We analyzed the diagnostic yield of repeat urine cultures in a retrospective study of adult inpatients. Most urine cultures repeated at less than 6 days provided redundant information. This was true whether the index culture was positive or negative, and whether the threshold for positivity was 10,000 or 100,000 CFU/mL.

Background: Duplicative laboratory testing is prevalent in health care. Prior research surrounding repeat urine cultures showed that when a negative index culture is repeated within 48 hours, less than 5% of repeat urine cultures show a new bacteriuria. We evaluated the diagnostic yield of repeating urine cultures at longer time intervals, and of repeating a positive urine culture. Methods: We conducted a retrospective study of adult inpatients at Stanford Healthcare who had more than one urine culture collected during hospitalization between January 2023 and February 2024. We included urine cultures that were collected with or without urinary catheters; nephrostomy tubes were excluded. Urine cultures were classified as index or repeat. We analyzed the diagnostic yield of the repeat urine culture, defined as the percent of repeat urine cultures that detected a new bacteriuria not detected in the index culture. Bacteriuria was defined as growth of a bacterial species in quantities >100,000 CFU/mL. A negative urine culture was defined as one that did not have bacteriuria meeting this threshold. Sensitivity analyses used a threshold of 10,000 CFU/mL as the threshold for significant bacteriuria. Results: Overall, 6,955 urine cultures were performed from 6,058 patients. Of these, 864 (12%) urine cultures were repeats. Of the 864 index cultures, 75% were negative. The median time to repeat urine culture was 4 days. When negative index cultures were repeated at 0-3 days, the diagnostic yield for detecting a new bacteriuria was only 9%. Diagnostic yield at 3-6 days was 10%, not significantly higher compared to 0-3 days (p=0.620). Diagnostic yield at 6-9 days was 19%; this increase was significant compared to the 0-3 days group (p=0.014). When positive index cultures were repeated at 0-3 days, the diagnostic yield for detecting a new bacteriuria was only 8%. Diagnostic yield at 3-6 days was also 8%. Yield increased significantly to 15% at 6-9 days from index culture (p=0.013). When the threshold for significant bacteriuria was adjusted to 10,000 CFU/mL, more bacteriuria was detected overall, but primarily of gram-positive organisms. Whether the threshold for significant bacteriuria was 100,000 CFU/mL or 10,000 CFU/mL, the rate of detection of new gram-negative bacteriuria was similar, and remained less than 10% until 6-9 days from index culture (Figure 1). Conclusions: Among inpatients, most urine cultures repeated at less than 6 days provide redundant information. This unnecessary retesting offers an opportunity for diagnostic stewardship.

Abstract Background Central line-associated bloodstream infection (CLABSI) remains a key quality measure. However, the CLABSI surveillance definition attributes bloodstream infections in patients with central venous access devices to the central line if no other sources are found, potentially overestimating true line-related cases. Incorporating non-culture based microbiologic testing, such as next-generation sequencing, into the CLABSI surveillance definition may further skew these estimates. We aimed to review the organisms identified in 16S rRNA sequencing tests from blood samples to determine if they were typically associated with CLABSI. Methods We retrieved all 16S rRNA sequencing orders from Stanford Hospitals & Clinics from May 2015– May 2024. We identified orders obtained from blood specimens and categorized those patients with and without central venous access devices. We compared the identified organisms with those included in the NSHN CLABSI definition (https://www.cdc.gov/nhsn/pdfs/pscmanual/17pscnosinfdef_current.pdf). Results Of the 3,830 16S rRNA tests ordered, 225 were from blood specimens. Among these, 40% (65/225) had a central venous access device at some point during admission. Eight tests were positive: two from patients with a device during collection, identifying Bartonella quintana and Ureaplasma urealyticum—both not excluded from the NHSN definition. Other positives included two cases of Borrelia hermsii, Paracoccus spp., Leptospira spp., Legionella spp., and coagulase-negative Staphylococcus, with only the latter typically associated with central venous access device infection. Only organisms from the genera Blastomyces, Histoplasma, Coccidioides, Paracoccidioides, Cryptococcus, and Pneumocystis are excluded from the NHSN CLABSI definition. Conclusion The increasing use of next-generation sequencing tests, such as 16S rRNA targeted sequencing, introduces unique scenarios where non-culturable organisms can be detected in blood specimens. There may be some risk of unfairly penalizing institutions for reporting organisms not associated with CLABSI. The list of organisms included in the NHSN CLABSI surveillance definition should be continuously updated to reflect the adoption of new non-culture-based testing methods. Disclosures All Authors: No reported disclosures

Abstract Background Preference lists in electronic health records are commonly used to streamline ordering processes, including antibiotic orders. In July 2023, we revised our institution's primary care preference list to align with institutional guidelines for the management of skin and soft tissue infections (SSTI) and pneumonia (Figure 1). Here we evaluate the impact of this intervention on antibiotic prescribing practices. Methods We included all adult telemedicine and office visits associated with antibiotic orders from 2/2023 to 2/2024 at 8 academic primary clinics. We used International Classification of Diseases, 10th revision (ICD10) data to identify encounters for SSTIs and pneumonia (Table 1 ). We defined “pre-intervention” as 2/1 – 7/31/2023 and “post-intervention” as 8/1/2023– 2/28/2024. We extracted encounter date, location, order source, antibiotic selection, and duration. We defined guideline adherence as 1st line antibiotic selection and 5-day duration (Figure 1). There were no education or dissemination efforts to providers. This was deemed a non-human subjects research quality improvement project. Results We included 349 total (165 pre, 184 post) encounters for SSTI (263) and pneumonia (86). 102 (29%) were telemedicine (50 pre, 52 post). Of the 349 encounters, 73 % of antibiotic orders were from the preference list (136 pre; 117 post). Guideline concordant antibiotic selection improved in the post-intervention group for pneumonia (8% pre, 44% post) and SSTIs (47% pre, 58% post), but only for orders sourced from the preference list (Table 2, Graphs 1-2). There was also improvement in guideline concordant 5-day durations with preference list orders post-intervention for pneumonia (55% pre, 78% post) and SSTI (20% pre, 50% post) (Table 2, Graphs 1-2). Antibiotic orders not using the preference list for these syndromes showed no improvement during this time. Conclusion We found that a simple revision of the primary care order preference list led to improved guideline concordant antibiotic prescribing for SSTI and pneumonia. For common syndromes in which antibiotic selection is typically made empirically in clinic, like SSTIs and pneumonia, pre-selected durations and highlighted first-line selections for antibiotic orders can improve adherence to guideline recommendations. Disclosures All Authors: No reported disclosures

Introduction: Social determinants of health can impact healthcare-associated infections. Hospital-onset bacteremia (HOB) may lead to poor outcomes, increased length of stay, and increased cost of care. We explored the association of social determinants of health and HOB. Methods: We retrieved blood culture data at Stanford Health Care from May 2019 to October 2023. We identified blood cultures ordered ≥4 days of admission. To evaluate the association between social determinants of health and HOB, we employed an unsupervised machine learning approach (K-Means clustering) to discern patterns in HOB rates based on the Social Vulnerability Index (SVI). The SVI indicates the relative vulnerability of every U.S. Census tract. It ranks the tracts on 16 measures of vulnerability across 4 themes: socioeconomic factors, household characteristics, racial and ethnic minority status, and housing/transportation aspects. The number of clusters was determined using the Elbow Method (Figure 1). Results: Out of 209,947 blood cultures from 23,938 unique patients with a California address, we identified 81,653 blood cultures collected after 4 days (40%). The K-Means clustering algorithm identified 3 distinct clusters within the Californian census tracts, suggesting heterogeneity in the relationship between SVI and HOB (Figure 2). Cluster 1 had a higher SVI (median 0.73, range 0.46 – 0.99), with logistic regression indicating a positive SVI-HOB association (OR 4.84, 95% CI 4.02 – 4.81, p <.001). Cluster 2, had a median SVI of 0.29 (range 0.0009 – 0.78), also showed a positive association between SVI and HOB (OR 1.67, 95% CI 1.4 – 1.89, p <.001), aligning with trends of higher infection risks in more vulnerable groups. In contrast, Cluster 3 had a median SVI of 0.22 (range 0.002 –0.84). In this cluster, the SVI showed a negative association with HOB (OR 0.24, 95% CI 0.18 – 0.31, p <.001). Cluster 3 was the cluster with the least number of subjects (15,000, versus 21,761 for Cluster 1 and 29,762 for Cluster 2). Most subjects in Cluster 3 resided in Santa Clara County, whereas those in Clusters 1 and 2 were spread across Santa Clara, San Mateo, Alameda, Merced, and Sacramento Counties (Figure 3). Conclusions: Advanced techniques can be used to explore the complex interplay between social determinants of health and healthcare-associated infections and could guide the development of community-specific strategies to improve outcomes.

Introduction: Many central line-associated bloodstream infections are identified in patients nearing the end of life. Stanford Health Care recently introduced the General Inpatient Hospice program. This program offers inpatient hospice care for patients who, due to uncontrolled symptoms, cannot be discharged to a hospice facility or receive home hospice care. We investigated whether this program would impact blood cultures practices near the time of death. Methods: We performed a retrospective cohort study at Stanford Health Care using records of blood culture events from May 2019 to October 2023. We defined a blood culture near-death as those collected within 2 days before the date of death. We performed an interrupted time series linear regression before and after the implementation of the General Inpatient Hospice program on July 1, 2022 to assess blood culture intensity near-death. Blood culture intensity was defined as the proportion of cultures collected near-death in relation to the total number of blood cultures. Additionally, we calculated blood culture positivity rate, which was defined as the proportion of positive blood cultures among all those collected during our study period. Results: Out of 220,269 blood cultures from 24,955 unique patients, a total of 6,147 cultures (9%) were obtained near the time of death. Among these subjects, the median age was 65 years (range 20–102), with 43% identifying as being of White race-ethnicity and 57% as male. Of these cultures, 3044 were positive (49.5%), with Escherichia coli (618, 24%), Klebsiella pneumoniae (341, 13%), and Staphylococcus aureus (166, 10%) being the most common organisms. After the implementation of the General Inpatient Hospice program, the median enrollment was 12 patients (range 3–18) and the median mortality rate was 2.3% (range 2–3%). The blood culture intensity near death decreased by 0.81%, a change that was not statistically significant (95% CI -2.4% to 0.8%, p=.32; Figure 1). Subsequently, the blood culture intensity showed a non-significant increasing trend of 0.05% (95% CI -0.1% to 0.2%, p=0.53). The blood culture positivity rate near the time of death increased by 16% following the intervention, but this increase was not statistically significant (95% CI – 11.8% to 43.3%, p=.26; Figure 2), and it was followed by a non-significant downtrend of 1.9% (95% CI -3.9% to 1.4%, p=.36). Conclusion: We found no significant association between the implementation of an inpatient hospice program and blood culture practices near the time of death, likely due to low patient enrollment.

We used a strand-specific RT-qPCR to evaluate viral replication as a surrogate for infectiousness among 242 asymptomatic inpatients with a positive severe acute respiratory coronavirus virus 2 (SARS-CoV-2) admission test. Only 21 patients (9%) had detectable SARS-CoV-2 minus-strand RNA. Because most patients were found to be noninfectious, our findings support the suspension of asymptomatic admission testing.

Background: SARS-CoV-2 viral load decreases over time after illness onset. However, immunocompromised patients may take longer for viral load decrease or have a more erratic viral-load trajectory. We used strand-specific assay data from admitted patients to evaluate viral-load trajectories after illness onset. Methods: We reviewed records of hospitalized patients with a positive SARS-CoV-2 PCR and tested using the strand-specific SARS-CoV-2 PCR during July 2020–April 2022. At Stanford Healthcare, we use a 2-step reverse real-time polymerase chain reaction (rRT-PCR) assay specific to the minus strand of the SARS-CoV-2 envelope gene to assess infectivity. Restricting our analysis to each patient’s first strand-specific assay, we used logistic regression models to compare patients with single versus multiple assays. Among patients with multiple tests, we compared those who had an upward trajectory in cycle threshold (Ct) values (a surrogate of decreasing viral load) versus those who did not. We analyzed presence of symptoms, immunocompromised state, immunosuppression reason, and severe COVID-19 leading to ICU care in univariate and multivariate models that further adjust for additional covariates. Significant differences were assessed using logistic regression odds ratios and an α level of 0.05. Results: In total, 848 inpatients were included. Among them, 703 were tested only once and 145 were tested 2–6 times. The longest duration of minus-strand detection was 163 days. In univariate analyses, patients with a single minus-strand assay had lower odds of being symptomatic (OR, 0.55), of being immunocompromised (OR, 0.58), and of being admitted to the ICU with severe COVID-19 (OR, 0.49). In the multivariate analysis, being admitted to the ICU with severe COVID-19 was the only significant variable associated with having >1 test (OR, 2.44). Among patients who had multiple strand-specific SARS-CoV-2 assays, 119 had upward minus-strand trends of Ct values (as expected) and 26 did not. Being immunocompromised was associated with nonrising minus-strand CT values (OR, 33.3) when holding all other covariates in the model constant. Conclusions: Immunocompromised patients with COVID-19 tend to actively replicate for longer and have unexpected viral trajectories compared to immunocompetent patients. Among immunocompromised patients, suspension of transmission-based precautions may require a case-by-case evaluation.Disclosures: None

Severe acute respiratory coronavirus virus 2 (SARS-CoV-2) real-time reverse-transcription polymerase chain reaction (rRT-PCR) strand-specific assay can be used to identify active SARS-CoV-2 viral replication. We describe the characteristics of 337 hospitalized patients with at least 1 minus-strand SARS-CoV-2 assay performed >20 days after illness onset. This test is a novel tool to identify high-risk hospitalized patients with prolonged SARS-CoV-2 replication.

Background: Many hospitals have implemented admission SARS-CoV-2 testing to evaluate for the need for transmission-based precautions. However, a positive test in an asymptomatic patient may represent (1) active infection, signifying infectiousness; (2) false positivity; or (3) past infection with prolonged viral shedding. We used a strand-specific SARS-CoV-2 reverse real-time polymerase chain reaction (rRT-PCR) assay to assess infectivity among asymptomatic patients with a positive SARS-CoV-2 PCR admission test. Methods: We used a 2-step rRT-PCR specific to the minus strand of the SARS-CoV-2 envelope gene. We reviewed records of patients with a positive SARS-CoV-2 PCR who were also tested for the strand-specific SARS-CoV-2 PCR within 2 days of admission at Stanford Health Care during July 2020–April 2022. We restricted our analysis to each patient’s first test. We calculated the percentage of detectable minus strand-specific tests among asymptomatic patients over time and gathered descriptive statistics for age, sex, and immunocompromised state. Results: In total, 848 admitted patients had strand-specific SARS-CoV-2 assays performed. Of 532 patients with a strand-specific assay done within 2 days of admission, 242 (45%) were asymp tomatic. Among asymptomatic patients, the mean age was 56 years (range, 19–99), 133 (55%) were male, 50 (21%) had immunocompromising conditions, and 30 (12%) were admitted for a surgical procedure. In total, 21 (9%; range, 4%–25% per quarter) had detectable minus strand-specific assays (Fig. 1). Conclusions: Most asymptomatic patients tested for SARS-CoV-2 on admission were not infectious. Hospitals using SARS-CoV-2 PCR admission testing may need to re-evaluate the continued use of this practice. Fig. 1. Minus strand-specific SARS-CoV-2 assay percentage positivity per quarter among asymptomatic patients tested within 2 days of admission. The peak positivity in November 2021–January 2022 quarter coincided with the SARS-CoV-2 omicron variant surge in our county. Disclosure: None

Introduction The risk, cost, and adverse outcomes associated with packed red blood cell (RBC) transfusions in patients with cardiopulmonary failure requiring extracorporeal membrane oxygenation (ECMO) have raised concerns regarding the overutilization of RBC products. It is, therefore, necessary to establish optimal transfusion criteria and protocols for patients supported with ECMO. The goal of this study was to establish specific criteria for RBC transfusions in patients undergoing ECMO. Methods This was a retrospective cohort study conducted at Stanford University Hospital. Data on RBC utilization during the entire hospital stay were obtained, which included patients aged ≥18 years who received ECMO support between 1 January 2017, and 30 June 2020 ( n = 281). The primary outcome was in-hospital mortality. Results Hemoglobin (HGB) levels >10 g/dL before transfusion did not improve in-hospital survival. Therefore, we revised the HGB threshold to ≤10 g/dL to guide transfusion in patients undergoing ECMO. To validate this intervention, we prospectively compared the pre- and post-intervention cohorts for in-hospital mortality. Post-intervention analyses found 100% compliance for all eligible records and a decrease in the requirement for RBC transfusion by 1.2 units per patient without affecting the mortality. Conclusions As an institution-driven value-based approach to guide transfusion in patients undergoing ECMO, we lowered the threshold HGB level. Validation of this revised intervention demonstrated excellent compliance and reduced the need for RBC transfusion while maintaining the clinical outcome. Our findings can help reform value-based healthcare in this cohort while maintaining the outcome.

Abstract Background Indwelling urinary catheters (IUC) are reinserted in patients who should initially be managed with intermittent straight catheterization for urinary retention. We hypothesize patients who have an IUC reinserted within 24 hours will be at higher risk of catheter-associated urinary tract infections (CAUTI) within 7 days compared to patients who were straight catheterized or did not have an IUC reinserted. Methods A retrospective review of electronic health records (EHR) using Epic Systems (Verona, Wisconsin) was conducted for all inpatients at Stanford Hospital, Palo Alto, CA who had an IUC removed and a CAUTI defined by the National Healthcare Safety Network (NHSN) between January 1, 2020 to March 31, 2023. Patients with an IUC reinserted within 24 hours from initial removal of an IUC were compared to patients who had an IUC removed and did not have a reinsertion of an IUC within 24 hours. Relative risk of a CAUTI was the primary outcome metric. Results Between January 1, 2020 and March 31, 2023 there were 30,161 IUCs removed and 204 NHSN defined CAUTI identified within 7 days of removal that were included in the study. Patients who had an IUC reinserted within 24 hours had significant risk (RR: 7.96, p< 0.05) of having a CAUTI within 7 days post IUC removal compared to patients who did not have an IUC reinserted within 24 hours.Figure 1.Relative Risk of CAUTI with Indwelling Catheter Reinsertion Conclusion Reinsertion of IUCs in patients with urinary retention following IUC removal should be managed with intermitted straight catheterization or more conversative methods if possible. Patients who are re-catheterized with an IUC within 24 hours of removal are at significantly higher risk of developing a CAUTI within 7 days compared to patients who are straight catheterized or do not have a Foley catheter reinserted. Healthcare providers should use alternative methods of bladder management to improve patient outcomes. Disclosures All Authors: No reported disclosures

Artificial intelligence (AI), including computer-aided detection (CADe), could revolutionize endoscopy. The adenoma detection rate (ADR) is inversely associated with the risk of postcolonoscopy colorectal cancer.1 The first CADe device approved in the United States (GI Genius; Medtronic, Minneapolis, MN) significantly increased the ADR and adenomas per colonoscopy (APC)2,3 and decreased the adenoma miss rate4 in randomized trials.

Abstract Background Central line-associated bloodstream infections (CLABSI) are associated with increased morbidity, mortality, and healthcare costs. Many CLABSIs can be prevented using evidence-based care. To make this information more accessible and actionable, we developed interactive dashboards that translate data on CLABSI-related metrics and prevention efforts into visual formats that can be easily understood by healthcare professionals. Methods A multidisciplinary work group of data analysts, infectious diseases physicians, and infection preventionists determined the content and layout of the dashboards. A query was written to extract necessary data elements from the Electronic Medical Record and NHSN. Data was then exported and used to build the dashboards using Tableau® software. The dashboard can be filtered at the facility level or at the unit level. Results We present the dashboard of one general ward (Figure 1), one intensive care unit (ICU) (Figure 2), and one cardiovascular ICU (CVICU) (Figure 3). The central line standard utilization ratio (SUR) was higher for the CVICU ( >1.5), followed by the ICU (≈1), and the general ward (< 1). Blood culture intensity (number of blood cultures collected/patient-days) was less for the general ward (< 5%), variable for the ICU (8-14%), and persistently higher for the CVICU (11%). Compliance with daily chlorhexidine bathing was higher for both the CVICU (80%) and the ICU (75%) compared to the general ward (40-60%). The CLABSI rate per 1,000 central line-days has been downtrending for the CVICU and uptrending for the ICU. Besides lower compliance with daily chlorhexidine bathing, the examined ICU has also recently shown a higher proportion of long-term devices (40%), calculated as proportion of central lines ≥ 7 days/all central lines, compared to the CVICU (25%). Conclusion Dashboards should contain meaningful outcomes and standardized process metrics that are mapped to strategic goals and be timely to support prompt identification of deviations. Our CLABSI dashboards are effective tools for communicating and tracking performance data. Filtering at the unit level allows us to identify unique unit characteristics, or “fingerprints,” and recognize specific areas for improvement. This enables us to develop targeted interventions for each unit. Disclosures All Authors: No reported disclosures

Abstract Background Determining if a patient with SARS-CoV-2 remains infectious is an infection control challenge in healthcare settings; specially, among critically ill or profoundly immunosuppressed patients. We use an assay that detects minus-strand RNA as a surrogate for actively replicating SARS-CoV-2. We report positive strand-specific assays in relationship to time since admission and describe patients with a detectable strand-specific assay >20 days since admission. Methods We use a 2-step rRT-PCR specific to the minus strand of the SARS-CoV-2 envelope gene. The strand-specific assay is used to evaluate for infectivity in asymptomatic patients with a positive admission screening or pre-procedural test or if ongoing replication is suspected (critical illness or profound immunosuppression). We retrieved strand-specific test results for patients hospitalized at Stanford Healthcare during August 2020–March 2022. We describe clinical characteristics for patients with a detectable minus strand-specific test >20 days since admission. Results A total of 774 strand-specific tests were collected from 624 hospitalized patients. A total of 523 patients had only one test (84%) and 101 (16%) had ≥2 tests. The test positivity rate varied by time since admission: 19% in tests performed 0–5 days, 28% in 6–10 days, 22% in 11–20 days, and 41% in those >20 days since admission. Among 35 patients tested >20 days since admission, 13 (37%) had ≥1 detectable minus strand-specific test. Most were male (n=8, 62%) and mean age was 59. Of 13 patients with a detectable assay, seven (54%) had prolonged viral replication with persistent symptoms and detectable minus strand assays for >20 days from symptom onset. Of these seven patients, four had a transplant (3 lung, 1 liver), 1 ovarian cancer, 1 CAR-T cell therapy, and 1 ESRD without immunosuppression. The remaining eight patients with a detectable assay >20 days since admission had illness onset while hospitalized. Conclusion Among hospitalized patients with SARS-CoV-2 infection, we found a varying positivity rate according to the timing of testing, possibly reflecting different indications for the test. The strand-specific assay may help assess for infectiousness in profoundly immunocompromised patients. Disclosures Aruna Subramanian, MD, Gilead Sciences: Grant/Research Support|Regeneron, Inc: Grant/Research Support.

BACKGROUND AND AIMS:All major U.S. guidelines now endorse average-risk colorectal cancer (CRC) screening at 45-49 years of age. Concerns exist that endoscopic capacity may be strained, that low-risk persons may self-select for screening, and that calculations of the adenoma detection rate may be diluted. We analyzed age-specific screening colonoscopy volumes and lesion detection rates before vs after the endorsement of CRC screening at 45-49 years of age.METHODS:We compared colonoscopy volumes and lesion detection rates in our healthcare system during period 1 (October 2017 to December 2018), before the first change in guidelines, vs period 2 (January 2019 to August 2021), the era of new guidelines.RESULTS:The proportion of first-time screening colonoscopies performed in 45- to 49-year-olds increased from 3.5% to 11.6% (relative risk, 3.36; 95% CI, 2.45-4.61). The period 2 detection rates for adenoma, advanced adenoma, sessile serrated lesion, advanced sessile serrated lesion, adenomas per colonoscopy, and lesions per colonoscopy were very similar for 45- to 49-year-olds (34.3%, 6.3%, 8.6%, 2.9%, 0.58, and 0.69, respectively) and 50- to 54-year-olds (38.2%, 5.8%, 9.4%, 3.0%, 0.63, and 0.76, respectively) at first-time screening, and for 60- to 64-year-olds at rescreening (33.4%, 6.1%, 7.2%, 2.3%, 0.61, and 0.70, respectively). All detection rates, adenomas per colonoscopy, and lesions per colonoscopy increased from period 1 to period 2 (eg, overall adenoma detection rate 35.1% vs 42.6%; P < .0001), without any decreases among 45- to 49-year-olds.CONCLUSIONS:In our healthcare system, a lower CRC screening initiation age has modestly affected colonoscopy volume by age without compromising screening yield. Lesion detection rates, including for advanced adenomas, in average-risk 45- to 49-year-olds approximate those in 50- to 54-year-olds at first-time screening and 60- to 64-year-olds at rescreening. National monitoring is needed to assess fully the impact of lowering the CRC screening initiation age.