0.27 | 0.6 | (0.2, 1.7) | 0.36 |
| Pharmacist | 303 | 286 (94.4 %) | 17 (5.6 %) | 0.4 | (0.1, 1.0) | 0.06 | 0.5 | (0.2, 1.4) | 0.18 |
| Trust in CDCd | |||||||||
| Low trust | 616 | 553 (89.8 %) | 63 (10.2 %) | Ref | Ref | ||||
| High trust | 458 | 456 (99.6 %) | 2 (0.4 %) | 26.0 | (9.1, 74.2) | <0.01 | 25.1 | (7.8, 80.7) | <0.01 |
aOR by HCP type adjusted for trust in CDC; aOR by trust in CDC adjusted for HCP type.
boldface indicates statistical significance (p < 0.05) using Pearson's Chi-Squared Test.
PA = Physician Assistant; NP = Nurse Practitioner.
See Appendix 1.
Almost two-thirds (65 %) of HCP reported believing COVID-19 vaccination should be mandatory for HCP (Table 1). Support for mandatory vaccination varied greatly by HCP type, being reported most frequently by pediatricians (81 %), followed by family medicine doctors (68 %), PAs/NPs/nurses (57 %), and pharmacists (54 %) (p < 0.01). Only one (1.5 %) HCP not vaccinating supported mandatory vaccination, compared to 69 % of vaccinating HCP (p < 0.01).
3.3. Reasons for HCP not yet vaccinating against COVID-19
Among the 81 still unvaccinated HCP surveyed, the most common reason given for delaying vaccination against COVID-19 were concerns about side effects (47 %). Other reasons included the vaccine being developed/approved too quickly (33 %), discomfort with EUA (30 %), low perceived risk of infection (30 %), desire to wait until more are vaccinated (26 %), having a temporary medical condition (17 %), distrust due to racism/discrimination/historical unethical treatment of minorities (15 %), having a permanent medical condition (10 %), and vaccine trials not including people similar to oneself (4 %). None of these reasons differed significantly by HCP type (Fig. 1 ).
Fig. 1.
Reasons for Not Vaccinating Against COVID-19 among Unvaccinated Healthcare Personnel (n = 81)*, * none of these reasons differed significantly (p < 0.05) by type of Healthcare Personnel.
More than half (55 %) of HCP's practices made changes during the pandemic in attempts to improve routine vaccination. Most of these practices incorporated patient-level interventions (82 %); more than half incorporated interventions at the practice-level (54 %) or provider-level (50 %). Nearly half (45 %) improved vaccine availability and access. Roughly 14 % of these practices were forced to stop or pause routine vaccination during the pandemic.
3.4. Vaccinating patients against COVID-19
About two-thirds (67 %) of HCP's practices were offering COVID-19 vaccines to patients, more than three-quarters of which (77 %) were offering the Pfizer-BioNTech vaccine, followed by 65 % offering the Moderna vaccine and 27 % offering the J&J vaccine (p < 0.01) (Table 1). The most common strategy used to improve COVID-19 vaccine series completion was scheduling the next dose at the current visit (83 %), followed by paper reminder cards (60 %), reminder telephone calls (54 %), using a computerized immunization database/registry (51 %), and flagging patient charts (33 %). Almost half of HCP were interested in further resources to improve their discussions of COVID-19 and other vaccines with their patients, such as a continuing medical education (CME) module (46 %) or an informational website/e-book (46 %), including 47 % and 48 % of HCP vaccinating and 30 % and 15 % of HCP not vaccinating, respectively.
3.5. Strength of recommendations to patients to Receive COVID-19 vaccines
Three quarters (75 %) of HCP reported strongly recommending the Pfizer-BioNTech COVID-19 vaccine to their patients, compared to 70 % for Moderna and 24 % for J&J COVID-19 vaccines, respectively (p < 0.01) (Fig. 2 ). Most HCP reported strongly recommending COVID-19 vaccination to their patients who were at high risk of severe COVID-19 (79 %) or were close contacts of high-risk persons (82 %). HCP were more likely to strongly recommend COVID-19 vaccination to their older patients compared to their younger patients: 89 % reported strongly recommending COVID-19 vaccination to patients at least 65 years old, followed by 81 % for patients 25–64 years old, 70 % for patients 16–24 years old, and 61 % for patients 12–15 years old. Vaccinating HCP reported strongly recommending COVID-19 vaccines to their patients much more frequently than HCP not vaccinating, whether Pfizer-BioNTech (79 % vs 12 %; p < 0.01), Moderna (74 % vs 9 %; p < 0.01), or J&J (25 % vs 3 %; p < 0.01).
Fig. 2.
Strong Recommendations by Healthcare Personnel (n = 1074) for Specific Populations to Receive COVID-19 Vaccine*. * all of these recommendations differed significantly (p < 0.05) by type of Healthcare Personnel, except for Johnson & Johnson vaccine (p = 0.13).
3.6. Strength of recommendations to patients to Receive routine vaccines
HCP were most likely to report strongly recommending MMR/DTaP (88 %) and pneumococcal vaccines (85 %), followed by influenza vaccines (77 %), shingles vaccines (70 %), and HPV vaccines (65 %) (Fig. 3 ). Pediatricians typically recommended routine vaccines the most frequently (with the exception of shingles vaccine, which is not routinely administered by pediatricians), whereas pharmacists typically recommended routine vaccination the least frequently (again, with the exception of shingles vaccine, which is commonly given at pharmacies instead of physician offices).
Fig. 3.
Strong Recommendations by Healthcare Personnel (n = 1074) for Patients to Receive Routine Vaccines*, * all of these recommendations differed significantly (p < 0.05) by type of Healthcare Personnel, except for shingles vaccine (p = 0.06).
3.7. Impact of the pandemic on routine vaccination
The percentage of HCP conducting some patient visits via telehealth increased by 63 % during the pandemic, from 16 % before March 2020 to 79 % after March 2020 (p < 0.01) (Table 3 ). This increase in telehealth was largest among pediatricians (12 % to 93 %) and family medicine doctors (14 % to 97 %), and smallest (but still notable) among pharmacists (14 % to 42 %). More than half (51 %) of HCP conducting telehealth visits reported that telehealth decreased their ability to provide routine vaccination. Most HCP conducting telehealth visits (83 %) planned to continue telehealth after the pandemic was over.
Table 3.
Impact of the Pandemic on Routine Vaccination.
| Total | PA, NP, Nursea | Pediatrician | Family Medicine | Pharmacist | p-valueb | |
|---|---|---|---|---|---|---|
| N = 1,074 | N = 260 | N = 277 | N = 234 | N = 303 | ||
| Included telehealth visits before March 2020 | 166 (15.5 %) | 61 (23.5 %) | 32 (11.6 %) | 32 (13.7 %) | 41 (13.5 %) | <0.01 |
| % of total visits telehealth before March 2020 | 0.04 | |||||
| 1–24 % | 133 (80.1 %) | 44 (72.1 %) | 31 (96.9 %) | 29 (90.6 %) | 29 (70.7 %) | |
| 25–49 % | 21 (12.7 %) | 8 (13.1 %) | 1 (3.1 %) | 3 (9.4 %) | 9 (22.0 %) | |
| 50–74 % | 9 (5.4 %) | 6 (9.8 %) | 0 (0.0 %) | 0 (0.0 %) | 3 (7.3 %) | |
| 75–100 % | 3 (1.8 %) | 3 (4.9 %) | 0 (0.0 %) | 0 (0.0 %) | 0 (0.0 %) | |
| Included telehealth visits since March 2020 | 843 (78.5 %) | 230 (88.5 %) | 258 (93.1 %) | 228 (97.4 %) | 127 (41.9 %) | <0.01 |
| % of total visits telehealth since March 2020 | <0.01 | |||||
| 1–24 % | 490 (58.1 %) | 87 (37.8 %) | 196 (76.0 %) | 143 (62.7 %) | 64 (50.4 %) | |
| 25–49 % | 236 (28.0 %) | 91 (39.6 %) | 50 (19.4 %) | 56 (24.6 %) | 39 (30.7 %) | |
| 50–74 % | 90 (10.7 %) | 39 (17.0 %) | 11 (4.3 %) | 21 (9.2 %) | 19 (15.0 %) | |
| 75–100 % | 27 (3.2 %) | 13 (5.7 %) | 1 (0.4 %) | 8 (3.5 %) | 5 (3.9 %) | |
| Change in % of practices including telehealth visits after versus before March 2020 | (63.0 %) | (65.0 %) | (81.5 %) | (83.7 %) | (28.4 %) | |
| Plan to continue telehealth after pandemic | 0.02 | |||||
| No, for sure | 11 (1.3 %) | 4 (1.7 %) | 3 (1.2 %) | 2 (0.9 %) | 2 (1.6 %) | |
| Most likely not | 62 (7.4 %) | 18 (7.8 %) | 24 (9.3 %) | 12 (5.3 %) | 8 (6.3 %) | |
| Not sure | 71 (8.4 %) | 13 (5.7 %) | 34 (13.2 %) | 11 (4.8 %) | 13 (10.2 %) | |
| Most likely yes | 313 (37.1 %) | 89 (38.7 %) | 93 (36.0 %) | 78 (34.2 %) | 53 (41.7 %) | |
| Yes, for sure | 386 (45.8 %) | 106 (46.1 %) | 104 (40.3 %) | 125 (54.8 %) | 51 (40.2 %) | |
| Ability to provide routine vaccination (other than COVID-19) due to telehealth | <0.01 | |||||
| Greatly decreased | 110 (13.0 %) | 26 (11.3 %) | 32 (12.4 %) | 40 (17.5 %) | 12 (9.4 %) | |
| Somewhat decreased | 323 (38.3 %) | 114 (49.6 %) | 77 (29.8 %) | 93 (40.8 %) | 39 (30.7 %) | |
| No impact | 358 (42.5 %) | 78 (33.9 %) | 146 (56.6 %) | 77 (33.8 %) | 57 (44.9 %) | |
| Increased | 52 (6.2 %) | 12 (5.2 %) | 3 (1.2 %) | 18 (7.9 %) | 19 (15.0 %) | |
| Barriers to vaccinating during pandemic so far: | ||||||
| decreased access (e.g., fewer in-person visits) | 777 (72.3 %) | 188 (72.3 %) | 236 (85.2 %) | 181 (77.4 %) | 172 (56.8 %) | <0.01 |
| lenient enforcement of school immunization requirements | 255 (23.7 %) | 60 (23.1 %) | 80 (28.9 %) | 50 (21.4 %) | 65 (21.5 %) | 0.13 |
| disruption of vaccine supply | 252 (23.5 %) | 71 (27.3 %) | 41 (14.8 %) | 58 (24.8 %) | 82 (27.1 %) | <0.01 |
| disruption of vaccination due to staffing | 330 (30.7 %) | 92 (35.4 %) | 54 (19.5 %) | 74 (31.6 %) | 110 (36.3 %) | <0.01 |
| hesitancy/refusal/low demand | 7 (0.7 %) | 1 (0.4 %) | 2 (0.7 %) | 1 (0.4 %) | 3 (1.0 %) | 0.80 |
| none | 21 (2.0 %) | 5 (1.9 %) | 2 (0.7 %) | 3 (1.3 %) | 11 (3.6 %) | 0.07 |
| Barriers to vaccinating expected in the future: | ||||||
| decreased access (e.g., fewer in-person visits) | 660 (84.9 %) | 160 (85.1 %) | 209 (88.6 %) | 159 (87.8 %) | 132 (76.7 %) | <0.01 |
| lenient enforcement of school immunization requirements | 161 (63.1 %) | 38 (63.3 %) | 48 (60.0 %) | 32 (64.0 %) | 43 (66.2 %) | 0.89 |
| disruption of vaccine supply | 169 (67.1 %) | 51 (71.8 %) | 22 (53.7 %) | 37 (63.8 %) | 59 (72.0 %) | 0.16 |
| disruption of vaccination due to staffing / personal protective equipment shortages | 207 (62.7 %) | 56 (60.9 %) | 23 (42.6 %) | 37 (50.0 %) | 91 (82.7 %) | <0.01 |
| Made changes to improve routine vaccination | 592 (55.1 %) | 137 (52.7 %) | 140 (50.5 %) | 102 (43.6 %) | 213 (70.3 %) | <0.01 |
| patient-focused intervention(s) | 483 (81.6 %) | 107 (78.1 %) | 109 (77.9 %) | 80 (78.4 %) | 187 (87.8 %) | 0.04 |
| provider-focused intervention(s) | 298 (50.3 %) | 84 (61.3 %) | 54 (38.6 %) | 49 (48.0 %) | 111 (52.1 %) | <0.01 |
| practice-focused intervention(s) | 320 (54.1 %) | 73 (53.3 %) | 85 (60.7 %) | 51 (50.0 %) | 111 (52.1 %) | 0.32 |
| improved vaccine availability and access | 265 (44.8 %) | 63 (46.0 %) | 40 (28.6 %) | 31 (30.4 %) | 131 (61.5 %) | <0.01 |
| stopped or paused routine vaccination | 77 (13.0 %) | 17 (12.4 %) | 10 (7.1 %) | 16 (15.7 %) | 34 (16.0 %) | 0.02 |
| other | 14 (2.4 %) | 4 (2.9 %) | 4 (2.9 %) | 3 (2.9 %) | 3 (1.4 %) | 0.72 |
PA = Physician Assistant; NP = Nurse Practitioner.
boldface indicates statistical significance (p < 0.05) using Pearson's Chi-Squared Test.
Nearly all HCP (98 %) reported facing at least one barrier to routine vaccination since the start of the pandemic. The most commonly reported barrier faced was decreased access (e.g., fewer in-person visits), reported by nearly-three-quarters (72 %) of HCP. Decreased access was reported most frequently by pediatricians (85 %), and more frequently by family medicine doctors (77 %) and PAs/NPs/nurses (72 %) than by pharmacists (57 %). Other commonly reported barriers were staffing issues (31 %), disruption of vaccine supply (24 %), and lenient enforcement of school immunization requirements (24 %). Staffing issues and disruption of vaccine supply were reported less frequently by pediatricians (15–20 %) than by other HCP (25–36 %) (p < 0.01). Most HCP anticipated facing these barriers in the future even if they hadn't yet; 85 % anticipated decreased access, 67 % anticipated disruption of vaccine supply, 63 % anticipated staffing issues, and 63 % anticipated lenient enforcement of school immunization requirements.
3.8. Familiarity with vaccine Adverse event reporting
Nearly all (491 of 529; 93 %) HCP asked about VAERS reported familiarity,[22] of which 180 (37 %) claimed they had made a report to VAERS at least once. However, nearly-three-quarters (396 of 545; 73 %) of HCP asked about the fictitious IARM system also reported familiarity, of which 99 (25 %) claimed to have made a report to IARM at least once. Pharmacists (97 %) and pediatricians (97 %) were familiar with VAERS the most frequently, followed by PAs/NPs/nurses (88 %) and family medicine doctors (86 %) (p < 0.01). Of those familiar with VAERS, pharmacists (46 %) and pediatricians (40 %) also made reports to VAERS the most frequently, followed by family medicine doctors (29 %) and PAs/NPs/nurses (26 %) (p < 0.01). Those reporting familiarity with IARM did not differ significantly by HCP type (p = 0.09).
4. Discussion
In this panel survey, more than nine out of ten HCP reported having received at least one dose of COVID-19 vaccine. Pediatricians reported the highest vaccine coverage, followed by family medicine doctors, pharmacists, and PAs/NPs/nurses.
HCP were more likely to recommend COVID-19 vaccination to patients who were older or either high-risk themselves or in close contact with high-risk persons. About three quarters of HCP reported strongly recommending the Pfizer-BioNTech and Moderna COVID-19 vaccines to their patients, compared to about one quarter strongly recommending the J&J vaccine. This gap was likely due to J&J’s lower efficacy (compared to mRNA vaccines) and rare side effects such as Thrombosis with Thrombocytopenia Syndrome (TTS), though the CDC did not recommend a preference for mRNA vaccines over J&J vaccine until several months after this survey.[23].
Our data are consistent with prior surveys of HCP which also showed high overall vaccine coverage with differences by HCP type. For example, 88 % of HCP in a large, university healthcare system in Upstate New York had either already received a COVID-19 vaccine or were planning to do so as of March 2021,[24] a substantial increase from the 58 % intending to vaccinate just prior to the initial EUA.[25] Physicians and scientists had the highest rates of vaccine acceptance (97 %), whereas staff in ancillary (e.g., clerical, dietary, phlebotomy, unit support, clinical support, registration, and environmental) services had the lowest rates (80 %), with nurses in between (87 %).[24] Relatively small increases in coverage among HCP between March and September 2021 are unsurprising, as HCP were included in the first wave of US adults eligible for vaccination in December 2020, and had thus already achieved relatively high coverage by March.
In contrast, data from the US Department of Health and Human Services (HHS) Unified Hospital Data Surveillance System found that only 70 % of hospital-based HCP were fully vaccinated against COVID-19 as of September 2021.[26] However, the gap between our and HHS's estimates of vaccine coverage may primarily be due to our measuring vaccination as at least one dose compared to two doses, focusing on specific HCP types, and not including ancillary hospital staff who are known to have lower uptake of COVID-19 vaccines.
Trust in CDC was strongly positively associated with COVID-19 vaccination; HCP with high trust had 12 times the odds of vaccination of HCP with low trust, even when controlling for HCP type. A strong relationship between COVID-19 vaccination and trust in CDC has also been seen among the general population; a nationally representative panel survey of adults in the general US population, also conducted in September 2021, found an 11-fold increase in the odds of COVID-19 vaccination with high (versus low) trust in CDC.[13].
Nearly half of unvaccinated HCP were concerned about potential side effects. About one third of unvaccinated HCP were concerned the vaccine was developed and approved too quickly, were uncomfortable with EUA, or perceived a low risk of infection. About one quarter wanted to wait until more people had been vaccinated. These attitudes did not differ by HCP type, and reflected the attitudes of the unvaccinated in the general population at this time.[13], [27].
Nearly all HCP reported a negative impact of the pandemic on routine vaccination, primarily due to replacing in-person visits with telehealth. This is consistent with other data,[28], [29] and underscores the need to catch up on and maintain high coverage for routine vaccines to prevent future outbreaks of vaccine-preventable disease.
Most unvaccinated US adults in the aforementioned September 2021 panel survey also expressed suspicion of pharmaceutical companies and government, illustrating the limited potential of vaccine messaging from these sources.[13] Fortunately, having a discussion with an HCP who encouraged vaccination was strongly positively associated with patients vaccinating against COVID-19. This aligns with trends from before the pandemic, as HCP have long been the most frequently used and credible source of vaccine information.[14] However, our data confirmed that unvaccinated HCP were far less likely to recommend vaccinating to their patients and harbored many of the same concerns as the public. Nearly half of HCP were interested in further resources to improve their discussions of COVID-19 and other vaccines with their patients. Even vaccinated HCP need sufficient resources to understand and confidently discuss vaccines with their hesitant patients, especially as vaccine science progresses and concerns evolve, the pace of which has only accelerated during the pandemic. Public health should thus prioritize providing resources to HCP to aid in their own vaccine decision-making and their efforts to support the decision-making of their patients.
The main limitation of this study is its cross-sectional design, which restricts our findings to associations at a single point in time. We plan to conduct a second survey using the same methods to compare changes over time. Another limitation is that we were unable to power the study to see differences between more than four HCP types. We focused our efforts on four of the most common HCP types, but this naturally excluded specialists in favor of generalists and primary care providers (PCPs). Our findings thus may not be representative of specialists, whose recommendations may be equally or even more relevant for certain populations than those of PCPs. We also had to combine PAs, NPs, and nurses into one group for recruitment and analysis purposes, despite differences in their education and roles. However, a secondary analysis examining PAs/NPs separately from nurses found that COVID-19 vaccine coverage was similar between PAs/NPs (83 %) and nurses (89 %), both lower than each of the other three HCP types measured; and that the odds of vaccinating were lowest and similar for PAs/NPs (OR: 0.1; 95 %CI: 0.1–0.3) and nurses (OR: 0.2; 95 %CI: 0.1–0.7), compared to pediatricians (Appendix 2). This secondary analysis supports combining these HCP types together as the study was designed to do. Another limitation is that although all respondents were asked to rate the strength of their recommendations for each vaccine product (e.g., Pfizer, Moderna, J&J), pediatricians would have only recommended Pfizer to most of their patient population (e.g., children) given the EUAs at the time. Our data are also subject to the limitations of self-reporting; nearly-three-quarters of our sample reporting familiarity with a fictitious adverse event monitoring system illustrates the potential effects of social desirability bias. Strengths of our work include the focus on HCP of different types and the use of a well-established nationally representative panel.
5. Conclusions
Increasing vaccine coverage remains the best way to control the pandemic. HCP have long been the most frequently used and credible source of vaccine information for the public. Although most HCP are vaccinated against COVID-19 and strongly recommend vaccination to their patients, some harbor the same concerns as the public. Additional informational resources that are regularly updated to explain the progressing scientific landscape and address ever evolving public concerns are needed to further improve vaccine coverage among HCP and aid them in supporting the decision-making of their patients.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
Acknowledgements
Funding/Support: Supported in part by a research grant from Investigator-Initiated Studies Program of Merck Sharp & Dohme Corp. The opinions expressed in this paper are those of the authors and do not necessarily represent those of Merck Sharp & Dohme Corp.
Role of Funder/Sponsor: Merck Sharp & Dohme Corp had no role in the design or conduct of the study.
Contributors' Statement:
Dr Dudley conceptualized and designed the study and drafted the initial manuscript.
Drs Salmon, Rimal, and Harvey conceptualized and designed the study.
Dr Schuh carried out the initial analyses.
All authors contributed to survey design, reviewed and revised the manuscript, approved the final manuscript as submitted, and agree to be accountable for all aspects of the work.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.vaccine.2023.01.030.
Appendix A. Supplementary data
The following are the Supplementary data to this article:
Data availability
The data used are confidential.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data used are confidential.