Letters With vaccination rates lagging in areas with higher social vulnerability, small financial incentives should be con- sidered in conjunction with other equity-promoting strategies.5,6 The social incentive of cash cards for drivers may also encourage people to help get their friends and fam- ily vaccinated, a powerful motivator for those undecided about vaccination. With hundreds of millions of dollars being spent to accelerate COVID-19 vaccine uptake, these study findings suggest that this strategy for increasing vacci- nation merits greater investment. Charlene A. Wong, MD, MSHP William Pilkington, DPA, MPA, PhD Irene A. Doherty, PhD, MPH Ziliang Zhu, PhD Hattie Gawande, BA Deepak Kumar, PhD Noel T. Brewer, PhD Author Affiliations: Office of the Secretary, North Carolina Department of Health and Human Services, Raleigh (Wong, Gawande); Advanced Center for COVID-19 Related Disparities (ACCORD), Julius L. Chambers Biomedical Biotechnology Research Institute, North Carolina Central University, Durham (Pilkington, Doherty, Kumar); Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill (Zhu); Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill (Brewer). Accepted for Publication: September 4, 2021. Published Online: October 25, 2021. doi:10.1001/jamainternmed.2021.6170 Corresponding Author: Charlene A. Wong, MD, MSHP, Office of the Secretary, North Carolina Department of Health and Human Services, 101 Blair Dr, Raleigh, NC 27603 (charlene.wong@dhhs.nc.gov). Author Contributions: Dr Kumar had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Wong, Gawande, Kumar, Brewer. Acquisition, analysis, or interpretation of data: Wong, Pilkington, Doherty, Zhu, Kumar, Brewer. Drafting of the manuscript: Wong, Pilkington, Doherty, Gawande, Brewer. Critical revision of the manuscript for important intellectual content: Wong, Doherty, Zhu, Kumar, Brewer. Statistical analysis: Wong, Pilkington, Doherty, Zhu, Brewer. Obtained funding: Wong, Kumar, Brewer. Administrative, technical, or material support: Pilkington, Gawande, Kumar, Brewer. Supervision: Wong, Gawande, Kumar. Conflict of Interest Disclosures: Dr Brewer reported grants from the North Carolina Department of Health and Human Services during the conduct of the study, and personal fees from the World Health Organization, the US Centers for Disease Control and Prevention, and Merck outside the submitted work. No other disclosures were reported. 1. Brewer NT, Chapman GB, Rothman AJ, Leask J, Kempe A. Increasing vaccination: putting psychological science into action. Psychol Sci Public Interest. 2017;18(3):149-207. doi:10.1177/1529100618760521 2. National Governors Association. COVID-19 vaccine incentives. 2021. Accessed June 22, 2021. https://www.nga.org/center/publications/covid-19- vaccine-incentives/ 3. Volpp KG, Cannuscio CC. Incentives for immunity–strategies for increasing COVID-19 vaccine uptake. N Engl J Med. 2021;385(1):e1. doi:10.1056/ NEJMp2107719 4. Walkey AJ, Law A, Bosch NA. Lottery-based incentive in ohio and COVID-19 vaccination rates. JAMA. 2021;326(8):766-767. doi:10.1001/jama.2021.11048 5. Barry V, Dasgupta S, Weller DL, et al. Patterns in COVID-19 vaccination coverage, by social vulnerability and urbanicity–United States, December 14, 2020-May 1, 2021. MMWR Morb Mortal Wkly Rep. 2021;70(22):818-824. doi:10. 15585/mmwr.mm7022e1 6. Wong CA, Dowler S, Moore AF, et al. COVID-19 vaccine administration, by race and ethnicity–North Carolina, December 14, 2020-April 6, 2021. MMWR Morb Mortal Wkly Rep. 2021;70(28):991-996. doi:10.15585/mmwr.mm7028a2 Age- and Sex-Specific Incidence of Cerebral Venous Sinus Thrombosis Associated With Ad26.COV2.S COVID-19 Vaccination Recent reports1-4 suggest a possible association between Ad26.COV2.S (Johnson & Johnson/Janssen) COVID-19 vacci- nation and cerebral venous sinus thrombosis (CVST). Esti- mates of postvaccination CVST risk require accurate age- and sex-specific prepandemic CVST incidence rates; how- ever, reported rates vary widely.5 We compared the age- and sex-specific CVST rates af- ter Ad26.COV2.S vaccination with the prepandemic CVST rate in the population. Supplemental content Methods | In this population-based cohort study, to estimate the risk of CVST after Ad26.COV2.S vaccination, we first iden- tified all incident cases of CVST in Olmsted County, Minnesota from January 1, 2001, through December 31, 2015 (eMethods in the Supplement). Sex-and age-adjusted incidence rates were adjusted to the 2010 US census population. We used CDC Vaccine Adverse Event Reporting System (VAERS) data from February 28, 2021 (vaccine approval date) to May 7, 2021, to estimate the incidence of CVST after Ad26.COV2.S vaccination assuming 3 (15, 30, and 92 days) plausible post- vaccination periods during which individuals were con- sidered to be at risk of CVST. We then compared post- Ad26.COV2.S vaccination CVST rates with prepandemic rates to estimate postvaccination CVST risk. This study was approved by the Mayo Clinic institutional review board. Medi- cal records of Olmsted County residents with CVST were reviewed only if the residents had signed an authorization for accessing their medical records for research purposes. SAS, version 9.4 (SAS Institute Inc) and R, version 4.0.3 (R Project for Statistical Computing) were used for statistical analyses. Significance was set at a 2-sided P < .05. Results | From 2001 through 2015, 39 Olmsted County resi- dents developed acute incident CVST. A total of 29 patients (74.4%) had a predisposing venous thromboembolism risk fac- tor (eg, infection, active cancer, or oral contraceptives [for wom- en]) within 92 days before the event. The median age at diag- nosis was 41 years (range, 22-84 years); 22 residents with CVST (56.4%) were female. The overall age- and sex-adjusted CVST incidence was 2.34 per 100 000 person-years (PY) (95% CI, 1.60-3.08 per 100 000 PY). Age-adjusted CVST rates for female and male individuals were 2.46 per 100 000 PY (95% CI, 1.43-3.49 per 100 000 PY) and 2.34 per 100 000 PY (95% CI, 1.22-3.46 per 100 000 PY), respectively. Men aged 65 years or older had the highest CVST rate (6.22 per 100 000 PY; 95% CI, 2.50-12.82 per 100 000 PY), followed by women aged 18 to 29 years (4.71 per 100 000 person-years; 95% CI, 2.26-8.66 per 100 000 PY) (Table 1). 80 JAMA Internal Medicine January 2022 Volume 182, Number 1 (Reprinted) jamainternalmedicine.com © 2021 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/05/2022 Letters Table 1. Annual Incidence of CVST Among Residents of Olmsted County, Minnesota, From 2001 to 2015 by Age and Sex Sex and age, y Female CVST cases, No. Population, person-years Incidence, per 100 000 person-years (95% CI) Age-adjusted ratea Male Age-adjusted ratea All 18-29 30-39 40-49 50-64 ≥65 Total 18-29 30-39 40-49 50-64 ≥65 Total 18-29 30-39 40-49 50-64 ≥65 Total Age-adjusted ratea Age- and sex-adjusted ratea 10 22 NA 4 2 4 2 2 3 2 3 7 7 4 7 9 17 NA 12 39 NA NA 212 441 156 541 157 433 195 110 148 204 869 729 NA 181 342 147 386 145 879 175 760 112 508 762 875 NA 393 783 303 927 303 312 370 870 260 712 1 632 604 NA NA 4.71 (2.26-8.66) 2.56 (0.70-6.54) 1.27 (0.15-4.59) 2.05 (0.56-5.25) 1.35 (0.16-4.88) 2.53 (1.59-3.83) 2.46 (1.43-3.49) 1.10 (0.13-3.99) 2.04 (0.42-5.95) 1.37 (0.16-4.96) 1.71 (0.35-4.99) 6.22 (2.50-12.82) 2.23 (1.30-3.57) 2.34 (1.22-3.46) 3.05 (1.57-5.32) 2.30 (0.92-4.74) 1.32 (0.36-3.38) 1.89 (0.76-3.89) 3.45 (1.58-5.53) 2.39 (0.61-1.67) 2.38 (1.63-3.13) 2.34 (1.60-3.08) Abbreviations: CVST, cerebral venous sinus thrombosis; NA, not applicable. a Adjusted to the US census 2010 population. As of May 7, 2021, 8 727 851 Ad26.COV2.S vaccine doses had been administered in the US; 46 potential CVST events occur- ring within 92 days after Ad26.COV2.S vaccination were re- ported to VAERS. Eight events were excluded because they were potentially duplicate reports (4) or were not objectively diagnosed (4). Twenty-seven of 38 objectively diagnosed cases of CVST after Ad26.COV2.S vaccination (71.1%) occurred in fe- male individuals. The median patient age was 45 years (range, 19-75 years). The median time from vaccination to CVST was 9 days (IQR, 6-13 days; range, 1-51 days); 31 of 38 cases of CVST (81.6%) occurred within 15 days after vaccination, and 36 (94.7%) occurred within 30 days. The overall incidence rate of post–Ad26.COV2.S vaccina- tion CVST was 8.65 per 100 000 PY (95% CI, 5.88-12.28 per 100 000 PY) at 15 days, 5.02 per 100 000 PY (95% CI, 3.52- 6.95 per 100 000 PY) at 30 days, and 1.73 per 100 000 PY (95% CI, 1.22-2.37 per 100 000 PY) at 92 days (Table 2). The 15-day postvaccination CVST incidence rates for female and male in- dividuals were 13.01 per 100 000 PY (95% CI, 8.24-19.52 per 100 000 PY) and 4.41 per 100 000 PY (95% CI, 1.90-8.68 per 100 000 PY), respectively. The postvaccination CVST rate among females was 5.1-fold higher compared with the pre- COVID-19 pandemic rate (13.01 vs 2.53 per 100 000 PY; P < .001) (Table 2). This risk was highest among women aged 40 to 49 years (29.50 per 100 000 PY; 95% CI, 13.50-55.95 per 100 000 PY), followed by women aged 30 to 39 years (26.50 per 100 000 PY; 10.65-54.63 per 100 000 PY). Discussion | In this population-based cohort study, we found that the CVST incidence rate 15 days after Ad26.COV2.S vaccina- tion was significantly higher than the prepandemic rate. How- ever, the higher rate of this rare adverse effect must be con- sidered in the context of the effectiveness of the vaccine in preventing COVID-19 (absolute reduction of severe or critical COVID-19 of 940 per 100 000 PY).6 Most CVST events occurred within 15 days after vaccina- tion, which is likely the highest at-risk period. The postvacci- nation CVST rate among females was higher than the prepan- demic rate among females. The highest risk was among women aged 30 to 49 years, but the absolute CVST risk was still low in this group (up to 29.5 per 100 000 PY among women aged 40-49 years). The reason that women had a higher incidence of postvaccination CVST is unclear; concomitant CVST risk fac- tors or autoantibody production might have been involved.2 The overall prepandemic CVST incidence rate was slightly higher in our study than in other studies (0.22-1.57 per 100 000 PY)5 likely because we captured all objectively diagnosed in- cident CVST cases in a well-defined population, including those discovered at autopsy. The present study avoided referral bias and included only objectively diagnosed and confirmed cases. Only cases with adequate details or imaging findings reported on VAERS were used. Study limitations include possible ascer- tainment bias by including only objectively diagnosed CVST cases. VAERS reporting is voluntary and subject to reporting jamainternalmedicine.com (Reprinted) JAMA Internal Medicine January 2022 Volume 182, Number 1 81 © 2021 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/05/2022 Table 2. Incidence Rate of CVST Occurring After the Administration of the Ad26.COV2.S Vaccine Doses administered, No. Person-years at risk Incidence, per 100 000 person-years (95% CI) Expected CVST cases, No.a Incidence rate ratio (95% CI)b P valuec Letters Risk period, sex, and age, y Observed CVST cases, No. 15 d Female Male Male 30 d Female 18-29 30-39 40-49 50-64 ≥65 Total 18-29 30-39 40-49 50-64 ≥65 Total 18-29 30-39 40-49 50-64 ≥65 Total 18-29 30-39 40-49 50-64 ≥65 Total 18-29 30-39 40-49 50-64 ≥65 Total 18-29 30-39 40-49 50-64 ≥65 Total 92 d Female Male 23 2 7 9 5 0 1 0 3 3 1 8 2 8 6 0 1 0 3 5 1 2 8 6 1 1 0 3 6 1 10 26 10 10 27 11 641 510 642 745 743 256 1 463 416 814 947 4 305 874 714 458 728 699 775 390 1 505 505 697 925 4 421 977 641 510 642 745 743 256 1 463 416 814 947 4 305 874 714 458 728 699 775 390 1 505 505 697 925 4 421 977 641 510 642 745 743 256 1 463 416 814 947 4 305 874 714 458 728 699 775 390 1 505 505 697 925 4 421 977 176 837 13.01 (8.24-19.52) 26 346 26 397 30 525 60 101 33 469 29 342 29 927 31 844 61 829 28 663 7.59 (0.91-27.40) 26.52 (10.65-54.63) 29.48 (13.50-55.95) 8.32 (2.70-19.42) 0.00 (0.00-11.03) 3.41 (0.10-18.98) 0.00 (0.00-12.33) 9.42 (1.95-27.54) 4.85 (1.00-14.18) 3.49 (0.10-19.43) 181 606 4.41 (1.90-8.68) 52 692 52 794 61 049 3.80 (0.46-13.70) 15.15 (6.53-29.85) 16.38 (7.86-30.12) 120 202 4.99 (1.83-10.87) 66 938 0.00 (0.00-5.51) 353 675 7.35 (4.80-10.77) 58 684 59 854 63 689 1.70 (0.05-9.49) 0.00 (0.00-6.17) 4.71 (0.97-13.77) 123 659 4.04 (1.31-9.44) 57 326 1.74 (0.05-9.72) 363 211 2.75 (1.32-5.06) 161 589 161 901 187 218 368 619 205 276 179 964 183 551 195 312 379 220 175 800 1.24 (0.15-4.47) 4.94 (2.13-9.73) 5.34 (2.56-9.82) 1.63 (0.60-3.54) 0.49 (0.01-2.71) 0.56 (0.02-3.10) 0.00 (0.00-2.01) 1.54 (0.32-4.49) 1.58 (0.58-3.44) 0.57 (0.02-3.17) 1 113 848 0.99 (0.49-1.77) 1.24 0.67 0.39 1.23 0.45 4.47 0.32 0.61 0.44 1.06 1.78 4.05 2.48 1.35 0.78 2.46 0.90 8.95 0.65 1.22 0.87 2.11 3.57 8.09 7.61 4.14 2.38 7.56 2.77 1.98 3.74 2.68 6.47 10.94 24.82 1.61 (0.17-7.57) 10.38 (2.64-48.33) 23.21 (4.80-221.05) 4.06 (0.87-20.45) 0.00 (0.004-23.58) 5.14 (2.74-9.68) 3.09 (0.05-59.36) 0.00 (0.00-11.92) 6.87 (0.79-82.34) 2.84 (0.38-21.32) 0.56 (0.01-4.36) 1.98 (0.74-4.83) 0.81 (0.09-3.78) 5.93 (1.59-26.93) 12.89 (2.75-120.81) 2.43 (0.58-11.73) 0.00 (0.00-11.79) 2.91 (1.58-5.38) 1.55 (0.03-29.68) 0.00 (0.00-5.96) 3.44 (0.39-41.17) 2.37 (0.46-15.26) 0.28 (0.01-2.18) 1.24 (0.51-2.86) 0.26 (0.03-1.23) 1.93 (0.52-8.78) 4.20 (0.90-39.39) 0.79 (0.19-3.82) 0.36 (0.01-6.93) 0.50 (0.01-9.68) 0.00 (0.00-1.94) 1.12 (0.13-13.43) 0.93 (0.20-5.72) 0.09 (0.00-0.71) 0.44 (0.19-1.00) 1 084 603 2.49 (1.64-3.62) 27.44 0.98 (0.54-1.81) .63 <.001 <.001 .04 >.99 <.001 .36 >.99 .04 .19 >.99 .12 >.99 .003 <.001 .20 >.99 <.001 .56 .56 .16 .29 .28 .54 .08 .39 .05 .75 .58 >.99 >.99 .09 >.99 >.99 .007 .05 Abbreviation: CVST, cerebral venous sinus thrombosis. a Based on the population of Olmsted County, Minnesota. b Observed vs expected. c The exact binomial test P value was calculated using the binom.test() function in the R, version 4.0.3, with the probability of an observed CVST case being calculated as K2/(K1+K2), where K1 was the number of prepandemic CVST cases in the general population (expected) and K2 was the number of postvaccination CVST cases (observed). 82 JAMA Internal Medicine January 2022 Volume 182, Number 1 (Reprinted) jamainternalmedicine.com © 2021 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/05/2022 biases. VAERS monitors vaccine adverse events but does not prove causality. Aneel A. Ashrani, MD, MS Daniel J. Crusan, BS Tanya Petterson, MS Kent Bailey, PhD John A. Heit, MD Author Affiliations: Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota (Ashrani, Heit); Divisions of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota (Crusan, Petterson, Bailey); Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota (Heit); Division of Epidemiology, Mayo Clinic, Rochester, Minnesota (Heit). Accepted for Publication: September 12, 2021. Published Online: November 1, 2021. doi:10.1001/jamainternmed.2021.6352 Corresponding Author: Aneel A. Ashrani, MD, MS, Division of Hematology, Department of Internal Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (ashrani.aneel@mayo.edu). Author Contributions: Dr Ashrani and Mr Crusan had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Ashrani, Petterson, Bailey, Heit. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Ashrani, Crusan, Petterson. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Crusan, Petterson, Bailey. Obtained funding: Ashrani, Heit. Administrative, technical, or material support: Ashrani, Heit. Supervision: Ashrani, Petterson, Bailey, Heit. Conflict of Interest Disclosures: Dr Ashrani reported receiving grants from the National Heart, Lung and Blood Institute (NHLBI), National Institutes of Health (NIH) during the conduct of the study. Mr Crusan reported receiving grants from the NIH during the conduct of the study. Dr Heit reported receiving grants from the NHLBI, NIH during the conduct of the study. No other disclosures were reported. Funding/Support: This study was supported in part by grant R01HL66216 from the NHLBI, NIH (Drs Ashrani and Bailey), the Rochester Epidemiology Project (grant R01AG034676 from the National Institute on Aging, NIH), and the Mayo Foundation. Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. 1. Centers for Disease Control and Prevention. Cases of cerebral venous sinus thrombosis with thrombocytopenia after receipt of the Johnson & Johnson COVID-19 vaccine New release. April 13, 2021. Accessed April 21, 2021. https:// emergency.cdc.gov/han/2021/han00442.asp 2. See I, Su JR, Lale A, et al. US case reports of cerebral venous sinus thrombosis with thrombocytopenia after Ad26.COV2.S vaccination, March 2 to April 21, 2021. JAMA. 2021;325(24):2448-2456. doi:10.1001/jama.2021.7517 3. Shay DK, Gee J, Su JR, et al. Safety monitoring of the Janssen (Johnson & Johnson) COVID-19 vaccine—United States, March-April 2021. MMWR Morb Mortal Wkly Rep. 2021;70(18):680-684. doi:10.15585/mmwr.mm7018e2 4. Shimabukuro T. Update: thrombosis with thrombocytopenia syndrome (TTS) following COVID-19 vaccination. Paper presented at: Advisory Committee on Immunization Practices; May 12, 2021. 5. Devasagayam S, Wyatt B, Leyden J, Kleinig T. Cerebral venous sinus thrombosis incidence is higher than previously thought: a retrospective population-based study. Stroke. 2016;47(9):2180-2182. doi:10.1161/ STROKEAHA.116.013617 6. Sadoff J, Gray G, Vandebosch A, et al; ENSEMBLE Study Group. Safety and efficacy of single-dose Ad26.COV2.S vaccine against COVID-19. N Engl J Med. 2021;384(23):2187-2201. doi:10.1056/NEJMoa2101544 Letters Payer-Specific Negotiated Prices for Prescription Drugs at Top-Performing US Hospitals Nearly one-third of pharmaceutical spending in the US is for clinician-administered drugs (eg, infusions).1 Medicare Part B reimbursement for these drugs is set at the average sales price (ASP)—the average price charged by manufacturers to whole- salers net of any rebates or discounts—plus a 6% markup (or 4.3% during budget se- questration). By contrast, hospitals and physician offices charge commercial insurers whatever price they negotiate, and they retain any difference between the negotiated price and cost of acquisition. Supplemental content While these negotiated prices have long been confiden- tial, a transparency rule that took effect on January 1, 2021, re- quires hospitals to post payer-specific negotiated prices for all items and services, including clinician-administered drugs. We analyzed a set of top-performing hospitals to quantify drug pricing variation across insurers. Methods | We searched the websites of the 20 top-rated hospi- tals by US News and World Report rankings for pricing files from January 1 through September 15, 2021. We selected these hospitals because they were likely to have sufficient resources to comply with reporting requirements and would serve as a model for other hospitals that were deciding on how to comply (eTable 1 in the Supplement). We extracted commercial insurer-negotiated prices and self-pay cash prices (the discounted prices for patients paying without insurance) for the 10 drugs with the highest 2019 Medicare Part B expen- ditures (eTable 2 in the Supplement).2 We evaluated median prices relative to the Medicare payment limit to enable com- parisons of hospital markups across drugs. We used Stata, release 16.1 (StataCorp LLC) and Excel, version 16.16.27 (Microsoft) for the study analysis, which was performed from July 1 to September 15, 2021. Institutional review board approval was not required because we used only publicly available data on prices of prescription drugs and did not use patient information. Results | Seventeen of the 20 hospitals (85%) posted files aimed at complying with the new transparency rule. Eleven (55%) included payer-specific pharmaceutical prices. Of the hospitals that released pharmaceutical data, 82% (and 85% of hospitals overall) were 340B entities, which entitled them to acquire drugs from manufacturers at prices below the ASP.3 Prices varied between and within hospitals (Figure). Me- dian negotiated prices for the 10 drugs in the study sample ranged from 169% (IQR, 137%-264%) of the Medicare pay- ment limit at Rush University Medical Center to 344% (IQR, 307- 368%) at the Mayo Clinic Hospital–Arizona, and median self-pay cash prices ranged from 149% (IQR, 124%-203%) of the Medicare payment limit at Rush to 306% at Brigham and Wo- men’s Hospital (IQR, 273%-327%) and Massachusetts General Hospital (IQR, 283%-327%; Table). There was also substantial variation by drug, with the lowest median negotiated prices relative to the Medicare payment limit observed for abata- jamainternalmedicine.com (Reprinted) JAMA Internal Medicine January 2022 Volume 182, Number 1 83 © 2021 American Medical Association. All rights reserved. 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