Processes and Outcomes of Care for Soft Tissue Sarcoma of the Extremities

Purpose: A population-based cohort study of soft tissue sarcoma of the extremities (STSE) in Ontario, Canada was conducted using linked administrative databases

Factors associated with the breast cancer diagnostic interval across five Canadian provinces: a CanIMPACT study

Introduction A long breast cancer diagnostic process can affect patient anxiety and survival. Variations in the length of the diagnostic interval for similar patient presentations can indicate health system inequities and/or inefficiencies. Objectives and Approach We describe the breast cancer diagnostic interval across Canada and factors associated with its length. We studied breast cancer patients diagnosed from 2004/7 to 2010/11/12 in the Canadian provinces: British Columbia, Alberta, Manitoba, Ontario, and Nova Scotia. Using administrative data, we created parallel population-based, provincial-level datasets and ran common analyses. The diagnostic interval was defined from the screening mammogram to the diagnosis for screen-led and from the first referral/test ordering date to the diagnosis for diagnostic-led patients. Stratified by these two diagnostic routes, we describe the variation in the interval across provinces and report on the province-specific associations between the diagnostic interval and: patient age, comorbid disease burden, socioeconomic status combined with rural residence, and continuity of primary care while controlling for cancer stage. Results The median diagnostic interval varied by 6 days (29 to 35 days) across provinces. Screen-led patients were diagnosed more quickly (median 2-12 days quicker). The 90th percentile diagnostic interval was 84-126 days longer in diagnostic-led patients. In the diagnostic-led group, increasing comorbid burden was consistently associated with longer diagnostic intervals and being >70 was associated with a shorter interval at the 90th percentile in Manitoba and Ontario. There was no evidence of a clear rural or low socioeconomic status effect and patients without a primary care physician had shorter intervals. In the screen-led group, patients age 40-49 and those in the medium or low income rural areas waited longer for a diagnosis. Conclusion/Implications Diagnostic wait times differ across Canada and are variably associated with comorbidity, age, area-level socioeconomic status and rural residence. These results point to practice and system-level effects that warrant further study

Lessons Learned: It Takes a Village to Understand Inter-Sectoral Care Using Administrative Data across Jurisdictions

Cancer care is complex and exists within the broader healthcare system. The CanIMPACT team sought to enhance primary cancer care capacity and improve integration between primary and cancer specialist care, focusing on breast cancer. In Canada, all medically-necessary healthcare is publicly funded but overseen at the provincial/territorial level. The CanIMPACT Administrative Health Data Group’s (AHDG) role was to describe inter-sectoral care across five Canadian provinces: British Columbia, Alberta, Manitoba, Ontario and Nova Scotia. This paper describes the process used and challenges faced in creating four parallel administrative health datasets. We present the content of those datasets and population characteristics. We provide guidance for future research based on ‘lessons learned’. The AHDG conducted population-based comparisons of care for breast cancer patients diagnosed from 2007-2011. We created parallel provincial datasets using knowledge from data inventories, our previous work, and ongoing bi-weekly conference calls. Common dataset creation plans (DCPs) ensured data comparability and documentation of data differences. In general, the process had to be flexible and iterative as our understanding of the data and needs of the broader team evolved. Inter-sectoral data inconsistencies that we had to address occurred due to differences in: 1) healthcare systems, 2) data sources, 3) data elements and 4) variable definitions. Our parallel provincial datasets describe the breast cancer diagnostic, treatment and survivorship phases and address ten research objectives. Breast cancer patient demographics reflect inter-provincial general population differences. Across provinces, disease characteristics are similar but underlying health status and use of healthcare services differ. Describing healthcare across Canadian jurisdictions assesses whether our provincial healthcare systems are delivering similar high quality, timely, accessible care to all of our citizens. We have provided a description of our experience in trying to achieve this goal and include a list of ‘lessons learned’ and a study process checklist for future use

Adherence to Breast Cancer Follow-up Care Guidelines for Vulnerable Populations in four Canadian provinces: a CanIMPACT study

Introduction Breast cancer survivors are at risk for late and ongoing problems including cancer recurrence and late effects of treatment. Vulnerable groups may not enjoy equitable access to quality follow-up care. This study examines utilization of guideline-based follow-up care among vulnerable subpopulations in four Canadian provinces. Objectives and Approach For vulnerable groups of breast cancer survivors diagnosed from 2007-2010 in British Columbia (BC), 2007-2011 in Manitoba (MB), 2007-2010 in Ontario (ON), and 2007-2012 in Nova Scotia (NS), alive at 30 months post-diagnosis and followed for five years from diagnosis, we undertook a retrospective population-based cohort study linking cancer registries, clinical and health administrative databases. We calculated adherence to recommended follow-up care for surveillance of recurrent and new cancer, late effects, and general preventive care, and examined variation among provinces. Vulnerable groups were defined as those diagnosed at older ages, with lower income status, and/or who resided in rural area. Results Survivor numbers were 23,700 (ON), 9493 (BC), 2688 (MB), and 2735 (NS). In Year 2, between 9.3% (BC) and 28.1% (ON) of survivors diagnosed aged 74+ years received annual breast cancer-related PCP or oncologist follow-up visits, a lower proportion than their younger-diagnosed counterparts; rates of surveillance breast imaging (between 34.2% (BC) and 68.6% (ON) in Year 2) were also lower than those diagnosed at younger ages. Those with incomes in the lowest 40\% did not have different rates of primary care physician and oncologist visits compared to the top 60%, nor did their utilization of surveillance imaging or imaging for metastatic disease differ. Guideline-adherent surveillance breast imaging was conducted on a higher proportion of urban than rural patients in all provinces. Conclusion/Implications While area-level incomes do not appear to appreciably affect follow-up care, older age and rural residence resulted in differential access to care. These results suggest that there are gaps in provision of follow-up care that potentially can be addressed through system and practice-level change

Adherence to Follow-up Care Guidelines for Breast Cancer Survivors in four Canadian provinces: a CanIMPACT study

Introduction Breast cancer survivors are at risk for late and ongoing problems including cancer recurrence and late effects of treatment. Lack of access to quality follow-up care may affect later mortality, morbidity, and quality of life. This study examines variation in utilization of guideline-based follow-up care separately for four Canadian provinces. Objectives and Approach For our retrospective population-based cohort study of breast cancer survivors diagnosed from 2007 to 2010 in British Columbia (BC), 2007-2011 in Manitoba (MB), 2007-2010 in Ontario (ON), and 2007-2012 in Nova Scotia (NS), we linked provincial cancer registries, clinical and health administrative databases, and followed cases alive at 30 months post-diagnosis to five years from diagnosis. For each province, we calculated percent adherence, overuse, and underuse of recommended follow-up care, including surveillance for recurrent and new cancer, surveillance for late effects, and general preventive care. We also examined variation among provinces and over time. Results Survivor numbers were 23,700 (ON), 9493 (BC), 2688 (MB), and 2735 (NS). Annual oncologist visit guideline compliance varied provincially (e.g. Year 2 ON=32.7%, BC=15.0%). For most provinces and follow-up years, the majority of survivors had fewer oncologist visits than recommended.  However, survivors had additional annual breast cancer-related visits to a primary care provider.  Surveillance breast imaging guideline compliance was high (e.g. Year 2, ON=81.1%, MB=72.0%, NS=52.8%, BC =49.7%), with rates declining in ON and MB (to approximately 64%), but increasing in NS and BC (to approximately 58%) by Year 5. Overuse of breast imaging was identified in NS (9.1%-20.7% overuse in follow-up years 2-5).  As per the guideline, 72.9%-79.7% (Years 2-5) of BC survivors had no imaging for metastastic disease, highest among all provinces. Conclusion/Implications Provincial and temporal variations in guideline adherence were identified. Patterns differed by guideline, and both overuse and underuse were observed. These results point to opportunities to improve survivor care and efficiencies in care delivery. In particular, regular care with a primary care physician has been shown to improve follow-up care

Colonoscopy resource availability and colonoscopy utilization in Ontario, Canada

ABSTRACT Objective Evidence of long wait times for colonoscopy and regional variations in colonoscopy utilization have raised concerns that the availability of colonoscopy resources may be insufficient to meet current needs. This study described colonoscopy resource availability in Ontario, Canada, evaluated regional variations in colonoscopy resource availability and utilization, and examined the association between colonoscopy resource availability and colonoscopy utilization. Approach This is a population-based cross-sectional study of colonoscopy resource availability in Ontario, Canada from 2007 to 2013 using linked administrative health databases from the Institute for Clinical Evaluative Sciences (ICES). We defined the catchment areas for colonoscopy resources using physician networks that were built upon existing patient flow patterns, with comparisons to observed colonoscopy patient travel patterns to ensure the networks reflected colonoscopy referral patterns in the province. Colonoscopy physicians were identified from physician billing data. Network-level colonoscopy availability was measured in terms of physician density, specialty, and quality, use of private colonoscopy clinics, and distance that patients travel for colonoscopy. Network-level age- and sex-standardized colonoscopy utilization rates were calculated for 2007 to 2013. Associations between colonoscopy resource availability and colonoscopy utilization were analyzed using Spearman’s rank correlation. Results The availability of colonoscopy resources in Ontario increased between 2007 and 2013. Physician density increased from 8.7 full-time equivalent (FTE) physicians per 100,000 residents in 2007 to 9.4 FTE per 100,000 residents in 2013. The proportion of colonoscopy physicians who achieved the recommended colonoscopy completion and polypectomy rates increased from 60% to 77%, and 28% to 53%, respectively. Use of private colonoscopy clinics also increased. In 2007, 21% of colonoscopies were completed in private clinics, and by 2013, that proportion increased to 30%. Across Ontario, we observed strong geographic variation in these measures of colonoscopy resource availability as well as in the utilization of colonoscopy. Colonoscopy utilization was positively correlated with physician availability (r=0.48, p=0.001), physician quality (r=0.6, p<0.0001) and use of private clinics for colonoscopy (r=0.5, p=0.001). Conclusion The availability of colonoscopy resources improved in Ontario between 2007 and 2013. However, the geographic variation in resource availability and findings that higher colonoscopy resource availability is associated with higher colonoscopy utilization suggest that certain areas of the province may be under-resourced. These areas may be appropriate targets for efforts to improve colonoscopy capacity in Ontario

Time to Surgery for Patients with Esophageal Cancer Undergoing Trimodal Therapy in Ontario: A Population-Based Cross-Sectional Study

Patients with resectable esophageal cancer are recommended to undergo chemoradiotherapy before esophagectomy. A longer time to surgery (TTS) and/or time to consultation (TTC) may be associated with inferior cancer-related outcomes and heightened anxiety. Thoracic cancer surgery centers (TCSCs) oversee esophageal cancer management, but differences in TTC/TTS between centers have not yet been examined. This Ontario population-level study used linked administrative healthcare databases to investigate patients with esophageal cancer between 2013&ndash;2018, who underwent neoadjuvant chemoradiotherapy and then surgery. TTC and TTS were time from diagnosis to the first surgical consultation and then to surgery, respectively. Patients were assigned a TCSC based on the location of the surgery. Patient, disease, and diagnosing physician characteristics were investigated. Quantile regression was used to model TTS/TTC at the 50th and 90th percentiles and identify associated factors. The median TTS and TTC were 130 and 29 days, respectively. The adjusted differences between the TCSCs with the longest and shortest median TTS and TTC were 32 and 18 days, respectively. Increasing age was associated with a 16-day longer median TTS. Increasing material deprivation was associated with a 6-day longer median TTC. Significant geographic variability exists in TTS and TTC. Therefore, the investigation of TCSC characteristics is warranted. Shortening wait times may reduce patient anxiety and improve the control of esophageal cancer

Wait times and patterns of care in the colorectal cancer diagnostic interval

ABSTRACT Objective There is concern that patients are waiting too long to be diagnosed with colorectal cancer (CRC) after presenting to the healthcare system. A prolonged time from first presentation to diagnosis, also known as the diagnostic interval, may be harmful to patients and indicate problems with the delivery of healthcare. The purpose of this study is to measure the length of the CRC diagnostic interval and describe variations in care that patients receive within the interval. Approach This is a population-based, cross-sectional study of CRC patients diagnosed in Ontario, Canada between 2009 and 2012 using data from the Institute for Clinical Evaluative Sciences (ICES). The diagnostic interval will be measured using physician billing, hospital discharge, emergency room and registry data. Patients’ healthcare encounters in the 18 months before diagnosis will be analyzed using control charts to identify the earliest cancer-related encounter. The diagnostic interval will be defined as the date of this first relevant healthcare encounter to the CRC diagnosis date. Cluster analysis will be used to identify and characterize groups of patients with similar diagnostic intervals, based on the care received within the interval. Analyses will examine factors associated with the length of the diagnostic interval and care received within the diagnostic interval. Results Analyses for this project are ongoing and will be complete by August 2016. Results from this study will describe the length of the CRC diagnostic interval and relevant sub-intervals, and variations in these intervals according to patient and clinical characteristics. Results will describe the care that patients received within the interval, including the number and types of tests received and physicians involved in the interval, and whether the care received in the interval was associated with how long patients wait for diagnosis. Conclusion The findings from this study will advance our understanding of the CRC diagnostic interval. The control chart methodology used to identify CRC-related healthcare encounters from administrative health data is an improvement on previous research that has used arbitrary time periods and encounters which likely underestimate the length of the diagnostic interval. The cluster analysis method is a novel approach to characterizing the diagnostic interval that will identify common patterns of care and diagnostic pathways using administrative health data. This study will provide population-level estimates of how long patients are waiting to be diagnosed with CRC and provide an understanding of how patterns of care influence the length of the diagnostic interval