Exploring COVID-19 census burdens by US hospital characteristics: Implications of quality reporting at rural and critical access hospitals.

PURPOSE: By assessing longitudinal associations between COVID-19 census burdens and hospital characteristics, such as bed size and critical access status, we can explore whether pandemic-era hospital quality benchmarking requires risk-adjustment or stratification for hospital-level characteristics. METHODS: We used hospital-level data from the US Department of Health and Human Services including weekly total hospital and COVID-19 censuses from August 2020 to August 2023 and the 2021 American Hospital Association survey. We calculated weekly percentages of total adult hospital beds containing COVID-19 patients. We then calculated the number of weeks each hospital spent at Extreme (≥20% of beds occupied by COVID-19 patients), High (10%-19%), Moderate (5%-9%), and Low (<5%) COVID-19 stress. We assessed longitudinal hospital-level COVID-19 stress, stratified by 15 hospital characteristics including joint commission accreditation, bed size, teaching status, critical access hospital status, and core-based statistical area (CBSA) rurality. FINDINGS: Among n = 2582 US hospitals, the median(IQR) weekly percentage of hospital capacity occupied by COVID-19 patients was 6.7%(3.6%-13.0%). 80,268/213,383 (38%) hospital-weeks experienced Low COVID-19 census stress, 28% Moderate stress, 22% High stress, and 12% Extreme stress. COVID-19 census burdens were similar across most hospital characteristics, but were significantly greater for critical access hospitals. CONCLUSIONS: US hospitals experienced similar COVID-19 census burdens across multiple institutional characteristics. Evidence-based inclusion of pandemic-era outcomes in hospital quality reporting may not require significant hospital-level risk-adjustment or stratification, with the exception of rural or critical access hospitals, which experienced differentially greater COVID-19 census burdens and may merit hospital-level risk-adjustment considerations.

Robotic-assisted hysterectomy for benign gynecologic disease in the United States: in-hospital use of opioid and non-opioid analgesics.

To compare the in-hospital opioid and non-opioid analgesic use among women who underwent robotic-assisted hysterectomy (RH) vs. open (OH), vaginal (VH), or laparoscopic hysterectomy (LH). Records of women in the United States who underwent hysterectomy for benign gynecologic disease were extracted from the Premier Healthcare Database (2013-2019). Propensity score methods were used to create three 1:1 matched cohorts stratified in inpatients [RH vs. OH (N = 16,821 pairs), RH vs. VH (N = 6149), RH vs. LH (N = 11,250)] and outpatients [RH vs. OH (N = 3139), RH vs. VH (N = 29,954), RH vs. LH (N = 85,040)]. Opioid doses were converted to morphine milligram equivalents (MME). Within matched cohorts, opioid and non-opioid analgesic use was compared. On the day of surgery, the percentage of patients who received opioids differed only for outpatients who underwent RH vs. LH or VH (maximum difference = 1%; p < 0.001). RH was associated with lower total doses of opioids in all matched cohorts (each p < 0.001), with the largest difference observed between RH and OH: median (IQR) of 47.5 (25.0-90.0) vs. 82.5 (36.0-137.0) MME among inpatients and 39.3 (19.5-66.0) vs. 60.0 (35.0-113.3) among outpatients. After the day of surgery, fewer inpatients who underwent RH received opioids vs. OH (78.7 vs. 87.5%; p < 0.001) or LH (78.6 vs. 80.6%; p < 0.001). The median MME was lower for RH (15.0; 7.5-33.5) versus OH (22.5; 15.0-55.0; p < 0.001). Minor differences were observed for non-opioid analgesics. RH was associated with lower in-hospital opioid use than OH, whereas the same magnitude of difference was not observed for RH vs. LH or VH.

Quality corner: Safely using cephalosporins in almost all patients with penicillin allergies: Mini-review and suggested protocol to improve efficacy and surgical outcomes.

Surgical site infections (SSI) are one of the most common gynecologic oncology postoperative complications and they have a significant deleterious impact on the healthcare system and in patients' outcomes. Cefazolin is the recommended antibiotic in women undergoing gynecologic surgical procedures that require that require prophylaxis. However, 10-20% of patients may report a penicillin allergy which can result in administration of a less effective antibiotic. This quality review evaluated the literature around this common perioperative issue and demonstrated that healthcare teams should consider the implementation of a protocol to safely use cefazolin in most patients with a penicillin allergy. Overall, literature shows this is a safe adjustment and would improve antimicrobial stewardship, decrease SSI rates, avoid acute kidney injury, and increase cost savings.

Impact of pharmacogenomic profiles on post-surgical pain following laparotomy for gynecologic pathology.

OBJECTIVES: The aim of this prospective study was to compare perioperative opioid use in women by status of CYP2D6, a highly polymorphic pharmacogene relevant to opioid metabolism. METHODS: Patients undergoing laparotomy were prospectively recruited and provided a preoperative saliva swab for a pharmacogenomic (PGx) gene panel. Postoperative opioid usage and pain scores were evaluated via chart review and a phone survey. Pharmacogenes known to be relevant to opioid metabolism were genotyped, and opioid metabolizing activity predicted by CYP2D6 genotyping. Patient and procedural factors were compared using Fisher's exact and Kruskal-Wallis tests. RESULTS: The 96 enrolled patients were classified as ultra-rapid (N = 3, 3%), normal (58, 60%), intermediate (27, 28%), and poor (8, 8%) opioid metabolizers. There was no difference in surgical complexity across CYP2D6 categories (p = 0.61). Morphine Milligram Equivalents (MME) consumed during the first 24 h after peri-operative suite exit were significantly different between groups: ultrarapid metabolizers had the highest median MME (75, IQR 45-88) compared to the other three groups (normal metabolizers 23 [8-45], intermediate metabolizers 48 [20-63], poor metabolizers 31 [12-53], p = 0.03). Opioid requirements were clinically greater in ultrarapid metabolizers during the second 24 h and last 24 h but were statistically similar (p = 0.07). There was no difference in MME prescribed at discharge (p = 0.22) or patient satisfaction with pain control (p = 0.64) between groups. CONCLUSIONS: A positive association existed between increased CYP2D6 activity and in-hospital opioid requirements, especially in the first 24 h after surgery. This provides important information to further individualize opioid prescriptions for patients undergoing laparotomy for gynecologic pathology.

An SGO commentary: U.S. News and World Report gynecologic oncology procedural ratings-Do they reflect high-quality care?

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Missed opportunities in hospital quality measurement during the COVID-19 pandemic: a retrospective investigation of US hospitals' CMS Star Ratings and 30-day mortality during the early pandemic.

OBJECTIVES: In the USA and UK, pandemic-era outcome data have been excluded from hospital rankings and pay-for-performance programmes. We assessed the relationship between US hospitals' pre-pandemic Centers for Medicare and Medicaid Services (CMS) Overall Hospital Star ratings and early pandemic 30-day mortality among both patients with COVID and non-COVID to understand whether pre-existing structures, processes and outcomes related to quality enabled greater pandemic resiliency. DESIGN AND DATA SOURCE: A retrospective, claim-based data study using the 100% Inpatient Standard Analytic File and Medicare Beneficiary Summary File including all US Medicare Fee-for-Service inpatient encounters from 1 April 2020 to 30 November 2020 linked with the CMS Hospital Star Ratings using six-digit CMS provider IDs. OUTCOME MEASURE: The outcome was risk-adjusted 30-day mortality. We used multivariate logistic regression adjusting for age, sex, Elixhauser mortality index, US Census Region, month, hospital-specific January 2020 CMS Star rating (1-5 stars), COVID diagnosis (U07.1) and COVID diagnosis×CMS Star Rating interaction. RESULTS: We included 4 473 390 Medicare encounters from 2533 hospitals, with 92 896 (28.2%) mortalities among COVID-19 encounters and 387 029 (9.3%) mortalities among non-COVID encounters. There was significantly greater odds of mortality as CMS Star Ratings decreased, with 18% (95% CI 15% to 22%; p<0.0001), 33% (95% CI 30% to 37%; p<0.0001), 38% (95% CI 34% to 42%; p<0.0001) and 60% (95% CI 55% to 66%; p<0.0001), greater odds of COVID mortality comparing 4-star, 3-star, 2-star and 1-star hospitals (respectively) to 5-star hospitals. Among non-COVID encounters, there were 17% (95% CI 16% to 19%; p<0.0001), 24% (95% CI 23% to 26%; p<0.0001), 32% (95% CI 30% to 33%; p<0.0001) and 40% (95% CI 38% to 42%; p<0.0001) greater odds of mortality at 4-star, 3-star, 2-star and 1-star hospitals (respectively) as compared with 5-star hospitals. CONCLUSION: Our results support a need to further understand how quality outcomes were maintained during the pandemic. Valuable insights can be gained by including the reporting of risk-adjusted pandemic era hospital quality outcomes for high and low performing hospitals.

Prognostic stratification of endometrial cancers with high microsatellite instability or no specific molecular profile.

Objective: To identify high-risk disease in clinicopathologic low-risk endometrial cancer (EC) with high microsatellite instability (MSI-H) or no specific molecular profile (NSMP) and therapeutic insensitivity in clinicopathologic high-risk MSI-H/NSMP EC. Methods: We searched The Cancer Genome Atlas for DNA sequencing, RNA expression, and surveillance data regarding MSI-H/NSMP EC. We used a molecular classification system of E2F1 and CCNA2 expression and sequence variations in POLE, PPP2R1A, or FBXW7 (ECPPF) to prognostically stratify MSI-H/NSMP ECs. Clinical outcomes were annotated after integrating ECPPF and sequence variations in homologous recombination (HR) genes. Results: Data were available for 239 patients with EC, which included 58 MSI-H and 89 NSMP cases. ECPPF effectively stratified MSI-H/NSMP EC into distinct molecular groups with prognostic implications: molecular low risk (MLR), with low CCNA2 and E2F1 expression, and molecular high risk (MHR), with high CCNA2 and E2F1 expression and/or PPP2R1A and/or FBXW7 variants. The 3-year disease-free survival (DFS) rate was 43.8% in the MHR group with clinicopathologic low-risk indicators and 93.9% in the MLR group (P<.001). In the MHR group, wild-type HR genes were present in 28% of cases but in 81% of documented recurrences. The 3-year DFS rate in patients with MSI-H/NSMP EC with clinicopathologic high-risk indicators was significantly higher in the MLR (94.1%) and MHR/HR variant gene (88.9%) groups than in the MHR/HR wild-type gene group (50.3%, P<.001). Conclusion: ECPPF may resolve prognostic challenges for MSI-H/NSMP EC by identifying occult high-risk disease in EC with clinicopathologic low-risk indicators and therapeutic insensitivity in EC with clinicopathologic high-risk indicators.

Hospital quality reporting in the pandemic era: to what extent did hospitals' COVID-19 census burdens impact 30-day mortality among non-COVID Medicare beneficiaries?

OBJECTIVES: Highly visible hospital quality reporting stakeholders in the USA such as the US News & World Report (USNWR) and the Centers for Medicare & Medicaid Services (CMS) play an important health systems role via their transparent public reporting of hospital outcomes and performance. However, during the pandemic, many such quality measurement stakeholders and pay-for-performance programmes in the USA and Europe have eschewed the traditional risk adjustment paradigm, instead choosing to pre-emptively exclude months or years of pandemic era performance data due largely to hospitals' perceived COVID-19 burdens. These data exclusions may lead patients to draw misleading conclusions about where to seek care, while also masking genuine improvements or deteriorations in hospital quality that may have occurred during the pandemic. Here, we assessed to what extent hospitals' COVID-19 burdens (proportion of hospitalised patients with COVID-19) were associated with their non-COVID 30-day mortality rates from March through November 2020 to inform whether inclusion of pandemic-era data may still be appropriate. DESIGN: This was a retrospective cohort study using the 100% CMS Inpatient Standard Analytic File and Master Beneficiary Summary File to include all US Medicare inpatient encounters with admission dates from 1 April 2020 through 30 November 2020, excluding COVID-19 encounters. Using linear regression, we modelled the association between hospitals' COVID-19 proportions and observed/expected (O/E) ratios, testing whether the relationship was non-linear. We calculated alternative hospital O/E ratios after selective pandemic data exclusions mirroring the USNWR data exclusion methodology. SETTING AND PARTICIPANTS: We analysed 4 182 226 consecutive Medicare inpatient encounters from across 2601 US hospitals. RESULTS: The association between hospital COVID-19 proportion and non-COVID O/E 30-day mortality was statistically significant (p<0.0001), but weakly correlated (r2=0.06). The median (IQR) pairwise relative difference in hospital O/E ratios comparing the alternative analysis with the original analysis was +3.7% (-2.5%, +6.7%), with 1908/2571 (74.2%) of hospitals having relative differences within ±10%. CONCLUSIONS: For non-COVID patient outcomes such as mortality, evidence-based inclusion of pandemic-era data is methodologically plausible and must be explored rather than exclusion of months or years of relevant patient outcomes data.

A Multisite Assessment of Inpatient Safety Event Rates During the Coronavirus Disease 2019 Pandemic.

To date, there has been a notable lack of peer-reviewed or publicly available data documenting rates of hospital quality outcomes and patient safety events during the coronavirus disease 2019 pandemic era. The dearth of evidence is perhaps related to the US health care system triaging resources toward patient care and away from reporting and research and also reflects that data used in publicly reported hospital quality rankings and ratings typically lag 2-5 years. At our institution, a learning health system assessment is underway to evaluate how patient safety was affected by the pandemic. Here we share and discuss early findings, noting the limitations of self-reported safety event reporting, and suggest the need for further widespread investigations at other US hospitals. During the 2-year study period from January 1, 2020, through December 31, 2021 across 3 large US academic medical centers at our institution, we documented an overall rate of 25.8 safety events per 1000 inpatient days. The rate of events meeting "harm" criteria was 12.4 per 1000 inpatient days, the rate of nonharm events was 11.1 per 1000 inpatient days, and the fall rate was 2.3 per 1000 inpatient days. This descriptive exploratory analysis suggests that patient safety event rates at our institution did not increase over the course of the pandemic. However, increasing health care worker absences were nonlinearly and strongly associated with patient safety event rates, which raises questions regarding the mechanisms by which patient safety event rates may be affected by staff absences during pandemic peaks.

A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance Reporting.

Objective: To develop a simple, interpretable value metric (VM) to assess the value of care of hospitals for specific procedures or conditions by operationalizing the value equation: Value = Quality/Cost. Patients and Methods: The present study was conducted on a retrospective cohort from 2015 to 2018 drawn from the 100% US sample of Medicare inpatient claims. The final cohort comprised 637,341 consecutive inpatient encounters with a cancer-related Medicare Severity-Diagnosis Related Grouping and 13,307 consecutive inpatient encounters with the International Classification of Diseases, Ninth Revision or International Classification of Diseases, Tenth Revision procedure code for partial or total gastrectomy. Claims-based demographic and clinical variables were used for risk adjustment, including age, sex, year, dual eligibility, reason for Medicare entitlement, and binary indicators for each of the Elixhauser comorbidities used in the Elixhauser mortality index. Risk-adjusted 30-day mortality and risk-adjusted encounter-specific costs were combined to form the VM, which was calculated as follows: number needed to treat = 1/(Mortalitynational - Mortalityhospital), and VM = number needed to treat × risk-adjusted cost per encounter. Results: Among hospitals with better-than-average 30-day cancer mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient cancer encounter ranged from $71,000 (best value) to $1.4 billion (worst value), with a median value of $543,000. Among hospitals with better-than-average 30-day gastrectomy mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient gastrectomy encounter ranged from $710,000 (best value) to $95 million (worst value), with a median value of $1.8 million. Conclusion: This simple VM may have utility for interpretable reporting of hospitals' value of care for specific conditions or procedures. We found substantial inter- and intrahospital variation in value when defined as the costs of preventing 1 excess cancer or gastrectomy mortality compared with the national average, implying that hospitals with similar quality of care may differ widely in the value of that care.

ECPPF (E2F1, CCNA2, POLE, PPP2R1A, FBXW7) stratification: Profiling high-risk subtypes of histomorphologically low-risk and treatment-insensitive endometrioid endometrial cancer.

In endometrial cancer, occult high-risk subtypes (rooted in histomorphologically low-risk disease) with insensitivity to adjuvant therapies impede improvements in therapeutic efficacy. Therefore, we aimed to assess the ability of molecular high-risk (MHR) and low-risk (MLR) ECPPF (E2F1, CCNA2, POLE, PPP2R1A, FBXW7) stratification to profile recurrence in early, low-risk endometrioid endometrial cancer (EEC) and insensitivity to platinum-based chemotherapy or radiotherapy (or both) in high-risk EEC. Using The Cancer Genome Atlas endometrial cancer database, we identified 192 EEC cases with available DNA sequencing and RNA expression data. Molecular parameters were integrated with clinicopathologic risk factors and adverse surveillance events. MHR was defined as high (-H) CCNA2 or E2F1 log2 expression (≥2.75), PPP2R1A mutations (-mu), or FBXW7mu; MLR was defined as low (-L) CCNA2 and E2F1 log2 expression (<2.75). We assessed 164 cases, plus another 28 with POLEmu for favorable-outcomes comparisons. MHR and MLR had significantly different progression-free survival (PFS) rates (P < .001), independent of traditional risk factors (eg, TP53mu), except for stage IV disease. PFS of CCNA2-L/E2F1-L paralleled that of POLEmu. ECPPF status stratified responses to adjuvant therapy in stage III-IV EEC (P < .01) and profiled stage I, grade 1-2 cases with risk of recurrence (P < .001). MHR was associated with CTNNB1mu-linked treatment failures (P < .001). Expression of homologous recombination repair (HR) and cell cycle genes was significantly elevated in CCNA2-H/E2F1-H compared with CCNA2-L/E2F1-L (P<1.0E-10), suggesting that HR deficiencies may underlie the favorable PFS in MLR. HRmu were detected in 20.7%. No treatment failures were observed in high-grade or advanced EEC with HRmu (P = .02). Favorable PFS in clinically high-risk EEC was associated with HRmu and MLR ECPPF (P < .001). In summary, MLR ECPPF and HRmu were associated with therapeutic efficacy in EEC. MHR ECPPF was associated with low-risk, early-stage recurrences and insensitivity to adjuvant therapies.

A Learning Health System Approach to Hospital Quality Performance Benchmarking: The Composite Hospital Quality Index.

US hospital quality rankings and ratings use disparate methodologies and are weakly correlated. This causes confusion for patients and hospital quality staff. At the authors' institution, a Composite Hospital Quality Index (CHQI) was developed to combine hospital quality ratings. This approach is described and a calculator is shared here for other health systems to explore their performance. Among the US News and World Report Top 50 Hospitals, hospital-specific numeric summary scores were aggregated from the 2021 Centers for Medicare and Medicaid Services (CMS) Hospital Overall Star Rating, the Spring 2021 Leapfrog Safety Grade, and the April 2021 Hospital Consumer Assessment of Healthcare Providers and Systems Star Rating. The CHQI is the hospital-specific sum of the national percentile-rankings across these 3 ratings. In this example, mean (SD) percentiles were as follows: CMS Stars 74 (19), Hospital Consumer Assessment of Healthcare Providers and Systems 63 (19), Leapfrog 65 (24), with mean (SD) CHQI of 202 (49). The CHQI is used at the authors' institution to identify improvement opportunities and ensure that high-quality care is delivered across the health system.

Effect of hospital-at-home vs. traditional brick-and-mortar hospital care in acutely ill adults: study protocol for a pragmatic randomized controlled trial.

BACKGROUND: Delivering acute hospital care to patients at home might reduce costs and improve patient experience. Mayo Clinic's Advanced Care at Home (ACH) program is a novel virtual hybrid model of "Hospital at Home." This pragmatic randomized controlled non-inferiority trial aims to compare two acute care delivery models: ACH vs. traditional brick-and-mortar hospital care in acutely ill patients. METHODS: We aim to enroll 360 acutely ill adult patients (≥18 years) who are admitted to three hospitals in Arizona, Florida, and Wisconsin, two of which are academic medical centers and one is a community-based practice. The eligibility criteria will follow what is used in routine practice determined by local clinical teams, including clinical stability, social stability, health insurance plans, and zip codes. Patients will be randomized 1:1 to ACH or traditional inpatient care, stratified by site. The primary outcome is a composite outcome of all-cause mortality and 30-day readmission. Secondary outcomes include individual outcomes in the composite endpoint, fall with injury, medication errors, emergency room visit, transfer to intensive care unit (ICU), cost, the number of days alive out of hospital, and patient-reported quality of life. A mixed-methods study will be conducted with patients, clinicians, and other staff to investigate their experience. DISCUSSION: The pragmatic trial will examine a novel virtual hybrid model for delivering high-acuity medical care at home. The findings will inform patient selection and future large-scale implementation. TRIAL REGISTRATION: ClinicalTrials.gov NCT05212077. Registered on 27 January 2022.

The association of acute COVID-19 infection with Patient Safety Indicator-12 events in a multisite healthcare system.

BACKGROUND: Patient Safety Indicator (PSI)-12, a hospital quality measure designed by Agency for Healthcare Research and Quality (AHRQ) to capture potentially preventable adverse events, captures perioperative venous thromboembolism (VTE). It is unclear how COVID-19 has affected PSI-12 performance. OBJECTIVE: We sought to compare the cumulative incidence of PSI-12 in patients with and without acute COVID-19 infection. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective cohort study including PSI-12-eligible events at three Mayo Clinic medical centers (4/1/2020-10/5/2021). EXPOSURE, MAIN OUTCOMES, AND MEASURES: We compared the unadjusted rate and adjusted risk ratio (aRR) for PSI-12 events among patients with and without COVID-19 infection using Fisher's exact χ2  test and the AHRQ risk-adjustment software, respectively. We summarized the clinical outcomes of COVID-19 patients with a PSI-12 event. RESULTS: Our cohort included 50,400 consecutive hospitalizations. Rates of PSI-12 events were significantly higher among patients with acute COVID-19 infection (8/257 [3.11%; 95% confidence interval {CI}, 1.35%-6.04%]) compared to patients without COVID-19 (210/50,143 [0.42%; 95% CI, 0.36%-0.48%]) with a PSI-12 event during the encounter (p < .001). The risk-adjusted rate of PSI-12 was significantly higher in patients with acute COVID-19 infection (1.50% vs. 0.38%; aRR, 3.90; 95% CI, 2.12-7.17; p < .001). All COVID-19 patients with PSI-12 events had severe disease and 4 died. The most common procedure was tracheostomy (75%); the mean (SD) days from surgical procedure to VTE were 0.12 (7.32) days. CONCLUSION: Patients with acute COVID-19 infection are at higher risk for PSI-12. The present definition of PSI-12 does not account for COVID-19. This may impact hospitals' quality performance if COVID-19 infection is not accounted for by exclusion or risk adjustment.

Avoiding Retained Surgical Items at an Academic Medical Center: Sustainability of a Surgical Quality Improvement Project.

Unintentionally retained surgical items (RSIs) are a serious complication representing a surgical "Never" event. The authors previously reported the process and significant improvement over a 3-year multiphased quality improvement RSI reduction effort that included sponge-counting technology. Herein, they report the sustainability of that effort over the decade following the formal quality improvement project conclusion. This retrospective analysis includes descriptive and qualitative data collected during RSI event root cause analysis. Between January 2009 and December 2019, 640 889 operations were performed with 24 RSIs reported. The resulting RSI rate of 1 per 26 704 operations represent a 486% performance improvement compared to the preintervention rate of 1 per 5500 operations. The interval, in days, between RSI events increased to 160 from 26 during the preintervention phase. Cotton sponges were the most retained RSI despite the use of sponge-counting technology. A significant and sustained reduction in RSI is possible after designing a sustainable comprehensive multidisciplinary effort.

Quantifying the Importance of COVID-19 Vaccination to Our Future Outlook.

Predictive models have played a critical role in local, national, and international response to the COVID-19 pandemic. In the United States, health care systems and governmental agencies have relied on several models, such as the Institute for Health Metrics and Evaluation, Youyang Gu (YYG), Massachusetts Institute of Technology, and Centers for Disease Control and Prevention ensemble, to predict short- and long-term trends in disease activity. The Mayo Clinic Bayesian SIR model, recently made publicly available, has informed Mayo Clinic practice leadership at all sites across the United States and has been shared with Minnesota governmental leadership to help inform critical decisions during the past year. One key to the accuracy of the Mayo Clinic model is its ability to adapt to the constantly changing dynamics of the pandemic and uncertainties of human behavior, such as changes in the rate of contact among the population over time and by geographic location and now new virus variants. The Mayo Clinic model can also be used to forecast COVID-19 trends in different hypothetical worlds in which no vaccine is available, vaccinations are no longer being accepted from this point forward, and 75% of the population is already vaccinated. Surveys indicate that half of American adults are hesitant to receive a COVID-19 vaccine, and lack of understanding of the benefits of vaccination is an important barrier to use. The focus of this paper is to illustrate the stark contrast between these 3 scenarios and to demonstrate, mathematically, the benefit of high vaccine uptake on the future course of the pandemic.