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PURPOSE: A validated risk model with inputs of pretreatment sodium and albumin can identify patients at risk for hospitalization during cancer treatment. We evaluated how the model compares with risk estimates from treating oncologists. METHODS: We evaluated the 30-day risk of hospitalization or death in patients starting palliative-intent systemic therapy for solid tumor malignancy. For each patient, we prospectively recorded categorical estimates of 30-day hospitalization risk (bottom third, middle third, top third) generated by a treating oncologist and by the two-variable model; a third hybrid risk estimate represented a composite of the oncologist and model risk assessments. We analyzed the agreement of oncologist and model-based risk estimates and compared discrimination, sensitivity, and specificity of each risk assessment method. RESULTS: We collected oncologist, model, and hybrid estimates of hospitalization risk for 120 patients. The 30-day rate of hospitalization or death was 20%. There was minimal agreement between oncologist and model risk estimates (weighted kappa = 0.27). The c-statistic (a measure of discrimination) was 0.69 (95% CI, 0.57 to 0.81) for the clinician assessment, 0.77 for the model assessment (CI, 0.67 to 0.86; P = .24 compared with the oncologist assessment), and 0.79 for the hybrid assessment (CI, 0.69 to 0.90; P = .007 compared with the oncologist assessment). Sensitivity and specificity of the high-risk categorization did not differ significantly between the oncologist and model assessments; the hybrid assessment was significantly more sensitive ( P = .02) and less specific ( P = .03) than the oncologist assessment. CONCLUSION: A model with inputs of pretreatment sodium and albumin improves oncologists' predictions of hospitalization risk during cancer treatment.

Radiation utilization for breast cancer and metastatic bone disease varies in modality, fractionation, and cost, despite evidence demonstrating equal effectiveness and consensus recommendations such as Choosing Wisely that advocate for higher value care. We assessed whether the Oncology Care Model (OCM), an alternative payment model for practices providing chemotherapy to patients with cancer, affected the overall use and value of radiation therapy in terms of Choosing Wisely recommendations.We used Centers for MedicareMedicaid Services administrative data to identify beneficiaries enrolled in traditional fee-for-service Medicare who initiated chemotherapy episodes at OCM and propensity-matched comparison practices. Difference-in-difference (DID) analyses evaluated the effect of OCM on overall use of postoperative radiation for breast cancer, use of intensity modulated radiation therapy and hypofractionation for breast cancer, and fractionation patterns for treatment of metastatic bone disease from breast or prostate cancer. We performed additional analyses stratified by the presence or absence of a radiation oncologist in the practice.Among 27,859 postoperative breast cancer episodes, OCM had no effect on overall use of radiation therapy after breast surgery (DID percentage point difference = 0.4%; 90% confidence interval [CI], -1.7%, 2.4%) or on use of intensity modulated radiation therapy in this setting (DID = -0.6; 90% CI, -3.1, 2.0). Among 19,366 metastatic bone disease episodes, OCM had no effect on fractionation patterns for palliation of bone metastases (DID for ≤10 fractions = -1.1%; 90% CI, -2.6%, 0.4% and DID for single fraction = -0.2%; 90% CI, -1.9%, 1.6%). Results were similar for practices with and without a radiation oncologist. We did not evaluate the effect of OCM on hypofractionated radiation after breast-conserving surgery owing to evidence of differential baseline trends.OCM had no effect on use of radiation therapy after breast-conserving surgery for breast cancer or on fractionation patterns for metastatic bone disease. Future payment models directly focused on radiation oncology providers may be better poised to improve the value of radiation oncology care.

Background Pancreatectomy is a necessary component of curative intent therapy for pancreatic cancer, and patients living in non-metropolitan areas may face barriers to accessing timely surgical care. We evaluated the intersecting associations of rurality, socioeconomic status (SES), and race on treatment and outcomes of Medicare beneficiaries with pancreatic cancer. Methods We conducted a retrospective cohort study, using fee-for-service Medicare claims of beneficiaries with incident pancreatic cancer (2016-2018). We categorized beneficiary place of residence as metropolitan, micropolitan, or small town/rural. Measures of SES were Medicare-Medicaid dual eligibility and the Area Deprivation Index (ADI). Primary study outcomes were receipt of pancreatectomy and one-year mortality. Exposure-outcome associations were assessed with competing risks and logistic regression. Results We identified 45,915 beneficiaries with pancreatic cancer, including 78.4%, 10.9%, and 10.7% residing in metropolitan, micropolitan, and rural areas, respectively. In analyses adjusted for age, sex, comorbidity, and metastasis, residents of micropolitan and rural areas were less likely to undergo pancreatectomy (adjusted subdistribution hazard ratio=0.88 for rural, 95%CI 0.81-0.95) and had higher one-year mortality (aOR=1.25 for rural, 95%CI 1.17-1.33), compared with metropolitan residents. Adjustment for measures of SES attenuated the association of non-metropolitan residence with mortality, and there was no significant association of rurality with pancreatectomy after adjustment. Black beneficiaries had lower likelihood of pancreatectomy than White, non-Hispanic beneficiaries (aSHR=0.80, 95%CI 0.72-0.89, adjusted for SES). One-year mortality in metropolitan areas was higher for Black beneficiaries (aOR=1.15 95%CI 1.05-1.26). Conclusions Rurality, socioeconomic deprivation, and race have complex interrelationships and are associated with disparities in pancreatic cancer treatment and outcomes.

Background Delays between breast cancer diagnosis and surgery are associated with worsened survival. Delays are more common in urban-residing patients, although factors specific to surgical delays among rural and urban patients are not well understood. Methods We used a 100% sample of fee-for-service Medicare claims during 2007–2014 to identify 238,491 women diagnosed with early-stage breast cancer undergoing initial surgery and assessed whether they experienced biopsy-to-surgery intervals > 90 days. We employed multilevel regression to identify associations between delays and patient, regional, and surgeon characteristics, both in combined analyses and stratified by rurality of patient residence. Results Delays were more prevalent among urban patients (2.5%) than rural patients (1.9%). Rural patients with medium- or high-volume surgeons had lower odds of delay than patients with low-volume surgeons (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.58–0.88; OR = 0.74, 95% CI = 0.61–0.90). Rural patients whose surgeon operated at ≥ 3 hospitals were more likely to experience delays (OR = 1.29, 95% CI = 1.01–1.64, Ref: 1 hospital). Patient driving times ≥ 1 h were associated with delays among urban patients only. Age, black race, Hispanic ethnicity, multimorbidity, and academic/specialty hospital status were associated with delays. Conclusions Sociodemographic, geographic, surgeon, and facility factors have distinct associations with > 90-day delays to initial breast cancer surgery. Interventions to improve timeliness of breast cancer surgery may have disparate impacts on vulnerable populations by rural-urban status.

BACKGROUND: Pancreatic cancer has a 5-year survival of just 10%. Services such as palliative care and hospice are thus crucial in this population, yet their geographic accessibility and utilization remains unknown. AIM: We studied the association between rurality of patient residence and the use of palliative care and hospice. DESIGN, SETTING, AND PARTICIPANTS: Cohort study of continuously enrolled fee-for-service Medicare beneficiaries age≥65 diagnosed with incident pancreatic cancer between 04/01/2016-08/31/2018 and who died by 12/31/2018. RESULTS: In this decedent cohort of 31,460 patients, 77% lived in metropolitan areas, 11% in micropolitan areas, 7% in small towns, and 5% in rural areas. Patient demographics were largely similar across rurality; however, the proportion of White, Non-Hispanic patients and social deprivation was highest in rural areas and lowest in metropolitan areas. Overall, 33% of patients used any palliative care and 77% received hospice services. After risk adjustment, there were no statistically significant differences in the use of palliative care for patients residing in metropolitan versus micropolitan, small town, or rural areas. Patients in small town (OR=0.77, 95% CI:0.69–0.86) and rural areas (OR=0.75, 95% CI:0.66–0.85) had lower adjusted odds of receiving hospice care compared to patients in metropolitan areas. CONCLUSIONS: The use of palliative care services captured in Medicare was low, representing either underutilization or failure to accurately measure the extent of services used. While the overall level of hospice enrollment was high, patients in rural communities had relatively lower use of hospice services compared to those in metropolitan areas.

Background In response to the COVID-19 pandemic, cancer centers rapidly adopted telehealth to deliver care remotely. Telehealth will likely remain a model of care for years to come and may not only affect the way oncologists deliver care to their own patients but also the physicians with whom they share patients. Objective This study aimed to examine oncologist characteristics associated with telehealth use and compare patient-sharing networks before and after the COVID-19 pandemic in a rural catchment area with a particular focus on the ties between physicians at the comprehensive cancer center and regional facilities. Methods In this retrospective observational study, we obtained deidentified electronic health record data for individuals diagnosed with breast, colorectal, or lung cancer at Dartmouth Health in New Hampshire from 2018-2020. Hierarchical logistic regression was used to identify physician factors associated with telehealth encounters post COVID-19. Patient-sharing networks for each cancer type before and post COVID-19 were characterized with global network measures. Exponential-family random graph models were performed to estimate homophily terms for the likelihood of ties existing between physicians colocated at the hub comprehensive cancer center. Results Of the 12,559 encounters between patients and oncologists post COVID-19, 1228 (9.8%) were via telehealth. Patient encounters with breast oncologists who practiced at the hub hospital were over twice as likely to occur via telehealth compared to encounters with oncologists who practiced in regional facilities (odds ratio 2.2, 95% CI 1.17-4.15; P=.01). Patient encounters with oncologists who practiced in multiple locations were less likely to occur via telehealth, and this association was statistically significant for lung cancer care (odds ratio 0.26, 95% CI 0.09-0.76; P=.01). We observed an increase in ties between oncologists at the hub hospital and oncologists at regional facilities in the lung cancer network post COVID-19 compared to before COVID-19 (93/318, 29.3%, vs 79/370, 21.6%, respectively), which was also reflected in the lower homophily coefficients post COVID-19 compared to before COVID-19 for physicians being colocated at the hub hospital (estimate: 1.92, 95% CI 1.46-2.51, vs 2.45, 95% CI 1.98-3.02). There were no significant differences observed in breast cancer or colorectal cancer networks. Conclusions Telehealth use and associated changes to patient-sharing patterns associated with telehealth varied by cancer type, suggesting disparate approaches for integrating telehealth across clinical groups within this health system. The limited changes to the patient-sharing patterns between oncologists at the hub hospital and regional facilities suggest that telehealth was less likely to create new referral patterns between these types of facilities and rather replace care that would otherwise have been delivered in person. However, this study was limited to the 2 years immediately following the initial outbreak of COVID-19, and longer-term follow-up may uncover delayed effects that were not observed in this study period.

ImportancePhysician headcounts provide useful information about the cancer care delivery workforce; however, efforts to track the oncology workforce would benefit from new measures that capture how essential a physician is for meeting the multidisciplinary cancer care needs of the region. Physicians are considered linchpins when fewer of their peers are connected to other physicians of the same specialty as the focal physician. Because they are locally unique for their specialty, these physicians’ networks may be particularly vulnerable to their removal from the network (eg, through relocation or retirement).ObjectiveTo examine a novel network-based physician linchpin score within nationwide cancer patient-sharing networks and explore variation in network vulnerability across hospital referral regions (HRRs).Design, Setting, and ParticipantsThis cross-sectional study analyzed fee-for-service Medicare claims and included Medicare beneficiaries with an incident diagnosis of breast, colorectal, or lung cancer from 2016 to 2018 and their treating physicians. Data were analyzed from March 2022 to October 2022.ExposuresPhysician characteristics assessed were specialty, rurality, and Census region. HRR variables assessed include sociodemographic and socioeconomic characteristics and use of cancer services.Main Outcomes and MeasuresOncologist linchpin score, which examined the extent to which a physician’s peers were connected to other physicians of the same specialty as the focal physician. Network vulnerability, which distinguished HRRs with more linchpin oncologists than expected based on oncologist density. χ2 and Fisher exact tests were used to examine relationships between oncologist characteristics and linchpin score. Spearman rank correlation coefficient (ρ) was used to measure the strength and direction of relationships between HRR network vulnerability, oncologist density, population sociodemographic and socioeconomic characteristics, and cancer service use.ResultsThe study cohort comprised 308 714 patients with breast, colorectal, or lung cancer. The study cohort of 308 714 patients included 161 206 (52.2%) patients with breast cancer, 76 604 (24.8%) patients with colorectal cancer, and 70 904 (23.0%) patients with lung cancer. In our sample, 272 425 patients (88%) were White, and 238 603 patients (77%) lived in metropolitan areas. The cancer patient-sharing network included 7221 medical oncologists and 3573 radiation oncologists. HRRs with more vulnerable networks for medical oncology had a higher percentage of beneficiaries eligible for Medicaid (ρ, 0.19; 95% CI, 0.08 to 0.29). HRRs with more vulnerable networks for radiation oncology had a higher percentage of beneficiaries living in poverty (ρ, 0.17; 95% CI, 0.06 to 0.27), and a higher percentage of beneficiaries eligible for Medicaid (ρ, 0.21; 95% CI, 0.09 to 0.31), and lower rates of cohort patients receiving radiation therapy (ρ, –0.18; 95% CI, –0.28 to –0.06; P = .003). The was no association between network vulnerability for medical oncology and percent of cohort patients receiving chemotherapy (ρ, –0.03; 95% CI, –0.15 to 0.08).Conclusions and RelevanceThis study found that patient-sharing network vulnerability was associated with poverty and lower rates of radiation therapy. Health policy strategies for addressing network vulnerability may improve access to interdisciplinary care and reduce treatment disparities.

Background Pathogenic variants of the DPYD gene are strongly associated with grade ≥3 toxicity during fluoropyrimidine chemotherapy. We conducted a systematic review and meta-analysis to estimate the risk of treatment-related death associated with DPYD gene variants. Materials and Methods We searched for reports published prior to September 17, 2020, that described patients receiving standard-dose fluoropyrimidine chemotherapy (5-fluorouracil or capecitabine) who had baseline testing for at least one of four pathogenic DPYD variants (c.1129-5923C>G [HapB3], c.1679T>G [*13], c.1905+1G>A [*2A], and c.2846A>T) and were assessed for toxicity. Two reviewers assessed studies for inclusion and extracted study-level data. The primary outcome was the relative risk of treatment-related mortality for DPYD variant carriers versus noncarriers; we performed data synthesis using a Mantel-Haenszel fixed effects model. Results Of the 2,923 references screened, 35 studies involving 13,929 patients were included. DPYD variants (heterozygous or homozygous) were identified in 566 patients (4.1%). There were 14 treatment-related deaths in 13,363 patients without identified DPYD variants (treatment-related mortality, 0.1%; 95% confidence interval [CI], 0.1–0.2) and 13 treatment-related deaths in 566 patients with any of the four DPYD variants (treatment-related mortality, 2.3%; 95% CI, 1.3%–3.9%). Carriers of pathogenic DPYD gene variants had a 25.6 times increased risk of treatment-related death (95% CI, 12.1–53.9; p G variant, carriers of c.1679T>G, c.1905+1G>A, and/or c.2846A>T had treatment-related mortality of 3.7%. Conclusion Patients with pathogenic DPYD gene variants who receive standard-dose fluoropyrimidine chemotherapy have greatly increased risk for treatment-related death. Implications for Practice The syndrome of dihydropyrimidine dehydrogenase (DPD) deficiency is an uncommon but well-described cause of severe toxicity related to fluoropyrimidine chemotherapy agents (5-fluorouracil and capecitabine). Patients with latent DPD deficiency can be identified preemptively with genotyping of the DPYD gene, or with measurement of the plasma uracil concentration. In this systematic review and meta-analysis, the authors study the rare outcome of treatment-related death after fluoropyrimidine chemotherapy. DPYD gene variants associated with DPD deficiency were linked to a 25.6 times increased risk of fluoropyrimidine-related mortality. These findings support the clinical utility of DPYD genotyping as a screening test for DPD deficiency.

We describe racially discordant oncology encounters involving EOL decision-making. Fifty-eight provider interviews were content analyzed using the tenets of problematic integration theory. We found EOL discussions between non-Black providers and their Black patients were often complex and anxiety-inducing. That anxiety consisted of (1) ontological uncertainty in which providers characterized the nature of Black patients as distrustful, especially in the context of clinical trials; (2) ontological and epistemological uncertainty in which provider intercultural incompetency and perceived lack of patient health literacy were normalized and intertwined with provider assumptions about patients' religion and support systems; (3) epistemological uncertainty as ambivalence in which providers' feelings conflicted when deciding whether to speak with family members they perceived as lacking health literacy; (4) divergence in which the provider advised palliative care while the family desired surgery or cancer-directed medical treatment; and (5) impossibility when an ontological uncertainty stance of Black distrust was seen as natural by providers and therefore impossible to change. Some communication strategies used were indirect stereotyping, negotiating, asking a series of value questions, blame-guilt framing, and avoidance. We concluded that provider perceptions of Black distrust, religion, and social support influenced their ability to communicate effectively with patients.

ImportanceAll patients with newly diagnosed non–small cell lung cancer (NSCLC) and colorectal cancer (CRC) should receive molecular testing to identify those who can benefit from targeted therapies. However, many patients do not receive recommended testing and targeted therapies.ObjectiveTo compare rates of molecular testing and targeted therapy use by practice type and across practices.Design, Setting, and ParticipantsThis cross-sectional study used 100% Medicare fee-for-service data from 2015 through 2019 to identify beneficiaries with new metastatic NSCLC or CRC diagnoses receiving systemic therapy and to assign patients to oncology practices. Hierarchical linear models were used to characterize variation by practice type and across practices. Data analysis was conducted from June 2019 to October 2022.ExposuresOncology practice providing care.OutcomesPrimary outcomes were rates of molecular testing and targeted therapy use for patients with NSCLC and CRC. Secondary outcomes were rates of multigene testing for NSCLC and CRC.ResultsThere were 106 228 Medicare beneficiaries with incident NSCLC (31 521 [29.7%] aged 65-69 years; 50 348 [47.4%] female patients; 2269 [2.1%] Asian, 8282 [7.8%] Black, and 91 215 [85.9%] White patients) and 39 512 beneficiaries with incident CRC (14 045 [35.5%] aged 65-69 years; 17 518 [44.3%] female patients; 896 [2.3%] Asian, 3521 [8.9%] Black, and 32 753 [82.9%] White patients) between 2015 and 2019. Among these beneficiaries, 18 435 (12.9%) were treated at National Cancer Institute (NCI)–designated centers, 8187 (5.6%) were treated at other academic centers, and 94 329 (64.7%) were treated at independent oncology practices. Molecular testing rates increased from 74% to 85% for NSCLC and 45% to 65% for CRC. First-line targeted therapy use decreased from 12% to 8% among patients with NSCLC and was constant at 5% for patients with CRC. For NSCLC, molecular testing rates were similar across practice types while rates of multigene panel use (13.2%) and targeted therapy use (16.6%) were highest at NCI-designated cancer centers. For CRC, molecular testing rates were 3.8 (95% CI: 1.2-6.5), 3.3 (95% CI, 0.4-6.1), and 12.2 (95% CI, 9.1-15.3) percentage points lower at hospital-owned practices, large independent practices, and small independent practices, respectively. Rates of targeted therapy use for CRC were similar across practice types. After adjusting for patient characteristics, there was moderate variation in molecular testing and targeted therapy use across oncology practices.Conclusions and RelevanceIn this cross-sectional study of Medicare beneficiaries, molecular testing rates for NSCLC and CRC increased in recent years but remained lower than recommended levels. Rates of targeted therapy use decreased for NSCLC and remained stable for CRC. Variation across practices suggests that where a patient was treated may have affected access to recommended testing and efficacious treatments.

ObjectiveMeasures of variation in end-of-life (EOL) care intensity across hospitals are typically summarised using unidimensional measures. These measures do not capture the full dimensionality of complex clinical care trajectories over time that are needed to inform quality improvement efforts. The objective is to develop a novel visual map of EOL care trajectories that illustrates multidimensional utilisation over time.SettingUnited States’ National Cancer Institute or National Comprehensive Cancer Network (NCI/NCCN)-designated hospitals.ParticipantsWe identified Medicare claims for fee-for-service beneficiaries with poor prognosis cancers who died between April and December 2016 and received the preponderance of treatment in the last 6 months of life at an NCI/NCCN-designated hospital.DesignFor each beneficiary, we transformed each Medicare claim into two elements to generate a two-dimensional individual-level heatmap. On the y-axis, each claim was classified into a categorical description of the service delivered by a healthcare resource. On the x-axis, the date for each claim was converted into the day number prior to death it occurred on. We then summed up individual-level heatmaps of patients attributed to each hospital to generate two-dimensional hospital-level heatmaps. We used four case studies to illustrate the feasibility of interpreting these heatmaps and to shed light on how they might be used to guide value-based, quality improvement initiatives.ResultsWe identified nine distinct EOL care delivery patterns from hospital-level heatmaps based on signal intensity and patterns for inpatient, outpatient and home-based hospice services. We illustrate that in most cases, heatmaps illustrating patterns of multidimensional healthcare utilisation over time provide more information about care trajectories and highlight more heterogeneity than current unidimensional measures.ConclusionsThis study illustrates the feasibility of representing multidimensional EOL utilisation over time as a heatmap. These heatmaps may provide potentially actionable insights into hospital-level care delivery patterns, and the approach may generalise to other serious illness populations.

Racial inequities in clinical performance diminish overall health care system performance; however, quality assessments have rarely incorporated reliable measures of racial inequities. We studied care for more than one million Medicare fee-for-service beneficiaries with cancer to assess the feasibility of calculating reliable practice-level measures of racial inequities in chemotherapy-associated emergency department (ED) visits and hospitalizations. Specifically, we used hierarchical models to estimate adjusted practice-level Black-White differences in these events and described differences across practices. We calculated reliable inequity measures for 426 and 322 practices, depending on the measure. These practices reflected fewer than 10 percent of practices treating Medicare beneficiaries with chemotherapy, but they treated approximately half of all White and Black Medicare beneficiaries receiving chemotherapy and two-thirds of Black Medicare beneficiaries receiving chemotherapy. Black patients experienced chemotherapy-associated ED visits and hospitalizations at higher rates (54.2 percent and 35.8 percent, respectively) than White patients (45.7 percent and 31.9 percent, respectively). The median within-practice Black-White difference was 8.1 percentage points for chemotherapy-associated ED visits and 2.7 percentage points for chemotherapy-associated hospitalizations. Additional research is needed to identify other reliable measures of racial inequities in health care quality, measure care inequities in smaller practices, and assess whether providing practice-level feedback could improve equity.

Background A critical barrier to improving the quality of end-of-life (EOL) cancer care is our lack of understanding of the mechanisms underlying variation in EOL treatment intensity. This study aims to fill this gap by identifying 1) organizational and provider practice norms at major US cancer centers, and 2) how these norms influence provider decision making heuristics and patient expectations for EOL care, particularly for minority patients with advanced cancer. Methods This is a multi-center, qualitative case study at six National Comprehensive Cancer Network (NCCN) and National Cancer Institute (NCI) Comprehensive Cancer Centers. We will theoretically sample centers based upon National Quality Forum (NQF) endorsed EOL quality metrics and demographics to ensure heterogeneity in EOL intensity and region. A multidisciplinary team of clinician and non-clinician researchers will conduct direct observations, semi-structured interviews, and artifact collection. Participants will include: 1) cancer center and clinical service line administrators; 2) providers from medical, surgical, and radiation oncology; palliative or supportive care; intensive care; hospital medicine; and emergency medicine who see patients with cancer and have high clinical practice volume or high local influence (provider interviews and observations); and 3) adult patients with metastatic solid tumors and whom the provider would not be surprised if they died in the next 12 months and their caregivers (patient and caregiver interviews). Leadership interviews will probe about EOL institutional norms and organization. We will observe inpatient and outpatient care for two weeks. Provider interviews will use vignettes to probe explicit and implicit motivations for treatment choices. Semi-structured interviews with patients near EOL, or their family members and caregivers will explore past, current, and future decisions related to their cancer care. We will import transcribed field notes and interviews into Dedoose software for qualitative data management and analysis, and we will develop and apply a deductive and inductive codebook to the data. Discussion This study aims to improve our understanding of organizational and provider practice norms pertinent to EOL care in U.S. cancer centers. This research will ultimately be used to inform a provider-oriented intervention to improve EOL care for racial and ethnic minority patients with advanced cancer. Trial registration Clinicaltrials.gov; NCT03780816; December 19, 2018.

Background We calculated the performance of National Cancer Institute (NCI)/National Comprehensive Cancer Network (NCCN) cancer centers’ end‐of‐life (EOL) quality metrics among minority and white decedents to explore center‐attributable sources of EOL disparities. Methods We conducted a retrospective cohort study of Medicare beneficiaries with poor‐prognosis cancers who died between April 1, 2016 and December 31, 2016 and had any inpatient services in the last 6 months of life. We attributed patients’ EOL treatment to the center at which they received the preponderance of EOL inpatient services and calculated eight risk‐adjusted metrics of EOL quality (hospice admission ≤3 days before death; chemotherapy last 14 days of life; ≥2 emergency department (ED) visits; intensive care unit (ICU) admission; or life‐sustaining treatment last 30 days; hospice referral; palliative care; advance care planning last 6 months). We compared performance between patients across and within centers. Results Among 126,434 patients, 10,119 received treatment at one of 54 NCI/NCCN centers. In aggregate, performance was worse among minorities for ED visits (10.3% vs 7.4%, P, We evaluated end‐of‐life quality metrics by minority serving status at NCI/NCCN cancer centers. We found higher minority‐serving status associated with worse end‐of‐life quality on some but not all measures. However, at any given cancer center, care was similar for minority and white patients.

PURPOSE The Oncology Care Model (OCM) is an episode-based alternative payment model for cancer care that seeks to reduce Medicare spending while maintaining care quality. We evaluated the impact of OCM on appropriate use of supportive care medications during cancer treatment. METHODS We evaluated chemotherapy episodes assigned to OCM (n = 201) and comparison practices (n = 534) using Medicare claims (2013-2019). We assessed denosumab use for beneficiaries with bone metastases from breast, lung, or prostate cancer; prophylactic WBC growth factor use for beneficiaries receiving chemotherapy for breast, lung, or colorectal cancer; and prophylactic use of neurokinin-1 (NK1) antagonists and long-acting serotonin antagonists for beneficiaries receiving chemotherapy for any cancer type. Analyses used a difference-in-difference approach. RESULTS After its launch in 2016, OCM led to a relative reduction in the use of denosumab for beneficiaries with bone metastases receiving bone-modifying medications (eg, 5.0 percentage point relative reduction in breast cancer episodes [90% CI, –7.1 to –2.8]). There was no OCM impact on use of prophylactic WBC growth factors during chemotherapy with high or low risk for febrile neutropenia. Among beneficiaries receiving chemotherapy with intermediate febrile neutropenia risk, OCM led to a 7.6 percentage point reduction in the use of prophylactic WBC growth factors during breast cancer episodes (90% CI, –12.6 to –2.7); there was no OCM impact in lung or colorectal cancer episodes. Among beneficiaries receiving chemotherapy with high or moderate emetic risk, OCM led to reductions in the prophylactic use of NK1 antagonists and long-acting serotonin antagonists (eg, 6.0 percentage point reduction in the use of NK1 antagonists during high emetic risk chemotherapy [90% CI, –9.0 to –3.1]). CONCLUSION OCM led to the reduced use of some high-cost supportive care medications, suggesting more value-conscious care.

Adjuvant fluoropyrimidine-based chemotherapy substantially reduces recurrence and mortality after resection of stage 3 colon cancer. While standard doses of 5-fluorouracil and capecitabine are safe for most patients, the risk of severe toxicity is increased for the approximately 6% of patients with dihydropyimidine dehydrogenase (DPD) deficiency caused by pathogenic DPYD gene variants. Pre-treatment screening for pathogenic DPYD gene variants reduces severe toxicity but has not been widely adopted in the United States.We conducted a cost-effectiveness analysis of DPYD genotyping prior to fluoropyrimidine-based adjuvant chemotherapy for stage 3 colon cancer, covering the c.1129-5923CG (HapB3), c.1679TG (*13), c.1905+1GA (*2A), and c.2846AT gene variants. We used a Markov model with a 5-year horizon, taking a United States healthcare perspective. Simulated patients with pathogenic DPYD gene variants received reduced-dose fluoropyrimidine chemotherapy. The primary outcome was the incremental cost-effectiveness ratio (ICER) for DPYD genotyping.Compared with no screening for DPD deficiency, DPYD genotyping increased per-patient costs by $78 and improved survival by 0.0038 quality-adjusted life years (QALYs), leading to an ICER of $20,506/QALY. In 1-way sensitivity analyses, The ICER exceeded $50,000 per QALY when the cost of the DPYD genotyping assay was greater than $286. In probabilistic sensitivity analysis using a willingness-to-pay threshold of $50,000/QALY DPYD genotyping was preferred to no screening in 96.2% of iterations.Among patients receiving adjuvant chemotherapy for stage 3 colon cancer, screening for DPD deficiency with DPYD genotyping is a cost-effective strategy for preventing infrequent but severe and sometimes fatal toxicities of fluoropyrimidine chemotherapy.

Delays between breast cancer diagnosis and surgery are associated with worsened survival. Delays are more common in urban-residing patients, although factors specific to surgical delays among rural and urban patients are not well understood.We used a 100% sample of fee-for-service Medicare claims during 2007-2014 to identify 238,491 women diagnosed with early-stage breast cancer undergoing initial surgery and assessed whether they experienced biopsy-to-surgery intervals 90 days. We employed multilevel regression to identify associations between delays and patient, regional, and surgeon characteristics, both in combined analyses and stratified by rurality of patient residence.Delays were more prevalent among urban patients (2.5%) than rural patients (1.9%). Rural patients with medium- or high-volume surgeons had lower odds of delay than patients with low-volume surgeons (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.58-0.88; OR = 0.74, 95% CI = 0.61-0.90). Rural patients whose surgeon operated at ≥ 3 hospitals were more likely to experience delays (OR = 1.29, 95% CI = 1.01-1.64, Ref: 1 hospital). Patient driving times ≥ 1 h were associated with delays among urban patients only. Age, black race, Hispanic ethnicity, multimorbidity, and academic/specialty hospital status were associated with delays.Sociodemographic, geographic, surgeon, and facility factors have distinct associations with 90-day delays to initial breast cancer surgery. Interventions to improve timeliness of breast cancer surgery may have disparate impacts on vulnerable populations by rural-urban status.

Difficulty in identifying cancer stage in health care claims data has limited oncology quality of care and health outcomes research. We fit prediction algorithms for classifying lung cancer stage into three classes (stages I/II, stage III, and stage IV) using claims data, and then demonstrate a method for incorporating the classification uncertainty in outcomes estimation. Leveraging set-valued classification and split conformal inference, we show how a fixed algorithm developed in one cohort of data may be deployed in another, while rigorously accounting for uncertainty from the initial classification step. We demonstrate this process using SEER cancer registry data linked with Medicare claims data., Code available at: https://github.com/sl-bergquist/cancer_classification

PURPOSE Hospitalizations are a common occurrence during chemotherapy for advanced cancer. Validated risk stratification tools could facilitate proactive approaches for reducing hospitalizations by identifying at-risk patients. PATIENTS AND METHODS We assembled two retrospective cohorts of patients receiving chemotherapy for advanced nonhematologic cancer; cohorts were drawn from three integrated health plans of the Cancer Research Network. We used these cohorts to develop and validate logistic regression models estimating 30-day hospitalization risk after chemotherapy initiation. The development cohort included patients in two health plans from 2005 to 2013. The validation cohort included patients in a third health plan from 2007 to 2016. Candidate predictor variables were derived from clinical data in institutional data warehouses. Models were validated based on the C-statistic, positive predictive value, and negative predictive value. Positive predictive value and negative predictive value were calculated in reference to a prespecified risk threshold (hospitalization risk ≥ 18.0%). RESULTS There were 3,606 patients in the development cohort (median age, 63 years) and 634 evaluable patients in the validation cohort (median age, 64 years). Lung cancer was the most common diagnosis in both cohorts (26% and 31%, respectively). The selected risk stratification model included two variables: albumin and sodium. The model C-statistic in the validation cohort was 0.69 (95% CI, 0.62 to 0.75); 39% of patients were classified as high risk according to the prespecified threshold; 30-day hospitalization risk was 24.2% (95% CI, 19.9% to 32.0%) in the high-risk group and 8.7% (95% CI, 6.1% to 12.0%) in the low-risk group. CONCLUSION A model based on data elements routinely collected during cancer treatment can reliably identify patients at high risk for hospitalization after chemotherapy initiation. Additional research is necessary to determine whether this model can be deployed to prevent chemotherapy-related hospitalizations.

PURPOSE Cancer stage is a key determinant of outcomes; however, stage is not available in claims-based data sources used for real-world evaluations. We compare multiple methods for classifying lung cancer stage from claims data. METHODS Our study used the linked SEER-Medicare data. The patient samples included fee-for-service Medicare beneficiaries diagnosed with lung cancer from 2010 to 2011 (development cohort) and 2012 to 2013 (validation cohort) who received chemotherapy. Classification algorithms considered Medicare Part A and B claims for care in the 3 months before and after chemotherapy initiation. We developed a clinical algorithm to predict stage IV ( v I to III) cancer on the basis of treatment patterns (surgery, radiotherapy, chemotherapy). We also considered an ensemble of claims-based machine learning algorithms. Classification methods were trained in the development cohort, and performance was measured in both cohorts. The SEER data were the gold standard for cancer stage. RESULTS Development and validation cohorts included 14,760 and 14,620 patients with lung cancer, respectively. Validation analyses assessed clinical, random forest, and simple logistic regression algorithms. The best performing classifier within the development cohort was the random forests, but this performance was not replicated in validation analysis. Logistic regression had stable performance across cohorts. Compared with the clinical algorithm, the 14-variable logistic regression algorithm demonstrated higher accuracy in both the development (77% v 71%) and validation cohorts (77% v 73%), with improved specificity for stage IV disease. CONCLUSION Machine learning algorithms have potential to improve lung cancer stage classification but may be prone to overfitting. Use of ensembles, cross-validation, and external validation can aid generalizability. Degradation of accuracy between development and validation cohorts suggests the need for caution in implementing machine learning in research or care delivery.

Background: FOLFOX (folinic acid, 5-fluorouracil and oxaliplatin) is the most commonly used chemotherapy regimen for the treatment of colorectal cancer. FOLFOX is administered in 14-day cycles, though toxicities frequently lead to unplanned delays. We report the incidence of unplanned delays among patients receiving FOLFOX and describe the reasons for delays. Methods: We conducted a retrospective analysis of patients receiving FOLFOX chemotherapy for colorectal cancer. Patients were treated at one of two tertiary cancer centers between January 2012 and April 2016. Cycles 2–6 were assessed for delays, and treatments were considered delayed when the interval from prior treatment was >18 days. Reasons for unplanned delays were categorized based on review of clinical records. Results: We identified 214 patients receiving FOLFOX as standard-of-care therapy. The median age was 59 years, and 55% were female. Of 961 evaluable treatment cycles, 124 (13%) had unplanned delays, and 92 of 214 patients (43%) had one or more unplanned delays in cycles 2–6. Cytopenias (neutropenia and/or thrombocytopenia) were the most common cause of unplanned delays, affecting 34% of patients and accounting for 74 of 124 unplanned delays (60%). Conclusions: Delays are common during FOLFOX chemotherapy, with 43% of patients having at least one unplanned delay prior to completing cycle 6. Neutropenia and thrombocytopenia were the leading causes of unplanned delays. Our findings justify the development of systematic approaches for preventing unplanned delays, such as standardized laboratory treatment criteria and/or proactive dose adjustment strategies.

Loot boxes are virtual goods in video games that produce randomly-generated in-game rewards, and have attracted scrutiny because of a resemblance to gambling. This study tests relationships between gaming involvement, engagement with loot boxes, and their associations with disordered gambling and gambling-related cognitions. Online questionnaires were completed by 144 adults via MTurk (Study 1) and 113 undergraduates (Study 2). Gaming and loot box-related variables included estimated time spent gaming and monthly expenditure, the Internet Gaming Disorder Scale (IGDS), and questions that assessed perceptions and behaviours related to loot boxes. Most participants thought loot boxes were a form of gambling (68.1% & 86.2%). A subset of items were condensed into a unidimensional "Risky Loot-box Index" (RLI) via exploratory factor analysis. In Study 1, the RLI showed significant associations with the Problem Gambling Severity Index (r = .491, p < .001) and the Gambling Related Cognitions Scale (r = .518, p < .001). Overall, gambling-related variables predicted 37.1% (p < .001) of the variance in RLI scores. Findings were replicated, though attenuated, in Study 2. These results demonstrate that besides the surface similarity of loot boxes to gambling, loot box engagement is correlated with gambling beliefs and problematic gambling behaviour in adult gamers.

BACKGROUND/PURPOSE: Clinical trials in oncology evaluating the effects of patient reported outcomes (PRO) collection have found that monitoring of symptoms with PROs is associated with improved clinical care through reduced acute care utilization and decreased patient symptom burden. This educational review will evaluate strategies for systematic PRO integration into everyday oncology clinical practice. METHODS: We outline key considerations for using PROs in clinical practice, highlighting evidence from published studies. We also discuss the benefits and challenges of PRO implementation in oncology. RESULTS: Implementing PRO collection in clinical practice can improve care delivery and facilitate patient-centered clinical research. Considerations for using PROs in clinical practice include choice of instrument, method of delivery, and frequency of query. Challenges with implementing systematic PRO collection include the costs and resources needed for implementation, impact on clinical workflow, and controlling/monitoring physician burnout. DISCUSSION: While challenges exist in terms of financial resources and staff participation/burnout, patient reported outcomes in clinical practice provide a number of benefits including symptom monitoring, clinical research, and potential real-time personalized clinical decision support.

Background: Electronic health records are central to cancer care delivery. Electronic clinical decision support (CDS) systems can potentially improve cancer care quality and safety. However, little is known regarding the use of CDS systems in clinical oncology and their impact on patient outcomes. Methods: A systematic review of peer-reviewed studies was performed to evaluate clinically relevant outcomes related to the use of CDS tools for the diagnosis, treatment, and supportive care of patients with cancer. Peer-reviewed studies published from 1995 through 2016 were included if they assessed clinical outcomes, patient-reported outcomes (PROs), costs, or care delivery process measures. Results: Electronic database searches yielded 2,439 potentially eligible papers, with 24 studies included after final review. Most studies used an uncontrolled, pre-post intervention design. A total of 23 studies reported improvement in key study outcomes with use of oncology CDS systems, and 12 studies assessing the systems for computerized chemotherapy order entry demonstrated reductions in prescribing error rates, medication-related safety events, and workflow interruptions. The remaining studies examined oncology clinical pathways, guideline adherence, systems for collection and communication of PROs, and prescriber alerts. Conclusions: There is a paucity of data evaluating clinically relevant outcomes of CDS system implementation in oncology care. Currently available data suggest that these systems can have a positive impact on the quality of cancer care delivery. However, there is a critical need to rigorously evaluate CDS systems in oncology to better understand how they can be implemented to improve patient outcomes.

PURPOSE: Increasingly epidemiological cohorts are being linked to claims data to provide rich data for healthcare research. These cohorts tend to be different than the general US population. We will analyze healthcare utilization of Nurses’ Health Study participants (NHS) to determine if studies of newly diagnosed incident early stage breast cancer can be generalized to the broader US Medicare population. METHODS: Analytic cohorts of fee-for-service NHS-Medicare linked participants and a 1:13 propensity matched SEER-Medicare cohort (SEER) with incident breast cancer in the years 2007–2011 were considered. Screening leading to, treatment-related, and general utilization in the year following early stage breast cancer diagnosis were determined using Medicare claims data. RESULTS: After propensity matching, NHS and SEER were statistically balanced on all demographics. NHS and SEER had statistically similar rates of treatments including chemotherapy, breast conserving surgery, mastectomy, and overall radiation use. Rates of general utilization include those related to hospitalizations, total visits, and ED visits were also balanced between the two groups. Total spending in the year following diagnosis were statistically equivalent for NHS and SEER ($36,180 vs. $35,399, p = 0.7045). CONCLUSIONS: NHS and the general female population had comparable treatment and utilization patterns following diagnosis of early stage incident breast cancers with the exception of type of radiation therapy received. This study provides support for the larger value of population-based cohorts in research on healthcare costs and utilization in breast cancer

Rural patients with colon cancer experience worse outcomes than urban patients, but the extent to which disparities are explained by social determinants is not known.To evaluate the association of rurality with surgical treatment and outcomes of colon cancer and to investigate the intersection of rurality with race and ethnicity and socioeconomic status.This cohort study included fee-for-service Medicare beneficiaries 65 years or older diagnosed with incident, nonmetastatic colon cancer between April 1, 2016, and September 30, 2018, with follow-up until December 31, 2018. Data were analyzed from August 3, 2020, to April 30, 2021.Rurality of patient's residence, categorized as metropolitan, micropolitan, or small town or rural, using Rural-Urban Commuting Area codes.Receipt of surgery, emergent surgery, or minimally invasive surgery (MIS); 90-day surgical complications; and 90-day mortality.Among 57 710 Medicare beneficiaries with incident, nonmetastatic colon cancer, 46.6% were men, 53.4% were women, and the mean (SD) age was 76.6 (7.2) years. In terms of race and ethnicity, 3.7% were Hispanic, 6.4% were non-Hispanic Black (hereinafter Black), 86.1% were non-Hispanic White (hereinafter White), and 3.8% were American Indian or Alaska Native, Asian or Pacific Islander, or unknown race or ethnicity. Patients residing in nonmetropolitan areas were more likely to undergo surgical resection than those residing in metropolitan areas (69.2% vs 63.9%; P .001). Black race was independently associated with lower hazard of surgical resection (hazard ratio, 0.92 [95% CI, 0.88-0.95]). Race and ethnicity and measures of socioeconomic status did not modify the association of rurality with surgery. Beneficiaries from small town and rural areas had higher odds of undergoing emergent surgery (adjusted odds ratio [OR], 1.32 [95% CI, 1.20-1.44]) but lower odds of undergoing MIS (adjusted OR, 0.75 [95% CI, 0.70-0.80]), with similar findings for patients residing in micropolitan areas. Members of racial and ethnic minority groups who resided in small town and rural settings experienced higher odds of postoperative surgical complications (P = .001 for interaction) and mortality (P = .001 for interaction). Notably, White patients who resided in small town and rural areas experienced lower odds of postoperative mortality than their White metropolitan counterparts (adjusted OR, 0.81 [95% CI, 0.71-0.92]), but Black patients who resided in small town and rural areas had significantly higher odds of postoperative mortality (adjusted OR, 1.86 [95% CI, 1.16-2.97]) than their Black metropolitan counterparts.These findings suggest that Medicare beneficiaries from small town and rural areas were more likely to undergo surgery for nonmetastatic colon cancer than metropolitan beneficiaries but also more likely to undergo emergent surgery and less likely to have MIS. The experiences of rural patients varied by race; rurality was associated with higher postoperative mortality for Black patients but not for other racial and ethnic groups.

Concerns regarding the similarities between video game 'loot boxes' and gambling have been supported by correlations in survey studies between loot box engagement and problem gambling scores. It is generally noted that this correlation could reflect loot box users migrating to conventional gambling, and/or people with gambling problems being attracted to loot boxes when they play video games. We describe a third possibility, that when gamers complete problem gambling screens they may be referring to harms incurred from their loot box use. Using three secondary datasets from cross-sectional online surveys, we explore this account in two ways. First, in participants who do not endorse any participation in conventional forms of gambling, we compare rates of positive (i.e. non-zero) scores on the Problem Gambling Severity Index (PGSI) in participants with and without loot box use. Second, noting that some PGSI items have less relevance to loot box use versus gambling, we compare endorsement rates of individual PGSI items, in gamers versus gamblers, and loot box users vs non-loot box users (focusing on item 3 "going back another day to win back the money you lost"). In analysis 1, positive PGSI scorers among non-gamblers were significantly elevated in loot box users vs non-loot box users, although absolute numbers were low overall. In analysis 2, there were no reliable differences (gamers vs gamblers, loot box users vs non-loot box users) in PGSI item 3 endorsement rates. We conclude that these results provide partial support for this third option, and highlight a need for future studies to consider this possibility more directly.

This cross-sectional study assesses measures of care process, utilization, end-of-life care, and survival at oncology practices that treat older Medicare beneficiaries with newly diagnosed lung, breast, or colorectal cancer., Key Points Question Can the quality of care be assessed reliably across medical oncology practices, and what are the correlations of different types of practice-level performance across quality measure and cancer types? Findings In this cross-sectional study, registry and claims-based measures of care processes, utilization, end-of-life care, and survival for newly diagnosed fee-for-service Medicare beneficiaries with cancer were limited by small numbers of patients across oncology practices, even after pooling 5 years of data. Measures of care quality had low reliability and had limited to no correlation across measure and cancer types. Meaning Results of this study suggest that additional research is needed to identify reliable quality measures for practice-level assessments of quality., Importance Measurement of the quality of care is important for alternative payment models in oncology, yet the ability to distinguish high-quality from low-quality care across oncology practices remains uncertain. Objective To assess the reliability of cancer care quality measures across oncology practices using registry and claims-based measures of process, utilization, end-of-life (EOL) care, and survival, and to assess the correlations of practice-level performance across measure and cancer types. Design, Setting, and Participants This cross-sectional study used the Surveillance, Epidemiology, and End Results (SEER) Program registry linked to Medicare administrative data to identify individuals with lung cancer, breast cancer, or colorectal cancer (CRC) that was newly diagnosed between January 1, 2011, and December 31, 2015, and who were treated in oncology practices with 20 or more patients. Data were analyzed from January 2018 to December 2020. Main Outcomes and Measures Receipt of guideline-recommended treatment and surveillance, hospitalizations or emergency department visits during 6-month chemotherapy episodes, care intensity in the last month of life, and 12-month survival were measured. Summary measures for each domain in each cohort were calculated. Practice-level rates for each measure were estimated from hierarchical linear models with practice-level random effects; practice-level reliability (reproducibility) for each measure based on the between-measure variance, within-measure variance, and distribution of patients treated in each practice; and correlations of measures across measure and cancer types. Results In this study of SEER registry data linked to Medicare administrative data from 49 715 patients with lung cancer treated in 502 oncology practices, 21 692 with CRC treated in 347 practices, and 52 901 with breast cancer treated in 492 practices, few practices had 20 or more patients who were eligible for most process measures during the 5-year study period. Patients were 65 years or older; approximately 50% of the patients with lung cancer and CRC and all of the patients with breast cancer were women. Most measures had limited variability across practices. Among process measures, 0 of 6 for lung cancer, 0 of 6 for CRC, and 3 of 11 for breast cancer had a practice-level reliability of 0.75 or higher for the median-sized practice. No utilization, EOL care, or survival measure had reliability across practices of 0.75 or higher. Correlations across measure types were low (r ≤ 0.20 for all) except for a correlation between the CRC process and 1-year survival summary measures (r = 0.35; P

1584 Background: There has been increasing hospital and health system ownership of physician practices in recent years, particularly in oncology. However, relatively little is known about how this impacts care delivery for patients with cancer, who use many hospital-based services that may be impacted by integration. We evaluated the impact of physician-hospital integration in oncology on spending and quality of care for Medicare beneficiaries with cancer. Methods: We used Medicare Fee-for-Service claims from 2005-2019 linked with a unique Health System and Provider Database, developed by National Bureau of Economic Research and Harvard University researchers, to track practice ownership relationships over time. We used a stacked event study to assess outcomes for patients three years before and after oncologists move from independent practices to hospital- or system- owned practices. We compared outcomes to a control group with oncologists who shifted from independent to hospital- or system-owned practices in later years. We focused on two cohorts of patients. The first cohort included cancer patients with presumed incident or recurrent cancer based on ≥2 visits to an oncologist and no visit in the past year. For these patients, we evaluated the impact of physician-hospital integration on the likelihood of receiving chemotherapy following the visit. The second cohort included 6-month episodes for patients receiving chemotherapy. For these patients we evaluated the impact of physician-hospital integration on spending, utilization, and quality. Quality measures included receipt of timely chemotherapy (within 60 days) following surgery, inpatient readmissions, non-use of tamoxifen + strong CYPD26 inhibitors, and end-of-life intensity of care measures. Results: There was no change in the likelihood of receiving chemotherapy with an initial oncology consultation following an oncologist’s transition to hospital-based employment. Total spending during six-month chemotherapy episodes increased by $1391 (95%CI: $465, $2316). The primary contributors to this growth were increases in spending on inpatient care, chemotherapy administration, and office visits. Spending growth, where observed, was driven primarily by higher Medicare prices for care in hospital outpatient settings. We found no positive impact of physician-hospital integration on timeliness of chemotherapy initiation, readmissions, concurrent use of tamoxifen+strong CYPD26 inhibitors, or intensity of end-of-life care. Conclusions: Physician-hospital integration resulted in higher prices and thus higher spending, but had limited impact on utilization and no detectable impacts on measures of quality. These results suggest that claims of quality improvements and concerns regarding overuse associated with physician-hospital integration may be overstated. Our results also support continued movement towards site-neutral payments.

e13627 Background: Physician practices across the U.S. are increasingly merging with hospitals and other practices. The extent of such “practice consolidation” varies by specialty and across geography but has not been well characterized within medical oncology. Methods: Utilizing Medicare data, we identified all medical oncologists (MO) who billed for Medicare services each year between 2015 and January 2022. We associated each physician to one or more unique practices via organizational Taxpayer Identification Numbers (TIN), and classified practices by the number of medical oncologists—including solo (1 MO), small (2-10 MOs), medium (11-24 MOs), and large (25+ MOs) practices. We defined the extent of regional healthcare markets according to Hospital Referral Regions (HRRs), and calculated levels of practice consolidation using the Herfindahl-Hirschman Index (HHI). The HHI is a commonly used measure of consolidation, calculated by summing the square of each practice’s market share. HHI values range from 0 to 1 with higher numbers indicating greater consolidation and less competition among practices. Finally, we generated a multivariable linear regression model to determine which regional market factors were associated with changes in levels of medical oncology practice consolidation over time. Results: Between 2015 and 2022, the number of practices with MOs in the U.S. declined 18.0% from 2,774 to 2,276, while the number of practicing MOs increased 14.5% from 11,727 to 13,433. The median medical oncology practice HHI increased from 0.3204 to 0.3480. Over time the proportion of solo practices fell (48.4% in 2015, 43.9% in 2022) while the proportion of medium and large practices increased (medium: 5.7% to 8.4%; large: 2.7% to 4.5%). By 2022, large practices had grown to employ a significantly larger proportion of all medical oncologists (33.6% to 43.7%, p < 0.001). Between 2015 and 2022, the proportion of practices solely comprised of MOs (as opposed to multispecialty practices) decreased from 40.0% to 28.2%. On multivariable analysis, HRRs with higher levels of hospital consolidation (p < 0.001), greater numbers of hospital beds per 1,000 persons (p = 0.02), and a lesser degree of baseline medical oncology practice consolidation in 2015 (p < 0.001) experienced more consolidation during the study period. Conclusions: Medical oncologists across the U.S. are increasingly working in larger practices. By 2022, more than 40% of all practicing MOs were employed at the largest 5% of practices. Consolidation of medical oncology practices occurred more readily in regions with higher levels of hospital consolidation and a greater supply of hospital beds, suggesting that integration into hospital systems may be a leading source of consolidation. Further study is required to determine the impact of practice consolidation on the cost, quality, and accessibility of cancer care.

6551 Background: Targeted therapies are important first-line treatments for many patients with non-small cell lung cancer (NSCLC) and colorectal cancer (CRC). All patients with newly-diagnosed metastatic NSCLC and CRC should undergo molecular diagnostic testing to guide treatment selection. Methods: We used 100% Medicare fee-for-service data from 2015 through 2019 to identify beneficiaries with incident metastatic NSCLC or CRC receiving systemic therapy and to assign beneficiaries to oncology practices. We then assessed for use of molecular diagnostic testing and targeted therapies in these cohorts. We used linear mixed effects models to assess patient and practice characteristics associated with molecular diagnostic testing and targeted therapy use. Results: Rates of molecular diagnostic testing increased between 2015 and 2019 for NSCLC and CRC. In 2019, rates of molecular diagnostic testing were 85% and 65% for NSCLC and CRC, respectively. Rates of targeted therapy use did not increase over time for NSCLC or CRC, and were 8% and 5%, respectively, in 2019. Compared to National Cancer Institute (NCI)-designated cancer centers, rates of molecular diagnostic testing for CRC were 3.7 percentage points lower at practices associated with non-academic hospitals and 10.6 percentage points lower at small independent practices. Rates of targeted therapy use for NSCLC were 4.8, 5.9 and 5.5 percentage points lower at academic medical centers, large independent practices and small independent practices, respectively, compared to NCI centers. Conclusions: Rates of molecular diagnostic testing for NSCLC and CRC increased in recent years, but testing rates remain below recommended levels, and targeted therapy use remains low. Substantial variation in testing and targeted therapy use by practice type suggest that the practice where a patient is treated may impact access to recommended testing and efficacious treatments. [Table: see text]

Objectives Assess whether frequently-used claims-based end-of-life (EOL) measures are associated with higher ratings of care quality. Design Retrospective cohort study. Setting/participants Deceased fee-for-service Medicare beneficiaries with cancer who underwent chemotherapy during July 2016 to January 2017 and died within 12 months and their caregiver respondents to an after-death survey (n = 2,559). Measurements We examined claims-based measures of EOL care: chemotherapy 14 days or more before death; inpatient admissions, intensive care unit (ICU) use, and emergency department (ED) visits 30 days or more before death; hospice election and the timing of election before death. Primary outcomes are family ratings of "excellent" care in the last month of life and reports that hospice care began "at the right time." Associations were assessed with logistic regression, adjusted by patient characteristics. Results Family rated EOL care as excellent less often, if within 30 days before death the cancer patient had inpatient admissions (1 hospitalization = 41.5% vs 51.5% none, adjusted difference -10.1 percentage points), ICU use (38.6% for any ICU use vs 47.4% none; adjusted difference -8.8 percentage points), ED visits (41.0% 1 visit vs 51.6% no visits; adjusted difference -10.6 percentage points), or elected hospice within 7 days before death. Among hospice enrollees, family more often reported that hospice began at the right time if it started at least 7 days before death (hospice 1-2 days before death 60.2% vs hospice 7-13 days 74.9%; adjusted difference +14.7 percentage points). Conclusions Claims-based measures of EOL care for cancer patients that reflect avoidance of hospital-based care and earlier hospice enrollment are associated with higher ratings of care quality by bereaved family members.

Background There are limited data and conflicting guideline recommendations regarding the role of neuroimaging in the pretreatment evaluation of non-small cell lung cancer (NSCLC). Methods We performed a retrospective, pragmatic cohort study of patients with NSCLC diagnosed between January 1 and December 31, 2015. Eligible patients were identified from an institutional tumor registry. We collected all records of pretreatment neuroimaging within 12 weeks of diagnosis, including CT head (CT) and MRI brain (MRI). We abstracted the indication for neuroimaging, presence of central neurologic symptoms and cancer stage (with and without neuroimaging findings) from the tumor registry and the electronic health record. Results We identified 216 evaluable patients with newly diagnosed NSCLC. 157 of 216 patients (72.7%) underwent neuroimaging as part of initial staging, and 41 (26%) were found to have brain metastases. Of 43 patients with central neurologic symptoms at the time of neuroimaging, 28 (67%) had brain metastasis. In patients without central neurologic symptoms, brain metastases were discovered in 0 of 33 patients with clinical stage I or II, 4 of 36 (11%) with clinical stage III and 9 of 45 (20%) with clinical stage IV disease. Conclusions In patients with early stage NSCLC (i.e. clinical stage I and II) without central neurologic symptoms, brain metastases are unlikely. The continued use of neuroimaging in the pretreatment evaluation of clinical stage I patients without central neurologic symptoms is not needed., Health Sciences; Oncology; Medical Imaging; Radiology; Diagnostics; Non-small cell lung cancer; MRI brain; pretreatment evaluation; CT head; staging; outcomes.

Gambling disorder is recognized in DSM-5 and ICD-11 as a behavioral addiction that shares substantial psychological and neurobiological overlap with substance use disorders. This chapter outlines how cognitive processes originally described in the field of judgment and decision-making provide a foundation from which gambling-related cognitive distortions emerge. These cognitive mechanisms are implicated in the etiology, maintenance, and treatment of disordered gambling. We focus on three specific effects: the illusion of control, the tendency to anthropomorphize gambling games, and slot machine immersion. We conceptualize these biases as arising from the interaction between personal vulnerabilities to gambling disorder, which include neurocognitive dispositional factors and structural characteristics of gambling products. From this framework, the structural design of gambling products, including emerging technologies that facilitate access to gambling games, may perpetuate gambling-related distortions and thus gambling harms, with implications for regulation. Psychological therapies that build on this cognitive approach are widely deployed in the treatment of problem gambling and have evidence of effectiveness, including techniques directly aiming to restructure decision-making biases.

Importance In 2016, the US Centers for Medicare & Medicaid Services initiated the Oncology Care Model (OCM), an alternative payment model designed to improve the value of care delivered to Medicare beneficiaries with cancer. Objective To assess the association of the OCM with changes in Medicare spending, utilization, quality, and patient experience during the OCM's first 3 years. Design, setting, and participants Exploratory difference-in-differences study comparing care during 6-month chemotherapy episodes in OCM participating practices and propensity-matched comparison practices initiated before (January 2014 through June 2015) and after (July 2016 through December 2018) the start of the OCM. Participants included Medicare fee-for-service beneficiaries with cancer treated at these practices through June 2019. Exposures OCM participation. Main outcomes and measures Total episode payments (Medicare spending for Parts A, B, and D, not including monthly payments for enhanced oncology services); utilization and payments for hospitalizations, emergency department (ED) visits, office visits, chemotherapy, supportive care, and imaging; quality (chemotherapy-associated hospitalizations and ED visits, timely chemotherapy, end-of-life care, and survival); and patient experiences. Results Among Medicare fee-for-service beneficiaries with cancer undergoing chemotherapy, 483 319 beneficiaries (mean age, 73.0 [SD, 8.7] years; 60.1% women; 987 332 episodes) were treated at 201 OCM participating practices, and 557 354 beneficiaries (mean age, 72.9 [SD, 9.0] years; 57.4% women; 1 122 597 episodes) were treated at 534 comparison practices. From the baseline period, total episode payments increased from $28 681 for OCM episodes and $28 421 for comparison episodes to $33 211 for OCM episodes and $33 249 for comparison episodes during the intervention period (difference in differences, -$297; 90% CI, -$504 to -$91), less than the mean $704 Monthly Enhanced Oncology Services payments. Relative decreases in total episode payments were primarily for Part B nonchemotherapy drug payments (difference in differences, -$145; 90% CI, -$218 to -$72), especially supportive care drugs (difference in differences, -$150; 90% CI, -$216 to -$84). The OCM was associated with statistically significant relative reductions in total episode payments among higher-risk episodes (difference in differences, -$503; 90% CI, -$802 to -$204) and statistically significant relative increases in total episode payments among lower-risk episodes (difference in differences, $151; 90% CI, $39-$264). The OCM was not significantly associated with differences in hospitalizations, ED visits, or survival. Of 22 measures of utilization, 10 measures of quality, and 7 measures of care experiences, only 5 were significantly different. Conclusions and relevance In this exploratory analysis, the OCM was significantly associated with modest payment reductions during 6-month episodes for Medicare beneficiaries receiving chemotherapy for cancer in the first 3 years of the OCM that did not offset the monthly payments for enhanced oncology services. There were no statistically significant differences for most utilization, quality, and patient experience outcomes.

78 Background: Rural cancer patients face limited access to care due to greater travel distance and lack of specialty cancer care. Little is known about the intersection of rurality with well-documented racial disparities in colon cancer treatment and outcomes. Methods: We used fee-for-service Medicare claims to study patients age 65+ diagnosed with incident colon cancer without evidence of metastases who underwent cancer-directed surgery between 04/01/2016 and 09/30/2018. The primary exposure wasrurality of patient’s residence categorized as metropolitan (metro), micropolitan, and small town/rural. Outcomes were non-elective surgery (emergency department visit or transfer within 2 days prior to surgery), receipt of minimally invasive surgery (laparoscopic or robotic), 90-day surgical complications, and 90-day mortality. Logistic regression adjusted for patient demographics, cancer side (right vs left), comorbidities, and Area Deprivation Index. We assessed effect modification by race/ethnicity. Results: Of 57,710 patients with incident non-metastatic colon cancer, 37,691 (65%) underwent surgery. In this surgical cohort, small town/rural and micropolitan residents were more likely to be older, white, and Medicare-Medicaid dual-eligible than metro residents. After risk adjustment, patients in small town/rural areas had higher odds of non-elective surgery (OR =1.24, 95% CI:1.13-1.36) and lower odds of minimally invasive surgery (OR = 0.75, 95% CI:0.71-0.80) than patients living in metro areas. Similar results were seen for micropolitan areas. White rural patients had lower mortality than white urban patients, whereas black rural patients had higher mortality than black metro patients (see Table). Increasing area deprivation was associated with higher odds of non-elective surgery, surgical complications and mortality, and lower odds of minimally invasive surgery, even after adjusting for race and rurality. Conclusions: Small town/rural-residing Medicare beneficiaries undergoing surgery for non-metastatic colon cancer were less likely to receive optimal surgical management and had worse outcomes, especially among non-white patients. The compounded effect of rurality, race/ethnicity, and social deprivation should be incorporated in developing policies and interventions to improve care for rural cancer patients.[Table: see text]

216 Background: Dihyropyrimidine dehydrogenase (DPD) deficiency is present in 3-5% of patients, and is associated with substantially increased risk of severe and/or fatal toxicity during standard-dose FP chemotherapy. Genotyping of pathogenic DPYD variants is a readily available screening test for DPD deficiency, and prospective studies show that dose-reduced FP chemotherapy can be used safely in heterozygous DPYD variant carriers. Methods: Following a sentinel toxicity event the GI medical oncology group at the Norris Cotton Cancer Center adopted a shared practice of routine screening for pathogenic DPYD gene variants prior to FP chemotherapy (5-FU or capecitabine). Screening procedures involved physicians, NP/PAs, nurses, pharmacists, and schedulers. Testing was completed at a send-out lab until late 2020, when an in-house test became available. The current test panel evaluates for 3 gene variants: c.1905+1G > A (*2A), c.1679T > G (*13), and c.2846A > T. We report on the sustainability and clinical outcomes of DPYD gene variant screening. We identified all patients starting new FP-containing intravenous chemotherapy regimens (e.g., FOLFOX, CAPOX) for treatment of GI cancer at two sites (LEB & STJ) between Jan. 2019 and May 2021. We used electronic medical records to evaluate for completion of DPYD genotyping, and we describe the prevalence and management of DPYD gene variant carriers. Results: We identified 333 patients starting FP-containing chemotherapy regimens during the study period, including 287 patients without prior history of FP chemotherapy. Screening with DPYD genotyping was completed in 228 of 287 eligible patients (79%). Screening rates increased from 34% in Q1 of 2019 to 90% in Jan-May 2021. Five GI oncology sub-specialists accounted for 89% of screen-eligible patients and 96% of completed tests, but 10 unique physicians ordered ≥1 test. Of 228 screened patients, six (2.6%) were heterozygous carriers of pathogenic DPYD gene variants (*2A [2 patients], *13 [1], and c.2846A > T [3]). Variant carriers started FP chemotherapy with a 33-50% reduction. Two of six patients required further dose reduction due to FP-related toxicity (grade 4 neutropenia, grade 3 diarrhea). All evaluable variant carriers completed planned initial treatment. Implementation challenges included variable insurance coverage of DPYD genotyping, site-specific test ordering and reporting processes, and inconsistent turn-around time for send-out testing (resolved with on-site testing). Conclusions: Routine screening for pathogenic DPYD gene variants prior to FP chemotherapy is feasible and sustainable in the U.S. DPYD genotyping coupled with chemotherapy dose reductions for DPYD variant carriers facilitates safe and timely completion of planned chemotherapy treatments.