Search Results

Background: Although high-cost (HC) patients make up a small proportion of patients, they account for most health system costs. However, little is known about HC patients with cancer or whether some of their care could potentially be prevented. This analysis sought to characterize HC patients with cancer and quantify the costs of preventable acute care (emergency department visits and inpatient hospitalizations). Methods: This analysis examined a population-based sample of all HC patients in Ontario in 2013. HC patients were defined as those above the 90th percentile of the cost distribution; all other patients were defined as non–high-cost (NHC). Patients with cancer were identified through the Ontario Cancer Registry. Sociodemographic and clinical characteristics were examined and the costs of preventable acute care for both groups by category of visit/condition were estimated using validated algorithms. Results: Compared with NHC patients with cancer (n=369,422), HC patients with cancer (n=187,770) were older (mean age 70 vs 65 years), more likely to live in low-income neighborhoods (19% vs 16%), sicker, and more likely to live in long-term care homes (8% vs 0%). Although most patients from both cohorts tended to be diagnosed with breast, prostate, or colorectal cancer, those with multiple myeloma or pancreatic or liver cancers were overrepresented among the HC group. Moreover, HC patients were more likely to have advanced cancer at diagnosis and be in the initial or terminal phase of treatment compared with NHC patients. Among HC patients with cancer, 9% of spending stemmed from potentially preventable/avoidable acute care, whereas for NHC patients, this spending was approximately 30%. Conclusions: HC patients with cancer are a unique subpopulation. Given the type of care they receive, there seems to be limited scope to prevent acute care spending among this patient group. To reduce costs, other strategies, such as making hospital care more efficient and generating less costly encounters involving chemotherapy, should be explored.

Background: Although pancreatic adenocarcinoma (PA) surgery performed by high-volume (HV) providers yields better outcomes, volume–outcome relationships are unknown for medical oncologists. This study examined variation in practice and outcomes in noncurative management of PA based on medical oncology provider volume. Methods: This population-based cohort study linked administrative healthcare datasets and included nonresected PA from 2005 through 2016. The volume of PA consultations per medical oncology provider per year was divided into quintiles, with HV providers (≥16 patients/year) constituting the fifth quintile and low-volume (LV) providers the first to fourth quintiles. Outcomes were receipt of chemotherapy and overall survival (OS). The Brown-Forsythe-Levene (BFL) test for equality of variances was performed to assess outcome variability between provider-volume quintiles. Multivariate regression models were used to examine the association between management by HV provider and outcomes. Results: A total of 7,062 patients with noncurable PA consulted with medical oncology providers. Variability was seen in receipt of chemotherapy and median survival based on provider volume (BFL, P<.001 for both), with superior 1-year OS for HV providers (30.1%; 95% CI, 27.7%–32.4%) compared with LV providers (19.7%; 95% CI, 18.5%–20.6%) (P<.001). After adjustment for age at diagnosis, sex, comorbidity burden, rural residence, income, and diagnosis period, HV provider care was independently associated with higher odds of receiving chemotherapy (odds ratio, 1.19; 95% CI, 1.05–1.34) and with superior OS (hazard ratio, 0.79; 95% CI, 0.74–0.84). Conclusions: Significant variation was seen in noncurative management and outcomes of PA based on provider volume, with management by an HV provider being independently associated with superior OS and higher odds of receiving chemotherapy. This information is important to inform disease care pathways and care organization. Cancer care systems could consider increasing the number of HV providers to reduce variation and improve outcomes.

Background: Little is known about how the geographic distribution of cancer services may influence disparities in outcomes for noncurable pancreatic adenocarcinoma. We therefore examined the geographic distribution of outcomes for this disease in relation to distance to cancer centers. Methods: We conducted a retrospective population-based analysis of adults in Ontario, Canada, diagnosed with noncurable pancreatic adenocarcinoma from 2004 through 2017 using linked administrative healthcare datasets. The exposure was distance from place of residence to the nearest cancer center providing medical oncology assessment and systemic therapy. Outcomes were medical oncology consultation, receipt of cancer-directed therapy, and overall survival. We examined the relationship between distance and outcomes using adjusted multivariable regression models. Results: Of 15,970 patients surviving a median of 3.3 months, 65.6% consulted medical oncology and 38.5% received systemic therapy. Regions with comparable outcomes were clustered throughout Ontario. Mapping revealed regional discordances between outcomes. Increasing distance (reference, ≤10 km) was independently associated with lower likelihood of medical oncology consultation (relative risks [95% CI] for 11–50, 51–100, and ≥101 km were 0.90 [0.83–0.98], 0.78 [0.62–0.99], and 0.77 [0.55–1.08], respectively) and worse survival (hazard ratios [95% CI] for 11–50, 51–100, and ≥101 km were 1.08 [1.04–1.12], 1.17 [1.10–1.25], and 1.10 [1.02–1.18], respectively), but not with likelihood of receiving therapy. Receipt of therapy seems less sensitive to distance, suggesting that distance limits entry into the cancer care system via oncology consultation. Regional outcome discordances suggest inefficiencies within and protective factors outside of the cancer care system. Conclusions: These findings provide a basis for clinicians to optimize their practices for patients with noncurable pancreatic adenocarcinoma, for future studies investigating geographic barriers to care, and for regional interventions to improve access.

No population-based study exists to demonstrate the full-spectrum impact of COVID-19 on hindering incident cancer detection in a large cancer system. Building upon our previous publication in JNCCN, we conducted an updated analysis using 12 months of new data accrued in the pandemic era (extending the study period from September 26, 2020, to October 2, 2021) to demonstrate how multiple COVID-19 waves affected the weekly cancer incidence volume in Ontario, Canada, and if we have fully cleared the backlog at the end of each wave.

Background: Resource restrictions were established in many jurisdictions to maintain health system capacity during the COVID-19 pandemic. Disrupted healthcare access likely impacted early cancer detection. The objective of this study was to assess the impact of the pandemic on weekly reported cancer incidence. Patients and Methods: This was a population-based study involving individuals diagnosed with cancer from September 25, 2016, to September 26, 2020, in Ontario, Canada. Weekly cancer incidence counts were examined using segmented negative binomial regression models. The weekly estimated backlog during the pandemic was calculated by subtracting the observed volume from the projected/expected volume in that week. Results: The cohort consisted of 358,487 adult patients with cancer. At the start of the pandemic, there was an immediate 34.3% decline in the estimated mean cancer incidence volume (relative rate, 0.66; 95% CI, 0.57–0.75), followed by a 1% increase in cancer incidence volume in each subsequent week (relative rate, 1.009; 95% CI, 1.001–1.017). Similar trends were found for both screening and nonscreening cancers. The largest immediate declines were seen for melanoma and cervical, endocrinologic, and prostate cancers. For hepatobiliary and lung cancers, there continued to be a weekly decline in incidence during the COVID-19 period. Between March 15 and September 26, 2020, 12,601 fewer individuals were diagnosed with cancer, with an estimated weekly backlog of 450. Conclusions: We estimate that there is a large volume of undetected cancer cases related to the COVID-19 pandemic. Incidence rates have not yet returned to prepandemic levels.