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BACKGROUND: A number of treatment modalities are available to patients with early non-small cell lung cancer (NSCLC) but there is inconsistency regarding their effects on survival. The associated survival of each treatment modality is crucial for patients in making informed treatment decisions. We aimed to examine the change in treatment modality and trends in survival for patients with stage I NSCLC and assess the association between treatment modality and survival. METHODS: All patients diagnosed with stage I NSCLC in the Canadian province of Ontario between 2007 and 2015 were included in this population-based study. We used a flexible parametric model to estimate the trends in survival rate. RESULTS: Overall, 11,910 patients were identified of which 7,478 patients (62.8%) received surgical resection and 2,652 (22.3%) radiation only. The proportion of patients who received radiation only increased from 13.2% in 2007 to 28.0% in 2015 (P-for-trend

Background: Increasing involvement of palliative care generalists may improve access to palliative care. It is unknown, however, if their involvement with and without palliative care specialists are associated with different outcomes. Aim: To describe physician-based models of palliative care and their association with healthcare utilization outcomes including: emergency department visits, acute hospitalizations and intensive care unit (ICU) admissions in last 30 days of life; and, place of death. Design: Population-based retrospective cohort study using linked health administrative data. We used descriptive statistics to compare outcomes across three models (generalist-only palliative care; consultation palliative care, comprising of both generalist and specialist care; and specialist-only palliative care) and conducted a logistic regression for community death. Setting/participants: All adults aged 18–105 who died in Ontario, Canada between April 1, 2012 and March 31, 2017. Results: Of the 231,047 decedents who received palliative services, 40.3% received generalist, 32.3% consultation and 27.4% specialist palliative care. Across models, we noted minimal to modest variation for decedents with at least one emergency department visit (50%–59%), acute hospitalization (64%–69%) or ICU admission (7%–17%), as well as community death (36%–40%). In our adjusted analysis, receipt of a physician home visit was a stronger predictor for increased likelihood of community death (odds ratio 9.6, 95% confidence interval 9.4–9.8) than palliative care model (generalist vs consultation palliative care 2.0, 1.9–2.0). Conclusion: The generalist palliative care model achieved similar healthcare utilization outcomes as consultation and specialist models. Including a physician home visit component in each model may promote community death.

Background: To enable coordinated palliative care delivery, all clinicians should have basic palliative care skill sets (‘generalist palliative care’). Specialists should have skills for managing complex and difficult cases (‘specialist palliative care’) and co-exist to support generalists through consultation care and transfer of care. Little information exists about the actual mixes of generalist and specialist palliative care. Aim: To describe the models of physician-based palliative care services delivered to patients in the last 12 months of life. Design: This is a population-based retrospective cohort study using linked health care administrative data. Setting/participants: Physicians providing palliative care services to a decedent cohort in Ontario, Canada. The decedent cohort consisted of all adults (18+ years) who died in Ontario, Canada between April 2011 and March 2015 ( n = 361,951). Results: We describe four major models of palliative care services: (1) 53.0% of decedents received no physician-based palliative care, (2) 21.2% received only generalist palliative care, (3) 14.7% received consultation palliative care (i.e. care from both specialists and generalists), and (4) 11.1% received only specialist palliative care. Among physicians providing palliative care ( n = 11,006), 95.3% had a generalist palliative care focus and 4.7% a specialist focus; 74.2% were trained as family physicians. Conclusion: We examined how often a coordinated palliative care model is delivered to a large decedent cohort and identified that few actually received consultation care. The majority of care, in both the palliative care generalist and specialist models, was delivered by family physicians. Further research should evaluate how different models of care impact patient outcomes and costs.

Objectives: We examined the trends in survival based on treatment modality among non-small cell lung cancer (NSCLC) patients in the province of Ontario, Canada, from 2007 to 2015.Methods: We invest...

Background: Early palliative care can reduce end-of-life acute-care use, but findings are mainly limited to cancer populations receiving hospital interventions. Few studies describe how early versus late palliative care affects end-of-life service utilization. Aim: To investigate the association between early versus late palliative care (hospital/community-based) and acute-care use and other publicly funded services in the 2 weeks before death. Design: Retrospective population-based cohort study using linked administrative healthcare data. Setting/participants: Decedents (cancer, frailty, and organ failure) between 1 April 2010 and 31 December 2012 in Ontario, Canada. Initiation time before death (days): early (⩾60) and late (⩾15 and Results: We identified 230,921 decedents. Of them, 27% were early palliative care recipients and 13% were late; 45% of early recipients had a community-based initiation and 74% of late recipients had a hospital-based initiation. Compared to late recipients, fewer early recipients used palliative-acute care (42% vs 65%) with less days (mean days: 9.6 vs 12.0). Late recipients were more likely to use acute-care settings; this was further modified by disease: comparing late to early recipients, cancer decedents were nearly two times more likely to spend >1 week in acute-care settings (odds ratio = 1.84, 95% confidence interval: 1.83–1.85), frailty decedents were three times more likely (odds ratio = 3.04, 95% confidence interval: 3.01–3.07), and organ failure decedents were four times more likely (odds ratio = 4.04, 95% confidence interval: 4.02–4.06). Conclusion: Early palliative care was associated with improved end-of-life outcomes. Late initiations were associated with greater acute-care use, with the largest influence on organ failure and frailty decedents, suggesting potential opportunities for improvement.

Purpose Many oncology clinical trials departments (CTDs) are in serious fiscal deficit and their sustainability is in jeopardy. This study investigates whether the payment models used to fund industry versus cooperative group trials contribute to the fiscal deficit of a CTD. Methods We examined the lifetime costs of all cooperative group and industry trials activated in the CTD of a cancer center between 2007 and 2011. A trial's lifetime is defined as being from the date the first patient was accrued until the last patient's actual or projected final follow-up visit. For each trial, we calculated the lifetime monthly net income, which was defined as monthly revenue minus monthly costs. Data sources included study protocols, trial budgets, and accrual data. Results Of the 97 trials analyzed, 64 (66%) were cooperative group trials. The pattern of lifetime net income for cooperative group trials has a positive peak during patient accrual followed by a negative trough during follow-up. In contrast, the pattern for industry trials resembled an “l” shape. The patterns reflect the differing payment models: upfront lump-sum payments (cooperative group) versus milestone payments (industry). Conclusion The negative trough in the lifetime net income of a cooperative group trial occurs because follow-up costs are typically not funded or are underfunded. CTDs accrue more patients in new trials to offset that deficit. The CTD uses revenue from accrual to existing trials to cross-subsidize past trials in follow-up. As the number of patients on follow-up increases, the fiscal deficit grows larger each year, perpetuating the cycle.

Purpose To determine whether wait time from histologic diagnosis of uterine cancer to time of definitive surgery by hysterectomy had an impact on all-cause survival. Patients and Methods Women in Ontario with a confirmed histopathologic diagnosis of uterine cancer between April 1, 2000, and March 31, 2009, followed by surgery were identified in the Ontario Cancer Registry. Survival was calculated by using the Kaplan-Meier method. Factors were evaluated for their prognostic effect on survival by using Cox proportional hazards regression. Wait time was evaluated in a multivariable model after adjusting for other significant factors. Results The final study population included 9,417 women; 51.9% had surgery by a gynecologist, and 69.9% had endometrioid adenocarcinoma. Five-year survival for women with wait times of 0.1 to 2, 2.1 to 6, 6.1 to 12, or more than 12 weeks was 71.1%, 81.8%, 79.5%, and 71.9%, respectively. Wait times of ≤ 2 weeks were adversely prognostic for survival after adjusting for other significant factors in the multivariable model, and patients with wait times of more than 12 weeks had worse survival than those who had wait times between 2.1 and 12.0 weeks. Conclusion To the best of our knowledge, this is the first report in a large population-based cohort demonstrating that longer wait times from diagnosis of uterine cancer to definitive surgery have a negative impact on overall survival.

Background Health system planners aim to pursue the three goals of Triple Aim: 1) reduce health care costs; 2) improve population health; and 3) improve the care experience. Moreover, they also need measures that can reliably predict future health care needs in order to manage effectively the health system performance. Yet few measures exist to assess Triple Aim and predict future needs at a health system level. The purpose of this study is to explore the novel application of a case-mix adjustment method in order to measure and help improve the Triple Aim of health system performance. Methods We applied a case-mix adjustment method to a population-based analysis to assess its usefulness as a measure of health system performance and Triple Aim. The study design was a retrospective, cohort study of adults from Ontario, Canada using administrative databases: individuals were assigned a predicted illness burden score using a case-mix adjustment system from diagnoses and health utilization data in 2008, and then followed forward to assess the actual health care utilization and costs in the following year (2009). We applied the Johns Hopkins Adjusted Clinical Group (ACG) Case-Mix System to categorize individuals into 60 levels of healthcare need, called ACGs. The outcomes were: 1) Number of individuals per ACG; 2) Total system costs per ACG; and 3) Mean cost per person per ACG, which together formed a health system “dashboard”. Results We identified 11.4 million adults. 16.1% were aged 65 or older, 3.2 million (28%) did not use health care services that year, and 45,000 (0.4%) were in the highest acuity ACG category using 12 times more than an average adult. The sickest 1%, 5% and 15% of the population use about 10%, 30% and 50% of total health system costs respectively. The dashboard measures 2 dimensions of Triple Aim: 1) reduced costs: when total system costs per ACG or when average costs per person is reduced; and 2) improved population health: when more people move into healthier rather than sicker ACGs. It can help to achieve the third aim, improved care experience, when ACG utilization predictions are reported to providers to proactively develop care plans. Conclusions The dashboard, developed via case-mix methods, measures 2 of the Triple Aim goals and can help health system planners better manage their health delivery systems.